system

Abstract

To provide a system for creating business reports or progress reports.SOLUTION: A system includes means for: collecting a work history and performance data of a user; and creating a work report or progress report based on a generative AI model and a prompt sentence for instructing to create the work report or progress report based on the user's work history and performance data.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] The man-hours required to review the documents created are enormous, and even if a good job is done, it can be lost due to poor quality documents. Also, when the person in charge is absent, there is a lack of means to understand the work of that person. [Means for solving the problem]

[0005] It has business AI that corresponds to each individual user and provides a means to assist in the creation of documents in line with the supervisor's decision-making. This allows documents that are in line with the supervisor's wishes to be created in a short amount of time, reducing the man-hours required for document review. It also provides a means to understand the points of difficulty and thoughts of subordinates, and there is an agent that understands the person's work even when the person in charge is not present. This promotes the penetration of corporate culture. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

[0014] [First embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0027] "Example 1"

[0028] As one embodiment of the present invention, a system is provided that has a business AI that corresponds to each individual user. This business AI learns the user's work history and performance data, and assists in the creation of documents in line with the supervisor's decision-making. Specifically, the AI ​​provides the user with templates, formats, and necessary information for the documents they create, and the user creates the documents based on this. This makes it possible to create documents that meet the supervisor's preferences in a short amount of time.

[0029] "Example 2"

[0030] Furthermore, as another embodiment of the present invention, a means is provided for understanding the problems and thoughts of subordinates. Specifically, the business AI analyzes the user's work history and performance data and reports the results to the superior. This allows the superior to understand the progress and problems of the subordinate's work in real time.

[0031] "Example 3"

[0032] Furthermore, as a further embodiment of the present invention, a system is provided in which an agent that understands the work of a person in charge exists even when the person in charge is absent. Specifically, the task AI accumulates the user's work history and performance data and performs the work on behalf of the person in charge based on that data. This allows the person to continue their work even when the person in charge is absent.

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

[0034] "Example 1"

[0035] Step 1: The business AI collects the user's work history and performance data.

[0036] Step 2: The business AI learns based on the collected data.

[0037] Step 3: The business AI assists in the creation of documents in line with the supervisor's decision-making. Specifically, the AI ​​provides templates, formats, and necessary information for the documents the user creates. Step 4: The user creates the documents based on the information provided by the AI.

[0038] "Example 2"

[0039] Step 1: Business AI analyzes the user's work history and performance data.

[0040] Step 2: The business AI reports the analysis results to its superiors.

[0041] Step 3: Based on the report, the supervisor understands the progress and problems of the subordinate's work.

[0042] "Example 3"

[0043] Step 1: The business AI accumulates the user's work history and performance data.

[0044] Step 2: The business AI performs the business operations based on the accumulated data.

[0045] Step 3: Even if the person in charge is absent, the task AI continues the person's work.

[0046] Example 1

[0047] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0048] In the conventional document creation process, users had to spend a lot of time and effort creating documents that met their superiors' preferences, resulting in inefficiency. In addition, there was a lack of means to assist in creating documents that aligned with the superiors' decision-making, which made it difficult to reduce the man-hours required for document review and identify points of difficulty for subordinates. Furthermore, there was no agent to keep track of the work of the person in charge when they were absent, which sometimes disrupted the continuity of work. To solve these issues, a system was needed that utilized users' work history and performance data to efficiently assist in document creation.

[0049] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0050] In this invention, the server includes a means for owning a business AI corresponding to each user, a means for collecting the user's work history and performance data, a means for training the business AI using the collected data, a means for generating templates and formats according to the user's requests using a generative AI model, a means for providing the generated templates and formats to the user, a means for assisting in the creation of documents in line with the supervisor's decision-making, a means for quickly creating documents in line with the supervisor's preferences, a means for reducing the labor required for document review, a means for grasping the subordinate's difficulties and thoughts, a means for having an agent that understands the subordinate's work even when the person in charge is absent, and a means for promoting the penetration of corporate culture. This allows users to efficiently create documents in line with the supervisor's preferences, reduces the labor required for document review, and makes it easier to grasp the subordinate's difficulties. Furthermore, business continuity is ensured even when the person in charge is absent, promoting the penetration of corporate culture.

[0051] "Business AI" is an artificial intelligence system that learns from a user's work history and performance data and assists in document creation.

[0052] "User's work history" refers to data that refers to records and deliverables of work that a user has done in the past.

[0053] "Performance data" refers to data that indicates the results and evaluations of a user's work.

[0054] "Means for collection" refers to methods or devices for acquiring a user's work history and performance data.

[0055] "Training means" refers to methods or devices for training business AI using collected data.

[0056] A "generative AI model" is an artificial intelligence model that generates templates and formats according to user requests.

[0057] "Templates and formats" refer to standard structures and formats used when creating documents.

[0058] The "means for providing" refers to a method or device for delivering the generated template or format to the user.

[0059] "Means for assisting in the preparation of documents in line with decision-making" refers to methods or devices for supporting the preparation of documents based on the decision-making of a superior.

[0060] "Means for reducing document review man-hours" refers to methods and devices for reducing the time and effort required to check and correct documents.

[0061] "Means for grasping difficult points and thoughts" are methods or devices for understanding the problems and opinions that subordinates are facing.

[0062] An "agent that understands a person's work even when the person in charge is absent" is an artificial intelligence system that can understand a person's work and perform it on their behalf even when the person in charge is absent.

[0063] "Means to promote corporate culture" are methods and devices for spreading the company's values ​​and code of conduct to employees.

[0064] MODE FOR CARRYING OUT THE INVENTION

[0065] This invention is a system that has a task AI corresponding to each user and assists in creating documents in accordance with the decision-making of the superior. A specific embodiment of this system will be described below.

[0066] Server Roles

[0067] The server generates a business AI for each user. This business AI uses Python and TENSORFLOW (registered trademark) to collect and learn from the user's work history and performance data. The server uses this data to train a machine learning model and provides a function to assist in creating documents tailored to the user's supervisor's decision-making.

[0068] Specifically, the server retrieves user work history and performance data from a database (e.g., MySQL®). After collecting the data, the server preprocesses it and inputs it into a machine learning model. It normalizes the data and performs feature engineering to convert it into a format suitable for the model. Then, it trains the model using TensorFlow.

[0069] Device Role

[0070] When a user creates a document, the device receives templates, formats, and necessary information provided by the business AI. The device displays this information and helps the user create documents efficiently. Specifically, the device uses a web browser (e.g., GOOGLE CHROME (registered trademark)) to retrieve data from the server and display it on the user interface.

[0071] The terminal displays the template received from the server on a web page. Templates are dynamically generated using HTML and JavaScript (registered trademark) and displayed in a format that is easy for the user to view.

[0072] User Roles

[0073] Users create documents based on templates and formats provided by the business AI through their devices. By utilizing the information provided by the business AI, they can quickly create documents that meet their superiors' preferences.

[0074] For example, if a user wants to create a "sales report," the business AI will provide past sales data and the boss's preferred format. The user then enters the necessary data into the provided template to complete the document. The completed document is saved in PDF format and submitted to the boss.

[0075] Specific examples

[0076] An example of a prompt sentence to be input into a generative AI model is, "Please provide a template for creating a sales report in my boss's preferred format based on the sales data from the past three months." When this prompt sentence is input into the generative AI model, the business AI analyzes the past sales data and generates a sales report template based on the boss's preferred format. Based on this template, the user can create a high-quality sales report in a short amount of time.

[0077] In this way, a system is realized in which the server, terminals, and users can work together to efficiently create materials.

[0078] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0079] Step 1:

[0080] The server collects users' work history and performance data.

[0081] Input: User ID

[0082] Data processing: The server queries a database (e.g., MySQL) to retrieve user activity history and performance data.

[0083] Output: Acquired business history and performance data

[0084] Specific operation: The server executes the query "SELECT FROM user_performance WHERE user_id = '12345'" to retrieve the data.

[0085] Step 2:

[0086] The server preprocesses the collected data and converts it into a format suitable for machine learning models.

[0087] Input: Acquired work history and performance data

[0088] Data processing: Data normalization and feature engineering.

[0089] Output: Preprocessed data

[0090] Specific behavior: The server imputes missing values ​​in the data, normalizes numerical data, and performs one-hot encoding on categorical data.

[0091] Step 3:

[0092] The server uses the preprocessed data to train the business AI.

[0093] Input: Preprocessed data

[0094] Data Computing: Training machine learning models using TensorFlow.

[0095] Output: Trained business AI model

[0096] Specific operation: The server executes the code "model.fit(training_data, labels, epochs=10)" to train the model.

[0097] Step 4:

[0098] The server uses a generative AI model to generate templates and formats based on the user's requests.

[0099] Input: User request (prompt)

[0100] Data calculation: Input prompts into the generative AI model to generate templates and formats.

[0101] Output: Generated templates and formats

[0102] Specific operation: The server inputs the prompt statement "Please provide a template for creating a sales report in the format preferred by your boss based on the sales data from the past three months" into the generative AI model.

[0103] Step 5:

[0104] The terminal displays the templates and formats provided by the server to the user.

[0105] Input: Generated templates and formats

[0106] Data processing: Converting templates and formats into a format that can be displayed on a web page.

[0107] Output: The template or format that is displayed to the user

[0108] Specific behavior: The terminal uses HTML and JavaScript to dynamically generate a template and executes the code "document.getElementById('template').innerHTML = receivedTemplate;".

[0109] Step 6:

[0110] The user creates materials based on the templates and formats displayed on the terminal.

[0111] Input: Displayed template or format

[0112] Data processing: Enter the necessary data and complete the materials.

[0113] Output: Finished document

[0114] Specific operation: The user enters sales data and other information into the provided template to complete the document. The completed document is saved in PDF format and submitted to a supervisor.

[0115] (Application example 1)

[0116] Next, a description will be given of Application Example 1 of Embodiment Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0117] Conventional work support systems were unable to fully utilize the work history and performance data of individual users, making it difficult to create documents and optimize work instructions in line with supervisors' decision-making. Furthermore, the efficiency and optimization of work instructions for factory robots was not sufficiently implemented, making it difficult to improve work efficiency.

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

[0119] In this invention, the server includes: means for owning a task AI corresponding to each user; means for assisting in the creation of documents in line with the supervisor's decision-making; means for quickly creating documents in line with the supervisor's preferences; means for reducing the man-hours required for document review; means for understanding the difficulties and thoughts of subordinates; means for having an agent that understands a person's work even when the person in charge is absent; means for promoting the penetration of corporate culture; means for a factory robot to receive work instructions and provide optimal work procedures; means for learning work history and performance data and generating optimal work procedures; and means for providing work procedures based on the manager's instructions. This improves the work efficiency of users and enables the optimization of work instructions for factory robots.

[0120] "Business AI" is an artificial intelligence system that responds to individual users, learns their work history and performance data, and supports their work.

[0121] "Supervisor's decision-making" refers to the judgments and instructions given by a supervisor in the course of work.

[0122] "Means to assist in document creation" refers to a function that provides templates, formats, and necessary information for documents created by users.

[0123] "Document review man-hours" refers to the time and effort required to review and correct created documents.

[0124] "A means to understand the problems and thoughts of subordinates" is a function that collects and analyzes the problems and thoughts that subordinates face in the course of their work.

[0125] "An agent that understands a person's work even when the person in charge is absent" is a system that can understand a person's work content and handle it on their behalf even when the person in charge is absent.

[0126] "Means to promote the dissemination of corporate culture" refers to the function of helping employees understand and practice the company's values ​​and code of conduct.

[0127] A "factory robot" is a mechanical device used to automate work within a factory.

[0128] The "means for receiving work instructions and providing optimal work procedures" is a function that allows a factory robot to receive instructions and generate and provide optimal work procedures.

[0129] "Means for learning work history and performance data and generating optimal work procedures" is a function that learns and generates optimal work procedures based on past work history and performance data.

[0130] The "means for providing work procedures based on the manager's instructions" is a function for providing specific work procedures to factory robots based on the manager's instructions.

[0131] The system for implementing this invention consists of three main elements: a server, a terminal, and a user. The server has a business AI that corresponds to each user and has a function to assist in the creation of documents in line with the supervisor's decision-making. It also has a function to quickly create documents that meet the supervisor's preferences and reduce the labor required for document review. Furthermore, the system includes functions that can grasp the points of difficulty and thoughts of subordinates, a function to have an agent that understands the person's work even when the person in charge is absent, and a function to promote the penetration of corporate culture.

[0132] The server also has the function of allowing factory robots to receive work instructions and provide optimal work procedures. Specifically, it has the function of learning work history and performance data to generate optimal work procedures, and the function of providing work procedures based on instructions from managers.

[0133] The system's program is implemented using Python and the scikit-learn library. The server stores users' work history and performance data in JSON format, and uses this data to learn optimal work procedures using a linear regression model. Specifically, the system reads the user's work history data, extracts features and performance data, and uses a linear regression model to learn from them. It then generates new work procedures based on the manager's instructions and calculates predicted performance.

[0134] The terminal is a device that allows users to receive document templates and work procedures provided by the server and create documents and perform tasks based on them. Terminals include PCs, tablets, smartphones, etc.

[0135] Users perform their work based on document templates and work procedures provided by the server. The documents and work results created by the users are sent back to the server and stored as work history.

[0136] As a concrete example, consider the case where a factory robot performs assembly work. The manager instructs the "assembly work" and provides features such as the difficulty of the work, the required skills, and the time required. The server generates the optimal work procedure based on this and provides it to the factory robot.

[0137] Example prompt sentence:

[0138] User ID: 12345

[0139] Work Instructions: Assembly Work

[0140] Task features: [0.8, 0.6, 0.7]

[0141] Based on this prompt, the server provides optimal work procedures and predicted performance, improving user efficiency and optimizing work instructions for factory robots.

[0142] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0143] Step 1:

[0144] The server reads the user's work history data in JSON format. The input is the user ID, and the output is the user's work history data. This data includes past work content and performance.

[0145] Step 2:

[0146] The server extracts features and performance data from the loaded work history data. The input is the work history data, and the output is features and performance data. Features include the difficulty of the task, the required skills, and the time required.

[0147] Step 3:

[0148] The server trains a linear regression model using the extracted features and performance data. The inputs are the features and performance data, and the output is a trained linear regression model. This model learns the relationship between the features and performance.

[0149] Step 4:

[0150] The server receives work instructions from the manager. The input is the manager's instructions and the work's features, and the output is work instruction data. The work instruction data includes the specific work content and its features.

[0151] Step 5:

[0152] The server uses a trained linear regression model to generate optimal work procedures based on the manager's instructions. The input is the work instruction data and the trained model, and the output is the optimal work procedure. This procedure is generated based on predicted performance.

[0153] Step 6:

[0154] The server provides the generated optimal work procedure to the factory robot. The input is the optimal work procedure, and the output is work instructions for the factory robot. The factory robot performs the work based on these instructions.

[0155] Step 7:

[0156] The factory robot performs the work according to the provided work procedure. The input is the work instruction from the server, and the output is the work result. The work result is sent back to the server and accumulated as a work history.

[0157] Step 8:

[0158] The server receives the work results sent from the factory robots and stores them in a work history database. The input is the work results, and the output is updated work history data. This data is used for the next learning.

[0159] Example 2

[0160] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0161] In modern companies, it is important for managers to understand the progress and problems of their subordinates' work in real time. However, with conventional systems, it is difficult for managers to quickly and accurately grasp the points of difficulty and thoughts of their subordinates, and there are issues such as the time and effort required to create and review documents. Furthermore, when the person in charge is absent, it is difficult to understand that person's work, and corporate culture is often not fully ingrained.

[0162] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for possessing a task AI corresponding to each user, means for assisting in document creation in accordance with the supervisor's decision-making, means for quickly creating documents in line with the supervisor's preferences, means for reducing the man-hours required for document review, means for identifying the subordinate's difficulties and thoughts, means for having an agent that understands the subordinate's work even when the person in charge is absent, means for promoting the penetration of corporate culture, means for collecting the user's work history and performance data, means for preprocessing the collected data, means for inputting the preprocessed data into a generative AI model and generating analysis results, and means for reporting the generated analysis results to the supervisor. This allows the supervisor to grasp the progress and problems of the subordinate's work in real time, thereby improving the efficiency of document creation and review, understanding work even when the person in charge is absent, and promoting the penetration of corporate culture.

[0163] "Business AI" is an artificial intelligence system that analyzes users' work history and performance data to improve work efficiency and identify problems.

[0164] "User" refers to an individual employee who performs work using business AI.

[0165] "Supervisor" refers to a managerial person who oversees the progress and performance of the user's work and makes decisions.

[0166] "Work history" refers to data such as records of work a user has done in the past, task completion status, and comment history.

[0167] "Performance data" refers to data such as the results, efficiency, and evaluation of a user's work.

[0168] A "generative AI model" refers to an artificial intelligence model that analyzes collected data and generates results in text format.

[0169] A "prompt" is an instruction entered into a generative AI model to encourage it to analyze data and generate results.

[0170] "Preprocessing" refers to the process of data cleaning and normalization to prepare collected data in an analyzable format.

[0171] "Analysis Results" refers to the conclusions and suggestions regarding the progress and problems of the user's work that the generative AI model generates after analyzing the data.

[0172] "Reporting" refers to a means of communicating the generated analysis results to a superior, and includes formats such as dashboard display and email notification.

[0173] An "agent" is a system that keeps track of a person's work and provides them with the necessary information even when they are not present.

[0174] "Corporate culture" refers to the values, code of conduct, and communication style shared within a company.

[0175] This invention is a system that collects a user's work history and performance data, analyzes them using a generative AI model, and reports the results to a superior. A specific embodiment of this system will be described below.

[0176] The server obtains data from business management software and performance evaluation tools to collect users' work history and performance data. Specifically, business management software such as JIRA and Trello are used, and performance evaluation tools such as SAP SuccessFactors are used. Data is obtained from these tools via APIs.

[0177] The server then preprocesses the collected data, which includes cleaning the data (imputing missing values ​​and removing outliers) and normalizing the data (scaling and encoding). The preprocessing is performed using the Python Pandas library.

[0178] The preprocessed data is then input into a generative AI model, such as OpenAI's GPT-4, which analyzes the data based on the prompt and identifies potential problems or difficulties the user may be facing.

[0179] As a concrete example, consider a case where a user is using the project management tool JIRA. The server collects the user's task completion status and comment history from JIRA. Next, it inputs the following prompt sentence to the generative AI model:

[0180] "Analyze the following work history and performance data to identify potential pain points your users may be experiencing. Data includes: task completion status, comment history, and progress reports."

[0181] The generative AI model analyzes the data based on this prompt and draws conclusions such as, "The user may be having difficulty prioritizing tasks."

[0182] Finally, the server reports the generated analysis results to the manager, who can display the results on a dashboard (e.g., Tableau or Power BI) or send them via email or a notification system, allowing the manager to keep track of the progress and issues of their subordinates' work in real time.

[0183] This system allows managers to quickly grasp the progress and problems of their subordinates' work and provide appropriate support. It also improves the efficiency of document creation and review, keeps track of work when the person in charge is absent, and promotes the penetration of corporate culture.

[0184] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0185] Step 1: Data collection

[0186] The server collects user work history and performance data. Specifically, it obtains data from work management software (e.g., JIRA, Trello) and performance evaluation tools (e.g., SAP SuccessFactors) via API. The input is raw data obtained from the API endpoint, and the output is the collected work history and performance data. For example, using the JIRA API, task completion status and comment history are obtained from the endpoint GET / rest / api / 2 / search?jql=assignee=currentUser().

[0187] Step 2: Data Preprocessing

[0188] The server preprocesses the collected data. Preprocessing includes data cleaning (filling in missing values ​​and removing outliers) and data normalization (scaling and encoding). The input is the collected raw data, and the output is the preprocessed, clean data. Specifically, it uses the Python Pandas library to fill in missing values ​​with the fillna() method and remove outliers with conditional filtering.

[0189] Step 3: Data analysis

[0190] The server inputs the preprocessed data into a generative AI model. OpenAI's GPT-4 is used as the generative AI model. The input is the preprocessed clean data and a prompt, and the output is the analysis result by the generative AI model. Specifically, the server sends the following prompt to the generative AI model:

[0191] "Analyze the following work history and performance data to identify potential pain points your users may be experiencing. Data includes: task completion status, comment history, and progress reports."

[0192] Step 4: Generate results

[0193] The generative AI model analyzes data based on the prompt and identifies problems or difficulties the user may be facing. The input is the prompt sent to the generative AI model and preprocessed data, and the output is the analysis results in text format. For example, it may conclude that "the user may be having difficulty prioritizing tasks."

[0194] Step 5: Reporting the results

[0195] The server reports the generated analysis results to the manager. The report is displayed on a dashboard used by the manager (e.g., Tableau, Power BI) or sent via email or a notification system. The input is the analysis results obtained from the generative AI model, and the output is in the form of a report for the manager. Specifically, the results are converted to JSON format and added to the dashboard using Tableau's API.

[0196] In this way, superiors can grasp the progress and problems of their subordinates' work in real time.

[0197] (Application example 2)

[0198] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0199] With conventional work management systems, it was difficult for managers to grasp the progress and problems of their subordinates in real time, which sometimes led to delays when a quick response was required. Furthermore, there was a lack of means to monitor the performance of robots operating in factories in real time and respond immediately when a problem occurred. This led to problems such as a decline in work efficiency and reduced productivity.

[0200] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for possessing a task AI corresponding to each user; means for assisting in the creation of documents in accordance with the supervisor's decision-making; means for quickly creating documents in line with the supervisor's preferences; means for reducing the labor required for document review; means for identifying the difficulties and thoughts of subordinates; means for having an agent who understands the person's work even when the person in charge is absent; means for promoting the penetration of corporate culture; means for collecting and analyzing robot work history data and reporting the results to a manager; and means for monitoring robot performance data in real time and notifying the manager if a problem occurs. This allows a manager to understand the progress and problems of their subordinates in real time, monitor the performance of robots operating in the factory in real time, and respond immediately if a problem occurs.

[0201] "Business AI" is an artificial intelligence system that analyzes a user's work history and performance data to understand the progress and problems of work.

[0202] "Means to assist in the creation of documents in line with the supervisor's decision-making" is a function for quickly creating necessary documents based on the supervisor's instructions and intentions.

[0203] "Means for quickly creating materials that meet the boss's preferences" is a function for quickly generating materials that meet the boss's preferences and requests.

[0204] "Means to reduce document review man-hours" is a function for reducing the time and effort required to check and correct documents.

[0205] "A means of understanding the problems and thoughts of subordinates" is a function that allows you to understand the problems and thoughts that your subordinates are facing in real time.

[0206] "A means to have an agent who understands the person's work even when the person in charge is absent" is a function that has an agent who understands the person's work and can handle it in their place, even when the person in charge is absent.

[0207] "Means to promote the dissemination of corporate culture" is a function that spreads and helps employees understand the company's values ​​and code of conduct.

[0208] "Means of collecting and analyzing work history data of robots and reporting the results to managers" is a function for collecting work history data of robots operating in factories and reporting the analysis results to managers.

[0209] "Means for monitoring robot performance data in real time and notifying administrators if a problem occurs" refers to a function for monitoring robot performance data in real time and immediately notifying administrators if a problem occurs.

[0210] A system for carrying out this invention comprises a server, a terminal, and a user element. The server has a task AI corresponding to each user, and includes means for assisting in the creation of documents in accordance with the decision-making of a supervisor, means for quickly creating documents in line with the supervisor's preferences, means for reducing the man-hours required for document review, means for understanding points of difficulty and thoughts of subordinates, means for having an agent that understands the work of each person even when the person in charge is absent, means for promoting the penetration of corporate culture, means for collecting and analyzing work history data of robots and reporting the results to a manager, and means for monitoring robot performance data in real time and notifying if a problem occurs.

[0211] The server uses software such as Python, pandas, and smtplib to collect the robot's work history data and monitor performance data in real time. The data is provided in CSV file format, which the server reads and records as a problem if performance falls below a certain threshold. If a problem is detected, the server reports it to the administrator by email.

[0212] As a concrete example, the robot's work history data is provided in a CSV file like this:

[0213] csv

[0214] timestamp,performance

[0215] 2023-10-01 08:00:00,85

[0216] 2023-10-01 09:00:00,65

[0217] 2023-10-01 10:00:00,90

[0218] Based on this data, the server detects time periods where performance is below 70 and records them as problems. For example, the data for 2023-10-01 09:00:00 shows performance as 65, so this is recorded as a problem.

[0219] An example of a prompt to input to a generative AI model is as follows:

[0220] "Write a Python program that analyzes the work history data of robots operating in a factory, and if the performance falls below a certain threshold, logs it as a problem and reports it to a manager via email. The data will be provided in a CSV file, and the performance threshold will be 70."

[0221] In this way, the server allows managers to understand the progress and problems of their subordinates in real time, and can monitor the performance of robots operating in the factory in real time and respond immediately if a problem occurs.

[0222] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0223] Step 1:

[0224] The server reads the robot's work history data in CSV file format. The input is a CSV file, and the output is data in data frame format. Specifically, the CSV file is converted to a data frame using the Python pandas library.

[0225] Step 2:

[0226] The server analyzes the loaded data frame and extracts performance data for each timestamp. The input is business history data in data frame format, and the output is a list of performance data. Specifically, it loops through each row of the data frame and adds the values ​​of the performance column to the list.

[0227] Step 3:

[0228] The server records a problem if the performance falls below a certain threshold (e.g., 70) based on the extracted performance data. The input is a list of performance data, and the output is a list of problems. Specifically, each value of the performance data is checked, and if it falls below the threshold, the timestamp and performance value are added to the problem list.

[0229] Step 4:

[0230] The server generates the content of the email to be reported to the administrator based on the problem list. The input is the problem list, and the output is the email body. Specifically, it loops through each item in the problem list and adds details of the problem to the email body.

[0231] Step 5:

[0232] The server sends the generated email body to the administrator. The input is the email body and the output is the sending result. Specifically, it uses the Python smtplib library to send the email to the administrator's email address via the mail server.

[0233] In this way, the server can monitor the robot's work history data in real time and immediately notify the administrator if a problem occurs.

[0234] Example 3

[0235] Next, a description will be given of a third embodiment of the third embodiment. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0236] With conventional business systems, it was difficult to substitute for the person in charge when they were absent, resulting in problems of business stagnation and reduced efficiency. There were also insufficient means to create documents in line with the supervisor's decision-making, to understand the points of difficulty of subordinates, and to promote the penetration of corporate culture. Furthermore, there was no established method for effectively utilizing users' work history and performance data, making it difficult to improve business performance.

[0237] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0238] In this invention, the server includes: a means for owning a business AI corresponding to each user; a means for assisting in the creation of documents in accordance with a supervisor's decision-making; a means for quickly creating documents in line with the supervisor's preferences; a means for reducing the labor required for document review; a means for identifying subordinates' difficulties and thoughts; a means for providing an agent that understands a user's work even when the person in charge is absent; a means for promoting the penetration of corporate culture; a means for collecting a user's work history and performance data and storing it in a database; a means for analyzing the collected data and inputting prompt statements into a generative AI model to generate instructions for performing the work; and a means for sending the generated instructions to an agent, which then performs the user's work. This allows a user to continue their work even when the person in charge is absent, preventing work stagnation and improving efficiency. It also enables the creation of documents in accordance with a supervisor's decision-making, identifying subordinates' difficulties, and promoting the penetration of corporate culture. Furthermore, by effectively utilizing a user's work history and performance data, business performance can be improved.

[0239] "Business AI" is an artificial intelligence system that automates or assists business operations based on the user's work history and performance data.

[0240] "Means to assist in the creation of documents in line with the supervisor's decision-making" refers to a function that enables the necessary documents to be created quickly and accurately based on the supervisor's instructions and decisions.

[0241] "A means for quickly creating materials that meet the boss's preferences" is a function for quickly generating materials that meet the boss's preferences and requests.

[0242] "Means to reduce document review man-hours" is a function for reducing the time and effort required to check and correct documents.

[0243] "A means of understanding the problems and thoughts of subordinates" is a function for collecting and understanding the problems and opinions that subordinates are facing.

[0244] "A means to have an agent who understands a person's work even when the person in charge is absent" is a function that provides an agent who understands a person's work and can act on their behalf even when the person in charge is absent.

[0245] "Means to promote the dissemination of corporate culture" is a function that spreads and helps employees understand the company's values ​​and code of conduct.

[0246] "Means for collecting user's work history and performance data and saving it in a database" is a function for collecting data on the history and performance of work performed by a user and saving it in a database.

[0247] "Means for analyzing collected data and inputting prompt sentences into a generative AI model to generate instructions for performing tasks on behalf of others" refers to a function that analyzes collected data, inputs prompt sentences into a generative AI model based on the results, and generates specific instructions for performing tasks on behalf of others.

[0248] "Means for sending generated instructions to an agent and for the agent to perform the user's work" refers to a function that sends instructions generated from a generative AI model to an agent and for the agent to perform the user's work.

[0249] This invention provides a system that can take over a person's work even when that person is absent. Specifically, the task AI accumulates the user's work history and performance data and performs the work based on that.

[0250] The server collects data generated in real time as users perform their daily work. Specifically, it obtains work-related data (e.g., work logs, reports, email content, etc.) from the devices used by users. This is done using dedicated data collection software (e.g., Logstash).

[0251] The server stores the collected data in a database. Specifically, it uses a database management system such as MySQL to structure and store the data. A table is created in the database for each user, and each table stores work history and performance data.

[0252] The server periodically extracts data from the database and analyzes it using data analysis software (e.g., Python's Pandas library). Specifically, it analyzes user work patterns and performance trends and extracts key indicators. The results of this analysis become the basic data to input into the generative AI model.

[0253] Based on the results of the data analysis, the server generates prompts to be input into the generative AI model. Specifically, the server references the user's past work history and performance data to create prompts containing specific instructions for performing the work on behalf of the user. For example, it generates a prompt such as, "Please prepare today's report based on User A's report data from the past month."

[0254] The server inputs the generated prompt sentence into a generative AI model (e.g., OpenAI's GPT-4) to generate specific instructions for performing the task. The generated instructions are sent to the agent, which then performs the user's task. Specifically, the agent automatically creates a report, makes any necessary corrections, and submits it as the final report.

[0255] As a concrete example, consider the task of creating reports that a user performs daily. If the user is absent, the task AI automatically generates a similar report based on past report data.

[0256] Example prompt sentence:

[0257] "Please create today's report based on User A's report data from the past month."

[0258] By inputting this prompt sentence into the generative AI model, the model generates a new report by referring to past data. The generated report is checked by the agent, and after corrections are made as necessary, it is submitted as the final report. The flow of the identification process in Example 3 will be explained using Figure 15.

[0259] Step 1: Collect user data

[0260] The server collects data in real time that is generated when users perform their daily work. Specifically, it obtains work-related data (e.g., work logs, reports, email contents, etc.) from the devices used by the users. For this purpose, it uses dedicated data collection software (e.g., Logstash). The input is the user's work data, and the output is the collected work data. For example, when a user clicks the "Start creating report" button, the timestamp and user ID at that time are recorded as a log.

[0261] Step 2: Save your data

[0262] The server saves the collected data in a database. Specifically, it uses a database management system such as MySQL to structure and store the data. The input is the collected business data, and the output is the data saved in the database. A table is created for each user in the database, and each table stores work history and performance data. For example, information such as user ID, timestamp, and work content is stored in the "user_logs" table.

[0263] Step 3: Analyze the data

[0264] The server periodically extracts data from the database and analyzes it using data analysis software (e.g., Python's Pandas library). The input is the business data extracted from the database, and the output is the analysis results. Specifically, it analyzes users' work patterns and performance trends and extracts important indicators. For example, a scheduled job is run every night to extract data from the past month and calculate indicators such as users' average work time and frequency.

[0265] Step 4: Generate a prompt statement

[0266] Based on the results of the data analysis, the server generates a prompt to be input into the generative AI model. The input is the analysis result, and the output is the prompt. Specifically, the server references the user's past work history and performance data to create a prompt that includes specific instructions for performing the work on behalf of the user. For example, it generates a prompt that reads, "Please prepare today's report based on User A's report data from the past month."

[0267] Step 5: Executing the business on your behalf

[0268] The server inputs the generated prompt into a generative AI model (e.g., OpenAI's GPT-4) to generate specific instructions for performing the task. The input is the prompt, and the output is the generated instructions. The generated instructions are sent to the agent, which then performs the user's task. Specifically, the agent automatically creates a report, makes any necessary corrections, and submits it as the final report. For example, when the agent clicks the "Submit Report" button, the report is automatically sent to the supervisor.

[0269] (Application example 3)

[0270] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0271] In conventional production line management, work often stalls when the person in charge is absent, resulting in a decline in production efficiency. There was also a need for a system that could monitor the progress of the production line when the person in charge is absent and make necessary adjustments and troubleshooting.

[0272] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes means for possessing a task AI corresponding to each user, means for assisting in the creation of materials in accordance with the supervisor's decision-making, means for quickly creating materials that meet the supervisor's preferences, means for reducing the man-hours required for document review, means for grasping the difficulties and thoughts of subordinates, means for having an agent that understands the work of each person even when the person in charge is absent, means for promoting the penetration of corporate culture, means for monitoring the progress of the production line, means for making necessary adjustments, means for troubleshooting, and means for being installed in a production line management robot. This makes it possible to continue production line management operations and maintain production efficiency even when the person in charge is absent.

[0273] "Business AI" is an artificial intelligence system that accumulates the work history and performance data of individual users and performs work on their behalf based on that data.

[0274] "Means to assist in the creation of documents in line with the supervisor's decision-making" refers to a function that enables the necessary documents to be created quickly and accurately based on the supervisor's instructions and decisions.

[0275] "Means for quickly creating materials that meet the boss's preferences" is a function for quickly creating materials that meet the boss's preferences and requests.

[0276] "Means for reducing document review man-hours" refers to functions for reducing the time and effort required to review documents.

[0277] "A means of understanding the problems and thoughts of subordinates" is a function that allows you to understand the problems and thoughts that subordinates are facing and provide appropriate support.

[0278] "A means to have an agent who understands the person's work even when the person in charge is absent" is a function that has an agent who can take over the person's work even when the person in charge is absent.

[0279] "Means to promote the dissemination of corporate culture" is a function for disseminating the company's values ​​and code of conduct to employees.

[0280] The "means for monitoring the progress of the production line" is a function for monitoring the progress of the production line in real time.

[0281] The "means for making necessary adjustments" is a function for automatically making necessary adjustments according to the progress of the production line.

[0282] "Troubleshooting means" is a function for quickly identifying and resolving problems that occur on the production line.

[0283] "Means to be installed in the production line management robot" refers to a function to be installed in the robot that performs the production line management work.

[0284] A system for carrying out the present invention includes an application installed on a robot that manages a production line in a factory. A specific embodiment of this system will be described below.

[0285] System Program

[0286] The server runs a program using Python. The program accumulates the user's work history and performance data, and provides functions to carry out work on behalf of the user based on that data. Specifically, it performs the following processes:

[0287] 1. Load user data:

[0288] The server reads user data stored in JSON format and obtains the user's work history and performance data.

[0289] 2. Monitoring the progress of the production line:

[0290] The server monitors the progress of the production line in real time, using hardware such as sensors and cameras.

[0291] 3. Make any necessary adjustments:

[0292] The server automatically makes necessary adjustments based on the progress of the production line, such as adjusting production speed or changing machine settings.

[0293] 4. Troubleshooting:

[0294] The server quickly identifies problems that occur on the production line and takes steps to resolve them, including analyzing error logs and restarting machines.

[0295] Hardware and software used

[0296] Hardware: production line control robots, sensors, cameras

[0297] Software: Python, JSON format data files

[0298] Specific examples

[0299] For example, if a machine on a production line breaks down, the server analyzes data from sensors to identify the problem, then executes the necessary repair procedures and restarts the production line. If the production line is slowing down, the server automatically adjusts the production speed to make up for the delay.

[0300] Prompt Sentence Examples

[0301] An example of a prompt sentence to input to the generative AI model is as follows:

[0302] Based on the user's work history and performance data, generate a program for the production line management robot to take over the work in the absence of the person in charge, specifically include the ability to monitor progress, make necessary adjustments, and troubleshoot.

[0303] In this way, the present invention makes it possible to continue production line management operations even when the person in charge is absent, thereby maintaining production efficiency.

[0304] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0305] Step 1:

[0306] The server reads user data stored in JSON format. Specifically, it opens a file containing the user's work history and performance data and parses its contents. The input is the user data file, and the output is the parsed user data, which is used in subsequent processing steps.

[0307] Step 2:

[0308] The server monitors the progress of the production line in real time. It collects data from sensors and cameras and evaluates the progress. The input is real-time data from sensors and cameras, and the output is the progress evaluation result. Based on this evaluation result, any necessary adjustments or troubleshooting are made.

[0309] Step 3:

[0310] The server automatically makes necessary adjustments according to the progress of the production line, such as adjusting the production speed or changing machine settings. The input is the progress evaluation result, and the output is the adjusted production line settings. Specific actions include increasing the machine speed or changing settings.

[0311] Step 4:

[0312] The server quickly identifies problems that occur on the production line and executes procedures to resolve them, such as analyzing error logs and restarting machines. The input is error data from sensors and cameras, and the output is the normal state of the production line after the problem is resolved. Specific operations include analyzing error logs, identifying the fault location, and executing repair procedures.

[0313] Step 5:

[0314] The server runs an agent that performs tasks on behalf of the user, even when the person in charge is not present, based on the user's work history and performance data. The input is user data and real-time production line data, and the output is the results of the agent's work on behalf of the user. Specific operations include starting the agent, performing the work on behalf of the user, and reporting the results.

[0315] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0316] "Example 1"

[0317] One embodiment of the present invention is a business AI system incorporating an emotion engine. This system recognizes the user's emotions and adjusts the business AI's behavior according to the user's emotional state. Specifically, if the business AI recognizes that the user is feeling stressed, it takes action to reduce the user's workload. For example, it automatically reschedules the user's tasks or provides necessary information.

[0318] "Example 2"

[0319] The emotion engine also has the ability to report the user's emotional state to their superiors, allowing the superior to understand the emotional state of their subordinates in real time and take appropriate action. For example, if the superior senses that a subordinate is experiencing high levels of stress, the superior can have a direct conversation or provide appropriate support.

[0320] "Example 3"

[0321] Furthermore, the emotion engine trains the task AI based on the user's emotional state. This allows the task AI to more accurately understand the user's emotional state and respond more appropriately. For example, if a user tends to feel stressed when performing a certain task, the task AI can automate that task or help the user perform the task more efficiently.

[0322] The processing flow of each embodiment will be described below.

[0323] "Example 1"

[0324] Step 1: The user begins working with the business AI system.

[0325] Step 2: The emotion engine recognizes the user's emotions in real time and determines their emotional state.

[0326] Step 3: The emotion engine adjusts the task AI's behavior based on the emotional state it recognizes. For example, if it recognizes that the user is feeling stressed, the task AI will automatically reschedule the user's tasks.

[0327] "Example 2"

[0328] Step 1: The user begins working with the business AI system.

[0329] Step 2: The emotion engine recognizes the user's emotions in real time and determines their emotional state.

[0330] Step 3: The emotion engine reports the perceived emotional state to the supervisor. The supervisor receives the report and takes appropriate action. For example, if the supervisor senses that the subordinate is experiencing high stress, the supervisor may have a direct dialogue or provide appropriate support.

[0331] "Example 3"

[0332] Step 1: The user begins working with the business AI system.

[0333] Step 2: The emotion engine recognizes the user's emotions in real time and determines their emotional state.

[0334] Step 3: The emotion engine trains the task AI based on the user's emotional state. For example, if the user tends to feel stressed when performing a certain task, the task AI can automate that task or help the user perform the task more efficiently.

[0335] Example 1

[0336] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0337] Conventional work support systems were unable to effectively utilize users' work history and performance data, making it difficult to create materials that matched the supervisor's decision-making. Furthermore, work adjustments were not made taking into account the user's emotional state, and the workload was not sufficiently reduced. Furthermore, issues arose with regard to continuing work when the person in charge was absent and the penetration of corporate culture.

[0338] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0339] In this invention, the server includes means for owning a task AI corresponding to each user, means for assisting in the creation of documents in accordance with the supervisor's decision-making, means for quickly creating documents in line with the supervisor's preferences, means for reducing the man-hours required for document review, means for grasping the points of difficulty and thoughts of subordinates, means for having an agent that understands the person's work even when the person in charge is absent, means for promoting the penetration of corporate culture, means for recognizing the user's emotional state, means for adjusting the operation of the task AI according to the user's emotional state, means for automatically rescheduling the user's tasks, and means for providing necessary information. This improves the user's work efficiency and enables work adjustments according to the user's emotional state, thereby reducing the workload and promoting the penetration of corporate culture.

[0340] "Business AI" is an artificial intelligence that learns the user's work history and performance data and assists in creating documents in line with the supervisor's decision-making.

[0341] "Supervisor's decision-making" refers to the judgments and instructions given by a supervisor in the course of work.

[0342] "Means to assist in document creation" refers to a function that provides templates, formats, and necessary information for documents created by users.

[0343] "Supervisor's preferences" refer to the format and content of materials that the supervisor prefers.

[0344] "Document review man-hours" refers to the time and effort required to review documents and provide corrections and feedback.

[0345] "Troublesome points of subordinates" refer to the problems and challenges that subordinates face when carrying out their work.

[0346] An "agent that understands the work to be done when the person in charge is absent" is a system that can understand the work content of a person and handle it on their behalf even when the person in charge is absent.

[0347] "Permeating corporate culture" refers to the company's values ​​and code of conduct being widely understood and practiced by employees.

[0348] "Means for recognizing emotional state" refers to a function that analyzes the user's facial expressions and tone of voice to determine their emotions.

[0349] "Means for adjusting the behavior of business AI" is a function that changes the behavior of business AI according to the user's emotional state.

[0350] The "means for automatically rescheduling tasks" is a function that automatically adjusts the priority and execution time of tasks in order to reduce the workload of the user.

[0351] "Means of providing necessary information" refers to a function that provides the data and materials necessary for users to carry out their work.

[0352] MODE FOR CARRYING OUT THE INVENTION

[0353] This invention is a system that has a business AI that corresponds to each user and assists in the creation of documents in line with the supervisor's decision-making. This system learns the user's work history and performance data and can quickly create documents that are in line with the supervisor's preferences. It also incorporates an emotion engine that adjusts the behavior of the business AI according to the user's emotional state.

[0354] Hardware and software used

[0355] Hardware: Servers, devices (PCs, tablets, smartphones)

[0356] Software: Business AI (e.g., TensorFlow, PyTorch), emotion engine (e.g., Affectiva SDK), database (e.g., MySQL, PostgreSQL)

[0357] Specific operation of the system

[0358] 1. Data Collection

[0359] The server collects the user's work history and performance data, specifically from the business applications used by the user (e.g., spreadsheet software, word processing software, email client).

[0360] The server stores the collected data in a database.

[0361] 2. Data Learning

[0362] The server uses the stored data to train the business AI model, specifically by applying machine learning algorithms to learn the user's work patterns and the supervisor's decision-making patterns.

[0363] The server saves the learning results as a model and uses them for subsequent document creation and emotion recognition.

[0364] 3. Assistance in preparing materials

[0365] When a user wants to create a document, they send a request to the business AI from their device, for example, by entering a prompt such as "Please provide a template for a monthly report."

[0366] The server receives the request and uses the business AI model to generate the appropriate template or format.

[0367] The server transmits the generated templates and formats to the terminal.

[0368] Users create materials based on the provided templates.

[0369] 4. Emotion recognition

[0370] Using the device's built-in camera and microphone, the emotion engine analyzes the user's facial expressions and tone of voice.

[0371] The terminal transmits the analysis results to the server.

[0372] The server determines the user's emotional state based on the received data, for example, whether the user is feeling stressed.

[0373] 5. Operation adjustment

[0374] If the server determines that the user is feeling stressed, it issues instructions to the business AI.

[0375] Business AI can automatically reschedule users' tasks, for example, deferring less urgent tasks and prioritizing more important ones.

[0376] The server transmits the rescheduled task information to the terminal.

[0377] Users can check the new schedule on their device and proceed with their work.

[0378] Specific examples

[0379] Assistance in creating materials

[0380] The user types into the terminal, "Please provide me with a monthly report template."

[0381] The server generates an optimal template based on past data and sends it to the terminal.

[0382] Users create reports based on the provided templates.

[0383] Emotion Recognition and Behavior Regulation

[0384] The device's camera captures the user's facial expressions, which are then analyzed by the emotion engine.

[0385] The device determines that the user is feeling stressed and sends that information to the server.

[0386] The server reschedules the user's tasks, pushing less urgent tasks to a later date.

[0387] The server transmits the new schedule to the terminal and notifies the user.

[0388] The user checks the new schedule and proceeds with their work.

[0389] Prompt Sentence Examples

[0390] "Please provide a template for the monthly report."

[0391] "Please tell me the format of presentation materials that suits my boss's preferences."

[0392] "If the user is stressed, reschedule the task."

[0393] "Propose actions to reduce workload based on the user's emotional state."

[0394] The above is a specific embodiment of the system of the present invention.

[0395] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0396] Step 1:

[0397] Data collection

[0398] Input: User work history and performance data

[0399] Specific operation: The server obtains data from the business application used by the user (e.g., spreadsheet software, word processing software, email client).

[0400] Data processing: The acquired data is standardized and stored in a database.

[0401] Output: Standardized historical and performance data is stored in a database.

[0402] Step 2:

[0403] Data Learning

[0404] Input: Business history and performance data stored in a database

[0405] How it works: The server uses the stored data to train the business AI model, specifically by applying machine learning algorithms to learn the user's work patterns and the supervisor's decision-making patterns.

[0406] Data computation: Analyze data using machine learning algorithms to generate models.

[0407] Output: A business AI model is generated as the learning result and saved.

[0408] Step 3:

[0409] Assistance in creating materials

[0410] Input: User request (e.g. "Please provide a template for monthly report")

[0411] Specific operation: When a user creates a document, the device sends a request to the business AI. The server receives the request and uses the business AI model to generate an appropriate template or format.

[0412] Data calculation: Using a business AI model, templates are generated based on past data and the manager's preferences.

[0413] Output: The generated template or format is sent to the terminal.

[0414] Step 4:

[0415] emotion recognition

[0416] Input: User facial expressions and tone of voice

[0417] How it works: Using the device's built-in camera and microphone, the emotion engine analyzes the user's facial expressions and tone of voice. The device then sends the analysis results to the server.

[0418] Data processing: Analyze facial expressions and tone of voice data to determine emotional state.

[0419] Output: The user's emotional state data is sent to the server.

[0420] Step 5:

[0421] Operation adjustment

[0422] Input: User emotional state data

[0423] Specific operation: If the server determines that the user is feeling stressed, it issues instructions to the work AI, which then automatically reschedules the user's tasks.

[0424] Data calculation: Recalculate task priorities and execution times and adjust schedules.

[0425] Output: Rescheduled task information is sent to the terminal.

[0426] Step 6:

[0427] Information provision

[0428] Input: User requests and business status

[0429] Specific operation: The server provides the necessary information according to the user's business situation and requests.

[0430] Data calculation: Using business AI models, search for the necessary information and provide it in the appropriate format.

[0431] Output: The required information is sent to the terminal and provided to the user.

[0432] (Application example 1)

[0433] Next, a description will be given of Application Example 1 of Embodiment Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0434] Conventional work support systems were unable to fully utilize the work history and performance data of individual users, making it difficult to create documents that matched the supervisor's decision-making process or adjust the workload according to the user's emotional state. Furthermore, they were unable to automatically generate work reports and progress reports, which led to problems with reduced work efficiency.

[0435] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes means for collecting a user's work history and performance data, a prompt statement instructing the user to create a work report or progress report based on the user's work history and performance data, and means for creating the work report or progress report based on a generative AI model. The server also includes a prompt statement instructing the user to propose an optimal procedure for the user's work based on the user's work history and performance data, and means for proposing an optimal procedure for the user's work based on the generative AI model. The server also includes means for recognizing the user's emotional state, a prompt statement instructing the user to propose an optimal workload for the user's work based on the user's work history and the user's emotional state, and means for proposing an optimal workload for the user's work based on the generative AI model. This improves the user's work efficiency, enables the creation of documents in line with supervisor decision-making, and enables the adjustment of the user's workload according to the user's emotional state.

[0436] "Business AI" is an artificial intelligence system that responds to individual users and supports their work by learning their work history and performance data.

[0437] "Means to assist in the creation of documents in line with the supervisor's decision-making" is a function that supports the creation of documents based on the supervisor's instructions and inclinations.

[0438] "A means for quickly creating materials that meet the boss's preferences" is a function that allows for the rapid creation of materials that meet the boss's preferences and requests.

[0439] "Means to reduce document review man-hours" refers to a function that reduces the time and effort required to check and correct documents.

[0440] "A means of understanding the points of difficulty and thoughts of subordinates" is a function for understanding the problems and opinions that subordinates are facing.

[0441] "A means to have an agent who understands the work of a person even when the person in charge is absent" is a function that has an agent who understands the work content even when the person in charge is absent.

[0442] "Means to promote the dissemination of corporate culture" is a function for spreading the company's values ​​and code of conduct to employees.

[0443] "Means for recognizing the emotional state of the user and adjusting the workload in accordance with the emotional state" is a function that detects the user's emotions and adjusts the workload in accordance with that state.

[0444] "Means for learning work history and performance data and proposing optimal work procedures" is a function that analyzes past work history and performance data and proposes optimal work procedures.

[0445] "Means for automatically generating business reports and progress reports" refers to a function that automatically generates work progress and results as reports.

[0446] A system for implementing this invention has the following configuration: The server has a business AI that corresponds to each user and assists in creating documents in line with the supervisor's decision-making. It also creates documents that are in line with the supervisor's preferences in a short amount of time, reducing the man-hours required for document review. It also has an agent that can understand the points of difficulty and thoughts of subordinates and understands their work even when the person in charge is not present. It promotes the penetration of corporate culture, recognizes the user's emotional state, and adjusts the workload accordingly. It learns work history and performance data, proposes optimal work procedures, and automatically generates work reports and progress reports.

[0447] Hardware and software used

[0448] Hardware: Factory robots, emotion-recognition cameras, sensors

[0449] Software: Python, EmotionEngine library, generative AI model, TaskScheduler library

[0450] Data processing and calculation

[0451] The server collects the user's work history and performance data and proposes optimal work procedures based on this. Specifically, it uses the EmotionEngine library to recognize the user's emotional state and proposes adjusting the user's workload according to their emotional state. It then adjusts the workload using the TaskScheduler library according to the user's instructions. It also automatically generates work reports and progress reports using a generative AI model.

[0452] Specific examples

[0453] For example, if a user working in a factory feels stressed, the emotion recognition camera detects this state, and the server suggests adjusting the user's workload and readjusts the work schedule using the TaskScheduler library according to the user's instructions.Furthermore, based on the supervisor's instructions, the server automatically generates a work report or progress report using a generative AI model and sends it to the supervisor in PDF format.

[0454] An example prompt to write a business report: After accepting the user's work history and performance data, the system will say, "This is the user's work history and performance data. Please create a work report based on this data."

[0455] An example of a prompt that suggests the best course of action for the user's task is: After accepting the user's work history and performance data, the system asks, "This is the user's work history and performance data. Based on this data, please suggest the optimal procedure for the user's work."

[0456] Prompt to suggest optimal workload for user's work: After receiving the user's work history, the system will say, "This is the user's work history. The user is feeling stressed. Please suggest the optimal workload for the user's work."

[0457] In this way, the server can improve the user's work efficiency, create documents in line with the supervisor's decisions, and adjust the workload according to the user's emotional state.

[0458] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0459] Step 1:

[0460] The server collects users' work history and performance data. The input includes users' work logs and performance metrics. This data is stored in a database for later analysis. The output is the collected data stored in a database.

[0461] Step 2:

[0462] The server uses the EmotionEngine library to recognize the user's emotional state. The input includes real-time video data acquired from an emotion-recognition camera. The video data is analyzed to identify the user's emotional state (e.g., stress, joy, fatigue, etc.). The output is the recognized emotional state.

[0463] Step 3:

[0464] The server Based on the user's work history and the recognized emotional state, the system proposes an optimal workload for the user's work based on a prompt sentence and a generative AI model. The system also uses the TaskScheduler library to adjust the workload according to the user's instructions. The inputs include the user's emotional state and current task schedule. If the emotional state is "stressed," the system reevaluates task priorities and suggests readjusting the schedule to reduce the workload. The schedule is readjusted according to the user's instructions. The output is the adjusted task schedule.

[0465] Step 4:

[0466] The server creates a business report or progress report based on a prompt statement instructing the server to create a business report or progress report based on the user's work history and performance data, and based on the generative AI model. The input includes instructions for the business report or progress report, the user's work history, and performance data. Based on this data, the server generates a report in a specified format. The generated report is obtained as the output.

[0467] Step 5:

[0468] The server converts the generated report to PDF format and sends it to the manager. The input contains the generated report, converts the report to PDF format and sends it to the manager's email address, and the output is a notification that the report has been sent.

[0469] Step 6:

[0470] The server proposes optimal procedures for the user's work based on a prompt that instructs the server to propose optimal procedures for the user's work based on the user's work history and performance data, and based on a generative AI model. The input includes past work history and performance data. The server analyzes this data to identify efficient work procedures. The output is the proposed work procedures.

[0471] Step 7:

[0472] The server notifies the user of the proposed work procedure. The input includes the proposed work procedure. The server sends a notification to the user's device and displays the work procedure. The output allows the user to confirm the proposed work procedure.

[0473] Through these steps, the server can improve the user's work efficiency, create documents in line with the supervisor's decision-making, and adjust the workload according to the user's emotional state.

[0474] Example 2

[0475] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0476] With conventional work management systems, it was difficult for managers to grasp the work progress and emotional state of their subordinates in real time, making it difficult to respond appropriately and quickly. Additionally, creating and reviewing documents required a lot of time and effort, which led to reduced work efficiency.

[0477] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for possessing a task AI corresponding to each user, means for assisting in document creation in accordance with the supervisor's decision-making, means for quickly creating documents in line with the supervisor's preferences, means for reducing the man-hours required for document review, means for identifying subordinates' difficulties and thoughts, means for having an agent who understands the user's work even when the person in charge is absent, means for promoting the penetration of corporate culture, means for collecting users' work history and performance data and storing them in a database, means for analyzing the user's work progress and problems using a data analysis tool, means for generating a report based on the analysis results and sending it to the supervisor's terminal, means for using an emotion engine to analyze the user's emotional state, and means for generating an emotion report based on the emotion analysis results and sending it to the supervisor's terminal. This allows the supervisor to grasp the subordinate's work progress and emotional state in real time and take appropriate action promptly.

[0478] "Business AI" is an artificial intelligence system that analyzes a user's work history and performance data to identify the progress of work and problems.

[0479] A "database" is an information management system for storing users' work history and performance data.

[0480] A "data analysis tool" is software that analyzes collected data and identifies the user's business progress and problems.

[0481] An "emotion engine" is software that analyzes a user's emotional state and generates an emotion report.

[0482] A "report" is a document generated based on the analysis results, and includes the user's work progress, problems, and emotional state.

[0483] A "terminal" is an electronic device such as a computer or smartphone used by a supervisor.

[0484] An "agent" is a system that keeps track of a person's work and acts on their behalf when they are not present.

[0485] "Corporate culture" refers to the values ​​and code of conduct shared within a company.

[0486] "Means to assist in document creation" is a support system for creating documents in accordance with the supervisor's decision-making.

[0487] "Means to reduce document review man-hours" is a system for reducing the time and effort required to check and correct documents.

[0488] This invention is a system that analyzes the work history and performance data of users, enabling a supervisor to grasp the work progress and emotional state of their subordinates in real time. Specific embodiments of this system are described below.

[0489] Data analysis and reporting using business AI

[0490] The server collects users' work history and performance data and stores it in a database. Specifically, it obtains data from the business applications used by users (e.g., project management tools, task management tools). The server obtains data from project management tools (e.g., JIRA, Trello) via API and stores it in a MySQL database.

[0491] The server then analyzes the collected data, using data analysis tools such as Python and R to identify the user's progress and problems. The server runs a Python script to read the data from the database and calculates task completion times and error rates using data analysis libraries (e.g., Pandas, NumPy). The analysis results are saved in JSON format.

[0492] The server then generates a report based on the analysis results and sends it to the supervisor's terminal.The server then generates a report in HTML format based on the analysis results and sends it to the supervisor's terminal via the mail server.

[0493] Examples:

[0494] Data collection: The server retrieves data from the project management tool and stores it in a MySQL database.

[0495] Data analysis: Use Python to calculate task completion times and error rates.

[0496] Report generation: Generate an HTML report based on the analysis results and send it to the supervisor's device.

[0497] Example prompt for a generative AI model:

[0498] Analyze user progress and issues based on user work history and performance data, and generate reports.

[0499] Emotion engine reports emotional state

[0500] The server collects data necessary to analyze the user's emotional state. Specifically, it acquires the user's text messages and voice data. The server acquires text messages from chat applications (e.g., Slack, MICROSOFT® TEAMS®), and voice data is converted to text using a speech recognition API (e.g., Google® Speech-to-Text).

[0501] The server then analyzes the collected data using an emotion engine, which identifies the user's emotional state. The server calls the IBM Watson® Tone Analyzer API to analyze the text data, and the emotional state (e.g., happy, sad, angry) is identified, and the results are stored in JSON format.

[0502] The server then generates an emotion report based on the analysis results and sends it to the superior's terminal.The server then generates an emotion report in HTML format based on the analysis results and sends it to the superior's terminal via a mail server.

[0503] Examples:

[0504] Data collection: The server retrieves text messages from the chat application and converts the voice data into text using a speech recognition API.

[0505] Sentiment Analysis: Uses the IBM Watson Tone Analyzer API to analyze text data and identify emotional states.

[0506] Report generation: An HTML-formatted emotion report is generated based on the analysis results and sent to the supervisor's device.

[0507] Example prompt for a generative AI model:

[0508] Analyze and report on the user's emotional state based on their text messages and voice data.

[0509] This system allows managers to grasp their subordinates' work progress and emotional state in real time, enabling them to respond promptly and appropriately.

[0510] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0511] Step 1: Data collection

[0512] The server collects users' work history and performance data. Specifically, it obtains data from business applications used by users (e.g., project management tools, task management tools). The server obtains data from project management tools (e.g., JIRA, Trello) via API and stores it in a MySQL database. The input is data from the business applications, and the output is the work history and performance data stored in the database.

[0513] Step 2: Data analysis

[0514] The server analyzes the collected data and uses data analysis tools such as Python and R to identify the user's work progress and problems. The server executes Python scripts to read data from the database and calculates task completion times and error rates using data analysis libraries (e.g., Pandas, NumPy). The input is the work history and performance data read from the database, and the output is JSON-formatted data that is the analysis result.

[0515] Step 3: Generate and send the report

[0516] The server generates a report based on the analysis results and sends it to the supervisor's terminal.The server generates an HTML report based on the analysis results and sends it to the supervisor's terminal via the mail server.The input is the JSON data of the analysis results, and the output is the HTML report sent to the supervisor's terminal.

[0517] Step 4: Collect emotional data

[0518] The server collects the data necessary to analyze the user's emotional state. Specifically, it obtains the user's text messages and voice data. The server obtains text messages from chat applications (e.g., Slack, Microsoft Teams) and converts the voice data into text using a speech recognition API (e.g., Google Speech-to-Text). The input is the text messages and voice data from the chat application, and the output is the data converted into text.

[0519] Step 5: Sentiment Analysis

[0520] The server analyzes the collected data using an emotion engine. The emotion engine identifies the user's emotional state. The server calls the IBM Watson Tone Analyzer API to analyze the text data, and the emotional state (e.g., happy, sad, or angry) is identified, and the results are saved in JSON format. The input is the data converted to text, and the output is JSON-formatted data indicating the emotional state.

[0521] Step 6: Generate and send sentiment reports

[0522] The server generates an emotion report based on the analysis results and sends it to the superior's device.The server generates an emotion report in HTML format based on the analysis results and sends it to the superior's device via a mail server.The input is JSON data of the emotion analysis results, and the output is the HTML emotion report sent to the superior's device.

[0523] (Application example 2)

[0524] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0525] Conventional factory robots lack the ability to analyze work history and performance data in real time and report it to managers, making it difficult for managers to immediately grasp the robot's work progress and any problems. They also lack the ability to estimate the robot's emotional state based on its movements and sensor information and report it to managers, making it impossible to detect stress levels or declines in work efficiency in the robots early on. This leads to lower factory production efficiency and delays in robot maintenance and support, which has been an issue.

[0526] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0527] In this invention, the server includes: means for owning a task AI corresponding to each user; means for assisting in the creation of documents in accordance with the supervisor's decision-making; means for quickly creating documents in line with the supervisor's preferences; means for reducing the labor required for document review; means for understanding the difficulties and thoughts of subordinates; means for having an agent that understands a person's work even when the person in charge is absent; means for promoting the spread of corporate culture; means for analyzing the work history and performance data of robots working in the factory in real time and reporting to a manager; means for estimating the emotional state of the robot based on the robot's movements and sensor information and reporting to a manager; and means for the manager to understand the robot's work progress, problems, and emotional state in real time and take appropriate action. This allows the manager to understand the robot's work progress, problems, and emotional state in real time and take appropriate action.

[0528] "Business AI" is an artificial intelligence system that responds to individual users and analyzes their work history and performance data.

[0529] "Means to assist in document creation" is a function that supports the process of creating documents in accordance with the supervisor's decision-making.

[0530] "Means to reduce document review man-hours" refers to a function that reduces the time and effort required to check and correct documents.

[0531] "A means of understanding the problems and thoughts of subordinates" is a function that collects the problems and opinions that subordinates are facing and reports them to their superiors.

[0532] "A means to have an agent who understands the work of a person even when the person in charge is absent" is a function that has an agent who understands the work content and can act on behalf of the person in charge even when the person in charge is absent.

[0533] "Means to promote the dissemination of corporate culture" refers to the function of spreading and helping employees understand the company's values ​​and code of conduct.

[0534] "A means of analyzing the work history and performance data of robots working in factories in real time and reporting to managers" is a function that instantly analyzes the work history and performance data of factory robots and conveys the results to managers.

[0535] "Means of estimating the emotional state of a robot based on its movements and sensor information and reporting it to an administrator" is a function that uses data obtained from the robot's movements and sensors to infer the emotional state of a robot and conveys that information to an administrator.

[0536] "A means for managers to grasp the robot's work progress, problems, and emotional state in real time and take appropriate action" is a function that allows managers to instantly check the robot's work status, problems, and emotional state and take appropriate measures.

[0537] The system for implementing this invention has the function of analyzing the work history and performance data of robots working in a factory in real time and reporting the results to managers. It also has the function of estimating the emotional state of the robot based on the robot's movements and sensor information and reporting the results to managers.

[0538] 1. System Program

[0539] The system is implemented using the following hardware and software.

[0540] Hardware: Factory robots (e.g., KUKA, ABB), sensors (e.g., accelerometers, temperature sensors)

[0541] Software: Python, data analysis libraries (e.g., pandas, numpy), machine learning libraries (e.g., scikit-learn)

[0542] 2. Program processing explanation

[0543] The server stores the work history and performance data collected from the factory robots in a database. It then uses a machine learning model to estimate the robot's emotional state. This allows managers to understand the robot's work progress, problems, and emotional state in real time and take appropriate action.

[0544] Specifically, the server performs the following process.

[0545] 1. Collect the robot's work history and performance data and store it in a database.

[0546] 2. Use machine learning models to estimate the emotional state of the robot.

[0547] 3. Report the results of the estimation to the administrator.

[0548] 3. Specific Examples

[0549] For example, when a robot assembles parts, the success rate and work time are recorded. Based on the robot's operation data, the stress level can be estimated and reported to the manager, who can then take appropriate measures to improve the robot's work efficiency.

[0550] Example prompt for a generative AI model:

[0551] Please estimate the robot's emotional state based on its work history and performance data. Please use the following data:

[0552] Work history: [Success / Failure]

[0553] Performance data: [Work time, number of errors]

[0554] In this way, a factory robot operation monitoring and emotion analysis system can be realized.

[0555] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0556] Step 1:

[0557] The server collects work history and performance data from factory robots. Specifically, it obtains data such as the success rate, work time, and number of errors of the robot's work from sensors and the robot's internal logs. The input is the robot's sensor information and internal logs, and the output is the collected work history and performance data.

[0558] Step 2:

[0559] The server stores the collected business history and performance data in a database. Specifically, it uses a database management system (e.g., MySQL or PostgreSQL) to store the data in an appropriate format. The input is the collected business history and performance data, and the output is the data stored in the database.

[0560] Step 3:

[0561] The server uses a machine learning model based on the stored data to estimate the robot's emotional state. Specifically, it preprocesses the data using a data analysis library (e.g., pandas, numpy) and estimates the emotional state using a machine learning library (e.g., scikit-learn). The input is the work history and performance data stored in the database, and the output is the estimated emotional state.

[0562] Step 4:

[0563] The server reports the estimated emotional state to the administrator by sending a notification to the administrator's device and displaying it on a dashboard. The input is the estimated emotional state, and the output is the emotional state reported to the administrator.

[0564] Step 5:

[0565] Based on the reported emotional state, the manager can understand the robot's work progress and any problems and take appropriate action. Specifically, the manager checks the dashboard and adjusts the robot's work schedule or performs maintenance as necessary. The input is the reported emotional state and work history, and the output is the manager's response.

[0566] Example 3

[0567] Next, a description will be given of a third embodiment of the third embodiment. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0568] With conventional work support systems, work often stalls when the person in charge is absent, and work adjustments do not take into account the user's emotional state, resulting in problems that decrease work efficiency and increase user stress.Furthermore, there is a lack of means to create materials that align with supervisors' decision-making and to promote the spread of corporate culture, making it difficult to improve the performance of the entire organization.

[0569] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0570] In this invention, the server includes means for owning a task AI corresponding to each user, means for assisting in the creation of documents in accordance with the supervisor's decision-making, means for quickly creating documents in line with the supervisor's preferences, means for reducing the man-hours required for document review, means for understanding the difficulties and thoughts of subordinates, means for having an agent that understands a person's work even when the person in charge is absent, means for promoting the penetration of corporate culture, means for monitoring the user's emotional state in real time, means for training the task AI based on the user's emotional state, and means for adjusting work in accordance with the user's emotional state.This allows work to continue even when the person in charge is absent, and by adjusting work taking the user's emotional state into consideration, it is possible to improve work efficiency and reduce user stress.

[0571] "Business AI" is artificial intelligence that learns from a user's work history and performance data and acts on their behalf or assists them in their work.

[0572] "Means to assist in the creation of documents in line with the supervisor's decision-making" refers to a function that allows the necessary documents to be created quickly and accurately based on the supervisor's instructions and intentions.

[0573] "A means for quickly creating materials that meet the boss's preferences" is a function for efficiently creating materials that meet the boss's preferences and requests.

[0574] "Means to reduce document review man-hours" is a function for reducing the time and effort required to check and correct documents.

[0575] "A means of understanding subordinates' problems and thoughts" is a function that allows superiors to collect the problems and opinions that subordinates are facing and understand them.

[0576] "A means to have an agent who understands a person's work even when the person in charge is absent" is a function that provides an agent who understands a person's work and can act on their behalf even when the person in charge is absent.

[0577] "Means to promote the dissemination of corporate culture" is a function for spreading and establishing the company's values ​​and code of conduct among employees.

[0578] "Means for monitoring the user's emotional state in real time" is a function for observing the user's emotions in real time and collecting them as data.

[0579] "Means for training business AI based on the user's emotional state" is a function that enables business AI to learn based on collected emotional data and respond according to the user's emotions.

[0580] The "means for adjusting work in accordance with the user's emotional state" is a function for appropriately adjusting the progress and content of work in consideration of the user's emotional state.

[0581] The present invention provides a system that performs tasks on behalf of a user based on the user's task history and emotional state, and supports the user in performing the tasks efficiently. Specific embodiments of this system will be described below.

[0582] Data collection and storage

[0583] The server collects users' work history and performance data. Specifically, it obtains data from the business applications (e.g., office suites, cloud services) used by the users. This is often done using APIs. The collected data is stored in a relational database (e.g., MySQL, PostgreSQL).

[0584] Example: A server periodically retrieves the change history of documents and spreadsheets created by users and stores it in a database.

[0585] Data analysis and learning

[0586] The server analyzes the collected data and identifies the user's business patterns using machine learning algorithms (e.g., random forests and support vector machines). The analysis results are fed back to the business AI.

[0587] Example: A server analyzes the frequency and duration of tasks a user performs each week and finds patterns, for example, determining that a user creates reports every Monday.

[0588] Business agency

[0589] Business AI performs tasks on behalf of users based on the analysis results. Specifically, it automatically executes tasks that users should perform. Business AI is built using machine learning frameworks such as TensorFlow and PyTorch.

[0590] Example: Business AI automatically creates a report every Monday and sends it to the boss, even if the user is not present.

[0591] Collecting Emotional Data

[0592] The device monitors the user's emotional state in real time using wearable devices (e.g., smartwatches) and camera-based facial recognition software (e.g., facial recognition APIs), and the collected data is sent to a server.

[0593] Example: The device collects the user's heart rate and facial expression data and sends it to a server.

[0594] Emotional Data Analysis

[0595] The emotion engine analyzes the collected emotion data and identifies the user's emotional state using emotion recognition algorithms (e.g., deep learning models). The analysis results are fed back to the business AI.

[0596] Example: An emotion engine identifies when a user is stressed when performing a particular task.

[0597] Emotion-based work adjustments

[0598] Based on feedback from the emotion engine, the business AI responds to the user's emotional state by automating or helping them perform stressful tasks more efficiently.

[0599] Example: Business AI automates tasks that users find frustrating, so they don't have to do them.

[0600] Prompt Sentence Examples

[0601] 1. "Auto-generate this week's report based on the user's past report data."

[0602] 2. "Identify a task that users find frustrating and suggest ways to automate it."

[0603] In this way, the system performs tasks on behalf of the user based on the user's task history and emotional state, and supports the user in performing the tasks efficiently. The flow of the identification process in the third embodiment will be described with reference to FIG.

[0604] Step 1:

[0605] Data collection and storage

[0606] The server collects users' work history and performance data. Specifically, it obtains data from the business applications (e.g., office suites, cloud services) used by the user via API. The input is the change history of the user's documents and spreadsheets, and the output is stored in a relational database (e.g., MySQL, PostgreSQL). Specifically, the server periodically calls the API to obtain the latest data and adds it to the database.

[0607] Step 2:

[0608] Data analysis and learning

[0609] The server analyzes the collected data and identifies the user's work patterns. The input is the work history data stored in the database, and the output is the analysis results. This is done using a machine learning algorithm (e.g., random forest, support vector machine). Specifically, the server periodically reads data from the database, inputs it into the machine learning model, analyzes it, and identifies the user's work patterns.

[0610] Step 3:

[0611] Business agency

[0612] Business AI performs tasks on behalf of the user based on the analysis results. The analysis results are input, and the tasks that the user should perform are automatically executed as output. Specifically, business AI is built using machine learning frameworks such as TensorFlow and PyTorch. Specifically, business AI schedules tasks based on the analysis results and executes them automatically. For example, even if the user is absent, it can automatically create a report every Monday and send it to the supervisor.

[0613] Step 4:

[0614] Collecting Emotional Data

[0615] The device monitors the user's emotional state in real time. The input is data from a wearable device (e.g., a smartwatch) or camera-based facial expression recognition software (e.g., a facial recognition API), and the output is the collected emotional data sent to a server. Specifically, the device collects the user's heart rate and facial expression data in real time and sends it to the server.

[0616] Step 5:

[0617] Emotional Data Analysis

[0618] The emotion engine analyzes the collected emotion data and identifies the user's emotional state. The input is the emotion data sent from the server, and the output is the analysis result. This is done using an emotion recognition algorithm (e.g., deep learning model). Specifically, the emotion engine analyzes the emotion data and identifies that the user is feeling stressed when performing a specific task.

[0619] Step 6:

[0620] Emotion-based work adjustments

[0621] The business AI responds according to the user's emotional state based on feedback from the emotion engine. The input is the analysis results from the emotion engine, and the output is work adjustments according to the user's emotional state. Specifically, the business AI automates stressful tasks so that the user does not have to perform them. For example, it identifies tasks that cause stress to the user and proposes ways to automate those tasks.

[0622] (Application example 3)

[0623] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0624] With conventional work support systems, work often stalls when the person in charge is absent, which can lead to a decline in productivity, especially in factory work. Furthermore, by carrying out work without taking into account the emotional state of the workers, stress and fatigue accumulate, leading to a decline in work efficiency.

[0625] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes means for possessing a task AI corresponding to each user, means for assisting in document creation in accordance with the supervisor's decision-making, means for quickly creating documents in line with the supervisor's preferences, means for reducing the man-hours required for document review, means for identifying subordinates' difficulties and thoughts, means for having an agent that understands a person's work even when the person in charge is absent, means for promoting the spread of corporate culture, means for being installed in robots responsible for work in the factory and continuing work even when the person in charge is absent, means for the task AI to accumulate the work history and performance data of factory workers, understand the worker's emotional state using an emotion engine, and take appropriate action, and means for monitoring the worker's emotional state in real time using a heart rate sensor and a face recognition camera and automatically taking over the work if stress is detected. This allows work to continue uninterrupted even when the person in charge is absent, and enables work support that takes the worker's emotional state into consideration.

[0626] "Business AI" is an artificial intelligence system that accumulates users' work history and performance data and performs or supports work on their behalf.

[0627] "A means to assist in the creation of documents in line with the supervisor's decision-making" is a system that has the function of assisting in the creation of documents based on the supervisor's instructions and intentions.

[0628] "A means for quickly creating materials that meet the superior's preferences" is a system that has the function of quickly creating materials that meet the superior's preferences and requests.

[0629] A "means for reducing document review labor" is a system that has the function of reducing the time and effort required to check and correct documents.

[0630] "A means of understanding the problems and thoughts of subordinates" is a system that has the ability to understand the problems and opinions that subordinates are facing and respond appropriately.

[0631] "A means to have an agent who understands the person's work even when the person in charge is absent" is a system that has the function of having an agent who can take over the person's work even when the person in charge is absent.

[0632] "Means to promote the dissemination of corporate culture" are systems that have the function of spreading and establishing the company's values ​​and code of conduct among employees.

[0633] "A means to be installed on robots that perform work within a factory, allowing them to continue operations even when the person in charge is absent" refers to a system that is installed on robots that perform work within a factory, and has the function of allowing them to continue operations even when the person in charge is absent.

[0634] "A means for business AI to accumulate work history and performance data of factory workers, use an emotion engine to understand the emotional state of the workers, and take appropriate action" refers to a system that has the function of collecting work history and performance data of factory workers, using an emotion engine to understand the emotional state of the workers, and taking appropriate action.

[0635] "Means for monitoring the emotional state of workers in real time using heart rate sensors and facial recognition cameras, and automatically taking over work if stress is detected" is a system that uses heart rate sensors and facial recognition cameras to monitor the emotional state of workers in real time, and has the function of automatically taking over work if stress is detected.

[0636] A system for implementing this invention includes a program installed on a robot in charge of work in a factory. The system uses task AI, an emotion engine, a heart rate sensor, and a facial recognition camera to continue work even when the person in charge is absent and monitors the emotional state of the worker in real time.

[0637] The server first stores the work history and performance data of factory workers, including the tasks they have performed in the past, their results, and the time it took to complete the tasks. It then uses an emotion engine to understand the worker's emotional state. The emotion engine analyzes data obtained from heart rate sensors and facial recognition cameras to determine whether the worker is experiencing stress.

[0638] If the server determines that a worker is feeling stressed, it automatically instructs a robot to take over the task. This reduces worker stress and improves work efficiency. The task AI also learns to optimize work based on the worker's work history and performance data. This further improves work efficiency.

[0639] As a concrete example, consider the case where a factory worker feels stressed while performing a specific assembly task. A heart rate sensor detects an increase in the worker's heart rate, and a facial recognition camera reads stress from the worker's facial expression. An emotion engine analyzes this data to determine the worker's stress level. If stress is detected, the task AI instructs a robot to take over the task, allowing the worker to move on to other tasks.

[0640] An example of a prompt sentence might be:

[0641] "Based on the work history and performance data of factory workers, please use an emotion engine to understand their emotional state, and design a system in which a robot will automatically take over the work if the worker feels stressed."

[0642] In this way, a system can be realized that can improve the efficiency of work within a factory and reduce the stress of workers.

[0643] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0644] Step 1:

[0645] The server collects the work history and performance data of factory workers and stores it in a database. As input, it receives data such as the worker's work content, work time, and results, and stores this in the database. As output, it obtains the accumulated work history data.

[0646] Step 2:

[0647] The server receives data in real time from the heart rate sensor and facial recognition camera. As input, it receives the worker's heart rate data and facial recognition data and sends them to the emotion engine. As output, it obtains the raw data sent to the emotion engine.

[0648] Step 3:

[0649] The server uses an emotion engine to analyze the worker's emotional state. As input, it receives heart rate data and facial recognition data, analyzes them, and determines the worker's emotional state (e.g., stress level). As output, it obtains emotional state data as the analysis result.

[0650] Step 4:

[0651] The server determines whether the worker is feeling stressed based on the emotional state data. As input, it receives the emotional state data and determines whether the worker is feeling stressed. As output, it obtains the result of the stress state determination.

[0652] Step 5:

[0653] If a stress state is detected, the server instructs the robot to take over the work. As input, it receives the stress state assessment result and sends a work handover instruction to the robot. As output, it obtains instruction data for the robot to take over the work.

[0654] Step 6:

[0655] The robot receives instructions from the server and takes over the work. As input, it receives instructions to take over the work from the server and starts the actual work. As output, it obtains data on the progress of the work.

[0656] Step 7:

[0657] The server monitors the robot's work progress and issues additional instructions as needed. As input, it receives work progress data from the robot, analyzes it, and generates the necessary instructions. As output, it obtains additional instruction data.

[0658] In this way, the server can monitor the work history and emotional state of factory workers in real time, and by having robots take over the work as needed, it is possible to reduce worker stress and improve work efficiency.

[0659] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0660] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0661] Another example of generative AI is Gemini (registered trademark) (Internet search engine). <url: https: gemini.google.com ?hl="ja">) are listed.

[0662] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0663] [Second embodiment]

[0664] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0665] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0666] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0667] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0668] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0669] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0670] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0671] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

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

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

[0674] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0675] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0676] "Example 1"

[0677] As one embodiment of the present invention, a system is provided that has a business AI that corresponds to each individual user. This business AI learns the user's work history and performance data, and assists in the creation of documents in line with the supervisor's decision-making. Specifically, the AI ​​provides the user with templates, formats, and necessary information for the documents they create, and the user creates the documents based on this. This makes it possible to create documents that meet the supervisor's preferences in a short amount of time.

[0678] "Example 2"

[0679] Furthermore, as another embodiment of the present invention, a means is provided for understanding the problems and thoughts of subordinates. Specifically, the business AI analyzes the user's work history and performance data and reports the results to the superior. This allows the superior to understand the progress and problems of the subordinate's work in real time.

[0680] "Example 3"

[0681] Furthermore, as a further embodiment of the present invention, a system is provided in which an agent that understands the work of a person in charge exists even when the person in charge is absent. Specifically, the task AI accumulates the user's work history and performance data and performs the work on behalf of the person in charge based on that data. This allows the person to continue their work even when the person in charge is absent.

[0682] The processing flow of each embodiment will be described below.

[0683] "Example 1"

[0684] Step 1: The business AI collects the user's work history and performance data.

[0685] Step 2: The business AI learns based on the collected data.

[0686] Step 3: The business AI assists in the creation of documents in line with the supervisor's decision-making. Specifically, the AI ​​provides templates, formats, and necessary information for the documents the user creates. Step 4: The user creates the documents based on the information provided by the AI.

[0687] "Example 2"

[0688] Step 1: Business AI analyzes the user's work history and performance data.

[0689] Step 2: The business AI reports the analysis results to its superiors.

[0690] Step 3: Based on the report, the supervisor understands the progress and problems of the subordinate's work.

[0691] "Example 3"

[0692] Step 1: The business AI accumulates the user's work history and performance data.

[0693] Step 2: The business AI performs the business operations based on the accumulated data.

[0694] Step 3: Even if the person in charge is absent, the task AI continues the person's work.

[0695] Example 1

[0696] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0697] In the conventional document creation process, users had to spend a lot of time and effort creating documents that met their superiors' preferences, resulting in inefficiency. In addition, there was a lack of means to assist in creating documents that aligned with the superiors' decision-making, which made it difficult to reduce the man-hours required for document review and identify points of difficulty for subordinates. Furthermore, there was no agent to keep track of the work of the person in charge when they were absent, which sometimes disrupted the continuity of work. To solve these issues, a system was needed that utilized users' work history and performance data to efficiently assist in document creation.

[0698] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0699] In this invention, the server includes a means for owning a business AI corresponding to each user, a means for collecting the user's work history and performance data, a means for training the business AI using the collected data, a means for generating templates and formats according to the user's requests using a generative AI model, a means for providing the generated templates and formats to the user, a means for assisting in the creation of documents in line with the supervisor's decision-making, a means for quickly creating documents in line with the supervisor's preferences, a means for reducing the labor required for document review, a means for grasping the subordinate's difficulties and thoughts, a means for having an agent that understands the subordinate's work even when the person in charge is absent, and a means for promoting the penetration of corporate culture. This allows users to efficiently create documents in line with the supervisor's preferences, reduces the labor required for document review, and makes it easier to grasp the subordinate's difficulties. Furthermore, business continuity is ensured even when the person in charge is absent, promoting the penetration of corporate culture.

[0700] "Business AI" is an artificial intelligence system that learns from a user's work history and performance data and assists in document creation.

[0701] "User's work history" refers to data that refers to records and deliverables of work that a user has done in the past.

[0702] "Performance data" refers to data that indicates the results and evaluations of a user's work.

[0703] "Means for collection" refers to methods or devices for acquiring a user's work history and performance data.

[0704] "Training means" refers to methods or devices for training business AI using collected data.

[0705] A "generative AI model" is an artificial intelligence model that generates templates and formats according to user requests.

[0706] "Templates and formats" refer to standard structures and formats used when creating documents.

[0707] The "means for providing" refers to a method or device for delivering the generated template or format to the user.

[0708] "Means for assisting in the preparation of documents in line with decision-making" refers to methods or devices for supporting the preparation of documents based on the decision-making of a superior.

[0709] "Means for reducing document review man-hours" refers to methods and devices for reducing the time and effort required to check and correct documents.

[0710] "Means for grasping difficult points and thoughts" are methods or devices for understanding the problems and opinions that subordinates are facing.

[0711] An "agent that understands a person's work even when the person in charge is absent" is an artificial intelligence system that can understand a person's work and perform it on their behalf even when the person in charge is absent.

[0712] "Means to promote corporate culture" are methods and devices for spreading the company's values ​​and code of conduct to employees.

[0713] MODE FOR CARRYING OUT THE INVENTION

[0714] This invention is a system that has a task AI corresponding to each user and assists in creating documents in accordance with the decision-making of the superior. A specific embodiment of this system will be described below.

[0715] Server Roles

[0716] The server generates a business AI for each user. This business AI uses Python and TensorFlow to collect and learn from the user's work history and performance data. The server uses this data to train a machine learning model and provides a function to assist in creating documents tailored to the user's supervisor's decision-making.

[0717] Specifically, the server retrieves user work history and performance data from a database (e.g., MySQL). After collecting the data, the server preprocesses it and inputs it into a machine learning model. It normalizes the data, performs feature engineering, and converts it into a format suitable for the model. Then, it trains the model using TensorFlow.

[0718] Device Role

[0719] When a user creates a document, the device receives templates, formats, and necessary information provided by the business AI. The device displays this information and helps the user create documents efficiently. Specifically, the device retrieves data from the server using a web browser (e.g., Google Chrome) and displays it on the user interface.

[0720] The terminal displays the template received from the server on a web page. Using HTML and JavaScript, the template is dynamically generated and displayed in a format that is easy for the user to view.

[0721] User Roles

[0722] Users create documents based on templates and formats provided by the business AI through their devices. By utilizing the information provided by the business AI, they can quickly create documents that meet their superiors' preferences.

[0723] For example, if a user wants to create a "sales report," the business AI will provide past sales data and the boss's preferred format. The user then enters the necessary data into the provided template to complete the document. The completed document is saved in PDF format and submitted to the boss.

[0724] Specific examples

[0725] An example of a prompt sentence to be input into a generative AI model is, "Please provide a template for creating a sales report in my boss's preferred format based on the sales data from the past three months." When this prompt sentence is input into the generative AI model, the business AI analyzes the past sales data and generates a sales report template based on the boss's preferred format. Based on this template, the user can create a high-quality sales report in a short amount of time.

[0726] In this way, a system is realized in which the server, terminals, and users can work together to efficiently create materials.

[0727] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0728] Step 1:

[0729] The server collects users' work history and performance data.

[0730] Input: User ID

[0731] Data processing: The server queries a database (e.g., MySQL) to retrieve user activity history and performance data.

[0732] Output: Acquired business history and performance data

[0733] Specific operation: The server executes the query "SELECT FROM user_performance WHERE user_id = '12345'" to retrieve the data.

[0734] Step 2:

[0735] The server preprocesses the collected data and converts it into a format suitable for machine learning models.

[0736] Input: Acquired work history and performance data

[0737] Data processing: Data normalization and feature engineering.

[0738] Output: Preprocessed data

[0739] Specific behavior: The server imputes missing values ​​in the data, normalizes numerical data, and performs one-hot encoding on categorical data.

[0740] Step 3:

[0741] The server uses the preprocessed data to train the business AI.

[0742] Input: Preprocessed data

[0743] Data Computing: Training machine learning models using TensorFlow.

[0744] Output: Trained business AI model

[0745] Specific operation: The server executes the code "model.fit(training_data, labels, epochs=10)" to train the model.

[0746] Step 4:

[0747] The server uses a generative AI model to generate templates and formats based on the user's requests.

[0748] Input: User request (prompt)

[0749] Data calculation: Input prompts into the generative AI model to generate templates and formats.

[0750] Output: Generated templates and formats

[0751] Specific operation: The server inputs the prompt statement "Please provide a template for creating a sales report in the format preferred by your boss based on the sales data from the past three months" into the generative AI model.

[0752] Step 5:

[0753] The terminal displays the templates and formats provided by the server to the user.

[0754] Input: Generated templates and formats

[0755] Data processing: Converting templates and formats into a format that can be displayed on a web page.

[0756] Output: The template or format that is displayed to the user

[0757] Specific behavior: The terminal uses HTML and JavaScript to dynamically generate a template and executes the code "document.getElementById('template').innerHTML = receivedTemplate;".

[0758] Step 6:

[0759] The user creates materials based on the templates and formats displayed on the terminal.

[0760] Input: Displayed template or format

[0761] Data processing: Enter the necessary data and complete the materials.

[0762] Output: Finished document

[0763] Specific operation: The user enters sales data and other information into the provided template to complete the document. The completed document is saved in PDF format and submitted to a supervisor.

[0764] (Application example 1)

[0765] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0766] Conventional work support systems were unable to fully utilize the work history and performance data of individual users, making it difficult to create documents and optimize work instructions in line with supervisors' decision-making. Furthermore, the efficiency and optimization of work instructions for factory robots was not sufficiently implemented, making it difficult to improve work efficiency.

[0767] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0768] In this invention, the server includes: means for owning a task AI corresponding to each user; means for assisting in the creation of documents in line with the supervisor's decision-making; means for quickly creating documents in line with the supervisor's preferences; means for reducing the man-hours required for document review; means for understanding the difficulties and thoughts of subordinates; means for having an agent that understands a person's work even when the person in charge is absent; means for promoting the penetration of corporate culture; means for a factory robot to receive work instructions and provide optimal work procedures; means for learning work history and performance data and generating optimal work procedures; and means for providing work procedures based on the manager's instructions. This improves the work efficiency of users and enables the optimization of work instructions for factory robots.

[0769] "Business AI" is an artificial intelligence system that responds to individual users, learns their work history and performance data, and supports their work.

[0770] "Supervisor's decision-making" refers to the judgments and instructions given by a supervisor in the course of work.

[0771] "Means to assist in document creation" refers to a function that provides templates, formats, and necessary information for documents created by users.

[0772] "Document review man-hours" refers to the time and effort required to review and correct created documents.

[0773] "A means to understand the problems and thoughts of subordinates" is a function that collects and analyzes the problems and thoughts that subordinates face in the course of their work.

[0774] An "agent that understands a person's work even when the person in charge is absent" is a system that can understand a person's work and handle it on their behalf even when the person in charge is absent.

[0775] "Means to promote the dissemination of corporate culture" refers to the function of helping employees understand and practice the company's values ​​and code of conduct.

[0776] A "factory robot" is a mechanical device used to automate work within a factory.

[0777] The "means for receiving work instructions and providing optimal work procedures" is a function that allows a factory robot to receive instructions and generate and provide optimal work procedures.

[0778] "Means for learning work history and performance data and generating optimal work procedures" is a function that learns and generates optimal work procedures based on past work history and performance data.

[0779] The "means for providing work procedures based on the manager's instructions" is a function for providing specific work procedures to factory robots based on the manager's instructions.

[0780] The system for implementing this invention consists of three main elements: a server, a terminal, and a user. The server has a business AI that corresponds to each user and has a function to assist in the creation of documents in line with the supervisor's decision-making. It also has a function to quickly create documents that meet the supervisor's preferences and reduce the labor required for document review. Furthermore, the system includes functions that can grasp the points of difficulty and thoughts of subordinates, a function to have an agent that understands the person's work even when the person in charge is absent, and a function to promote the penetration of corporate culture.

[0781] The server also has the function of allowing factory robots to receive work instructions and provide optimal work procedures. Specifically, it has the function of learning work history and performance data to generate optimal work procedures, and the function of providing work procedures based on instructions from managers.

[0782] The system's program is implemented using Python and the scikit-learn library. The server stores users' work history and performance data in JSON format, and uses this data to learn optimal work procedures using a linear regression model. Specifically, the system reads the user's work history data, extracts features and performance data, and uses a linear regression model to learn from them. It then generates new work procedures based on the manager's instructions and calculates predicted performance.

[0783] The terminal is a device that allows users to receive document templates and work procedures provided by the server and create documents and perform tasks based on them. Terminals include PCs, tablets, smartphones, etc.

[0784] Users perform their work based on document templates and work procedures provided by the server. The documents and work results created by the users are sent back to the server and stored as work history.

[0785] As a concrete example, consider the case where a factory robot performs assembly work. The manager instructs the "assembly work" and provides features such as the difficulty of the work, the required skills, and the time required. The server generates the optimal work procedure based on this and provides it to the factory robot.

[0786] Example prompt sentence:

[0787] User ID: 12345

[0788] Work Instructions: Assembly Work

[0789] Task features: [0.8, 0.6, 0.7]

[0790] Based on this prompt, the server provides optimal work procedures and predicted performance, improving user efficiency and optimizing work instructions for factory robots.

[0791] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0792] Step 1:

[0793] The server reads the user's work history data in JSON format. The input is the user ID, and the output is the user's work history data. This data includes past work content and performance.

[0794] Step 2:

[0795] The server extracts features and performance data from the loaded work history data. The input is the work history data, and the output is features and performance data. Features include the difficulty of the task, the required skills, and the time required.

[0796] Step 3:

[0797] The server trains a linear regression model using the extracted features and performance data. The inputs are the features and performance data, and the output is a trained linear regression model. This model learns the relationship between the features and performance.

[0798] Step 4:

[0799] The server receives work instructions from the manager. The input is the manager's instructions and the work's features, and the output is work instruction data. The work instruction data includes the specific work content and its features.

[0800] Step 5:

[0801] The server uses a trained linear regression model to generate optimal work procedures based on the manager's instructions. The input is the work instruction data and the trained model, and the output is the optimal work procedure. This procedure is generated based on predicted performance.

[0802] Step 6:

[0803] The server provides the generated optimal work procedure to the factory robot. The input is the optimal work procedure, and the output is work instructions for the factory robot. The factory robot performs the work based on these instructions.

[0804] Step 7:

[0805] The factory robot performs the work according to the provided work procedure. The input is the work instruction from the server, and the output is the work result. The work result is sent back to the server and accumulated as a work history.

[0806] Step 8:

[0807] The server receives the work results sent from the factory robots and stores them in a work history database. The input is the work results, and the output is updated work history data. This data is used for the next learning.

[0808] Example 2

[0809] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0810] In modern companies, it is important for managers to understand the progress and problems of their subordinates' work in real time. However, with conventional systems, it is difficult for managers to quickly and accurately grasp the points of difficulty and thoughts of their subordinates, and there are issues such as the time and effort required to create and review documents. Furthermore, when the person in charge is absent, it is difficult to understand that person's work, and corporate culture is often not fully ingrained.

[0811] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for possessing a task AI corresponding to each user, means for assisting in document creation in accordance with the supervisor's decision-making, means for quickly creating documents in line with the supervisor's preferences, means for reducing the man-hours required for document review, means for identifying the subordinate's difficulties and thoughts, means for having an agent that understands the subordinate's work even when the person in charge is absent, means for promoting the penetration of corporate culture, means for collecting the user's work history and performance data, means for preprocessing the collected data, means for inputting the preprocessed data into a generative AI model and generating analysis results, and means for reporting the generated analysis results to the supervisor. This allows the supervisor to grasp the progress and problems of the subordinate's work in real time, thereby improving the efficiency of document creation and review, understanding work even when the person in charge is absent, and promoting the penetration of corporate culture.

[0812] "Business AI" is an artificial intelligence system that analyzes users' work history and performance data to improve work efficiency and identify problems.

[0813] "User" refers to an individual employee who performs work using business AI.

[0814] "Supervisor" refers to a managerial person who oversees the progress and performance of the user's work and makes decisions.

[0815] "Work history" refers to data such as records of work a user has done in the past, task completion status, and comment history.

[0816] "Performance data" refers to data such as the results, efficiency, and evaluation of a user's work.

[0817] A "generative AI model" refers to an artificial intelligence model that analyzes collected data and generates results in text format.

[0818] A "prompt" is an instruction entered into a generative AI model to encourage it to analyze data and generate results.

[0819] "Preprocessing" refers to the process of data cleaning and normalization to prepare collected data in an analyzable format.

[0820] "Analysis Results" refers to the conclusions and suggestions regarding the progress and problems of the user's work that the generative AI model generates after analyzing the data.

[0821] "Reporting" refers to a means of communicating the generated analysis results to a superior, and includes formats such as dashboard display and email notification.

[0822] An "agent" is a system that keeps track of a person's work and provides them with the necessary information even when they are not present.

[0823] "Corporate culture" refers to the values, code of conduct, and communication style shared within a company.

[0824] This invention is a system that collects a user's work history and performance data, analyzes them using a generative AI model, and reports the results to a superior. A specific embodiment of this system will be described below.

[0825] The server obtains data from business management software and performance evaluation tools to collect users' work history and performance data. Specifically, business management software such as JIRA and Trello are used, and performance evaluation tools such as SAP SuccessFactors are used. Data is obtained from these tools via APIs.

[0826] The server then preprocesses the collected data, which includes cleaning the data (imputing missing values ​​and removing outliers) and normalizing the data (scaling and encoding). The preprocessing is performed using the Python Pandas library.

[0827] The preprocessed data is then fed into a generative AI model, OpenAI's GPT-4, which analyzes the data based on the prompt and identifies potential problems or difficulties the user may be facing.

[0828] As a concrete example, consider a case where a user is using the project management tool JIRA. The server collects the user's task completion status and comment history from JIRA. Next, it inputs the following prompt sentence to the generative AI model:

[0829] "Analyze the following work history and performance data to identify potential pain points your users may be experiencing. Data includes: task completion status, comment history, and progress reports."

[0830] The generative AI model analyzes the data based on this prompt and draws conclusions such as, "The user may be having difficulty prioritizing tasks."

[0831] Finally, the server reports the generated analysis results to the manager, who can display the results on a dashboard (e.g., Tableau or Power BI) or send them via email or a notification system, allowing the manager to keep track of the progress and issues of their subordinates' work in real time.

[0832] This system allows managers to quickly grasp the progress and problems of their subordinates' work and provide appropriate support. It also improves the efficiency of document creation and review, keeps track of work when the person in charge is absent, and promotes the penetration of corporate culture.

[0833] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0834] Step 1: Data collection

[0835] The server collects user work history and performance data. Specifically, it obtains data from work management software (e.g., JIRA, Trello) and performance evaluation tools (e.g., SAP SuccessFactors) via API. The input is raw data obtained from the API endpoint, and the output is the collected work history and performance data. For example, using the JIRA API, task completion status and comment history are obtained from the endpoint GET / rest / api / 2 / search?jql=assignee=currentUser().

[0836] Step 2: Data Preprocessing

[0837] The server preprocesses the collected data. Preprocessing includes data cleaning (filling in missing values ​​and removing outliers) and data normalization (scaling and encoding). The input is the collected raw data, and the output is the preprocessed, clean data. Specifically, it uses the Python Pandas library to fill in missing values ​​with the fillna() method and remove outliers with conditional filtering.

[0838] Step 3: Data analysis

[0839] The server inputs the preprocessed data into a generative AI model. OpenAI's GPT-4 is used as the generative AI model. The input is the preprocessed clean data and a prompt, and the output is the analysis result by the generative AI model. Specifically, the server sends the following prompt to the generative AI model:

[0840] "Analyze the following work history and performance data to identify potential pain points your users may be experiencing. Data includes: task completion status, comment history, and progress reports."

[0841] Step 4: Generate results

[0842] The generative AI model analyzes data based on the prompt and identifies problems or difficulties the user may be facing. The input is the prompt sent to the generative AI model and preprocessed data, and the output is the analysis results in text format. For example, it may conclude that "the user may be having difficulty prioritizing tasks."

[0843] Step 5: Reporting the results

[0844] The server reports the generated analysis results to the manager. The report is displayed on a dashboard used by the manager (e.g., Tableau, Power BI) or sent via email or a notification system. The input is the analysis results obtained from the generative AI model, and the output is in the form of a report for the manager. Specifically, the results are converted to JSON format and added to the dashboard using Tableau's API.

[0845] In this way, superiors can grasp the progress and problems of their subordinates' work in real time.

[0846] (Application example 2)

[0847] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0848] With conventional work management systems, it was difficult for managers to grasp the progress and problems of their subordinates in real time, which sometimes led to delays when a quick response was required. Furthermore, there was a lack of means to monitor the performance of robots operating in factories in real time and respond immediately when a problem occurred. This led to problems such as a decline in work efficiency and reduced productivity.

[0849] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for possessing a task AI corresponding to each user; means for assisting in the creation of documents in accordance with the supervisor's decision-making; means for quickly creating documents in line with the supervisor's preferences; means for reducing the labor required for document review; means for identifying the difficulties and thoughts of subordinates; means for having an agent who understands the person's work even when the person in charge is absent; means for promoting the penetration of corporate culture; means for collecting and analyzing robot work history data and reporting the results to a manager; and means for monitoring robot performance data in real time and notifying the manager if a problem occurs. This allows a manager to understand the progress and problems of their subordinates in real time, monitor the performance of robots operating in the factory in real time, and respond immediately if a problem occurs.

[0850] "Business AI" is an artificial intelligence system that analyzes a user's work history and performance data to understand the progress and problems of work.

[0851] "Means to assist in the creation of documents in line with the supervisor's decision-making" is a function for quickly creating necessary documents based on the supervisor's instructions and intentions.

[0852] "Means for quickly creating materials that meet the boss's preferences" is a function for quickly generating materials that meet the boss's preferences and requests.

[0853] "Means to reduce document review man-hours" is a function for reducing the time and effort required to check and correct documents.

[0854] "A means of understanding the problems and thoughts of subordinates" is a function that allows you to understand the problems and thoughts that your subordinates are facing in real time.

[0855] "A means to have an agent who understands the person's work even when the person in charge is absent" is a function that has an agent who understands the person's work and can handle it in their place, even when the person in charge is absent.

[0856] "Means to promote the dissemination of corporate culture" is a function that spreads and helps employees understand the company's values ​​and code of conduct.

[0857] "Means of collecting and analyzing work history data of robots and reporting the results to managers" is a function for collecting work history data of robots operating in factories and reporting the analysis results to managers.

[0858] "Means for monitoring robot performance data in real time and notifying administrators if a problem occurs" refers to a function for monitoring robot performance data in real time and immediately notifying administrators if a problem occurs.

[0859] A system for carrying out this invention comprises a server, a terminal, and a user element. The server has a task AI corresponding to each user, and includes means for assisting in the creation of documents in accordance with the decision-making of a supervisor, means for quickly creating documents in line with the supervisor's preferences, means for reducing the man-hours required for document review, means for understanding points of difficulty and thoughts of subordinates, means for having an agent that understands the work of each person even when the person in charge is absent, means for promoting the penetration of corporate culture, means for collecting and analyzing work history data of robots and reporting the results to a manager, and means for monitoring robot performance data in real time and notifying if a problem occurs.

[0860] The server uses software such as Python, pandas, and smtplib to collect the robot's work history data and monitor performance data in real time. The data is provided in CSV file format, which the server reads and records as a problem if performance falls below a certain threshold. If a problem is detected, the server reports it to the administrator by email.

[0861] As a concrete example, the robot's work history data is provided in a CSV file like this:

[0862] csv

[0863] timestamp,performance

[0864] 2023-10-01 08:00:00,85

[0865] 2023-10-01 09:00:00,65

[0866] 2023-10-01 10:00:00,90

[0867] Based on this data, the server detects time periods where performance is below 70 and records them as problems. For example, the data for 2023-10-01 09:00:00 shows performance as 65, so this is recorded as a problem.

[0868] An example of a prompt to input to a generative AI model is as follows:

[0869] "Write a Python program that analyzes the work history data of robots operating in a factory, and if the performance falls below a certain threshold, logs it as a problem and reports it to a manager via email. The data will be provided in a CSV file, and the performance threshold will be 70."

[0870] In this way, the server allows managers to understand the progress and problems of their subordinates in real time, and can monitor the performance of robots operating in the factory in real time and respond immediately if a problem occurs.

[0871] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0872] Step 1:

[0873] The server reads the robot's work history data in CSV file format. The input is a CSV file, and the output is data in data frame format. Specifically, the CSV file is converted to a data frame using the Python pandas library.

[0874] Step 2:

[0875] The server analyzes the loaded data frame and extracts performance data for each timestamp. The input is business history data in data frame format, and the output is a list of performance data. Specifically, it loops through each row of the data frame and adds the values ​​of the performance column to the list.

[0876] Step 3:

[0877] The server records a problem if the performance falls below a certain threshold (e.g., 70) based on the extracted performance data. The input is a list of performance data, and the output is a list of problems. Specifically, each value of the performance data is checked, and if it falls below the threshold, the timestamp and performance value are added to the problem list.

[0878] Step 4:

[0879] The server generates the content of the email to be reported to the administrator based on the problem list. The input is the problem list, and the output is the email body. Specifically, it loops through each item in the problem list and adds details of the problem to the email body.

[0880] Step 5:

[0881] The server sends the generated email body to the administrator. The input is the email body and the output is the sending result. Specifically, it uses the Python smtplib library to send the email to the administrator's email address via the mail server.

[0882] In this way, the server can monitor the robot's work history data in real time and immediately notify the administrator if a problem occurs.

[0883] Example 3

[0884] Next, a description will be given of Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0885] With conventional business systems, it was difficult to substitute for the person in charge when they were absent, resulting in problems of business stagnation and reduced efficiency. There were also insufficient means to create documents in line with the supervisor's decision-making, to understand the points of difficulty of subordinates, and to promote the penetration of corporate culture. Furthermore, there was no established method for effectively utilizing users' work history and performance data, making it difficult to improve business performance.

[0886] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0887] In this invention, the server includes: a means for owning a business AI corresponding to each user; a means for assisting in the creation of documents in accordance with a supervisor's decision-making; a means for quickly creating documents in line with the supervisor's preferences; a means for reducing the labor required for document review; a means for identifying subordinates' difficulties and thoughts; a means for providing an agent that understands a user's work even when the person in charge is absent; a means for promoting the penetration of corporate culture; a means for collecting a user's work history and performance data and storing it in a database; a means for analyzing the collected data and inputting prompt statements into a generative AI model to generate instructions for performing the work; and a means for sending the generated instructions to an agent, which then performs the user's work. This allows a user to continue their work even when the person in charge is absent, preventing work stagnation and improving efficiency. It also enables the creation of documents in accordance with a supervisor's decision-making, identifying subordinates' difficulties, and promoting the penetration of corporate culture. Furthermore, by effectively utilizing a user's work history and performance data, business performance can be improved.

[0888] "Business AI" is an artificial intelligence system that automates or assists business operations based on the user's work history and performance data.

[0889] "Means to assist in the creation of documents in line with the supervisor's decision-making" refers to a function that enables the necessary documents to be created quickly and accurately based on the supervisor's instructions and decisions.

[0890] "A means for quickly creating materials that meet the boss's preferences" is a function for quickly generating materials that meet the boss's preferences and requests.

[0891] "Means to reduce document review man-hours" is a function for reducing the time and effort required to check and correct documents.

[0892] "A means of understanding the problems and thoughts of subordinates" is a function for collecting and understanding the problems and opinions that subordinates are facing.

[0893] "A means to have an agent who understands a person's work even when the person in charge is absent" is a function that provides an agent who understands a person's work and can act on their behalf even when the person in charge is absent.

[0894] "Means to promote the dissemination of corporate culture" is a function that spreads and helps employees understand the company's values ​​and code of conduct.

[0895] "Means for collecting user's work history and performance data and saving it in a database" is a function for collecting data on the work history and performance of users and saving it in a database.

[0896] "Means for analyzing collected data and inputting prompt sentences into a generative AI model to generate instructions for performing tasks on behalf of others" refers to a function that analyzes collected data, inputs prompt sentences into a generative AI model based on the results, and generates specific instructions for performing tasks on behalf of others.

[0897] "Means for sending generated instructions to an agent and for the agent to perform the user's work" refers to a function that sends instructions generated from a generative AI model to an agent and for the agent to perform the user's work.

[0898] This invention provides a system that can take over a person's work even when that person is absent. Specifically, the task AI accumulates the user's work history and performance data and performs the work based on that.

[0899] The server collects data generated in real time as users perform their daily work. Specifically, it obtains work-related data (e.g., work logs, reports, email content, etc.) from the devices used by users. This is done using dedicated data collection software (e.g., Logstash).

[0900] The server stores the collected data in a database. Specifically, it uses a database management system such as MySQL to structure and store the data. A table is created in the database for each user, and each table stores work history and performance data.

[0901] The server periodically extracts data from the database and analyzes it using data analysis software (e.g., Python's Pandas library). Specifically, it analyzes user work patterns and performance trends and extracts key indicators. The results of this analysis become the basic data to input into the generative AI model.

[0902] Based on the results of the data analysis, the server generates prompts to be input into the generative AI model. Specifically, the server references the user's past work history and performance data to create prompts containing specific instructions for performing the work on behalf of the user. For example, it generates a prompt such as, "Please prepare today's report based on User A's report data from the past month."

[0903] The server inputs the generated prompt sentence into a generative AI model (e.g., OpenAI's GPT-4) to generate specific instructions for performing the task. The generated instructions are sent to the agent, which then performs the user's task. Specifically, the agent automatically creates a report, makes any necessary corrections, and submits it as the final report.

[0904] As a concrete example, consider the task of creating reports that a user performs daily. If the user is absent, the task AI automatically generates a similar report based on past report data.

[0905] Example prompt sentence:

[0906] "Please create today's report based on User A's report data from the past month."

[0907] By inputting this prompt sentence into the generative AI model, the model generates a new report by referring to past data. The generated report is checked by the agent, and after corrections are made as necessary, it is submitted as the final report. The flow of the identification process in Example 3 will be explained using Figure 15.

[0908] Step 1: Collect user data

[0909] The server collects data in real time that is generated when users perform their daily work. Specifically, it obtains work-related data (e.g., work logs, reports, email contents, etc.) from the devices used by the users. For this purpose, it uses dedicated data collection software (e.g., Logstash). The input is the user's work data, and the output is the collected work data. For example, when a user clicks the "Start creating report" button, the timestamp and user ID at that time are recorded as a log.

[0910] Step 2: Save your data

[0911] The server saves the collected data in a database. Specifically, it uses a database management system such as MySQL to structure and store the data. The input is the collected business data, and the output is the data saved in the database. A table is created for each user in the database, and each table stores work history and performance data. For example, information such as user ID, timestamp, and work content is stored in the "user_logs" table.

[0912] Step 3: Analyze the data

[0913] The server periodically extracts data from the database and analyzes it using data analysis software (e.g., Python's Pandas library). The input is the business data extracted from the database, and the output is the analysis results. Specifically, it analyzes users' work patterns and performance trends and extracts important indicators. For example, a scheduled job is run every night to extract data from the past month and calculate indicators such as users' average work time and frequency.

[0914] Step 4: Generate a prompt statement

[0915] Based on the results of the data analysis, the server generates a prompt to be input into the generative AI model. The input is the analysis result, and the output is the prompt. Specifically, the server references the user's past work history and performance data to create a prompt that includes specific instructions for performing the work on behalf of the user. For example, it generates a prompt that reads, "Please prepare today's report based on User A's report data from the past month."

[0916] Step 5: Executing the business on your behalf

[0917] The server inputs the generated prompt into a generative AI model (e.g., OpenAI's GPT-4) to generate specific instructions for performing the task. The input is the prompt, and the output is the generated instructions. The generated instructions are sent to the agent, which then performs the user's task. Specifically, the agent automatically creates a report, makes any necessary corrections, and submits it as the final report. For example, when the agent clicks the "Submit Report" button, the report is automatically sent to the supervisor.

[0918] (Application example 3)

[0919] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0920] In conventional production line management, work often stalls when the person in charge is absent, resulting in a decline in production efficiency. There was also a need for a system that could monitor the progress of the production line when the person in charge is absent and make necessary adjustments and troubleshooting.

[0921] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes means for possessing a task AI corresponding to each user, means for assisting in the creation of materials in accordance with the supervisor's decision-making, means for quickly creating materials that meet the supervisor's preferences, means for reducing the man-hours required for document review, means for grasping the difficulties and thoughts of subordinates, means for having an agent that understands the work of each person even when the person in charge is absent, means for promoting the penetration of corporate culture, means for monitoring the progress of the production line, means for making necessary adjustments, means for troubleshooting, and means for being installed in a production line management robot. This makes it possible to continue production line management operations and maintain production efficiency even when the person in charge is absent.

[0922] "Business AI" is an artificial intelligence system that accumulates the work history and performance data of individual users and performs work on their behalf based on that data.

[0923] "Means to assist in the creation of documents in line with the supervisor's decision-making" refers to a function that enables the necessary documents to be created quickly and accurately based on the supervisor's instructions and decisions.

[0924] "Means for quickly creating materials that meet the boss's preferences" is a function for quickly creating materials that meet the boss's preferences and requests.

[0925] "Means for reducing document review man-hours" refers to functions for reducing the time and effort required to review documents.

[0926] "A means of understanding the problems and thoughts of subordinates" is a function that allows you to understand the problems and thoughts that subordinates are facing and provide appropriate support.

[0927] "A means to have an agent who understands the person's work even when the person in charge is absent" is a function that has an agent who can take over the person's work even when the person in charge is absent.

[0928] "Means to promote the dissemination of corporate culture" is a function for disseminating the company's values ​​and code of conduct to employees.

[0929] The "means for monitoring the progress of the production line" is a function for monitoring the progress of the production line in real time.

[0930] The "means for making necessary adjustments" is a function for automatically making necessary adjustments according to the progress of the production line.

[0931] "Troubleshooting means" is a function for quickly identifying and resolving problems that occur on the production line.

[0932] "Means to be installed in the production line management robot" refers to a function to be installed in the robot that performs the production line management work.

[0933] A system for carrying out the present invention includes an application installed on a robot that manages a production line in a factory. A specific embodiment of this system will be described below.

[0934] System Program

[0935] The server runs a program using Python. The program accumulates the user's work history and performance data, and provides functions to carry out work on behalf of the user based on that data. Specifically, it performs the following processes:

[0936] 1. Load user data:

[0937] The server reads user data stored in JSON format and obtains the user's work history and performance data.

[0938] 2. Monitoring the progress of the production line:

[0939] The server monitors the progress of the production line in real time, using hardware such as sensors and cameras.

[0940] 3. Make any necessary adjustments:

[0941] The server automatically makes necessary adjustments based on the progress of the production line, such as adjusting production speed or changing machine settings.

[0942] 4. Troubleshooting:

[0943] The server quickly identifies problems that occur on the production line and takes steps to resolve them, including analyzing error logs and restarting machines.

[0944] Hardware and software used

[0945] Hardware: production line control robots, sensors, cameras

[0946] Software: Python, JSON format data files

[0947] Specific examples

[0948] For example, if a machine on a production line breaks down, the server analyzes data from sensors to identify the problem, then executes the necessary repair procedures and restarts the production line. If the production line is slowing down, the server automatically adjusts the production speed to make up for the delay.

[0949] Prompt Sentence Examples

[0950] An example of a prompt sentence to input to the generative AI model is as follows:

[0951] Based on the user's work history and performance data, generate a program for the production line management robot to take over the work in the absence of the person in charge, specifically include the ability to monitor progress, make necessary adjustments, and troubleshoot.

[0952] In this way, the present invention makes it possible to continue production line management operations even when the person in charge is absent, thereby maintaining production efficiency.

[0953] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0954] Step 1:

[0955] The server reads user data stored in JSON format. Specifically, it opens a file containing the user's work history and performance data and parses its contents. The input is the user data file, and the output is the parsed user data, which is used in subsequent processing steps.

[0956] Step 2:

[0957] The server monitors the progress of the production line in real time. It collects data from sensors and cameras and evaluates the progress. The input is real-time data from sensors and cameras, and the output is the progress evaluation result. Based on this evaluation result, any necessary adjustments or troubleshooting are made.

[0958] Step 3:

[0959] The server automatically makes necessary adjustments according to the progress of the production line, such as adjusting the production speed or changing machine settings. The input is the progress evaluation result, and the output is the adjusted production line settings. Specific actions include increasing the machine speed or changing settings.

[0960] Step 4:

[0961] The server quickly identifies problems that occur on the production line and executes procedures to resolve them, such as analyzing error logs and restarting machines. The input is error data from sensors and cameras, and the output is the normal state of the production line after the problem is resolved. Specific operations include analyzing error logs, identifying the fault location, and executing repair procedures.

[0962] Step 5:

[0963] The server runs an agent that performs tasks on behalf of the user, even when the person in charge is not present, based on the user's work history and performance data. The input is user data and real-time production line data, and the output is the results of the agent's work on behalf of the user. Specific operations include starting the agent, performing the work on behalf of the user, and reporting the results.

[0964] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0965] "Example 1"

[0966] One embodiment of the present invention is a business AI system incorporating an emotion engine. This system recognizes the user's emotions and adjusts the business AI's behavior according to the user's emotional state. Specifically, if the business AI recognizes that the user is feeling stressed, it takes action to reduce the user's workload. For example, it automatically reschedules the user's tasks or provides necessary information.

[0967] "Example 2"

[0968] The emotion engine also has the ability to report the user's emotional state to their superiors, allowing the superior to understand the emotional state of their subordinates in real time and take appropriate action. For example, if the superior senses that a subordinate is experiencing high levels of stress, the superior can have a direct conversation or provide appropriate support.

[0969] "Example 3"

[0970] Furthermore, the emotion engine trains the task AI based on the user's emotional state. This allows the task AI to more accurately understand the user's emotional state and respond more appropriately. For example, if a user tends to feel stressed when performing a certain task, the task AI can automate that task or help the user perform the task more efficiently.

[0971] The processing flow of each embodiment will be described below.

[0972] "Example 1"

[0973] Step 1: The user begins working with the business AI system.

[0974] Step 2: The emotion engine recognizes the user's emotions in real time and determines their emotional state.

[0975] Step 3: The emotion engine adjusts the task AI's behavior based on the emotional state it recognizes. For example, if it recognizes that the user is feeling stressed, the task AI will automatically reschedule the user's tasks.

[0976] "Example 2"

[0977] Step 1: The user begins working with the business AI system.

[0978] Step 2: The emotion engine recognizes the user's emotions in real time and determines their emotional state.

[0979] Step 3: The emotion engine reports the perceived emotional state to the supervisor. The supervisor receives the report and takes appropriate action. For example, if the supervisor senses that the subordinate is experiencing high stress, the supervisor may have a direct dialogue or provide appropriate support.

[0980] "Example 3"

[0981] Step 1: The user begins working with the business AI system.

[0982] Step 2: The emotion engine recognizes the user's emotions in real time and determines their emotional state.

[0983] Step 3: The emotion engine trains the task AI based on the user's emotional state. For example, if the user tends to feel stressed when performing a certain task, the task AI can automate that task or help the user perform the task more efficiently.

[0984] Example 1

[0985] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0986] Conventional work support systems were unable to effectively utilize users' work history and performance data, making it difficult to create materials that matched the supervisor's decision-making. Furthermore, work adjustments were not made taking into account the user's emotional state, and the workload was not sufficiently reduced. Furthermore, issues arose with regard to continuing work when the person in charge was absent and the penetration of corporate culture.

[0987] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0988] In this invention, the server includes means for owning a task AI corresponding to each user, means for assisting in the creation of documents in accordance with the supervisor's decision-making, means for quickly creating documents in line with the supervisor's preferences, means for reducing the man-hours required for document review, means for grasping the points of difficulty and thoughts of subordinates, means for having an agent that understands the person's work even when the person in charge is absent, means for promoting the penetration of corporate culture, means for recognizing the user's emotional state, means for adjusting the operation of the task AI according to the user's emotional state, means for automatically rescheduling the user's tasks, and means for providing necessary information. This improves the user's work efficiency and enables work adjustments according to the user's emotional state, thereby reducing the workload and promoting the penetration of corporate culture.

[0989] "Business AI" is an artificial intelligence that learns the user's work history and performance data and assists in creating documents in line with the supervisor's decision-making.

[0990] "Supervisor's decision-making" refers to the judgments and instructions given by a supervisor in the course of work.

[0991] "Means to assist in document creation" refers to a function that provides templates, formats, and necessary information for documents created by users.

[0992] "Supervisor's preferences" refer to the format and content of materials that the supervisor prefers.

[0993] "Document review man-hours" refers to the time and effort required to review documents and provide corrections and feedback.

[0994] "Troublesome points of subordinates" refer to the problems and challenges that subordinates face when carrying out their work.

[0995] An "agent that understands the work to be done when the person in charge is absent" is a system that can understand the work content of a person and handle it on their behalf even when the person in charge is absent.

[0996] "Permeating corporate culture" refers to the company's values ​​and code of conduct being widely understood and practiced by employees.

[0997] "Means for recognizing emotional state" refers to a function that analyzes the user's facial expressions and tone of voice to determine their emotions.

[0998] "Means for adjusting the behavior of business AI" is a function that changes the behavior of business AI according to the user's emotional state.

[0999] The "means for automatically rescheduling tasks" is a function that automatically adjusts the priority and execution time of tasks in order to reduce the workload of the user.

[1000] "Means of providing necessary information" refers to a function that provides the data and materials necessary for users to carry out their work.

[1001] MODE FOR CARRYING OUT THE INVENTION

[1002] This invention is a system that has a business AI that corresponds to each user and assists in the creation of documents in line with the supervisor's decision-making. This system learns the user's work history and performance data and can quickly create documents that are in line with the supervisor's preferences. It also incorporates an emotion engine that adjusts the behavior of the business AI according to the user's emotional state.

[1003] Hardware and software used

[1004] Hardware: Servers, devices (PCs, tablets, smartphones)

[1005] Software: Business AI (e.g., TensorFlow, PyTorch), emotion engine (e.g., Affectiva SDK), database (e.g., MySQL, PostgreSQL)

[1006] Specific operation of the system

[1007] 1. Data Collection

[1008] The server collects the user's work history and performance data, specifically from the business applications used by the user (e.g., spreadsheet software, word processing software, email client).

[1009] The server stores the collected data in a database.

[1010] 2. Data Learning

[1011] The server uses the stored data to train the business AI model, specifically by applying machine learning algorithms to learn the user's work patterns and the supervisor's decision-making patterns.

[1012] The server saves the learning results as a model and uses them for subsequent document creation and emotion recognition.

[1013] 3. Assistance in preparing materials

[1014] When a user wants to create a document, they send a request to the business AI from their device, for example, by entering a prompt such as "Please provide a template for a monthly report."

[1015] The server receives the request and uses the business AI model to generate the appropriate template or format.

[1016] The server transmits the generated templates and formats to the terminal.

[1017] Users create materials based on the provided templates.

[1018] 4. Emotion recognition

[1019] Using the device's built-in camera and microphone, the emotion engine analyzes the user's facial expressions and tone of voice.

[1020] The terminal transmits the analysis results to the server.

[1021] The server determines the user's emotional state based on the received data, for example, whether the user is feeling stressed.

[1022] 5. Operation adjustment

[1023] If the server determines that the user is feeling stressed, it issues instructions to the business AI.

[1024] Business AI can automatically reschedule users' tasks, for example, deferring less urgent tasks and prioritizing more important ones.

[1025] The server transmits the rescheduled task information to the terminal.

[1026] Users can check the new schedule on their devices and proceed with their work.

[1027] Specific examples

[1028] Assistance in creating materials

[1029] The user types into the terminal, "Please provide me with a monthly report template."

[1030] The server generates an optimal template based on past data and sends it to the terminal.

[1031] Users create reports based on the provided templates.

[1032] Emotion Recognition and Behavior Regulation

[1033] The device's camera captures the user's facial expressions, which are then analyzed by the emotion engine.

[1034] The device determines that the user is feeling stressed and sends that information to the server.

[1035] The server reschedules the user's tasks, pushing less urgent tasks to a later date.

[1036] The server transmits the new schedule to the terminal and notifies the user.

[1037] The user checks the new schedule and proceeds with their work.

[1038] Prompt Sentence Examples

[1039] "Please provide a template for the monthly report."

[1040] "Please tell me the format of presentation materials that suits my boss's preferences."

[1041] "If the user is stressed, reschedule the task."

[1042] "Propose actions to reduce workload based on the user's emotional state."

[1043] The above is a specific embodiment of the system of the present invention.

[1044] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1045] Step 1:

[1046] Data collection

[1047] Input: User work history and performance data

[1048] Specific operation: The server obtains data from the business application used by the user (e.g., spreadsheet software, word processing software, email client).

[1049] Data processing: The acquired data is standardized and stored in a database.

[1050] Output: Standardized historical and performance data is stored in a database.

[1051] Step 2:

[1052] Data Learning

[1053] Input: Business history and performance data stored in a database

[1054] How it works: The server uses the stored data to train the business AI model, specifically by applying machine learning algorithms to learn the user's work patterns and the supervisor's decision-making patterns.

[1055] Data computation: Analyze data using machine learning algorithms to generate models.

[1056] Output: A business AI model is generated as the learning result and saved.

[1057] Step 3:

[1058] Assistance in creating materials

[1059] Input: User request (e.g. "Please provide a template for monthly report")

[1060] Specific operation: When a user creates a document, the device sends a request to the business AI. The server receives the request and uses the business AI model to generate an appropriate template or format.

[1061] Data calculation: Using a business AI model, templates are generated based on past data and the manager's preferences.

[1062] Output: The generated template or format is sent to the terminal.

[1063] Step 4:

[1064] emotion recognition

[1065] Input: User facial expressions and tone of voice

[1066] How it works: Using the device's built-in camera and microphone, the emotion engine analyzes the user's facial expressions and tone of voice. The device then sends the analysis results to the server.

[1067] Data processing: Analyze facial expressions and tone of voice data to determine emotional state.

[1068] Output: The user's emotional state data is sent to the server.

[1069] Step 5:

[1070] Operation adjustment

[1071] Input: User emotional state data

[1072] Specific operation: If the server determines that the user is feeling stressed, it issues instructions to the work AI, which then automatically reschedules the user's tasks.

[1073] Data calculation: Recalculate task priorities and execution times and adjust schedules.

[1074] Output: Rescheduled task information is sent to the terminal.

[1075] Step 6:

[1076] Information provision

[1077] Input: User requests and business status

[1078] Specific operation: The server provides the necessary information according to the user's business situation and requests.

[1079] Data calculation: Using business AI models, search for the necessary information and provide it in the appropriate format.

[1080] Output: The required information is sent to the terminal and provided to the user.

[1081] (Application example 1)

[1082] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1083] Conventional work support systems were unable to fully utilize the work history and performance data of individual users, making it difficult to create documents that matched the supervisor's decision-making process or adjust the workload according to the user's emotional state. Furthermore, they were unable to automatically generate work reports and progress reports, which led to problems with reduced work efficiency.

[1084] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes means for collecting a user's work history and performance data, a prompt statement instructing the user to create a work report or progress report based on the user's work history and performance data, and means for creating the work report or progress report based on a generative AI model. The server also includes a prompt statement instructing the user to propose an optimal procedure for the user's work based on the user's work history and performance data, and means for proposing an optimal procedure for the user's work based on the generative AI model. The server also includes means for recognizing the user's emotional state, a prompt statement instructing the user to propose an optimal workload for the user's work based on the user's work history and the user's emotional state, and means for proposing an optimal workload for the user's work based on the generative AI model. This improves the user's work efficiency, enables the creation of documents in line with supervisor decision-making, and enables the adjustment of the user's workload according to the user's emotional state.

[1085] "Business AI" is an artificial intelligence system that responds to individual users and supports their work by learning their work history and performance data.

[1086] "Means to assist in the creation of documents in line with the supervisor's decision-making" is a function that supports the creation of documents based on the supervisor's instructions and inclinations.

[1087] "A means for quickly creating materials that meet the boss's preferences" is a function that allows for the rapid creation of materials that meet the boss's preferences and requests.

[1088] "Means to reduce document review man-hours" refers to a function that reduces the time and effort required to check and correct documents.

[1089] "A means of understanding the points of difficulty and thoughts of subordinates" is a function for understanding the problems and opinions that subordinates are facing.

[1090] "A means to have an agent who understands the work of a person even when the person in charge is absent" is a function that has an agent who understands the work content even when the person in charge is absent.

[1091] "Means to promote the dissemination of corporate culture" is a function for spreading the company's values ​​and code of conduct to employees.

[1092] "Means for recognizing the emotional state of the user and adjusting the workload in accordance with the emotional state" is a function that detects the user's emotions and adjusts the workload in accordance with that state.

[1093] "Means for learning work history and performance data and proposing optimal work procedures" is a function that analyzes past work history and performance data and proposes optimal work procedures.

[1094] "Means for automatically generating business reports and progress reports" refers to a function that automatically generates work progress and results as reports.

[1095] A system for implementing this invention has the following configuration: The server has a business AI that corresponds to each user and assists in creating documents in line with the supervisor's decision-making. It also creates documents that are in line with the supervisor's preferences in a short amount of time, reducing the man-hours required for document review. It also has an agent that can understand the points of difficulty and thoughts of subordinates and understands their work even when the person in charge is not present. It promotes the penetration of corporate culture, recognizes the user's emotional state, and adjusts the workload accordingly. It learns work history and performance data, proposes optimal work procedures, and automatically generates work reports and progress reports.

[1096] Hardware and software used

[1097] Hardware: Factory robots, emotion-recognition cameras, sensors

[1098] Software: Python, EmotionEngine library, generative AI model, TaskScheduler library

[1099] Data processing and calculation

[1100] The server collects the user's work history and performance data and proposes optimal work procedures based on this. Specifically, it uses the EmotionEngine library to recognize the user's emotional state and proposes adjusting the user's workload according to their emotional state. It then adjusts the workload using the TaskScheduler library according to the user's instructions. It also automatically generates work reports and progress reports using a generative AI model.

[1101] Specific examples

[1102] For example, if a user working in a factory feels stressed, the emotion recognition camera detects this state, and the server suggests adjusting the user's workload and readjusts the work schedule using the TaskScheduler library according to the user's instructions.Furthermore, based on the supervisor's instructions, the server automatically generates a work report or progress report using a generative AI model and sends it to the supervisor in PDF format.

[1103] An example prompt to write a business report: After accepting the user's work history and performance data, the system will say, "This is the user's work history and performance data. Please create a work report based on this data."

[1104] An example of a prompt that suggests the best course of action for the user's task is: After accepting the user's work history and performance data, the system asks, "This is the user's work history and performance data. Based on this data, please suggest the optimal procedure for the user's work."

[1105] Prompt to suggest optimal workload for user's work: After receiving the user's work history, the system will say, "This is the user's work history. The user is feeling stressed. Please suggest the optimal workload for the user's work."

[1106] In this way, the server can improve the user's work efficiency, create documents in line with the supervisor's decisions, and adjust the workload according to the user's emotional state.

[1107] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1108] Step 1:

[1109] The server collects users' work history and performance data. The input includes users' work logs and performance metrics. This data is stored in a database for later analysis. The output is the collected data stored in a database.

[1110] Step 2:

[1111] The server uses the EmotionEngine library to recognize the user's emotional state. The input includes real-time video data acquired from an emotion-recognition camera. The video data is analyzed to identify the user's emotional state (e.g., stress, joy, fatigue, etc.). The output is the recognized emotional state.

[1112] Step 3:

[1113] The server Based on the user's work history and the recognized emotional state, the system proposes an optimal workload for the user's work based on a prompt sentence and a generative AI model. The system also uses the TaskScheduler library to adjust the workload according to the user's instructions. The inputs include the user's emotional state and current task schedule. If the emotional state is "stressed," the system reevaluates task priorities and suggests readjusting the schedule to reduce the workload. The schedule is readjusted according to the user's instructions. The output is the adjusted task schedule.

[1114] Step 4:

[1115] The server creates a business report or progress report based on a prompt statement instructing the server to create a business report or progress report based on the user's work history and performance data, and based on the generative AI model. The input includes instructions for the business report or progress report, the user's work history, and performance data. Based on this data, the server generates a report in a specified format. The generated report is obtained as the output.

[1116] Step 5:

[1117] The server converts the generated report to PDF format and sends it to the manager. The input contains the generated report, converts the report to PDF format and sends it to the manager's email address, and the output is a notification that the report has been sent.

[1118] Step 6:

[1119] The server proposes optimal procedures for the user's work based on a prompt that instructs the server to propose optimal procedures for the user's work based on the user's work history and performance data, and based on a generative AI model. The input includes past work history and performance data. The server analyzes this data to identify efficient work procedures. The output is the proposed work procedures.

[1120] Step 7:

[1121] The server notifies the user of the proposed work procedure. The input includes the proposed work procedure. The server sends a notification to the user's device and displays the work procedure. The output allows the user to confirm the proposed work procedure.

[1122] Through these steps, the server can improve the user's work efficiency, create documents in line with the supervisor's decision-making, and adjust the workload according to the user's emotional state.

[1123] Example 2

[1124] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1125] With conventional work management systems, it was difficult for managers to grasp the work progress and emotional state of their subordinates in real time, making it difficult to respond appropriately and quickly. Additionally, creating and reviewing documents required a lot of time and effort, which led to reduced work efficiency.

[1126] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for possessing a task AI corresponding to each user, means for assisting in document creation in accordance with the supervisor's decision-making, means for quickly creating documents in line with the supervisor's preferences, means for reducing the man-hours required for document review, means for identifying subordinates' difficulties and thoughts, means for having an agent who understands the user's work even when the person in charge is absent, means for promoting the penetration of corporate culture, means for collecting users' work history and performance data and storing them in a database, means for analyzing the user's work progress and problems using a data analysis tool, means for generating a report based on the analysis results and sending it to the supervisor's terminal, means for using an emotion engine to analyze the user's emotional state, and means for generating an emotion report based on the emotion analysis results and sending it to the supervisor's terminal. This allows the supervisor to grasp the subordinate's work progress and emotional state in real time and take appropriate action promptly.

[1127] "Business AI" is an artificial intelligence system that analyzes a user's work history and performance data to identify the progress of work and problems.

[1128] A "database" is an information management system for storing users' work history and performance data.

[1129] A "data analysis tool" is software that analyzes collected data and identifies the user's business progress and problems.

[1130] An "emotion engine" is software that analyzes a user's emotional state and generates an emotion report.

[1131] A "report" is a document generated based on the analysis results, and includes the user's work progress, problems, and emotional state.

[1132] A "terminal" is an electronic device such as a computer or smartphone used by a supervisor.

[1133] An "agent" is a system that keeps track of a person's work and acts on their behalf when they are not present.

[1134] "Corporate culture" refers to the values ​​and code of conduct shared within a company.

[1135] "Means to assist in document creation" is a support system for creating documents in accordance with the supervisor's decision-making.

[1136] "Means to reduce document review man-hours" is a system for reducing the time and effort required to check and correct documents.

[1137] This invention is a system that analyzes the work history and performance data of users, enabling a supervisor to grasp the work progress and emotional state of their subordinates in real time. Specific embodiments of this system are described below.

[1138] Data analysis and reporting using business AI

[1139] The server collects users' work history and performance data and stores it in a database. Specifically, it obtains data from the business applications used by users (e.g., project management tools, task management tools). The server obtains data from project management tools (e.g., JIRA, Trello) via API and stores it in a MySQL database.

[1140] The server then analyzes the collected data, using data analysis tools such as Python and R to identify the user's progress and problems. The server runs a Python script to read the data from the database and calculates task completion times and error rates using data analysis libraries (e.g., Pandas, NumPy). The analysis results are saved in JSON format.

[1141] The server then generates a report based on the analysis results and sends it to the supervisor's terminal.The server then generates a report in HTML format based on the analysis results and sends it to the supervisor's terminal via the mail server.

[1142] Examples:

[1143] Data collection: The server retrieves data from the project management tool and stores it in a MySQL database.

[1144] Data analysis: Use Python to calculate task completion times and error rates.

[1145] Report generation: Generate an HTML report based on the analysis results and send it to the supervisor's device.

[1146] Example prompt for a generative AI model:

[1147] Analyze user progress and issues based on user work history and performance data, and generate reports.

[1148] Emotion engine reports emotional state

[1149] The server collects the data necessary to analyze the user's emotional state. Specifically, it acquires the user's text messages and voice data. The server acquires text messages from chat applications (e.g., Slack, Microsoft Teams), and voice data is converted into text using a speech recognition API (e.g., Google Speech-to-Text).

[1150] The server then analyzes the collected data using an emotion engine, which identifies the user's emotional state. The server calls the IBM Watson Tone Analyzer API to analyze the text data, and the emotional state (e.g., happy, sad, or angry) is identified, and the results are stored in JSON format.

[1151] The server then generates an emotion report based on the analysis results and sends it to the superior's terminal.The server then generates an emotion report in HTML format based on the analysis results and sends it to the superior's terminal via a mail server.

[1152] Examples:

[1153] Data collection: The server retrieves text messages from the chat application and converts the voice data into text using a speech recognition API.

[1154] Sentiment Analysis: Uses the IBM Watson Tone Analyzer API to analyze text data and identify emotional states.

[1155] Report generation: An HTML-formatted emotion report is generated based on the analysis results and sent to the supervisor's device.

[1156] Example prompt for a generative AI model:

[1157] Analyze and report on the user's emotional state based on their text messages and voice data.

[1158] This system allows managers to grasp their subordinates' work progress and emotional state in real time, enabling them to respond promptly and appropriately.

[1159] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1160] Step 1: Data collection

[1161] The server collects users' work history and performance data. Specifically, it obtains data from business applications used by users (e.g., project management tools, task management tools). The server obtains data from project management tools (e.g., JIRA, Trello) via API and stores it in a MySQL database. The input is data from the business applications, and the output is the work history and performance data stored in the database.

[1162] Step 2: Data analysis

[1163] The server analyzes the collected data and uses data analysis tools such as Python and R to identify the user's work progress and problems. The server executes Python scripts to read data from the database and calculates task completion times and error rates using data analysis libraries (e.g., Pandas, NumPy). The input is the work history and performance data read from the database, and the output is JSON-formatted data that is the analysis result.

[1164] Step 3: Generate and send the report

[1165] The server generates a report based on the analysis results and sends it to the supervisor's terminal.The server generates an HTML report based on the analysis results and sends it to the supervisor's terminal via the mail server.The input is the JSON data of the analysis results, and the output is the HTML report sent to the supervisor's terminal.

[1166] Step 4: Collect emotional data

[1167] The server collects the data necessary to analyze the user's emotional state. Specifically, it obtains the user's text messages and voice data. The server obtains text messages from chat applications (e.g., Slack, Microsoft Teams) and converts the voice data into text using a speech recognition API (e.g., Google Speech-to-Text). The input is the text messages and voice data from the chat application, and the output is the data converted into text.

[1168] Step 5: Sentiment Analysis

[1169] The server analyzes the collected data using an emotion engine. The emotion engine identifies the user's emotional state. The server calls the IBM Watson Tone Analyzer API to analyze the text data, and the emotional state (e.g., happy, sad, or angry) is identified, and the results are saved in JSON format. The input is the data converted to text, and the output is JSON-formatted data indicating the emotional state.

[1170] Step 6: Generate and send sentiment report

[1171] The server generates an emotion report based on the analysis results and sends it to the superior's device.The server generates an emotion report in HTML format based on the analysis results and sends it to the superior's device via a mail server.The input is JSON data of the emotion analysis results, and the output is the HTML emotion report sent to the superior's device.

[1172] (Application example 2)

[1173] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1174] Conventional factory robots lack the ability to analyze work history and performance data in real time and report it to managers, making it difficult for managers to immediately grasp the robot's work progress and any problems. They also lack the ability to estimate the robot's emotional state based on its movements and sensor information and report it to managers, making it impossible to detect stress levels or declines in work efficiency in the robots early on. This leads to lower factory production efficiency and delays in robot maintenance and support, which has been an issue.

[1175] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1176] In this invention, the server includes: means for owning a task AI corresponding to each user; means for assisting in the creation of documents in accordance with the supervisor's decision-making; means for quickly creating documents in line with the supervisor's preferences; means for reducing the labor required for document review; means for understanding the difficulties and thoughts of subordinates; means for having an agent that understands a person's work even when the person in charge is absent; means for promoting the spread of corporate culture; means for analyzing the work history and performance data of robots working in the factory in real time and reporting to a manager; means for estimating the emotional state of the robot based on the robot's movements and sensor information and reporting to a manager; and means for the manager to understand the robot's work progress, problems, and emotional state in real time and take appropriate action. This allows the manager to understand the robot's work progress, problems, and emotional state in real time and take appropriate action.

[1177] "Business AI" is an artificial intelligence system that responds to individual users and analyzes their work history and performance data.

[1178] "Means to assist in document creation" is a function that supports the process of creating documents in accordance with the supervisor's decision-making.

[1179] "Means to reduce document review man-hours" refers to a function that reduces the time and effort required to check and correct documents.

[1180] "A means of understanding the problems and thoughts of subordinates" is a function that collects the problems and opinions that subordinates are facing and reports them to their superiors.

[1181] "A means to have an agent who understands the work of a person even when the person in charge is absent" is a function that has an agent who understands the work content and can act on behalf of the person in charge even when the person in charge is absent.

[1182] "Means to promote the dissemination of corporate culture" refers to the function of spreading and helping employees understand the company's values ​​and code of conduct.

[1183] "A means of analyzing the work history and performance data of robots working in factories in real time and reporting to managers" is a function that instantly analyzes the work history and performance data of factory robots and conveys the results to managers.

[1184] "Means of estimating the emotional state of a robot based on its movements and sensor information and reporting it to an administrator" is a function that uses data obtained from the robot's movements and sensors to infer the emotional state of a robot and conveys that information to an administrator.

[1185] "A means for managers to grasp the robot's work progress, problems, and emotional state in real time and take appropriate action" is a function that allows managers to instantly check the robot's work status, problems, and emotional state and take appropriate measures.

[1186] The system for implementing this invention has the function of analyzing the work history and performance data of robots working in a factory in real time and reporting the results to managers. It also has the function of estimating the emotional state of the robot based on the robot's movements and sensor information and reporting the results to managers.

[1187] 1. System Program

[1188] The system is implemented using the following hardware and software.

[1189] Hardware: Factory robots (e.g., KUKA, ABB), sensors (e.g., accelerometers, temperature sensors)

[1190] Software: Python, data analysis libraries (e.g., pandas, numpy), machine learning libraries (e.g., scikit-learn)

[1191] 2. Program processing explanation

[1192] The server stores the work history and performance data collected from the factory robots in a database. It then uses a machine learning model to estimate the robot's emotional state. This allows managers to understand the robot's work progress, problems, and emotional state in real time and take appropriate action.

[1193] Specifically, the server performs the following process.

[1194] 1. Collect the robot's work history and performance data and store it in a database.

[1195] 2. Use machine learning models to estimate the emotional state of the robot.

[1196] 3. Report the results of the estimation to the administrator.

[1197] 3. Specific Examples

[1198] For example, when a robot assembles parts, the success rate and work time are recorded. Based on the robot's operation data, the stress level can be estimated and reported to the manager, who can then take appropriate measures to improve the robot's work efficiency.

[1199] Example prompt for a generative AI model:

[1200] Please estimate the robot's emotional state based on its work history and performance data. Please use the following data:

[1201] Work history: [Success / Failure]

[1202] Performance data: [Work time, number of errors]

[1203] In this way, a factory robot operation monitoring and emotion analysis system can be realized.

[1204] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1205] Step 1:

[1206] The server collects work history and performance data from factory robots. Specifically, it obtains data such as the success rate, work time, and number of errors of the robot's work from sensors and the robot's internal logs. The input is the robot's sensor information and internal logs, and the output is the collected work history and performance data.

[1207] Step 2:

[1208] The server stores the collected business history and performance data in a database. Specifically, it uses a database management system (e.g., MySQL or PostgreSQL) to store the data in an appropriate format. The input is the collected business history and performance data, and the output is the data stored in the database.

[1209] Step 3:

[1210] The server uses a machine learning model based on the stored data to estimate the robot's emotional state. Specifically, it preprocesses the data using a data analysis library (e.g., pandas, numpy) and estimates the emotional state using a machine learning library (e.g., scikit-learn). The input is the work history and performance data stored in the database, and the output is the estimated emotional state.

[1211] Step 4:

[1212] The server reports the estimated emotional state to the administrator by sending a notification to the administrator's device and displaying it on a dashboard. The input is the estimated emotional state, and the output is the emotional state reported to the administrator.

[1213] Step 5:

[1214] Based on the reported emotional state, the manager can understand the robot's work progress and any problems and take appropriate action. Specifically, the manager checks the dashboard and adjusts the robot's work schedule or performs maintenance as necessary. The input is the reported emotional state and work history, and the output is the manager's response.

[1215] Example 3

[1216] Next, a description will be given of Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1217] With conventional work support systems, work often stalls when the person in charge is absent, and work adjustments do not take into account the user's emotional state, resulting in problems that decrease work efficiency and increase user stress.Furthermore, there is a lack of means to create materials that align with supervisors' decision-making and to promote the spread of corporate culture, making it difficult to improve the performance of the entire organization.

[1218] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1219] In this invention, the server includes means for owning a task AI corresponding to each user, means for assisting in the creation of documents in accordance with the supervisor's decision-making, means for quickly creating documents in line with the supervisor's preferences, means for reducing the man-hours required for document review, means for understanding the difficulties and thoughts of subordinates, means for having an agent that understands a person's work even when the person in charge is absent, means for promoting the penetration of corporate culture, means for monitoring the user's emotional state in real time, means for training the task AI based on the user's emotional state, and means for adjusting work in accordance with the user's emotional state.This allows work to continue even when the person in charge is absent, and by adjusting work taking the user's emotional state into consideration, it is possible to improve work efficiency and reduce user stress.

[1220] "Business AI" is artificial intelligence that learns from a user's work history and performance data and acts on their behalf or assists them in their work.

[1221] "Means to assist in the creation of documents in line with the supervisor's decision-making" refers to a function that allows the necessary documents to be created quickly and accurately based on the supervisor's instructions and intentions.

[1222] "A means for quickly creating materials that meet the boss's preferences" is a function for efficiently creating materials that meet the boss's preferences and requests.

[1223] "Means to reduce document review man-hours" is a function for reducing the time and effort required to check and correct documents.

[1224] "A means of understanding subordinates' problems and thoughts" is a function that allows superiors to collect the problems and opinions that subordinates are facing and understand them.

[1225] "A means to have an agent who understands a person's work even when the person in charge is absent" is a function that provides an agent who understands a person's work and can act on their behalf even when the person in charge is absent.

[1226] "Means to promote the dissemination of corporate culture" is a function for spreading and establishing the company's values ​​and code of conduct among employees.

[1227] "Means for monitoring the user's emotional state in real time" is a function for observing the user's emotions in real time and collecting them as data.

[1228] "Means for training business AI based on the user's emotional state" is a function that enables business AI to learn based on collected emotional data and respond according to the user's emotions.

[1229] The "means for adjusting work in accordance with the user's emotional state" is a function for appropriately adjusting the progress and content of work in consideration of the user's emotional state.

[1230] The present invention provides a system that performs tasks on behalf of a user based on the user's task history and emotional state, and supports the user in performing the tasks efficiently. Specific embodiments of this system will be described below.

[1231] Data collection and storage

[1232] The server collects users' work history and performance data. Specifically, it obtains data from the business applications (e.g., office suites, cloud services) used by the users. This is often done using APIs. The collected data is stored in a relational database (e.g., MySQL, PostgreSQL).

[1233] Example: A server periodically retrieves the change history of documents and spreadsheets created by users and stores it in a database.

[1234] Data analysis and learning

[1235] The server analyzes the collected data and identifies the user's business patterns using machine learning algorithms (e.g., random forests and support vector machines). The analysis results are fed back to the business AI.

[1236] Example: A server analyzes the frequency and duration of tasks a user performs each week and finds patterns, for example, determining that a user creates reports every Monday.

[1237] Business agency

[1238] Business AI performs tasks on behalf of users based on the analysis results. Specifically, it automatically executes tasks that users should perform. Business AI is built using machine learning frameworks such as TensorFlow and PyTorch.

[1239] Example: Business AI automatically creates a report every Monday and sends it to the boss, even if the user is not present.

[1240] Collecting Emotional Data

[1241] The device monitors the user's emotional state in real time using wearable devices (e.g., smartwatches) and camera-based facial recognition software (e.g., facial recognition APIs), and the collected data is sent to a server.

[1242] Example: The device collects the user's heart rate and facial expression data and sends it to a server.

[1243] Emotional Data Analysis

[1244] The emotion engine analyzes the collected emotion data and identifies the user's emotional state using emotion recognition algorithms (e.g., deep learning models). The analysis results are fed back to the business AI.

[1245] Example: An emotion engine identifies when a user is stressed when performing a particular task.

[1246] Emotion-based work adjustments

[1247] Based on feedback from the emotion engine, the business AI responds to the user's emotional state by automating or helping them perform stressful tasks more efficiently.

[1248] Example: Business AI automates tasks that users find frustrating, so they don't have to do them.

[1249] Prompt Sentence Examples

[1250] 1. "Auto-generate this week's report based on the user's past report data."

[1251] 2. "Identify a task that users find frustrating and suggest ways to automate it."

[1252] In this way, the system performs tasks on behalf of the user based on the user's task history and emotional state, and supports the user in performing the tasks efficiently. The flow of the identification process in the third embodiment will be described with reference to FIG.

[1253] Step 1:

[1254] Data collection and storage

[1255] The server collects users' work history and performance data. Specifically, it obtains data from the business applications (e.g., office suites, cloud services) used by the user via API. The input is the change history of the user's documents and spreadsheets, and the output is stored in a relational database (e.g., MySQL, PostgreSQL). Specifically, the server periodically calls the API to obtain the latest data and adds it to the database.

[1256] Step 2:

[1257] Data analysis and learning

[1258] The server analyzes the collected data and identifies the user's work patterns. The input is the work history data stored in the database, and the output is the analysis results. This is done using a machine learning algorithm (e.g., random forest, support vector machine). Specifically, the server periodically reads data from the database, inputs it into the machine learning model, analyzes it, and identifies the user's work patterns.

[1259] Step 3:

[1260] Business agency

[1261] Business AI performs tasks on behalf of the user based on the analysis results. The analysis results are input, and the tasks that the user should perform are automatically executed as output. Specifically, business AI is built using machine learning frameworks such as TensorFlow and PyTorch. Specifically, business AI schedules tasks based on the analysis results and executes them automatically. For example, even if the user is absent, it can automatically create a report every Monday and send it to the supervisor.

[1262] Step 4:

[1263] Collecting Emotional Data

[1264] The device monitors the user's emotional state in real time. The input is data from a wearable device (e.g., a smartwatch) or camera-based facial expression recognition software (e.g., a facial recognition API), and the output is the collected emotional data sent to a server. Specifically, the device collects the user's heart rate and facial expression data in real time and sends it to the server.

[1265] Step 5:

[1266] Emotional Data Analysis

[1267] The emotion engine analyzes the collected emotion data and identifies the user's emotional state. The input is the emotion data sent from the server, and the output is the analysis result. This is done using an emotion recognition algorithm (e.g., deep learning model). Specifically, the emotion engine analyzes the emotion data and identifies that the user is feeling stressed when performing a specific task.

[1268] Step 6:

[1269] Emotion-based work adjustments

[1270] The business AI responds according to the user's emotional state based on feedback from the emotion engine. The input is the analysis results from the emotion engine, and the output is work adjustments according to the user's emotional state. Specifically, the business AI automates stressful tasks so that the user does not have to perform them. For example, it identifies tasks that cause stress to the user and proposes ways to automate those tasks.

[1271] (Application example 3)

[1272] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1273] With conventional work support systems, work often stalls when the person in charge is absent, which can lead to a decline in productivity, especially in factory work. Furthermore, by carrying out work without taking into account the emotional state of the workers, stress and fatigue accumulate, leading to a decline in work efficiency.

[1274] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes means for possessing a task AI corresponding to each user, means for assisting in document creation in accordance with the supervisor's decision-making, means for quickly creating documents in line with the supervisor's preferences, means for reducing the man-hours required for document review, means for identifying subordinates' difficulties and thoughts, means for having an agent that understands a person's work even when the person in charge is absent, means for promoting the spread of corporate culture, means for being installed in robots responsible for work in the factory and continuing work even when the person in charge is absent, means for the task AI to accumulate the work history and performance data of factory workers, understand the worker's emotional state using an emotion engine, and take appropriate action, and means for monitoring the worker's emotional state in real time using a heart rate sensor and a face recognition camera and automatically taking over the work if stress is detected. This allows work to continue uninterrupted even when the person in charge is absent, and enables work support that takes the worker's emotional state into consideration.

[1275] "Business AI" is an artificial intelligence system that accumulates users' work history and performance data and performs or supports work on their behalf.

[1276] "A means to assist in the creation of documents in line with the supervisor's decision-making" is a system that has the function of assisting in the creation of documents based on the supervisor's instructions and intentions.

[1277] "A means for quickly creating materials that meet the superior's preferences" is a system that has the function of quickly creating materials that meet the superior's preferences and requests.

[1278] A "means for reducing document review labor" is a system that has the function of reducing the time and effort required to check and correct documents.

[1279] "A means of understanding the problems and thoughts of subordinates" is a system that has the ability to understand the problems and opinions that subordinates are facing and respond appropriately.

[1280] "A means to have an agent who understands the person's work even when the person in charge is absent" is a system that has the function of having an agent who can take over the person's work even when the person in charge is absent.

[1281] "Means to promote the dissemination of corporate culture" are systems that have the function of spreading and establishing the company's values ​​and code of conduct among employees.

[1282] "A means to be installed on robots that perform work within a factory, allowing them to continue operations even when the person in charge is absent" refers to a system that is installed on robots that perform work within a factory, and has the function of allowing them to continue operations even when the person in charge is absent.

[1283] "A means for business AI to accumulate work history and performance data of factory workers, use an emotion engine to understand the emotional state of the workers, and take appropriate action" refers to a system that has the function of collecting work history and performance data of factory workers, using an emotion engine to understand the emotional state of the workers, and taking appropriate action.

[1284] "Means for monitoring the emotional state of workers in real time using heart rate sensors and facial recognition cameras, and automatically taking over work if stress is detected" is a system that uses heart rate sensors and facial recognition cameras to monitor the emotional state of workers in real time, and has the function of automatically taking over work if stress is detected.

[1285] A system for implementing this invention includes a program installed on a robot in charge of work in a factory. The system uses task AI, an emotion engine, a heart rate sensor, and a facial recognition camera to continue work even when the person in charge is absent and monitors the emotional state of the worker in real time.

[1286] The server first stores the work history and performance data of factory workers, including the tasks they have performed in the past, their results, and the time it took to complete the tasks. It then uses an emotion engine to understand the worker's emotional state. The emotion engine analyzes data obtained from heart rate sensors and facial recognition cameras to determine whether the worker is experiencing stress.

[1287] If the server determines that a worker is feeling stressed, it automatically instructs a robot to take over the task. This reduces worker stress and improves work efficiency. The task AI also learns to optimize work based on the worker's work history and performance data. This further improves work efficiency.

[1288] As a concrete example, consider the case where a factory worker feels stressed while performing a specific assembly task. A heart rate sensor detects an increase in the worker's heart rate, and a facial recognition camera reads stress from the worker's facial expression. An emotion engine analyzes this data to determine the worker's stress level. If stress is detected, the task AI instructs a robot to take over the task, allowing the worker to move on to other tasks.

[1289] An example of a prompt sentence might be:

[1290] "Based on the work history and performance data of factory workers, please use an emotion engine to understand their emotional state, and design a system in which a robot will automatically take over the work if the worker feels stressed."

[1291] In this way, a system can be realized that can improve the efficiency of work within a factory and reduce the stress of workers.

[1292] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1293] Step 1:

[1294] The server collects the work history and performance data of factory workers and stores it in a database. As input, it receives data such as the worker's work content, work time, and results, and stores this in the database. As output, it obtains the accumulated work history data.

[1295] Step 2:

[1296] The server receives data in real time from the heart rate sensor and facial recognition camera. As input, it receives the worker's heart rate data and facial recognition data and sends them to the emotion engine. As output, it obtains the raw data sent to the emotion engine.

[1297] Step 3:

[1298] The server uses an emotion engine to analyze the worker's emotional state. As input, it receives heart rate data and facial recognition data, analyzes them, and determines the worker's emotional state (e.g., stress level). As output, it obtains emotional state data as the analysis result.

[1299] Step 4:

[1300] The server determines whether the worker is feeling stressed based on the emotional state data. As input, it receives the emotional state data and determines whether the worker is feeling stressed. As output, it obtains the result of the stress state determination.

[1301] Step 5:

[1302] If a stress state is detected, the server instructs the robot to take over the work. As input, it receives the stress state assessment result and sends a work handover instruction to the robot. As output, it obtains instruction data for the robot to take over the work.

[1303] Step 6:

[1304] The robot receives instructions from the server and takes over the work. As input, it receives instructions to take over the work from the server and starts the actual work. As output, it obtains data on the progress of the work.

[1305] Step 7:

[1306] The server monitors the robot's work progress and issues additional instructions as needed. As input, it receives work progress data from the robot, analyzes it, and generates the necessary instructions. As output, it obtains additional instruction data.

[1307] In this way, the server can monitor the work history and emotional state of factory workers in real time, and by having robots take over the work as needed, it is possible to reduce worker stress and improve work efficiency.

[1308] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1309] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image are also input.

[1310] The data generation model 58 performs inference on the input inference data according to the instructions given by the prompts, and outputs the inference results in the form of data such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1311] Another example of generative AI is Gemini (internet search engine). <url: https: gemini.google.com ?hl="ja">) are listed.

[1312] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1313] [Third embodiment]

[1314] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1315] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1316] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1317] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1318] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1319] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1320] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1321] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1322] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1323] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1324] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1325] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1326] "Example 1"

[1327] As one embodiment of the present invention, a system is provided that has a business AI that corresponds to each individual user. This business AI learns the user's work history and performance data, and assists in the creation of documents in line with the supervisor's decision-making. Specifically, the AI ​​provides the user with templates, formats, and necessary information for the documents they create, and the user creates the documents based on this. This makes it possible to create documents that meet the supervisor's preferences in a short amount of time.

[1328] "Example 2"

[1329] Furthermore, as another embodiment of the present invention, a means is provided for understanding the problems and thoughts of subordinates. Specifically, the business AI analyzes the user's work history and performance data and reports the results to the superior. This allows the superior to understand the progress and problems of the subordinate's work in real time.

[1330] "Example 3"

[1331] Furthermore, as a further embodiment of the present invention, a system is provided in which an agent that understands the work of a person in charge exists even when the person in charge is absent. Specifically, the task AI accumulates the user's work history and performance data and performs the work on behalf of the person in charge based on that data. This allows the person to continue their work even when the person in charge is absent.

[1332] The processing flow of each embodiment will be described below.

[1333] "Example 1"

[1334] Step 1: The business AI collects the user's work history and performance data.

[1335] Step 2: The business AI learns based on the collected data.

[1336] Step 3: The business AI assists in the creation of documents in line with the supervisor's decision-making. Specifically, the AI ​​provides templates, formats, and necessary information for the documents the user creates. Step 4: The user creates the documents based on the information provided by the AI.

[1337] "Example 2"

[1338] Step 1: Business AI analyzes the user's work history and performance data.

[1339] Step 2: The business AI reports the analysis results to its superiors.

[1340] Step 3: Based on the report, the supervisor understands the progress and problems of the subordinate's work.

[1341] "Example 3"

[1342] Step 1: The business AI accumulates the user's work history and performance data.

[1343] Step 2: The business AI performs the business operations based on the accumulated data.

[1344] Step 3: Even if the person in charge is absent, the task AI continues the person's work.

[1345] Example 1

[1346] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1347] In the conventional document creation process, users had to spend a lot of time and effort creating documents that met their superiors' preferences, resulting in inefficiency. In addition, there was a lack of means to assist in creating documents that aligned with the superiors' decision-making, which made it difficult to reduce the man-hours required for document review and identify points of difficulty for subordinates. Furthermore, there was no agent to keep track of the work of the person in charge when they were absent, which sometimes disrupted the continuity of work. To solve these issues, a system was needed that utilized users' work history and performance data to efficiently assist in document creation.

[1348] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1349] In this invention, the server includes a means for owning a business AI corresponding to each user, a means for collecting the user's work history and performance data, a means for training the business AI using the collected data, a means for generating templates and formats according to the user's requests using a generative AI model, a means for providing the generated templates and formats to the user, a means for assisting in the creation of documents in line with the supervisor's decision-making, a means for quickly creating documents in line with the supervisor's preferences, a means for reducing the labor required for document review, a means for grasping the subordinate's difficulties and thoughts, a means for having an agent that understands the subordinate's work even when the person in charge is absent, and a means for promoting the penetration of corporate culture. This allows users to efficiently create documents in line with the supervisor's preferences, reduces the labor required for document review, and makes it easier to grasp the subordinate's difficulties. Furthermore, business continuity is ensured even when the person in charge is absent, promoting the penetration of corporate culture.

[1350] "Business AI" is an artificial intelligence system that learns from a user's work history and performance data and assists in document creation.

[1351] "User's work history" refers to data that refers to records and deliverables of work that a user has done in the past.

[1352] "Performance data" refers to data that indicates the results and evaluations of a user's work.

[1353] "Means for collection" refers to methods or devices for acquiring a user's work history and performance data.

[1354] "Training means" refers to methods or devices for training business AI using collected data.

[1355] A "generative AI model" is an artificial intelligence model that generates templates and formats according to user requests.

[1356] "Templates and formats" refer to standard structures and formats used when creating documents.

[1357] The "means for providing" refers to a method or device for delivering the generated template or format to the user.

[1358] "Means for assisting in the preparation of documents in line with decision-making" refers to methods or devices for supporting the preparation of documents based on the decision-making of a superior.

[1359] "Means for reducing document review man-hours" refers to methods and devices for reducing the time and effort required to check and correct documents.

[1360] "Means for grasping difficult points and thoughts" are methods or devices for understanding the problems and opinions that subordinates are facing.

[1361] An "agent that understands a person's work even when the person in charge is absent" is an artificial intelligence system that can understand a person's work and perform it on their behalf even when the person in charge is absent.

[1362] "Means to promote corporate culture" are methods and devices for spreading the company's values ​​and code of conduct to employees.

[1363] MODE FOR CARRYING OUT THE INVENTION

[1364] This invention is a system that has a task AI corresponding to each user and assists in creating documents in accordance with the decision-making of the superior. A specific embodiment of this system will be described below.

[1365] Server Roles

[1366] The server generates a business AI for each user. This business AI uses Python and TensorFlow to collect and learn from the user's work history and performance data. The server uses this data to train a machine learning model and provides a function to assist in creating documents tailored to the user's supervisor's decision-making.

[1367] Specifically, the server retrieves user work history and performance data from a database (e.g., MySQL). After collecting the data, the server preprocesses it and inputs it into a machine learning model. It normalizes the data, performs feature engineering, and converts it into a format suitable for the model. Then, it trains the model using TensorFlow.

[1368] Device Role

[1369] When a user creates a document, the device receives templates, formats, and necessary information provided by the business AI. The device displays this information and helps the user create documents efficiently. Specifically, the device retrieves data from the server using a web browser (e.g., Google Chrome) and displays it on the user interface.

[1370] The terminal displays the template received from the server on a web page. Using HTML and JavaScript, the template is dynamically generated and displayed in a format that is easy for the user to view.

[1371] User Roles

[1372] Users create documents based on templates and formats provided by the business AI through their devices. By utilizing the information provided by the business AI, they can quickly create documents that meet their superiors' preferences.

[1373] For example, if a user wants to create a "sales report," the business AI will provide past sales data and the boss's preferred format. The user then enters the necessary data into the provided template to complete the document. The completed document is saved in PDF format and submitted to the boss.

[1374] Specific examples

[1375] An example of a prompt sentence to be input into a generative AI model is, "Please provide a template for creating a sales report in my boss's preferred format based on the sales data from the past three months." When this prompt sentence is input into the generative AI model, the business AI analyzes the past sales data and generates a sales report template based on the boss's preferred format. Based on this template, the user can create a high-quality sales report in a short amount of time.

[1376] In this way, a system is realized in which the server, terminals, and users can work together to efficiently create materials.

[1377] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1378] Step 1:

[1379] The server collects users' work history and performance data.

[1380] Input: User ID

[1381] Data processing: The server queries a database (e.g., MySQL) to retrieve user activity history and performance data.

[1382] Output: Acquired business history and performance data

[1383] Specific operation: The server executes the query "SELECT FROM user_performance WHERE user_id = '12345'" to retrieve the data.

[1384] Step 2:

[1385] The server preprocesses the collected data and converts it into a format suitable for machine learning models.

[1386] Input: Acquired work history and performance data

[1387] Data processing: Data normalization and feature engineering.

[1388] Output: Preprocessed data

[1389] Specific behavior: The server imputes missing values ​​in the data, normalizes numerical data, and performs one-hot encoding on categorical data.

[1390] Step 3:

[1391] The server uses the preprocessed data to train the business AI.

[1392] Input: Preprocessed data

[1393] Data Computing: Training machine learning models using TensorFlow.

[1394] Output: Trained business AI model

[1395] Specific operation: The server executes the code "model.fit(training_data, labels, epochs=10)" to train the model.

[1396] Step 4:

[1397] The server uses a generative AI model to generate templates and formats based on the user's requests.

[1398] Input: User request (prompt)

[1399] Data calculation: Input prompts into the generative AI model to generate templates and formats.

[1400] Output: Generated templates and formats

[1401] Specific operation: The server inputs the prompt statement "Please provide a template for creating a sales report in the format preferred by your boss based on the sales data from the past three months" into the generative AI model.

[1402] Step 5:

[1403] The terminal displays the templates and formats provided by the server to the user.

[1404] Input: Generated templates and formats

[1405] Data processing: Converting templates and formats into a format that can be displayed on a web page.

[1406] Output: The template or format that is displayed to the user

[1407] Specific behavior: The terminal uses HTML and JavaScript to dynamically generate a template and executes the code "document.getElementById('template').innerHTML = receivedTemplate;".

[1408] Step 6:

[1409] The user creates materials based on the templates and formats displayed on the terminal.

[1410] Input: Displayed template or format

[1411] Data processing: Enter the necessary data and complete the materials.

[1412] Output: Finished document

[1413] Specific operation: The user enters sales data and other information into the provided template to complete the document. The completed document is saved in PDF format and submitted to a supervisor.

[1414] (Application example 1)

[1415] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1416] Conventional work support systems were unable to fully utilize the work history and performance data of individual users, making it difficult to create documents and optimize work instructions in line with supervisors' decision-making. Furthermore, the efficiency and optimization of work instructions for factory robots was not sufficiently implemented, making it difficult to improve work efficiency.

[1417] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1418] In this invention, the server includes: means for owning a task AI corresponding to each user; means for assisting in the creation of documents in line with the supervisor's decision-making; means for quickly creating documents in line with the supervisor's preferences; means for reducing the man-hours required for document review; means for understanding the difficulties and thoughts of subordinates; means for having an agent that understands a person's work even when the person in charge is absent; means for promoting the penetration of corporate culture; means for a factory robot to receive work instructions and provide optimal work procedures; means for learning work history and performance data and generating optimal work procedures; and means for providing work procedures based on the manager's instructions. This improves the work efficiency of users and enables the optimization of work instructions for factory robots.

[1419] "Business AI" is an artificial intelligence system that responds to individual users, learns their work history and performance data, and supports their work.

[1420] "Supervisor's decision-making" refers to the judgments and instructions given by a supervisor in the course of work.

[1421] "Means to assist in document creation" refers to a function that provides templates, formats, and necessary information for documents created by users.

[1422] "Document review man-hours" refers to the time and effort required to review and correct created documents.

[1423] "A means to understand the problems and thoughts of subordinates" is a function that collects and analyzes the problems and thoughts that subordinates face in the course of their work.

[1424] "An agent that understands a person's work even when the person in charge is absent" is a system that can understand a person's work content and handle it on their behalf even when the person in charge is absent.

[1425] "Means to promote the dissemination of corporate culture" refers to the function of helping employees understand and practice the company's values ​​and code of conduct.

[1426] A "factory robot" is a mechanical device used to automate work within a factory.

[1427] The "means for receiving work instructions and providing optimal work procedures" is a function that allows a factory robot to receive instructions and generate and provide optimal work procedures.

[1428] "Means for learning work history and performance data and generating optimal work procedures" is a function that learns and generates optimal work procedures based on past work history and performance data.

[1429] The "means for providing work procedures based on the manager's instructions" is a function for providing specific work procedures to factory robots based on the manager's instructions.

[1430] The system for implementing this invention consists of three main elements: a server, a terminal, and a user. The server has a business AI that corresponds to each user and has a function to assist in the creation of documents in line with the supervisor's decision-making. It also has a function to quickly create documents that meet the supervisor's preferences and reduce the labor required for document review. Furthermore, the system includes functions that can grasp the points of difficulty and thoughts of subordinates, a function to have an agent that understands the person's work even when the person in charge is absent, and a function to promote the penetration of corporate culture.

[1431] The server also has the function of allowing factory robots to receive work instructions and provide optimal work procedures. Specifically, it has the function of learning work history and performance data to generate optimal work procedures, and the function of providing work procedures based on instructions from managers.

[1432] The system's program is implemented using Python and the scikit-learn library. The server stores users' work history and performance data in JSON format, and uses this data to learn optimal work procedures using a linear regression model. Specifically, the system reads the user's work history data, extracts features and performance data, and uses a linear regression model to learn from them. It then generates new work procedures based on the manager's instructions and calculates predicted performance.

[1433] The terminal is a device that allows users to receive document templates and work procedures provided by the server and create documents and perform tasks based on them. Terminals include PCs, tablets, smartphones, etc.

[1434] Users perform their work based on document templates and work procedures provided by the server. The documents and work results created by the users are sent back to the server and stored as work history.

[1435] As a concrete example, consider the case where a factory robot performs assembly work. The manager instructs the "assembly work" and provides features such as the difficulty of the work, the required skills, and the time required. The server generates the optimal work procedure based on this and provides it to the factory robot.

[1436] Example prompt sentence:

[1437] User ID: 12345

[1438] Work Instructions: Assembly Work

[1439] Task features: [0.8, 0.6, 0.7]

[1440] Based on this prompt, the server provides optimal work procedures and predicted performance, improving user efficiency and optimizing work instructions for factory robots.

[1441] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1442] Step 1:

[1443] The server reads the user's work history data in JSON format. The input is the user ID, and the output is the user's work history data. This data includes past work content and performance.

[1444] Step 2:

[1445] The server extracts features and performance data from the loaded work history data. The input is the work history data, and the output is features and performance data. Features include the difficulty of the task, the required skills, and the time required.

[1446] Step 3:

[1447] The server trains a linear regression model using the extracted features and performance data. The inputs are the features and performance data, and the output is a trained linear regression model. This model learns the relationship between the features and performance.

[1448] Step 4:

[1449] The server receives work instructions from the manager. The input is the manager's instructions and the work's features, and the output is work instruction data. The work instruction data includes the specific work content and its features.

[1450] Step 5:

[1451] The server uses a trained linear regression model to generate optimal work procedures based on the manager's instructions. The input is the work instruction data and the trained model, and the output is the optimal work procedure. This procedure is generated based on predicted performance.

[1452] Step 6:

[1453] The server provides the generated optimal work procedure to the factory robot. The input is the optimal work procedure, and the output is work instructions for the factory robot. The factory robot performs the work based on these instructions.

[1454] Step 7:

[1455] The factory robot performs the work according to the provided work procedure. The input is the work instruction from the server, and the output is the work result. The work result is sent back to the server and accumulated as a work history.

[1456] Step 8:

[1457] The server receives the work results sent from the factory robots and stores them in a work history database. The input is the work results, and the output is updated work history data. This data is used for the next learning.

[1458] Example 2

[1459] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1460] In modern companies, it is important for managers to understand the progress and problems of their subordinates' work in real time. However, with conventional systems, it is difficult for managers to quickly and accurately grasp the points of difficulty and thoughts of their subordinates, and there are issues such as the time and effort required to create and review documents. Furthermore, when the person in charge is absent, it is difficult to understand that person's work, and corporate culture is often not fully ingrained.

[1461] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for possessing a task AI corresponding to each user, means for assisting in document creation in accordance with the supervisor's decision-making, means for quickly creating documents in line with the supervisor's preferences, means for reducing the man-hours required for document review, means for identifying the subordinate's difficulties and thoughts, means for having an agent that understands the subordinate's work even when the person in charge is absent, means for promoting the penetration of corporate culture, means for collecting the user's work history and performance data, means for preprocessing the collected data, means for inputting the preprocessed data into a generative AI model and generating analysis results, and means for reporting the generated analysis results to the supervisor. This allows the supervisor to grasp the progress and problems of the subordinate's work in real time, thereby improving the efficiency of document creation and review, understanding work even when the person in charge is absent, and promoting the penetration of corporate culture.

[1462] "Business AI" is an artificial intelligence system that analyzes users' work history and performance data to improve work efficiency and identify problems.

[1463] "User" refers to an individual employee who performs work using business AI.

[1464] "Supervisor" refers to a managerial person who oversees the progress and performance of the user's work and makes decisions.

[1465] "Work history" refers to data such as records of work a user has done in the past, task completion status, and comment history.

[1466] "Performance data" refers to data such as the results, efficiency, and evaluation of a user's work.

[1467] A "generative AI model" refers to an artificial intelligence model that analyzes collected data and generates results in text format.

[1468] A "prompt" is an instruction entered into a generative AI model to encourage it to analyze data and generate results.

[1469] "Preprocessing" refers to the process of data cleaning and normalization to prepare collected data in an analyzable format.

[1470] "Analysis Results" refers to the conclusions and suggestions regarding the progress and problems of the user's work that the generative AI model generates after analyzing the data.

[1471] "Reporting" refers to a means of communicating the generated analysis results to a superior, and includes formats such as dashboard display and email notification.

[1472] An "agent" is a system that keeps track of a person's work and provides them with the necessary information even when they are not present.

[1473] "Corporate culture" refers to the values, code of conduct, and communication style shared within a company.

[1474] This invention is a system that collects a user's work history and performance data, analyzes them using a generative AI model, and reports the results to a superior. A specific embodiment of this system will be described below.

[1475] The server obtains data from business management software and performance evaluation tools to collect users' work history and performance data. Specifically, business management software such as JIRA and Trello are used, and performance evaluation tools such as SAP SuccessFactors are used. Data is obtained from these tools via APIs.

[1476] The server then preprocesses the collected data, which includes cleaning the data (imputing missing values ​​and removing outliers) and normalizing the data (scaling and encoding). The preprocessing is performed using the Python Pandas library.

[1477] The preprocessed data is then fed into a generative AI model, OpenAI's GPT-4, which analyzes the data based on the prompt and identifies potential problems or difficulties the user may be facing.

[1478] As a concrete example, consider a case where a user is using the project management tool JIRA. The server collects the user's task completion status and comment history from JIRA. Next, it inputs the following prompt sentence to the generative AI model:

[1479] "Analyze the following work history and performance data to identify potential pain points your users may be experiencing. Data includes: task completion status, comment history, and progress reports."

[1480] The generative AI model analyzes the data based on this prompt and draws conclusions such as, "The user may be having difficulty prioritizing tasks."

[1481] Finally, the server reports the generated analysis results to the manager, who can display the results on a dashboard (e.g., Tableau or Power BI) or send them via email or a notification system, allowing the manager to keep track of the progress and issues of their subordinates' work in real time.

[1482] This system allows managers to quickly grasp the progress and problems of their subordinates' work and provide appropriate support. It also improves the efficiency of document creation and review, keeps track of work when the person in charge is absent, and promotes the penetration of corporate culture.

[1483] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1484] Step 1: Data collection

[1485] The server collects user work history and performance data. Specifically, it obtains data from work management software (e.g., JIRA, Trello) and performance evaluation tools (e.g., SAP SuccessFactors) via API. The input is raw data obtained from the API endpoint, and the output is the collected work history and performance data. For example, using the JIRA API, task completion status and comment history are obtained from the endpoint GET / rest / api / 2 / search?jql=assignee=currentUser().

[1486] Step 2: Data Preprocessing

[1487] The server preprocesses the collected data. Preprocessing includes data cleaning (filling in missing values ​​and removing outliers) and data normalization (scaling and encoding). The input is the collected raw data, and the output is the preprocessed, clean data. Specifically, it uses the Python Pandas library to fill in missing values ​​with the fillna() method and remove outliers with conditional filtering.

[1488] Step 3: Data analysis

[1489] The server inputs the preprocessed data into a generative AI model. OpenAI's GPT-4 is used as the generative AI model. The input is the preprocessed clean data and a prompt, and the output is the analysis result by the generative AI model. Specifically, the server sends the following prompt to the generative AI model:

[1490] "Analyze the following work history and performance data to identify potential pain points your users may be experiencing. Data includes: task completion status, comment history, and progress reports."

[1491] Step 4: Generate results

[1492] The generative AI model analyzes data based on the prompt and identifies problems or difficulties the user may be facing. The input is the prompt sent to the generative AI model and preprocessed data, and the output is the analysis results in text format. For example, it may conclude that "the user may be having difficulty prioritizing tasks."

[1493] Step 5: Reporting the results

[1494] The server reports the generated analysis results to the manager. The report is displayed on a dashboard used by the manager (e.g., Tableau, Power BI) or sent via email or a notification system. The input is the analysis results obtained from the generative AI model, and the output is in the form of a report for the manager. Specifically, the results are converted to JSON format and added to the dashboard using Tableau's API.

[1495] In this way, superiors can grasp the progress and problems of their subordinates' work in real time.

[1496] (Application example 2)

[1497] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1498] With conventional work management systems, it was difficult for managers to grasp the progress and problems of their subordinates in real time, which sometimes led to delays when a quick response was required. Furthermore, there was a lack of means to monitor the performance of robots operating in factories in real time and respond immediately when a problem occurred. This led to problems such as a decline in work efficiency and reduced productivity.

[1499] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for possessing a task AI corresponding to each user; means for assisting in the creation of documents in accordance with the supervisor's decision-making; means for quickly creating documents in line with the supervisor's preferences; means for reducing the labor required for document review; means for identifying the difficulties and thoughts of subordinates; means for having an agent who understands the person's work even when the person in charge is absent; means for promoting the penetration of corporate culture; means for collecting and analyzing robot work history data and reporting the results to a manager; and means for monitoring robot performance data in real time and notifying the manager if a problem occurs. This allows a manager to understand the progress and problems of their subordinates in real time, monitor the performance of robots operating in the factory in real time, and respond immediately if a problem occurs.

[1500] "Business AI" is an artificial intelligence system that analyzes a user's work history and performance data to understand the progress and problems of work.

[1501] "Means to assist in the creation of documents in line with the supervisor's decision-making" is a function for quickly creating necessary documents based on the supervisor's instructions and intentions.

[1502] "Means for quickly creating materials that meet the boss's preferences" is a function for quickly generating materials that meet the boss's preferences and requests.

[1503] "Means to reduce document review man-hours" is a function for reducing the time and effort required to check and correct documents.

[1504] "A means of understanding the problems and thoughts of subordinates" is a function that allows you to understand the problems and thoughts that your subordinates are facing in real time.

[1505] "A means to have an agent who understands the person's work even when the person in charge is absent" is a function that has an agent who understands the person's work and can handle it in their place, even when the person in charge is absent.

[1506] "Means to promote the dissemination of corporate culture" is a function that spreads and helps employees understand the company's values ​​and code of conduct.

[1507] "Means of collecting and analyzing work history data of robots and reporting the results to managers" is a function for collecting work history data of robots operating in factories and reporting the analysis results to managers.

[1508] "Means for monitoring robot performance data in real time and notifying administrators if a problem occurs" refers to a function for monitoring robot performance data in real time and immediately notifying administrators if a problem occurs.

[1509] A system for carrying out this invention comprises a server, a terminal, and a user element. The server has a task AI corresponding to each user, and includes means for assisting in the creation of documents in accordance with the decision-making of a supervisor, means for quickly creating documents in line with the supervisor's preferences, means for reducing the man-hours required for document review, means for understanding points of difficulty and thoughts of subordinates, means for having an agent that understands the work of each person even when the person in charge is absent, means for promoting the penetration of corporate culture, means for collecting and analyzing work history data of robots and reporting the results to a manager, and means for monitoring robot performance data in real time and notifying if a problem occurs.

[1510] The server uses software such as Python, pandas, and smtplib to collect the robot's work history data and monitor performance data in real time. The data is provided in CSV file format, which the server reads and records as a problem if performance falls below a certain threshold. If a problem is detected, the server reports it to the administrator by email.

[1511] As a concrete example, the robot's work history data is provided in a CSV file like this:

[1512] csv

[1513] timestamp,performance

[1514] 2023-10-01 08:00:00,85

[1515] 2023-10-01 09:00:00,65

[1516] 2023-10-01 10:00:00,90

[1517] Based on this data, the server detects time periods where performance is below 70 and records them as problems. For example, the data for 2023-10-01 09:00:00 shows performance as 65, so this is recorded as a problem.

[1518] An example of a prompt to input to a generative AI model is as follows:

[1519] "Write a Python program that analyzes the work history data of robots operating in a factory, and if the performance falls below a certain threshold, logs it as a problem and reports it to a manager via email. The data will be provided in a CSV file, and the performance threshold will be 70."

[1520] In this way, the server allows managers to understand the progress and problems of their subordinates in real time, and can monitor the performance of robots operating in the factory in real time and respond immediately if a problem occurs.

[1521] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1522] Step 1:

[1523] The server reads the robot's work history data in CSV file format. The input is a CSV file, an...

Claims

1. A system comprising a server and a terminal, wherein the server: means for collecting user's work history data and performance data from the terminal used by the user; a means for generating a prompt sentence instructing the user to generate a business report or a progress report based on the results of analyzing the user's work history data and performance data, and inputting the prompt sentence into a generative AI model to generate the business report or the progress report; a means for inputting the work history data into a machine learning model to analyze the frequency or duration of tasks performed by the user each week, thereby identifying the user's work patterns, including identifying the days of the week on which the user creates reports; and means for automatically executing the task to be performed by the user in accordance with the user's work pattern, the means including automatically creating the report on a specified day of the week; Contains system.

2. The system described in claim 1 further includes a means for creating a prompt statement that instructs the system to suggest the optimal procedure for the user's work based on the results of analyzing the user's work history data and performance data, and inputting the prompt statement into the generative AI model, thereby suggesting the optimal procedure for the user's work.

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