system

Abstract

We provide the system. [Solution] A data integration means that collects data from various internal information management tools and integrates said data, An information provision means that searches the data in response to a user's request for information and provides information suitable for the request, A document generation means that uses a generation model to automatically generate documents in a specified format based on the integrated data and provides such documents, A means of sharing results that aggregates and shares the work progress and deliverables of multiple users, A business efficiency system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern corporate activities, improving business efficiency is an important issue. However, in the current situation where various information management tools are in disarray, data aggregation and utilization are not sufficiently carried out. Furthermore, employees spend a lot of time on information exchange between individual tools and document creation, leading to a decrease in productivity. These problems undermine the competitiveness of the entire company and increase the burden on employees. Therefore, there is a need for a system that organically links various tools, enables unified management and efficient use of data, and automates document creation and progress sharing.

Means for Solving the Problems

[0005] This invention proposes a system that includes a data integration means for collecting and integrating data from various internal information management tools, and an information provision means for searching data and providing necessary information in response to information requests from users. Furthermore, it includes an automatic document generation means that automatically generates and provides documents in a specified format based on the integrated data using a generation model, and a results sharing means for aggregating and sharing work progress and deliverables from multiple users. This system makes it possible to streamline operations and improve employee productivity and well-being.

[0006] A "data integration tool" is a function that integrates data obtained from various information management tools and manages it as a single dataset.

[0007] "Information provision means" refers to a function that searches for data based on requests from users and provides relevant information.

[0008] "Automatic document generation means" refers to a function that utilizes a generation model to automatically create and provide documents in a specified format based on integrated data.

[0009] A "means of sharing results" refers to a function that aggregates the progress and deliverables of tasks involving multiple users and shares that information among stakeholders.

[0010] A "generative model" refers to an algorithm that uses artificial intelligence to learn patterns from data and generate new information or materials.

[0011] "Users" refers to individuals or teams who operate the system to improve the efficiency of their work.

[0012] "Information management tools" refer to software used for creating and managing business data, including email systems and messaging applications. [Brief explanation of the drawing]

[0013] [Figure 1]This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0014] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

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

[0016] In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

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

[0018] In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0019] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor and an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), and the like.

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0021] [First Embodiment]

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

[0023] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0024] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0025] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0026] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0027] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0030] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0031] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0032] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0033] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0034] The system according to the present invention is built with the aim of improving operational efficiency within a company and collects, integrates, and analyzes data in conjunction with various information management tools. The system achieves effective data processing and information provision through the organic cooperation of the server, terminal, and user.

[0035] The server retrieves and integrates data from email systems, messaging applications, and business workspaces installed within the company via APIs. The server stores the integrated data in a central database, eliminating data redundancy and performing data cleansing to ensure that the information is always accurate.

[0036] Users can access the system via a terminal and request information necessary for their work. The terminal requests information from the server in response to the user's request. The server quickly searches the database based on the requested information and sends the relevant information to the terminal. The terminal displays this information visually and formats it in a way that is easily understandable to the user.

[0037] Furthermore, the server utilizes a generative model to automatically generate materials based on user instructions. For example, it automatically creates and provides users with reports summarizing the latest sales data and market trends to prepare for sales meetings. Users can then use these generated reports to efficiently conduct meetings.

[0038] The server also aggregates work progress and deliverables, and generates reports to share results regularly. For example, it creates a weekly report summarizing the work status of the entire project team and distributes it to team members, ensuring everyone is aware of the latest situation and supporting accurate decision-making. Based on the provided reports, users can quickly decide on the next actions and efficiently advance the project.

[0039] As described above, the system of the present invention enables centralized data management and efficient information provision, thereby supporting improved employee productivity and increased efficiency in business activities.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] The server collects data from the internal email system, messaging apps, and workspace tools via APIs. The collected data is temporarily cached and updated periodically.

[0043] Step 2:

[0044] The server integrates cached data into a central database and performs cleansing to eliminate data redundancy and inconsistencies. This database functions as a single, unified data source for all users.

[0045] Step 3:

[0046] The user uses a terminal to request specific information. The terminal transmits the requested information to the server through the user interface. Here, the user can specify the type of information needed and the search criteria.

[0047] Step 4:

[0048] The server searches the database and extracts data that matches the requested criteria. If results are found, the server formats the information and prepares it to be sent to the terminal.

[0049] Step 5:

[0050] The terminal displays information received from the server to the user. The information is provided in a visual format that is easy for the user to understand intuitively. The user can then proceed with their work based on this information.

[0051] Step 6:

[0052] When a user requests document creation, the server uses a generative model to automatically generate the document based on the requested format and content. For example, it can create meeting reports or market analysis documents.

[0053] Step 7:

[0054] The server automatically generates documents and sends them to the terminal, where the user can view the content on the screen. Users can then download the generated documents or share them within the company.

[0055] Step 8:

[0056] The server aggregates the work progress of multiple users and visualizes the results. It automatically generates reports from this data as needed and distributes them to the entire team periodically.

[0057] Step 9:

[0058] Through these progress reports, users can understand the activities of other members and the overall picture of the project, and make decisions about the next steps.

[0059] (Example 1)

[0060] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0061] Information management has become complex, and inconsistencies and redundancies in data from different sources make it difficult to use accurate information. Furthermore, there is a lack of means to integrate information and generate appropriate documents in order to improve operational efficiency. Additionally, there is a need for a system to effectively share work progress with team members.

[0062] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0063] In this invention, the server includes an information integration means that collects information from an information processing device, integrates the information, eliminates duplication and corrects inconsistencies; an information response means that searches a database in response to information requests from various terminals and provides information that matches the request; and a document generation means that uses generation AI technology to automatically create a formatted document based on the integrated information and provides the document. This enables centralized information management, rapid document generation, and effective progress sharing.

[0064] An "information integration means" is a mechanism for integrating various types of information collected from information processing devices, correcting duplication and inconsistencies, and managing accurate data.

[0065] An "information response means" is a mechanism for searching a database based on information requests from various terminals and quickly providing the requested information.

[0066] A "document generation means" is a mechanism that uses generation AI technology to automatically create formatted documents based on integrated information and provide those documents.

[0067] A "means for sharing results" is a mechanism for aggregating the work progress and results of multiple users, and for distributing and sharing reports that are generated periodically.

[0068] "Generative AI technology" is a technology that utilizes artificial intelligence to analyze data and automatically generate documents and information based on specific formats and content.

[0069] This invention is a system designed to support effective information management and operational efficiency within a company. Specific embodiments are described below.

[0070] The server is responsible for data collection, acquiring data from various information processing devices. To this end, it employs techniques to collect data using APIs from software such as email systems, messaging platforms, and shared workspaces. The server integrates this data, eliminating duplicates and correcting inconsistencies to build an accurate and consistent information database.

[0071] Users access the server using their terminals and request information necessary for their work. An example of a prompt message a user might send from their terminal is, "Please create a sales report based on the latest sales data." The terminal sends this prompt to the server, and the request is processed.

[0072] As a means of responding to information requests from terminals, the server searches the database, extracts the requested information, and provides it to the terminal. The terminal then displays this information to the user in a visually easy-to-understand format, such as a graph or table, thereby enhancing the immediacy and convenience of the information.

[0073] Furthermore, the server utilizes a generative AI model to function as a document generation tool. Based on collected and processed information, the AI ​​automatically generates documents in a specified format. A concrete example is a report for sales meetings summarizing sales and market trends. The generated documents are sent to the user and used as a tool to enable efficient work execution.

[0074] Inventions implemented in this manner significantly improve the efficiency of information management and support increased productivity and faster decision-making across the entire company.

[0075] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0076] Step 1:

[0077] The server collects data from information processing devices. This input includes email data from email systems, message logs from chat applications, and task information from work workspaces. The server collects this data using APIs and integrates it into a central database. During this process, the server performs data cleansing to eliminate duplication and correct inconsistencies. This results in an accurate and consistent information database as output.

[0078] Step 2:

[0079] The user requests information necessary for their work through their terminal. As input, the user enters a natural language prompt into the terminal, such as "I want to know the progress of the current project." The terminal parses this prompt and requests information from the server. After the request is sent, the server queries the database based on the prompt to find the relevant information. The requested information is then sent back to the user's terminal as output.

[0080] Step 3:

[0081] The terminal formats the information received from the server in a user-friendly format. The input data is displayed visually, for example, as a table or graph. This allows the user to intuitively understand the information. The terminal's operation involves processing the information using a data visualization engine and providing an organized display as output.

[0082] Step 4:

[0083] The server uses a generative AI model to automatically generate documents. When a user enters a prompt requesting specific documents, the server analyzes the prompt and issues instructions to the generative AI model. The generative AI model analyzes the input data (e.g., sales data or market trends) and generates a report in the specified format. As output, the completed report is sent to the user's terminal.

[0084] Step 5:

[0085] The server periodically compiles work progress and results, creates reports, and shares them with team members. Inputs include progress data and completed work data from each team member. The server aggregates and analyzes this data to generate reports. As output, regularly updated reports are delivered to the terminals of relevant parties. This allows everyone to stay informed of the latest situation and make informed decisions.

[0086] (Application Example 1)

[0087] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0088] In today's manufacturing environment, efficient data integration and information delivery are required to cope with data diversity and rapid change. Furthermore, achieving efficiency in manufacturing processes and real-time work optimization presents a significant challenge. Additionally, there is the challenge of providing users with the information they need quickly and accurately, and making it easier to understand overall work progress.

[0089] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0090] In this invention, the server includes data integration means for collecting and integrating data from various internal information management devices, information provision means for searching the data in response to information requests from users and providing information suitable for those requests, automatic document generation means for automatically generating documents in a specified format based on the integrated data using a generation model and providing those documents, and optimization command means for providing real-time work instructions to production equipment and optimizing work processes. This enables efficient data management, optimization of manufacturing processes, and rapid information provision.

[0091] "Information management equipment" is a general term for devices and software used to collect, store, and manage data.

[0092] "Data integration means" refers to a function for combining and integrating data obtained from different sources within a single system.

[0093] An "information provision method" is a system that searches for and presents appropriate information from the data it holds based on the user's request.

[0094] A "generative model" is an algorithm or AI system that automatically generates documents in a specified format based on data.

[0095] "Automatic document generation means" refers to a function that uses a generation model to automatically create documents in a predetermined format from integrated data.

[0096] The "optimization command means" is a function that issues work instructions to production equipment in real time to streamline the production process.

[0097] "Work progress" refers to the process from the start to the completion of a task, and means managing its progress.

[0098] "Deliverables" refer to the goods or results obtained as a result of a specific task or project.

[0099] "Production equipment" refers to machinery, robots, and other devices used in the manufacturing process.

[0100] This invention is a system aimed at improving the efficiency of production processes and managing information. It collects data from internal information management devices and utilizes it to achieve optimal operation of production equipment.

[0101] The server collects data from information management devices within the company via APIs. The collected data is diverse, including production schedules, inventory information, and robot status. This data is integrated and cleansed by the server to maintain an accurate and non-redundant dataset.

[0102] The server enables efficient information retrieval and delivery in response to user requests. When a user requests specific information, the server has the ability to quickly search the database and provide the relevant information in real time. The terminal's display is used for visual data display. This allows users to quickly access the information they need and supports intelligent decision-making.

[0103] Furthermore, the server uses a generative AI model to automatically generate documents in a specified format from integrated data. To achieve this, it utilizes AI libraries such as TENSORFLOW® to enhance the data analysis and document generation processes. For example, by automatically generating graphs for monthly reports based on the latest production line operation data and providing them to senior managers, it becomes possible to quickly visualize production policies.

[0104] For example, if a manufacturing line is facing a shortage of human resources, the server analyzes operational data in real time and sends appropriate work instructions to the production equipment using an optimization command mechanism. This maximizes production efficiency.

[0105] An example of a prompt to input into the generating AI model is: "Based on the current inventory information and production schedule, please generate the optimal manufacturing process schedule."

[0106] The implementation of this system will lead to more efficient data management in manufacturing operations, faster information delivery, and optimization of production processes.

[0107] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0108] Step 1:

[0109] The server collects data from the company's information management devices via APIs. Specifically, the server periodically retrieves data such as production schedules, inventory information, and robot operating status. At this stage, the input is raw data from the APIs, and the output is an unintegrated dataset.

[0110] Step 2:

[0111] The server integrates and cleanses the collected data. Here, the Pandas library is used to integrate the data and eliminate unnecessary redundancy. This results in a clean and accurate dataset. The input to this step is the raw dataset collected in step 1, and the output is the integrated and cleansed data.

[0112] Step 3:

[0113] When a user requests the necessary information via their terminal, the server searches the database. The input is the user's information request, and a search query is generated to quickly extract the most relevant data based on the prompt. The output is the information relevant to the request, which is then sent to the terminal.

[0114] Step 4:

[0115] The server automatically generates documents using a generative AI model. Specifically, it uses TensorFlow to generate monthly reports and production plan reports from integrated data. The input is the integrated data obtained in step 2, and the output is a formatted document.

[0116] Step 5:

[0117] On the terminal, the generated materials are visually displayed and formatted in a way that is easily understandable to the user. The input is the generated materials, and the output on the terminal is the screen display for the user to use in decision-making.

[0118] Step 6:

[0119] The server transmits work instructions to production equipment using an optimized command mechanism. This includes real-time data analysis results. The input consists of generated prompt statements and production data, while the output consists of specific work instructions for each production device.

[0120] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0121] The business efficiency system according to the present invention incorporates an emotion engine, enabling responses and business process optimization that take into account the emotional state of employees. The server, terminal, and user elements collaborate to realize an innovative business environment that includes emotional data.

[0122] The server collects and integrates data from internal information management tools and provides necessary information to the terminal in response to specific information requests from users. It also automatically generates materials using generative models based on the integrated data to meet user requests. Furthermore, an emotion engine is incorporated, enabling the recognition of user emotions.

[0123] The emotion engine reads the user's emotions through voice and text analysis and provides real-time feedback. This feedback allows the server to adjust the timing and method of information delivery to suit the user and display information optimized for the device. For example, if the user is feeling stressed, the server re-evaluates task priorities and sends information to the device to encourage relaxation and appropriate alerts.

[0124] Furthermore, the emotion engine also influences automated document generation methods. It selects recommended words and designs based on the user's emotions, optimizing the document content to match their emotional state. For example, if motivation is low, the document can include supportive messages or be rearranged to emphasize positive outcomes.

[0125] Furthermore, when aggregating work progress from multiple users, the system analyzes sentiment trends to understand the team's atmosphere. The server uses this information to include feedback in periodic reports that boost team morale. For example, it adds praise based on project successes and achievements to encourage the sharing of results.

[0126] Through the above configuration, a system is created that improves operational efficiency by taking emotions into account, contributing to increased employee productivity and strengthening the overall competitiveness of the company.

[0127] The following describes the processing flow.

[0128] Step 1:

[0129] The server collects data from internal information management tools and retrieves it using APIs. The retrieved data is stored in a central database for centralized management.

[0130] Step 2:

[0131] The user operates the terminal to input requests for specific information or document creation. The terminal provides a user interface, allowing the user to easily select the necessary information.

[0132] Step 3:

[0133] The terminal sends a request from the user to the server. Based on that request, the server searches the database and extracts the relevant information.

[0134] Step 4:

[0135] The emotion engine analyzes user input and interactions in real time to recognize user emotions. It analyzes emotions from voice and text data and generates necessary feedback.

[0136] Step 5:

[0137] The server adjusts search results based on the results of the emotion engine's analysis. For example, if the user's emotions are anxious, the server may soften the presentation of search results and add support messages.

[0138] Step 6:

[0139] The device displays adjusted information to the user. The information is presented in a visually clear and emotionally resonant way, making it easy to understand.

[0140] Step 7:

[0141] When a user requests the automatic generation of materials, the server uses a generative model to automatically create materials with the specified content. The generated materials are then adjusted by an emotion engine to match the user's motivation.

[0142] Step 8:

[0143] The materials are provided to users via their devices, allowing them to review the content and utilize it in their work. The language and expressions used in the materials are appropriate to the user's emotional state.

[0144] Step 9:

[0145] The server aggregates work progress and results, and also incorporates emotional trends obtained from the emotion engine into its analysis. Based on this information, it creates a report and distributes it to users and team members.

[0146] Step 10:

[0147] Users can view reports on their devices to understand the team's status and their own work progress. Receiving emotionally sensitive feedback provides guidance for deciding on their next course of action.

[0148] (Example 2)

[0149] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0150] In improving business efficiency, optimizing business processes and providing information while taking into account the emotional state of individual users is a challenge. Conventional systems do not automatically generate feedback or materials that reflect users' emotions, which can lead to decreased business efficiency and productivity.

[0151] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0152] In this invention, the server includes an information integration means, an emotion-adaptive information provision means, and an emotion-adaptive material automatic generation means. This enables optimized information provision and material automatic generation, as well as the sharing of emotion-based feedback, while taking into account the user's emotional state.

[0153] "Information integration means" refers to methods or devices that integrate and centrally manage data collected from internal information management means.

[0154] An "emotionally adaptive information provision method" is a method or device that analyzes the emotional state of a user and provides optimized information based on that analysis.

[0155] An "emotion-adapted data automatic generation method" is a method or device that automatically generates data in a format that takes into account the user's emotional state, based on data integrated using a generation model.

[0156] A "means for sharing results that share emotional trends" refers to a method or device for aggregating the activity progress and deliverables of multiple users and sharing that information along with trends in emotions.

[0157] A "generative model" is an algorithm or program used to generate a specific format or information from data.

[0158] "External information sources" refer to databases, systems, and services that exist both inside and outside a company or organization, and are used as references when creating documents or acquiring information.

[0159] The business efficiency system of the present invention achieves efficient business processes through the collaborative functioning of servers, terminals, and users. Specifically, the server collects and integrates data using various software platforms as a means of information management. This includes, in particular, customer relationship management systems and business management systems.

[0160] The server uses an emotion analysis engine and leverages natural language processing technology to analyze the user's emotional state in real time. This emotion analysis utilizes audio data and input text data. For example, speech recognition engines and text analysis engines can be incorporated as specific software tools.

[0161] Emotionally adaptive information delivery is achieved by providing information at the optimal timing according to the user's emotional state. The server automatically generates materials from data using a generative AI model. The generative AI model includes, for example, advanced predictive analytics algorithms, which enable the materials to be delivered in an emotionally adaptive manner.

[0162] The terminal displays data and materials provided by the server. The terminal includes customization options to help users receive information more easily.

[0163] Users streamline their work based on information provided through their devices. For example, materials generated by a generative AI model may contain information useful for solving problems within a project. A concrete example is inputting a prompt into the generative AI model such as, "Generate feedback materials for a sales team whose motivation is low. Highlight success stories and include positive messages."

[0164] As described above, the present invention aims to improve operational efficiency and productivity through optimized information provision, automated material generation, and feedback sharing, while taking emotions into consideration.

[0165] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0166] Step 1:

[0167] The server collects data from the information management system. Using internal APIs and scheduled data acquisition, the server collects customer data and project progress information and stores it in a database. The input in this process is raw data from the customer information system, and the output is a dataset in an integrated format.

[0168] Step 2:

[0169] Users enter business-related requests through a terminal. For example, they might request a progress report for a specific project. The input is the user's request information, and based on this information, the server searches for the corresponding data and extracts the appropriate information. The output is the filtered data according to the request.

[0170] Step 3:

[0171] The server uses an emotion analysis engine to analyze the user's emotions in real time. The server receives text and voice data entered by the user and identifies the emotional state through natural language processing. The input is voice or text data, and the output is an analysis result indicating the user's emotional state.

[0172] Step 4:

[0173] The server inputs prompt text into a generation AI model, which then automatically generates materials appropriate to the user's emotional state. For example, it might input the prompt text, "Please create follow-up materials for when project progress is unsatisfactory." The input consists of the prompt text and various datasets, and the output is materials adapted to the user's emotions.

[0174] Step 5:

[0175] The terminal displays materials provided by the server and notifies the user. The terminal displays material files, important alerts, and notifications on the user's screen, making them easily accessible. Input consists of materials sent from the server, and the user receives the resulting materials and notifications.

[0176] Step 6:

[0177] Users adjust business processes based on information provided on their terminals and plan new tasks as needed. Once users review the materials, they use them to revise project activities and develop new plans. Input is the information displayed on the terminal, and output is the specific business plan and its execution.

[0178] (Application Example 2)

[0179] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0180] Traditional business efficiency systems focus primarily on information integration and provision, automated document generation, and sharing of work deliverables, but they lack optimization that takes user emotions into account. This makes it difficult to effectively optimize business processes in accordance with user emotions and to create documents tailored to those emotions. Furthermore, providing appropriate feedback that reflects user emotions is challenging, hindering the development of a positive team atmosphere and improving user satisfaction.

[0181] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0182] In this invention, the server includes data integration means, information provision means, automatic material generation means, and emotion recognition means. This enables the analysis of user emotions, optimization of business processes based on these analyses, provision of materials tailored to emotions, and feedback that takes emotions into consideration.

[0183] A "data integration system" is a mechanism for collecting data from various sources and centrally combining that data.

[0184] An "information provision method" is a system that searches for necessary information based on requests from users and provides it in an appropriate format.

[0185] A "document generation system" is a mechanism that uses a generation model to automatically create documents in a specified format from integrated data and provide them to users.

[0186] A "method for sharing results" is a system for aggregating the work progress and deliverables of multiple users and sharing them within a team.

[0187] An "emotion recognition tool" is a system that analyzes the user's emotions and reflects them in optimizing processes and improving the content of materials.

[0188] The system of this invention uses a smart device, an emotion analysis engine, and a cloud server to provide information and optimize processes based on the user's emotions.

[0189] The server receives data transmitted from smart devices and uses an emotion analysis engine to analyze the user's emotions from voice and facial expressions. Based on the acquired emotion data, it becomes possible to optimize business processes and customize materials. The server processes the data with high accuracy using emotion analysis software such as Microsoft® Azure® Emotion API.

[0190] The device has the ability to display information on devices such as smart glasses and tablets, providing real-time information tailored to the user's emotions. For example, if the user is feeling stressed, it can display information related to relaxation. This device includes smart wear such as Google® Glass®.

[0191] Users can obtain information in real time through their devices, thereby improving work efficiency. For example, in customer service, emotion recognition can enable the most appropriate response.

[0192] By utilizing a generative AI model, automatically generated materials and information are customized to suit individual emotions. Therefore, the materials include positive messages and supportive content, leading to increased user motivation.

[0193] For example, if a customer shows discomfort due to background noise, the system can display a message on the screen using music or sound effects to encourage relaxation. An example of a prompt message in this case would be: "This system uses an emotion analysis engine to provide optimal information and adjust the process based on the user's emotions. Please display relaxation information based on voice and facial expression data."

[0194] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0195] Step 1:

[0196] The server receives audio and video data collected from smart devices. Here, data acquired via camera and microphone serves as input. This data is transferred to a cloud server and formatted into a format that can be analyzed using emotion analysis software.

[0197] Step 2:

[0198] The server inputs formatted data into an emotion analysis engine to calculate the user's emotional state. Specifically, it analyzes voice pitch and evaluates changes in facial expressions. As a result of the analysis, the user's emotional information (e.g., joy, surprise, anger) is output. Based on this information, prompt sentences are generated for the generative AI model.

[0199] Step 3:

[0200] The terminal receives emotion data and prompt messages sent from the server. Based on this information, it displays information and messages appropriate to the user. Here, the displayed content is dynamically determined according to the input emotion data. Specifically, if the user indicates stress, messages and music related to relaxation will be displayed.

[0201] Step 4:

[0202] Users review the information provided by their devices and adjust their actions as needed. For example, they might take action based on the information provided to shift their emotional state in a positive direction. Finally, user feedback is re-entered into the system and used to improve subsequent analysis and information provision. This cycle continuously optimizes the process.

[0203] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0204] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0205] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0206] [Second Embodiment]

[0207] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0208] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0209] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0210] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0211] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0212] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0213] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0214] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0215] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0216] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0217] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0218] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0219] The system according to the present invention is built with the aim of improving operational efficiency within a company and collects, integrates, and analyzes data in conjunction with various information management tools. The system achieves effective data processing and information provision through the organic cooperation of the server, terminal, and user.

[0220] The server retrieves and integrates data from email systems, messaging applications, and business workspaces installed within the company via APIs. The server stores the integrated data in a central database, eliminating data redundancy and performing data cleansing to ensure that the information is always accurate.

[0221] Users can access the system via a terminal and request information necessary for their work. The terminal requests information from the server in response to the user's request. The server quickly searches the database based on the requested information and sends the relevant information to the terminal. The terminal displays this information visually and formats it in a way that is easily understandable to the user.

[0222] Furthermore, the server utilizes a generative model to automatically generate materials based on user instructions. For example, it automatically creates and provides users with reports summarizing the latest sales data and market trends to prepare for sales meetings. Users can then use these generated reports to efficiently conduct meetings.

[0223] The server also aggregates work progress and deliverables, and generates reports to share results regularly. For example, it creates a weekly report summarizing the work status of the entire project team and distributes it to team members, ensuring everyone is aware of the latest situation and supporting accurate decision-making. Based on the provided reports, users can quickly decide on the next actions and efficiently advance the project.

[0224] As described above, the system of the present invention enables centralized data management and efficient information provision, thereby supporting improved employee productivity and increased efficiency in business activities.

[0225] The following describes the processing flow.

[0226] Step 1:

[0227] The server collects data from the internal email system, messaging apps, and workspace tools via APIs. The collected data is temporarily cached and updated periodically.

[0228] Step 2:

[0229] The server integrates cached data into a central database and performs cleansing to eliminate data redundancy and inconsistencies. This database functions as a single, unified data source for all users.

[0230] Step 3:

[0231] The user uses a terminal to request specific information. The terminal transmits the requested information to the server through the user interface. Here, the user can specify the type of information needed and the search criteria.

[0232] Step 4:

[0233] The server searches the database and extracts data that matches the requested criteria. If results are found, the server formats the information and prepares it to be sent to the terminal.

[0234] Step 5:

[0235] The terminal displays information received from the server to the user. The information is provided in a visual format that is easy for the user to understand intuitively. The user can then proceed with their work based on this information.

[0236] Step 6:

[0237] When a user requests document creation, the server uses a generative model to automatically generate the document based on the requested format and content. For example, it can create meeting reports or market analysis documents.

[0238] Step 7:

[0239] The server automatically generates documents and sends them to the terminal, where the user can view the content on the screen. Users can then download the generated documents or share them within the company.

[0240] Step 8:

[0241] The server aggregates the work progress of multiple users and visualizes the results. It automatically generates reports from this data as needed and distributes them to the entire team periodically.

[0242] Step 9:

[0243] Through these progress reports, users can understand the activities of other members and the overall picture of the project, and make decisions about the next steps.

[0244] (Example 1)

[0245] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0246] Information management has become complex, and inconsistencies and redundancies in data from different sources make it difficult to use accurate information. Furthermore, there is a lack of means to integrate information and generate appropriate documents in order to improve operational efficiency. Additionally, there is a need for a system to effectively share work progress with team members.

[0247] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0248] In this invention, the server includes an information integration means that collects information from an information processing device, integrates the information, eliminates duplication and corrects inconsistencies; an information response means that searches a database in response to information requests from various terminals and provides information that matches the request; and a document generation means that uses generation AI technology to automatically create a formatted document based on the integrated information and provides the document. This enables centralized information management, rapid document generation, and effective progress sharing.

[0249] An "information integration means" is a mechanism for integrating various types of information collected from information processing devices, correcting duplication and inconsistencies, and managing accurate data.

[0250] An "information response means" is a mechanism that searches a database based on information requests from various terminals and provides the requested information quickly.

[0251] A "document generation means" is a mechanism that uses generation AI technology to automatically create formatted documents based on integrated information and provide those documents.

[0252] A "means of sharing results" is a mechanism for aggregating the work progress and results of multiple users, and for distributing and sharing reports that are generated periodically.

[0253] "Generative AI technology" is a technology that utilizes artificial intelligence to analyze data and automatically generate documents and information based on specific formats and content.

[0254] This invention is a system designed to support effective information management and operational efficiency within a company. Specific embodiments are described below.

[0255] The server is responsible for data collection, acquiring data from various information processing devices. To this end, it employs techniques to collect data using APIs from software such as email systems, messaging platforms, and shared workspaces. The server integrates this data, eliminating duplicates and correcting inconsistencies to build an accurate and consistent information database.

[0256] Users access the server using their terminals and request information necessary for their work. An example of a prompt message a user might send from their terminal is, "Please create a sales report based on the latest sales data." The terminal sends this prompt to the server, and the request is processed.

[0257] As a means of responding to information requests from terminals, the server searches the database, extracts the requested information, and provides it to the terminal. The terminal then displays this information to the user in a visually easy-to-understand format, such as a graph or table, thereby enhancing the immediacy and convenience of the information.

[0258] Furthermore, the server utilizes a generative AI model to function as a document generation tool. Based on collected and processed information, the AI ​​automatically generates documents in a specified format. A concrete example is a report for sales meetings summarizing sales and market trends. The generated documents are sent to the user and used as a tool to enable efficient work execution.

[0259] Inventions implemented in this manner significantly improve the efficiency of information management and support increased productivity and faster decision-making across the entire company.

[0260] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0261] Step 1:

[0262] The server collects data from information processing devices. This input includes email data from email systems, message logs from chat applications, and task information from work workspaces. The server collects this data using APIs and integrates it into a central database. During this process, the server performs data cleansing to eliminate duplication and correct inconsistencies. This results in an accurate and consistent information database as output.

[0263] Step 2:

[0264] The user requests information necessary for their work through their terminal. As input, the user enters a natural language prompt into the terminal, such as "I want to know the progress of the current project." The terminal parses this prompt and requests information from the server. After the request is sent, the server queries the database based on the prompt to find the relevant information. The requested information is then sent back to the user's terminal as output.

[0265] Step 3:

[0266] The terminal formats the information received from the server in a user-friendly format. The input data is displayed visually, for example, as a table or graph. This allows the user to intuitively understand the information. The terminal's operation involves processing the information using a data visualization engine and providing an organized display as output.

[0267] Step 4:

[0268] The server uses a generative AI model to automatically generate documents. When a user enters a prompt requesting specific documents, the server analyzes the prompt and issues instructions to the generative AI model. The generative AI model analyzes the input data (e.g., sales data or market trends) and generates a report in the specified format. As output, the completed report is sent to the user's terminal.

[0269] Step 5:

[0270] The server periodically compiles work progress and results, creates reports, and shares them with team members. Inputs include progress data and completed work data from each team member. The server aggregates and analyzes this data to generate reports. As output, regularly updated reports are delivered to the terminals of relevant parties. This allows everyone to stay informed of the latest situation and make informed decisions.

[0271] (Application Example 1)

[0272] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0273] In today's manufacturing environment, efficient data integration and information delivery are required to cope with data diversity and rapid change. Furthermore, achieving efficiency in manufacturing processes and real-time work optimization presents a significant challenge. Additionally, there is the challenge of providing users with the information they need quickly and accurately, and making it easier to understand overall work progress.

[0274] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0275] In this invention, the server includes data integration means for collecting and integrating data from various internal information management devices, information provision means for searching the data in response to information requests from users and providing information suitable for those requests, automatic document generation means for automatically generating documents in a specified format based on the integrated data using a generation model and providing those documents, and optimization command means for providing real-time work instructions to production equipment and optimizing work processes. This enables efficient data management, optimization of manufacturing processes, and rapid information provision.

[0276] "Information management equipment" is a general term for devices and software used to collect, store, and manage data.

[0277] "Data integration means" refers to a function for combining and integrating data obtained from different sources within a single system.

[0278] An "information provision method" is a system that searches for and presents appropriate information from the data it holds based on the user's request.

[0279] A "generative model" is an algorithm or AI system that automatically generates documents in a specified format based on data.

[0280] The "document automatic generation means" refers to the function of automatically creating a document in accordance with a predetermined format from integrated data using a generation model.

[0281] The "optimization instruction means" is a function for giving a work instruction to a production device in real time to improve the production process efficiency.

[0282] "Work progress" refers to the process from the start to the completion of work, and means managing its progress.

[0283] "Deliverables" refer to goods or results obtained as a result of a specific work or project.

[0284] The "production device" refers to devices such as machines and robots used in the manufacturing process.

[0285] The present invention is a system aimed at improving the efficiency of the production process and information management. It aggregates data from an internal information management device and utilizes it to achieve optimal operation of the production device.

[0286] The server collects data from the information management devices within the company through an API. The data collected covers a wide range, such as production schedules, inventory information, and the status of robots. These data are integrated by the server and undergo cleansing to maintain an accurate and non-redundant dataset.

[0287] The server realizes efficient information search and provision in response to requests from users. When a user requests specific information, the server has the ability to quickly search the database and provide the relevant information in real time. A terminal display is used for visual data display. Thereby, users can quickly access the necessary information and support intelligent decision-making.

[0288] Furthermore, the server uses a generative AI model to automatically generate documents in a specified format from integrated data. To achieve this, it utilizes AI libraries such as TensorFlow to enhance the data analysis and document generation processes. For example, by automatically generating graphs for monthly reports based on the latest production line operation data and providing them to senior managers, it becomes possible to quickly visualize production policies.

[0289] For example, if a manufacturing line is facing a shortage of human resources, the server analyzes operational data in real time and sends appropriate work instructions to the production equipment using an optimization command mechanism. This maximizes production efficiency.

[0290] An example of a prompt to input into the generating AI model is, "Based on the current inventory information and production schedule, please generate the optimal manufacturing process schedule."

[0291] The implementation of this system will lead to more efficient data management in manufacturing operations, faster information delivery, and optimization of production processes.

[0292] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0293] Step 1:

[0294] The server collects data from the company's information management devices via APIs. Specifically, the server periodically retrieves data such as production schedules, inventory information, and robot operating status. At this stage, the input is raw data from the APIs, and the output is an unintegrated dataset.

[0295] Step 2:

[0296] The server integrates and cleanses the collected data. Here, the Pandas library is used to integrate the data and eliminate unnecessary redundancy. This results in a clean and accurate dataset. The input to this step is the raw dataset collected in step 1, and the output is the integrated and cleansed data.

[0297] Step 3:

[0298] When a user requests the necessary information via their terminal, the server searches the database. The input is the user's information request, and a search query is generated to quickly extract the most relevant data based on the prompt. The output is the information relevant to the request, which is then sent to the terminal.

[0299] Step 4:

[0300] The server automatically generates documents using a generative AI model. Specifically, it uses TensorFlow to generate monthly reports and production plan reports from integrated data. The input is the integrated data obtained in step 2, and the output is a formatted document.

[0301] Step 5:

[0302] On the terminal, the generated materials are visually displayed and formatted in a way that is easily understandable to the user. The input is the generated materials, and the output on the terminal is the screen display for the user to use in decision-making.

[0303] Step 6:

[0304] The server transmits work instructions to production equipment using an optimized command mechanism. This includes real-time data analysis results. The input consists of generated prompt statements and production data, while the output consists of specific work instructions for each production device.

[0305] Furthermore, an emotion engine for estimating the user's emotions may be combined. That is, the specific processing unit 290 may estimate the user's emotions using the emotion specific model 59 and perform specific processing using the user's emotions.

[0306] The business efficiency improvement system according to the present invention enables responses considering the emotional state of employees and optimization of business processes by incorporating an emotion engine. Each element of the server, terminal, and user collaborates to realize an innovative business environment including emotion data.

[0307] The server collects and integrates data from internal information management tools and provides the necessary information to the terminal in response to specific information requests from the user. Also, it utilizes a generation model based on the integrated data to automatically generate materials and respond to the user's requests. Furthermore, an emotion engine is incorporated here, making it possible to recognize the user's emotions.

[0308] The emotion engine reads the user's emotions through voice analysis and text analysis and provides real-time feedback. With this feedback, the server can adjust the timing and method of information provision according to the user and display optimized information on the terminal. For example, when the user is feeling stressed, the server re-evaluates the task priorities and sends information to encourage relaxation or appropriate alerts to the terminal.

[0309] Also, the emotion engine affects the material automatic generation means. It selects words and designs recommended by the user's emotions and optimizes the content of the materials for the emotional situation. As a specific example, when motivation is low, support messages can be incorporated into the materials or arrangements can be made to emphasize positive results.

[0310] Furthermore, when aggregating work progress from multiple users, the system analyzes sentiment trends to understand the team's atmosphere. The server uses this information to include feedback in periodic reports that boost team morale. For example, it adds praise based on project successes and achievements to encourage the sharing of results.

[0311] Through the above configuration, a system is created that improves operational efficiency by taking emotions into account, contributing to increased employee productivity and strengthening the overall competitiveness of the company.

[0312] The following describes the processing flow.

[0313] Step 1:

[0314] The server collects data from internal information management tools and retrieves it using APIs. The retrieved data is stored in a central database for centralized management.

[0315] Step 2:

[0316] The user operates the terminal to input requests for specific information or document creation. The terminal provides a user interface, allowing the user to easily select the necessary information.

[0317] Step 3:

[0318] The terminal sends a request from the user to the server. Based on that request, the server searches the database and extracts the relevant information.

[0319] Step 4:

[0320] The emotion engine analyzes user input and interactions in real time to recognize user emotions. It analyzes emotions from voice and text data and generates necessary feedback.

[0321] Step 5:

[0322] The server adjusts search results based on the results of the emotion engine's analysis. For example, if the user's emotions are anxious, the server may soften the presentation of search results and add support messages.

[0323] Step 6:

[0324] The device displays adjusted information to the user. The information is presented in a visually clear and emotionally resonant way, making it easy to understand.

[0325] Step 7:

[0326] When a user requests the automatic generation of materials, the server uses a generative model to automatically create materials with the specified content. The generated materials are then adjusted by an emotion engine to match the user's motivation.

[0327] Step 8:

[0328] The materials are provided to users via their devices, allowing them to review the content and utilize it in their work. The language and expressions used in the materials are appropriate to the user's emotional state.

[0329] Step 9:

[0330] The server aggregates work progress and results, and also incorporates emotional trends obtained from the emotion engine into its analysis. Based on this information, it creates a report and distributes it to users and team members.

[0331] Step 10:

[0332] Users can view reports on their devices to understand the team's status and their own work progress. Receiving emotionally sensitive feedback provides guidance for deciding on their next course of action.

[0333] (Example 2)

[0334] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0335] In improving business efficiency, optimizing business processes and providing information while taking into account the emotional state of individual users is a challenge. Conventional systems do not automatically generate feedback or materials that reflect users' emotions, which can lead to decreased business efficiency and productivity.

[0336] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0337] In this invention, the server includes an information integration means, an emotion-adaptive information provision means, and an emotion-adaptive material automatic generation means. This enables optimized information provision and material automatic generation, as well as the sharing of emotion-based feedback, while taking into account the user's emotional state.

[0338] "Information integration means" refers to methods or devices that integrate and centrally manage data collected from internal information management means.

[0339] An "emotionally adaptive information provision method" is a method or device that analyzes the emotional state of a user and provides optimized information based on that analysis.

[0340] An "emotion-adapted data automatic generation method" is a method or device that automatically generates data in a format that takes into account the user's emotional state, based on data integrated using a generation model.

[0341] A "means for sharing results that share emotional trends" refers to a method or device for aggregating the activity progress and deliverables of multiple users and sharing that information along with trends in emotions.

[0342] A "generative model" is an algorithm or program used to generate a specific format or information from data.

[0343] "External information sources" refer to databases, systems, and services that exist both inside and outside a company or organization, and are used as references when creating documents or acquiring information.

[0344] The business efficiency system of the present invention achieves efficient business processes through the collaborative functioning of servers, terminals, and users. Specifically, the server collects and integrates data using various software platforms as a means of information management. This includes, in particular, customer relationship management systems and business management systems.

[0345] The server uses an emotion analysis engine and leverages natural language processing technology to analyze the user's emotional state in real time. This emotion analysis utilizes audio data and input text data. For example, speech recognition engines and text analysis engines can be incorporated as specific software tools.

[0346] Emotionally adaptive information delivery is achieved by providing information at the optimal timing according to the user's emotional state. The server automatically generates materials from data using a generative AI model. The generative AI model includes, for example, advanced predictive analytics algorithms, which enable the materials to be delivered in an emotionally adaptive manner.

[0347] The terminal displays data and materials provided by the server. The terminal includes customization options to help users receive information more easily.

[0348] Users streamline their work based on information provided through their devices. For example, materials generated by a generative AI model may contain information useful for solving problems within a project. A concrete example is inputting a prompt into the generative AI model such as, "Generate feedback materials for a sales team whose motivation is low. Highlight success stories and include positive messages."

[0349] As described above, the present invention aims to improve operational efficiency and productivity through optimized information provision, automated material generation, and feedback sharing, while taking emotions into consideration.

[0350] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0351] Step 1:

[0352] The server collects data from the information management system. Using internal APIs and scheduled data acquisition, the server collects customer data and project progress information and stores it in a database. The input in this process is raw data from the customer information system, and the output is a dataset in an integrated format.

[0353] Step 2:

[0354] Users enter work-related requests through a terminal. For example, they might request a progress report for a specific project. The input is the user's request information, and based on this information, the server searches for the corresponding data and extracts the appropriate information. The output is the filtered data according to the request.

[0355] Step 3:

[0356] The server analyzes the user's emotions in real time using an emotion analysis engine. The server receives text and voice data input by the user and identifies the emotional state through natural language processing. The input is voice or text data, and the output is an analysis result indicating the user's emotional state.

[0357] Step 4:

[0358] The server inputs prompt text into a generation AI model, which then automatically generates materials appropriate to the user's emotional state. For example, it might input the prompt text, "Please create follow-up materials for when project progress is unsatisfactory." The input consists of the prompt text and various datasets, and the output is materials adapted to the user's emotions.

[0359] Step 5:

[0360] The terminal displays materials provided by the server and notifies the user. The terminal displays material files, important alerts, and notifications on the user's screen, making them easily accessible. Input consists of materials sent from the server, and the user receives the resulting materials and notifications.

[0361] Step 6:

[0362] Users adjust business processes based on information provided on their terminals and plan new tasks as needed. Once users review the materials, they use them to revise project activities and develop new plans. Input is the information displayed on the terminal, and output is the specific business plan and its execution.

[0363] (Application Example 2)

[0364] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0365] Traditional business efficiency systems focus primarily on information integration and provision, automated document generation, and sharing of work deliverables, but they lack optimization that takes user emotions into account. This makes it difficult to effectively optimize business processes in accordance with user emotions and to create documents tailored to those emotions. Furthermore, providing appropriate feedback that reflects user emotions is challenging, hindering the development of a positive team atmosphere and improving user satisfaction.

[0366] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0367] In this invention, the server includes data integration means, information provision means, automatic material generation means, and emotion recognition means. This enables the analysis of user emotions, optimization of business processes based on these analyses, provision of materials tailored to emotions, and feedback that takes emotions into consideration.

[0368] A "data integration system" is a mechanism for collecting data from various sources and centrally combining that data.

[0369] An "information provision method" is a system that searches for necessary information based on requests from users and provides it in an appropriate format.

[0370] A "document generation system" is a mechanism that uses a generation model to automatically create documents in a specified format from integrated data and provides them to users.

[0371] A "method for sharing results" is a system for aggregating the work progress and deliverables of multiple users and sharing them within a team.

[0372] An "emotion recognition tool" is a system that analyzes the user's emotions and reflects them in optimizing processes and improving the content of materials.

[0373] The system of this invention uses a smart device, an emotion analysis engine, and a cloud server to provide information and optimize processes based on the user's emotions.

[0374] The server receives data transmitted from smart devices and uses an emotion analysis engine to analyze the user's emotions from voice and facial expressions. Based on the acquired emotion data, it becomes possible to optimize business processes and customize materials. The server processes the data with high accuracy using emotion analysis software such as Microsoft Azure Emotion API.

[0375] The device has the ability to display information on devices such as smart glasses and tablets, providing real-time information tailored to the user's emotions. For example, if the user is feeling stressed, it can display information related to relaxation. This device includes smart wear such as Google Glass.

[0376] Users can obtain information in real time through their devices, thereby improving work efficiency. For example, in customer service, emotion recognition can enable them to provide the most appropriate response.

[0377] By utilizing a generative AI model, automatically generated materials and information are customized to suit individual emotions. Therefore, the materials include positive messages and supportive content, leading to increased user motivation.

[0378] For example, if a customer shows discomfort due to background noise, the system can display a message on the screen using music or sound effects to encourage relaxation. An example of a prompt message in this case would be: "This system uses an emotion analysis engine to provide optimal information and adjust the process based on the user's emotions. Please display relaxation information based on voice and facial expression data."

[0379] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0380] Step 1:

[0381] The server receives audio and video data collected from smart devices. Here, data acquired via camera and microphone serves as input. This data is transferred to a cloud server and formatted into a format that can be analyzed using emotion analysis software.

[0382] Step 2:

[0383] The server inputs formatted data into an emotion analysis engine to calculate the user's emotional state. Specifically, it analyzes voice pitch and evaluates changes in facial expressions. As a result of the analysis, the user's emotional information (e.g., joy, surprise, anger) is output. Based on this information, prompt sentences are generated for the generative AI model.

[0384] Step 3:

[0385] The terminal receives emotion data and prompt messages sent from the server. Based on this information, it displays information and messages appropriate to the user. Here, the displayed content is dynamically determined according to the input emotion data. Specifically, if the user indicates stress, messages and music related to relaxation will be displayed.

[0386] Step 4:

[0387] Users review the information provided by their devices and adjust their actions as needed. For example, they might take action based on the information provided to shift their emotional state in a positive direction. Finally, user feedback is re-entered into the system and used to improve subsequent analysis and information provision. This cycle continuously optimizes the process.

[0388] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0389] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0390] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0391] [Third Embodiment]

[0392] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0393] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0394] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0395] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0396] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0397] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0398] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0399] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0400] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0401] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0402] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0403] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0404] The system according to the present invention is built with the aim of improving operational efficiency within a company and collects, integrates, and analyzes data in conjunction with various information management tools. The system achieves effective data processing and information provision through the organic cooperation of the server, terminal, and user.

[0405] The server retrieves and integrates data from email systems, messaging applications, and business workspaces installed within the company via APIs. The server stores the integrated data in a central database, eliminating data redundancy and performing data cleansing to ensure that the information is always accurate.

[0406] Users can access the system via a terminal and request information necessary for their work. The terminal requests information from the server in response to the user's request. The server quickly searches the database based on the requested information and sends the relevant information to the terminal. The terminal displays this information visually and formats it in a way that is easily understandable to the user.

[0407] Furthermore, the server utilizes a generative model to automatically generate materials based on user instructions. For example, it automatically creates and provides users with reports summarizing the latest sales data and market trends to prepare for sales meetings. Users can then use these generated reports to efficiently conduct meetings.

[0408] The server also aggregates work progress and deliverables, and generates reports to share results regularly. For example, it creates a weekly report summarizing the work status of the entire project team and distributes it to team members, ensuring everyone is aware of the latest situation and supporting accurate decision-making. Based on the provided reports, users can quickly decide on the next actions and efficiently advance the project.

[0409] As described above, the system of the present invention enables centralized data management and efficient information provision, thereby supporting improved employee productivity and increased efficiency in business activities.

[0410] The following describes the processing flow.

[0411] Step 1:

[0412] The server collects data from the internal email system, messaging apps, and workspace tools via APIs. The collected data is temporarily cached and updated periodically.

[0413] Step 2:

[0414] The server integrates cached data into a central database and performs cleansing to eliminate data redundancy and inconsistencies. This database functions as a single, unified data source for all users.

[0415] Step 3:

[0416] The user uses a terminal to request specific information. The terminal transmits the requested information to the server through the user interface. Here, the user can specify the type of information needed and the search criteria.

[0417] Step 4:

[0418] The server searches the database and extracts data that matches the requested criteria. If results are found, the server formats the information and prepares it to be sent to the terminal.

[0419] Step 5:

[0420] The terminal displays information received from the server to the user. The information is provided in a visual format that is easy for the user to understand intuitively. The user can then proceed with their work based on this information.

[0421] Step 6:

[0422] When a user requests document creation, the server uses a generative model to automatically generate the document based on the requested format and content. For example, it can create meeting reports or market analysis documents.

[0423] Step 7:

[0424] The server automatically generates documents and sends them to the terminal, where the user can view the content on the screen. Users can then download the generated documents or share them within the company.

[0425] Step 8:

[0426] The server aggregates the work progress of multiple users and visualizes the results. It automatically generates reports from this data as needed and distributes them to the entire team periodically.

[0427] Step 9:

[0428] Through these progress reports, users can understand the activities of other members and the overall picture of the project, and make decisions about the next steps.

[0429] (Example 1)

[0430] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0431] Information management has become complex, and inconsistencies and redundancies in data from different sources make it difficult to use accurate information. Furthermore, there is a lack of means to integrate information and generate appropriate documents in order to improve operational efficiency. Additionally, there is a need for a system to effectively share work progress with team members.

[0432] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0433] In this invention, the server includes an information integration means that collects information from an information processing device, integrates the information, eliminates duplication and corrects inconsistencies; an information response means that searches a database in response to information requests from various terminals and provides information that matches the request; and a document generation means that uses generation AI technology to automatically create a formatted document based on the integrated information and provides the document. This enables centralized information management, rapid document generation, and effective progress sharing.

[0434] An "information integration means" is a mechanism for integrating various types of information collected from information processing devices, correcting duplication and inconsistencies, and managing accurate data.

[0435] An "information response means" is a mechanism that searches a database based on information requests from various terminals and provides the requested information quickly.

[0436] A "document generation means" is a mechanism that uses generation AI technology to automatically create formatted documents based on integrated information and provide those documents.

[0437] A "means of sharing results" is a mechanism for aggregating the work progress and results of multiple users, and for distributing and sharing reports that are generated periodically.

[0438] "Generative AI technology" is a technology that utilizes artificial intelligence to analyze data and automatically generate documents and information based on specific formats and content.

[0439] This invention is a system designed to support effective information management and operational efficiency within a company. Specific embodiments are described below.

[0440] The server is responsible for data collection, acquiring data from various information processing devices. To this end, it employs techniques to collect data using APIs from software such as email systems, messaging platforms, and shared workspaces. The server integrates this data, eliminating duplicates and correcting inconsistencies to build an accurate and consistent information database.

[0441] Users access the server using their terminals and request information necessary for their work. An example of a prompt message a user might send from their terminal is, "Please create a sales report based on the latest sales data." The terminal sends this prompt to the server, and the request is processed.

[0442] As a means of responding to information requests from terminals, the server searches the database, extracts the requested information, and provides it to the terminal. The terminal then displays this information to the user in a visually easy-to-understand format, such as a graph or table, thereby enhancing the immediacy and convenience of the information.

[0443] Furthermore, the server utilizes a generative AI model to function as a document generation tool. Based on collected and processed information, the AI ​​automatically generates documents in a specified format. A concrete example is a report for sales meetings summarizing sales and market trends. The generated documents are sent to the user and used as a tool to enable efficient work execution.

[0444] Inventions implemented in this manner significantly improve the efficiency of information management and support increased productivity and faster decision-making across the entire company.

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

[0446] Step 1:

[0447] The server collects data from information processing devices. This input includes email data from email systems, message logs from chat applications, and task information from work workspaces. The server collects this data using APIs and integrates it into a central database. During this process, the server performs data cleansing to eliminate duplication and correct inconsistencies. This results in an accurate and consistent information database as output.

[0448] Step 2:

[0449] The user requests information necessary for their work through their terminal. As input, the user enters a natural language prompt into the terminal, such as "I want to know the progress of the current project." The terminal parses this prompt and requests information from the server. After the request is sent, the server queries the database based on the prompt to find the relevant information. The requested information is then sent back to the user's terminal as output.

[0450] Step 3:

[0451] The terminal formats the information received from the server in a user-friendly format. The input data is displayed visually, for example, as a table or graph. This allows the user to intuitively understand the information. The terminal's operation involves processing the information using a data visualization engine and providing an organized display as output.

[0452] Step 4:

[0453] The server uses a generative AI model to automatically generate documents. When a user enters a prompt requesting specific documents, the server analyzes the prompt and issues instructions to the generative AI model. The generative AI model analyzes the input data (e.g., sales data or market trends) and generates a report in the specified format. As output, the completed report is sent to the user's terminal.

[0454] Step 5:

[0455] The server periodically compiles work progress and results, creates reports, and shares them with team members. Inputs include progress data and completed work data from each team member. The server aggregates and analyzes this data to generate reports. As output, regularly updated reports are delivered to the terminals of relevant parties. This allows everyone to stay informed of the latest situation and make informed decisions.

[0456] (Application Example 1)

[0457] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0458] In today's manufacturing environment, efficient data integration and information delivery are required to cope with data diversity and rapid change. Furthermore, achieving efficiency in manufacturing processes and real-time work optimization presents a significant challenge. Additionally, there is the challenge of providing users with the information they need quickly and accurately, and making it easier to understand overall work progress.

[0459] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0460] In this invention, the server includes data integration means for collecting and integrating data from various internal information management devices, information provision means for searching the data in response to information requests from users and providing information suitable for those requests, automatic document generation means for automatically generating documents in a specified format based on the integrated data using a generation model and providing those documents, and optimization command means for providing real-time work instructions to production equipment and optimizing work processes. This enables efficient data management, optimization of manufacturing processes, and rapid information provision.

[0461] "Information management equipment" is a general term for devices and software used to collect, store, and manage data.

[0462] "Data integration means" refers to a function for combining and integrating data obtained from different sources within a single system.

[0463] An "information provision method" is a system that searches for and presents appropriate information from the data it holds based on the user's request.

[0464] A "generative model" is an algorithm or AI system that automatically generates documents in a specified format based on data.

[0465] "Automatic document generation means" refers to a function that uses a generation model to automatically create documents in a predetermined format from integrated data.

[0466] The "optimization command means" is a function that issues work instructions to production equipment in real time to streamline the production process.

[0467] "Work progress" refers to the process from the start to the completion of a task, and means managing its progress.

[0468] "Deliverables" refer to the goods or results obtained as a result of a specific task or project.

[0469] "Production equipment" refers to machinery, robots, and other devices used in the manufacturing process.

[0470] This invention is a system aimed at improving the efficiency of production processes and managing information. It collects data from internal information management devices and utilizes it to achieve optimal operation of production equipment.

[0471] The server collects data from information management devices within the company via APIs. The collected data is diverse, including production schedules, inventory information, and robot status. This data is integrated and cleansed by the server to maintain an accurate and non-redundant dataset.

[0472] The server enables efficient information retrieval and delivery in response to user requests. When a user requests specific information, the server has the ability to quickly search the database and provide the relevant information in real time. The terminal's display is used for visual data display. This allows users to quickly access the information they need and supports intelligent decision-making.

[0473] Furthermore, the server uses a generative AI model to automatically generate documents in a specified format from integrated data. To achieve this, it utilizes AI libraries such as TensorFlow to enhance the data analysis and document generation processes. For example, by automatically generating graphs for monthly reports based on the latest production line operation data and providing them to senior managers, it becomes possible to quickly visualize production policies.

[0474] For example, if a manufacturing line is facing a shortage of human resources, the server analyzes operational data in real time and sends appropriate work instructions to the production equipment using an optimization command mechanism. This maximizes production efficiency.

[0475] An example of a prompt to input into the generating AI model is, "Based on the current inventory information and production schedule, please generate the optimal manufacturing process schedule."

[0476] The implementation of this system will lead to more efficient data management in manufacturing operations, faster information delivery, and optimization of production processes.

[0477] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0478] Step 1:

[0479] The server collects data from the company's information management devices via APIs. Specifically, the server periodically retrieves data such as production schedules, inventory information, and robot operating status. At this stage, the input is raw data from the APIs, and the output is an unintegrated dataset.

[0480] Step 2:

[0481] The server integrates and cleanses the collected data. Here, the Pandas library is used to integrate the data and eliminate unnecessary redundancy. This results in a clean and accurate dataset. The input to this step is the raw dataset collected in step 1, and the output is the integrated and cleansed data.

[0482] Step 3:

[0483] When a user requests the necessary information via their terminal, the server searches the database. The input is the user's information request, and a search query is generated to quickly extract the most relevant data based on the prompt. The output is the information relevant to the request, which is then sent to the terminal.

[0484] Step 4:

[0485] The server automatically generates documents using a generative AI model. Specifically, it uses TensorFlow to generate monthly reports and production plan reports from integrated data. The input is the integrated data obtained in step 2, and the output is a formatted document.

[0486] Step 5:

[0487] On the terminal, the generated materials are visually displayed and formatted in a way that is easily understandable to the user. The input is the generated materials, and the output on the terminal is the screen display for the user to use in decision-making.

[0488] Step 6:

[0489] The server transmits work instructions to production equipment using an optimized command mechanism. This includes real-time data analysis results. The input consists of generated prompt statements and production data, while the output consists of specific work instructions for each production device.

[0490] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0491] The business efficiency system according to the present invention incorporates an emotion engine, enabling responses and business process optimization that take into account the emotional state of employees. The server, terminal, and user elements collaborate to realize an innovative business environment that includes emotional data.

[0492] The server collects and integrates data from internal information management tools and provides necessary information to the terminal in response to specific information requests from users. It also automatically generates materials using generative models based on the integrated data to meet user requests. Furthermore, an emotion engine is incorporated, enabling the recognition of user emotions.

[0493] The emotion engine reads the user's emotions through voice and text analysis and provides real-time feedback. This feedback allows the server to adjust the timing and method of information delivery to suit the user and display information optimized for the device. For example, if the user is feeling stressed, the server re-evaluates task priorities and sends information to the device to encourage relaxation and appropriate alerts.

[0494] Furthermore, the emotion engine also influences automated document generation methods. It selects recommended words and designs based on the user's emotions, optimizing the document content to match their emotional state. For example, if motivation is low, the document can include supportive messages or be rearranged to emphasize positive outcomes.

[0495] Furthermore, when aggregating work progress from multiple users, the system analyzes sentiment trends to understand the team's atmosphere. The server uses this information to include feedback in periodic reports that boost team morale. For example, it adds praise based on project successes and achievements to encourage the sharing of results.

[0496] Through the above configuration, a system is created that improves operational efficiency by taking emotions into account, contributing to increased employee productivity and strengthening the overall competitiveness of the company.

[0497] The following describes the processing flow.

[0498] Step 1:

[0499] The server collects data from internal information management tools and retrieves it using APIs. The retrieved data is stored in a central database for centralized management.

[0500] Step 2:

[0501] The user operates the terminal to input requests for specific information or document creation. The terminal provides a user interface, allowing the user to easily select the necessary information.

[0502] Step 3:

[0503] The terminal sends a request from the user to the server. Based on that request, the server searches the database and extracts the relevant information.

[0504] Step 4:

[0505] The emotion engine analyzes user input and interactions in real time to recognize user emotions. It analyzes emotions from voice and text data and generates necessary feedback.

[0506] Step 5:

[0507] The server adjusts search results based on the results of the emotion engine's analysis. For example, if the user's emotions are anxious, the server may soften the presentation of search results and add support messages.

[0508] Step 6:

[0509] The device displays adjusted information to the user. The information is presented in a visually clear and emotionally resonant way, making it easy to understand.

[0510] Step 7:

[0511] When a user requests the automatic generation of materials, the server uses a generative model to automatically create materials with the specified content. The generated materials are then adjusted by an emotion engine to match the user's motivation.

[0512] Step 8:

[0513] The materials are provided to users via their devices, allowing them to review the content and utilize it in their work. The language and expressions used in the materials are appropriate to the user's emotional state.

[0514] Step 9:

[0515] The server aggregates work progress and results, and also incorporates emotional trends obtained from the emotion engine into its analysis. Based on this information, it creates a report and distributes it to users and team members.

[0516] Step 10:

[0517] Users can view reports on their devices to understand the team's status and their own work progress. Receiving emotionally sensitive feedback provides guidance for deciding on their next course of action.

[0518] (Example 2)

[0519] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0520] In improving business efficiency, optimizing business processes and providing information while taking into account the emotional state of individual users is a challenge. Conventional systems do not automatically generate feedback or materials that reflect users' emotions, which can lead to decreased business efficiency and productivity.

[0521] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0522] In this invention, the server includes an information integration means, an emotion-adaptive information provision means, and an emotion-adaptive material automatic generation means. This enables optimized information provision and material automatic generation, as well as the sharing of emotion-based feedback, while taking into account the user's emotional state.

[0523] "Information integration means" refers to methods or devices that integrate and centrally manage data collected from internal information management means.

[0524] An "emotionally adaptive information provision method" is a method or device that analyzes the emotional state of a user and provides optimized information based on that analysis.

[0525] An "emotion-adapted data automatic generation method" is a method or device that automatically generates data in a format that takes into account the user's emotional state, based on data integrated using a generation model.

[0526] A "means for sharing results that share emotional trends" refers to a method or device for aggregating the activity progress and deliverables of multiple users and sharing that information along with trends in emotions.

[0527] A "generative model" is an algorithm or program used to generate a specific format or information from data.

[0528] "External information sources" refer to databases, systems, and services that exist both inside and outside a company or organization, and are used as references when creating documents or acquiring information.

[0529] The business efficiency system of the present invention achieves efficient business processes through the collaborative functioning of servers, terminals, and users. Specifically, the server collects and integrates data using various software platforms as a means of information management. This includes, in particular, customer relationship management systems and business management systems.

[0530] The server uses an emotion analysis engine and leverages natural language processing technology to analyze the user's emotional state in real time. This emotion analysis utilizes audio data and input text data. For example, speech recognition engines and text analysis engines can be incorporated as specific software tools.

[0531] Emotionally adaptive information delivery is achieved by providing information at the optimal timing according to the user's emotional state. The server automatically generates materials from data using a generative AI model. The generative AI model includes, for example, advanced predictive analytics algorithms, which enable the materials to be delivered in an emotionally adaptive manner.

[0532] The terminal displays data and materials provided by the server. The terminal includes customization options to help users receive information more easily.

[0533] Users streamline their work based on information provided through their devices. For example, materials generated by a generative AI model may contain information useful for solving problems within a project. A concrete example is inputting a prompt into the generative AI model such as, "Generate feedback materials for a sales team whose motivation is low. Highlight success stories and include positive messages."

[0534] As described above, the present invention aims to improve operational efficiency and productivity through optimized information provision, automated material generation, and feedback sharing, while taking emotions into consideration.

[0535] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0536] Step 1:

[0537] The server collects data from the information management system. Using internal APIs and scheduled data acquisition, the server collects customer data and project progress information and stores it in a database. The input in this process is raw data from the customer information system, and the output is a dataset in an integrated format.

[0538] Step 2:

[0539] Users enter business-related requests through a terminal. For example, they might request a progress report for a specific project. The input is the user's request information, and based on this information, the server searches for the corresponding data and extracts the appropriate information. The output is the filtered data according to the request.

[0540] Step 3:

[0541] The server analyzes the user's emotions in real time using an emotion analysis engine. The server receives text and voice data input by the user and identifies the emotional state through natural language processing. The input is voice or text data, and the output is an analysis result indicating the user's emotional state.

[0542] Step 4:

[0543] The server inputs prompt text into a generation AI model, which then automatically generates materials appropriate to the user's emotional state. For example, it might input the prompt text, "Please create follow-up materials for when project progress is unsatisfactory." The input consists of the prompt text and various datasets, and the output is materials adapted to the user's emotions.

[0544] Step 5:

[0545] The terminal displays materials provided by the server and notifies the user. The terminal displays material files, important alerts, and notifications on the user's screen, making them easily accessible. Input consists of materials sent from the server, and the user receives the resulting materials and notifications.

[0546] Step 6:

[0547] Users adjust business processes based on information provided on their terminals and plan new tasks as needed. Once users review the materials, they use them to revise project activities and develop new plans. Input is the information displayed on the terminal, and output is the specific business plan and its execution.

[0548] (Application Example 2)

[0549] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0550] Traditional business efficiency systems focus primarily on information integration and provision, automated document generation, and sharing of work deliverables, but they lack optimization that takes user emotions into account. This makes it difficult to effectively optimize business processes in accordance with user emotions and to create documents tailored to those emotions. Furthermore, providing appropriate feedback that reflects user emotions is challenging, hindering the development of a positive team atmosphere and improving user satisfaction.

[0551] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0552] In this invention, the server includes data integration means, information provision means, automatic material generation means, and emotion recognition means. This enables the analysis of user emotions, optimization of business processes based on these analyses, provision of materials tailored to emotions, and feedback that takes emotions into consideration.

[0553] A "data integration system" is a mechanism for collecting data from various sources and centrally combining that data.

[0554] An "information provision method" is a system that searches for necessary information based on requests from users and provides it in an appropriate format.

[0555] A "document generation system" is a mechanism that uses a generation model to automatically create documents in a specified format from integrated data and provides them to users.

[0556] A "method for sharing results" is a system for aggregating the work progress and deliverables of multiple users and sharing them within a team.

[0557] An "emotion recognition tool" is a system that analyzes the user's emotions and reflects them in optimizing processes and improving the content of materials.

[0558] The system of this invention uses a smart device, an emotion analysis engine, and a cloud server to provide information and optimize processes based on the user's emotions.

[0559] The server receives data transmitted from smart devices and uses an emotion analysis engine to analyze the user's emotions from voice and facial expressions. Based on the acquired emotion data, it becomes possible to optimize business processes and customize materials. The server processes the data with high accuracy using emotion analysis software such as Microsoft Azure Emotion API.

[0560] The device has the ability to display information on devices such as smart glasses and tablets, providing real-time information tailored to the user's emotions. For example, if the user is feeling stressed, it can display information related to relaxation. This device includes smart wear such as Google Glass.

[0561] Users can obtain information in real time through their devices, thereby improving work efficiency. For example, in customer service, emotion recognition can enable them to provide the most appropriate response.

[0562] By utilizing a generative AI model, automatically generated materials and information are customized to suit individual emotions. Therefore, the materials include positive messages and supportive content, leading to increased user motivation.

[0563] For example, if a customer shows discomfort due to background noise, the system can display a message on the screen using music or sound effects to encourage relaxation. An example of a prompt message in this case would be: "This system uses an emotion analysis engine to provide optimal information and adjust the process based on the user's emotions. Please display relaxation information based on voice and facial expression data."

[0564] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0565] Step 1:

[0566] The server receives audio and video data collected from smart devices. Here, data acquired via camera and microphone serves as input. This data is transferred to a cloud server and formatted into a format that can be analyzed using emotion analysis software.

[0567] Step 2:

[0568] The server inputs formatted data into an emotion analysis engine to calculate the user's emotional state. Specifically, it analyzes voice pitch and evaluates changes in facial expressions. As a result of the analysis, the user's emotional information (e.g., joy, surprise, anger) is output. Based on this information, prompt sentences are generated for the generative AI model.

[0569] Step 3:

[0570] The terminal receives emotion data and prompt messages sent from the server. Based on this information, it displays information and messages appropriate to the user. Here, the displayed content is dynamically determined according to the input emotion data. Specifically, if the user indicates stress, messages and music related to relaxation will be displayed.

[0571] Step 4:

[0572] Users review the information provided by their devices and adjust their actions as needed. For example, they might take action based on the information provided to shift their emotional state in a positive direction. Finally, user feedback is re-entered into the system and used to improve subsequent analysis and information provision. This cycle continuously optimizes the process.

[0573] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0574] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0575] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0576] [Fourth Embodiment]

[0577] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0578] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0579] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0580] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0581] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0582] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0583] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0584] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0585] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0586] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0587] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0588] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0589] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0590] The system according to the present invention is built with the aim of improving operational efficiency within a company and collects, integrates, and analyzes data in conjunction with various information management tools. The system achieves effective data processing and information provision through the organic cooperation of the server, terminal, and user.

[0591] The server retrieves and integrates data from email systems, messaging applications, and business workspaces installed within the company via APIs. The server stores the integrated data in a central database, eliminating data redundancy and performing data cleansing to ensure that the information is always accurate.

[0592] Users can access the system via a terminal and request information necessary for their work. The terminal requests information from the server in response to the user's request. The server quickly searches the database based on the requested information and sends the relevant information to the terminal. The terminal displays this information visually and formats it in a way that is easily understandable to the user.

[0593] Furthermore, the server utilizes a generative model to automatically generate materials based on user instructions. For example, it automatically creates and provides users with reports summarizing the latest sales data and market trends to prepare for sales meetings. Users can then use these generated reports to efficiently conduct meetings.

[0594] The server also aggregates work progress and deliverables, and generates reports to share results regularly. For example, it creates a weekly report summarizing the work status of the entire project team and distributes it to team members, ensuring everyone is aware of the latest situation and supporting accurate decision-making. Based on the provided reports, users can quickly decide on the next actions and efficiently advance the project.

[0595] As described above, the system of the present invention enables centralized data management and efficient information provision, thereby supporting improved employee productivity and increased efficiency in business activities.

[0596] The following describes the processing flow.

[0597] Step 1:

[0598] The server collects data from the internal email system, messaging apps, and workspace tools via APIs. The collected data is temporarily cached and updated periodically.

[0599] Step 2:

[0600] The server integrates cached data into a central database and performs cleansing to eliminate data redundancy and inconsistencies. This database functions as a single, unified data source for all users.

[0601] Step 3:

[0602] The user uses a terminal to request specific information. The terminal transmits the requested information to the server through the user interface. Here, the user can specify the type of information needed and the search criteria.

[0603] Step 4:

[0604] The server searches the database and extracts data that matches the requested criteria. If results are found, the server formats the information and prepares it to be sent to the terminal.

[0605] Step 5:

[0606] The terminal displays information received from the server to the user. The information is provided in a visual format that is easy for the user to understand intuitively. The user can then proceed with their work based on this information.

[0607] Step 6:

[0608] When a user requests document creation, the server uses a generative model to automatically generate the document based on the requested format and content. For example, it can create meeting reports or market analysis documents.

[0609] Step 7:

[0610] The server automatically generates documents and sends them to the terminal, where the user can view the content on the screen. Users can then download the generated documents or share them within the company.

[0611] Step 8:

[0612] The server aggregates the work progress of multiple users and visualizes the results. It automatically generates reports from this data as needed and distributes them to the entire team periodically.

[0613] Step 9:

[0614] Through these progress reports, users can understand the activities of other members and the overall picture of the project, and make decisions about the next steps.

[0615] (Example 1)

[0616] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0617] Information management has become complex, and inconsistencies and redundancies in data from different sources make it difficult to use accurate information. Furthermore, there is a lack of means to integrate information and generate appropriate documents in order to improve operational efficiency. Additionally, there is a need for a system to effectively share work progress with team members.

[0618] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0619] In this invention, the server includes an information integration means that collects information from an information processing device, integrates the information, eliminates duplication and corrects inconsistencies; an information response means that searches a database in response to information requests from various terminals and provides information that matches the request; and a document generation means that uses generation AI technology to automatically create a formatted document based on the integrated information and provides the document. This enables centralized information management, rapid document generation, and effective progress sharing.

[0620] An "information integration means" is a mechanism for integrating various types of information collected from information processing devices, correcting duplication and inconsistencies, and managing accurate data.

[0621] An "information response means" is a mechanism that searches a database based on information requests from various terminals and provides the requested information quickly.

[0622] A "document generation means" is a mechanism that uses generation AI technology to automatically create formatted documents based on integrated information and provide those documents.

[0623] A "means of sharing results" is a mechanism for aggregating the work progress and results of multiple users, and for distributing and sharing reports that are generated periodically.

[0624] "Generative AI technology" is a technology that utilizes artificial intelligence to analyze data and automatically generate documents and information based on specific formats and content.

[0625] This invention is a system designed to support effective information management and operational efficiency within a company. Specific embodiments are described below.

[0626] The server is responsible for data collection, acquiring data from various information processing devices. To this end, it employs techniques to collect data using APIs from software such as email systems, messaging platforms, and shared workspaces. The server integrates this data, eliminating duplicates and correcting inconsistencies to build an accurate and consistent information database.

[0627] Users access the server using their terminals and request information necessary for their work. An example of a prompt message a user might send from their terminal is, "Please create a sales report based on the latest sales data." The terminal sends this prompt to the server, and the request is processed.

[0628] As a means of responding to information requests from terminals, the server searches the database, extracts the requested information, and provides it to the terminal. The terminal then displays this information to the user in a visually easy-to-understand format, such as a graph or table, thereby enhancing the immediacy and convenience of the information.

[0629] Furthermore, the server utilizes a generative AI model to function as a document generation tool. Based on collected and processed information, the AI ​​automatically generates documents in a specified format. A concrete example is a report for sales meetings summarizing sales and market trends. The generated documents are sent to the user and used as a tool to enable efficient work execution.

[0630] Inventions implemented in this manner significantly improve the efficiency of information management and support increased productivity and faster decision-making across the entire company.

[0631] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0632] Step 1:

[0633] The server collects data from information processing devices. This input includes email data from email systems, message logs from chat applications, and task information from work workspaces. The server collects this data using APIs and integrates it into a central database. During this process, the server performs data cleansing to eliminate duplication and correct inconsistencies. This results in an accurate and consistent information database as output.

[0634] Step 2:

[0635] The user requests information necessary for their work through their terminal. As input, the user enters a natural language prompt into the terminal, such as "I want to know the progress of the current project." The terminal parses this prompt and requests information from the server. After the request is sent, the server queries the database based on the prompt to find the relevant information. The requested information is then sent back to the user's terminal as output.

[0636] Step 3:

[0637] The terminal formats the information received from the server in a user-friendly format. The input data is displayed visually, for example, as a table or graph. This allows the user to intuitively understand the information. The terminal's operation involves processing the information using a data visualization engine and providing an organized display as output.

[0638] Step 4:

[0639] The server uses a generative AI model to automatically generate documents. When a user enters a prompt requesting specific documents, the server analyzes the prompt and issues instructions to the generative AI model. The generative AI model analyzes the input data (e.g., sales data or market trends) and generates a report in the specified format. As output, the completed report is sent to the user's terminal.

[0640] Step 5:

[0641] The server periodically compiles work progress and results, creates reports, and shares them with team members. Inputs include progress data and completed work data from each team member. The server aggregates and analyzes this data to generate reports. As output, regularly updated reports are delivered to the terminals of relevant parties. This allows everyone to stay informed of the latest situation and make informed decisions.

[0642] (Application Example 1)

[0643] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0644] In today's manufacturing environment, efficient data integration and information delivery are required to cope with data diversity and rapid change. Furthermore, achieving efficiency in manufacturing processes and real-time work optimization presents a significant challenge. Additionally, there is the challenge of providing users with the information they need quickly and accurately, and making it easier to understand overall work progress.

[0645] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0646] In this invention, the server includes data integration means for collecting and integrating data from various internal information management devices, information provision means for searching the data in response to information requests from users and providing information suitable for those requests, automatic document generation means for automatically generating documents in a specified format based on the integrated data using a generation model and providing those documents, and optimization command means for providing real-time work instructions to production equipment and optimizing work processes. This enables efficient data management, optimization of manufacturing processes, and rapid information provision.

[0647] "Information management equipment" is a general term for devices and software used to collect, store, and manage data.

[0648] "Data integration means" refers to a function for combining and integrating data obtained from different sources within a single system.

[0649] An "information provision method" is a system that searches for and presents appropriate information from the data it holds based on the user's request.

[0650] A "generative model" is an algorithm or AI system that automatically generates documents in a specified format based on data.

[0651] "Automatic document generation means" refers to a function that uses a generation model to automatically create documents in a predetermined format from integrated data.

[0652] The "optimization command means" is a function that issues work instructions to production equipment in real time to streamline the production process.

[0653] "Work progress" refers to the process from the start to the completion of a task, and means managing its progress.

[0654] "Deliverables" refer to the goods or results obtained as a result of a specific task or project.

[0655] "Production equipment" refers to machinery, robots, and other devices used in the manufacturing process.

[0656] This invention is a system aimed at improving the efficiency of production processes and managing information. It collects data from internal information management devices and utilizes it to achieve optimal operation of production equipment.

[0657] The server collects data from information management devices within the company via APIs. The collected data is diverse, including production schedules, inventory information, and robot status. This data is integrated and cleansed by the server to maintain an accurate and non-redundant dataset.

[0658] The server enables efficient information retrieval and delivery in response to user requests. When a user requests specific information, the server has the ability to quickly search the database and provide the relevant information in real time. The terminal's display is used for visual data display. This allows users to quickly access the information they need and supports intelligent decision-making.

[0659] Furthermore, the server uses a generative AI model to automatically generate documents in a specified format from integrated data. To achieve this, it utilizes AI libraries such as TensorFlow to enhance the data analysis and document generation processes. For example, by automatically generating graphs for monthly reports based on the latest production line operation data and providing them to senior managers, it becomes possible to quickly visualize production policies.

[0660] For example, if a manufacturing line is facing a shortage of human resources, the server analyzes operational data in real time and sends appropriate work instructions to the production equipment using an optimization command mechanism. This maximizes production efficiency.

[0661] An example of a prompt to input into the generating AI model is, "Based on the current inventory information and production schedule, please generate the optimal manufacturing process schedule."

[0662] The implementation of this system will lead to more efficient data management in manufacturing operations, faster information delivery, and optimization of production processes.

[0663] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0664] Step 1:

[0665] The server collects data from the company's information management devices via APIs. Specifically, the server periodically retrieves data such as production schedules, inventory information, and robot operating status. At this stage, the input is raw data from the APIs, and the output is an unintegrated dataset.

[0666] Step 2:

[0667] The server integrates and cleanses the collected data. Here, the Pandas library is used to integrate the data and eliminate unnecessary redundancy. This results in a clean and accurate dataset. The input to this step is the raw dataset collected in step 1, and the output is the integrated and cleansed data.

[0668] Step 3:

[0669] When a user requests the necessary information via their terminal, the server searches the database. The input is the user's information request, and a search query is generated to quickly extract the most relevant data based on the prompt. The output is the information relevant to the request, which is then sent to the terminal.

[0670] Step 4:

[0671] The server automatically generates documents using a generative AI model. Specifically, it uses TensorFlow to generate monthly reports and production plan reports from integrated data. The input is the integrated data obtained in step 2, and the output is a formatted document.

[0672] Step 5:

[0673] On the terminal, the generated materials are visually displayed and formatted in a way that is easily understandable to the user. The input is the generated materials, and the output on the terminal is the screen display for the user to use in decision-making.

[0674] Step 6:

[0675] The server transmits work instructions to production equipment using an optimized command mechanism. This includes real-time data analysis results. The input consists of generated prompt statements and production data, while the output consists of specific work instructions for each production device.

[0676] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0677] The business efficiency system according to the present invention incorporates an emotion engine, enabling responses and business process optimization that take into account the emotional state of employees. The server, terminal, and user elements collaborate to realize an innovative business environment that includes emotional data.

[0678] The server collects and integrates data from internal information management tools and provides necessary information to the terminal in response to specific information requests from users. It also automatically generates materials using generative models based on the integrated data to meet user requests. Furthermore, an emotion engine is incorporated, enabling the recognition of user emotions.

[0679] The emotion engine reads the user's emotions through voice and text analysis and provides real-time feedback. This feedback allows the server to adjust the timing and method of information delivery to suit the user and display information optimized for the device. For example, if the user is feeling stressed, the server re-evaluates task priorities and sends information to the device to encourage relaxation and appropriate alerts.

[0680] Furthermore, the emotion engine also influences automated document generation methods. It selects recommended words and designs based on the user's emotions, optimizing the document content to match their emotional state. For example, if motivation is low, the document can include supportive messages or be rearranged to emphasize positive outcomes.

[0681] Furthermore, when aggregating work progress from multiple users, the system analyzes sentiment trends to understand the team's atmosphere. The server uses this information to include feedback in periodic reports that boost team morale. For example, it adds praise based on project successes and achievements to encourage the sharing of results.

[0682] Through the above configuration, a system is created that improves operational efficiency by taking emotions into account, contributing to increased employee productivity and strengthening the overall competitiveness of the company.

[0683] The following describes the processing flow.

[0684] Step 1:

[0685] The server collects data from internal information management tools and retrieves it using APIs. The retrieved data is stored in a central database for centralized management.

[0686] Step 2:

[0687] The user operates the terminal to input requests for specific information or document creation. The terminal provides a user interface, allowing the user to easily select the necessary information.

[0688] Step 3:

[0689] The terminal sends a request from the user to the server. Based on that request, the server searches the database and extracts the relevant information.

[0690] Step 4:

[0691] The emotion engine analyzes user input and interactions in real time to recognize user emotions. It analyzes emotions from voice and text data and generates necessary feedback.

[0692] Step 5:

[0693] The server adjusts search results based on the results of the emotion engine's analysis. For example, if the user's emotions are anxious, the server may soften the presentation of search results and add support messages.

[0694] Step 6:

[0695] The device displays adjusted information to the user. The information is presented in a visually clear and emotionally resonant way, making it easy to understand.

[0696] Step 7:

[0697] When a user requests the automatic generation of materials, the server uses a generative model to automatically create materials with the specified content. The generated materials are then adjusted by an emotion engine to match the user's motivation.

[0698] Step 8:

[0699] The materials are provided to users via their devices, allowing them to review the content and utilize it in their work. The language and expressions used in the materials are appropriate to the user's emotional state.

[0700] Step 9:

[0701] The server aggregates work progress and results, and also incorporates emotional trends obtained from the emotion engine into its analysis. Based on this information, it creates a report and distributes it to users and team members.

[0702] Step 10:

[0703] Users can view reports on their devices to understand the team's status and their own work progress. Receiving emotionally sensitive feedback provides guidance for deciding on their next course of action.

[0704] (Example 2)

[0705] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0706] In improving business efficiency, optimizing business processes and providing information while taking into account the emotional state of individual users is a challenge. Conventional systems do not automatically generate feedback or materials that reflect users' emotions, which can lead to decreased business efficiency and productivity.

[0707] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0708] In this invention, the server includes an information integration means, an emotion-adaptive information provision means, and an emotion-adaptive material automatic generation means. This enables optimized information provision and material automatic generation, as well as the sharing of emotion-based feedback, while taking into account the user's emotional state.

[0709] "Information integration means" refers to methods or devices that integrate and centrally manage data collected from internal information management means.

[0710] An "emotionally adaptive information provision method" is a method or device that analyzes the emotional state of a user and provides optimized information based on that analysis.

[0711] An "emotion-adapted data automatic generation method" is a method or device that automatically generates data in a format that takes into account the user's emotional state, based on data integrated using a generation model.

[0712] A "means for sharing results that share emotional trends" refers to a method or device for aggregating the activity progress and deliverables of multiple users and sharing that information along with trends in emotions.

[0713] A "generative model" is an algorithm or program used to generate a specific format or information from data.

[0714] "External information sources" refer to databases, systems, and services that exist both inside and outside a company or organization, and are used as references when creating documents or acquiring information.

[0715] The business efficiency system of the present invention achieves efficient business processes through the collaborative functioning of servers, terminals, and users. Specifically, the server collects and integrates data using various software platforms as a means of information management. This includes, in particular, customer relationship management systems and business management systems.

[0716] The server uses an emotion analysis engine and leverages natural language processing technology to analyze the user's emotional state in real time. This emotion analysis utilizes audio data and input text data. For example, speech recognition engines and text analysis engines can be incorporated as specific software tools.

[0717] Emotionally adaptive information delivery is achieved by providing information at the optimal timing according to the user's emotional state. The server automatically generates materials from data using a generative AI model. The generative AI model includes, for example, advanced predictive analytics algorithms, which enable the materials to be delivered in an emotionally adaptive manner.

[0718] The terminal displays data and materials provided by the server. The terminal includes customization options to help users receive information more easily.

[0719] Users streamline their work based on information provided through their devices. For example, materials generated by a generative AI model may contain information useful for solving problems within a project. A concrete example is inputting a prompt into the generative AI model such as, "Generate feedback materials for a sales team whose motivation is low. Highlight success stories and include positive messages."

[0720] As described above, the present invention aims to improve operational efficiency and productivity through optimized information provision, automated material generation, and feedback sharing, while taking emotions into consideration.

[0721] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0722] Step 1:

[0723] The server collects data from the information management system. Using internal APIs and scheduled data acquisition, the server collects customer data and project progress information and stores it in a database. The input in this process is raw data from the customer information system, and the output is a dataset in an integrated format.

[0724] Step 2:

[0725] Users enter business-related requests through a terminal. For example, they might request a progress report for a specific project. The input is the user's request information, and based on this information, the server searches for the corresponding data and extracts the appropriate information. The output is the filtered data according to the request.

[0726] Step 3:

[0727] The server analyzes the user's emotions in real time using an emotion analysis engine. The server receives text and voice data input by the user and identifies the emotional state through natural language processing. The input is voice or text data, and the output is an analysis result indicating the user's emotional state.

[0728] Step 4:

[0729] The server inputs prompt text into a generation AI model, which then automatically generates materials appropriate to the user's emotional state. For example, it might input the prompt text, "Please create follow-up materials for when project progress is unsatisfactory." The input consists of the prompt text and various datasets, and the output is materials adapted to the user's emotions.

[0730] Step 5:

[0731] The terminal displays materials provided by the server and notifies the user. The terminal displays material files, important alerts, and notifications on the user's screen, making them easily accessible. Input consists of materials sent from the server, and the user receives the resulting materials and notifications.

[0732] Step 6:

[0733] Users adjust business processes based on information provided on their terminals and plan new tasks as needed. Once users review the materials, they use them to revise project activities and develop new plans. Input is the information displayed on the terminal, and output is the specific business plan and its execution.

[0734] (Application Example 2)

[0735] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0736] Traditional business efficiency systems focus primarily on information integration and provision, automated document generation, and sharing of work deliverables, but they lack optimization that takes user emotions into account. This makes it difficult to effectively optimize business processes in accordance with user emotions and to create documents tailored to those emotions. Furthermore, providing appropriate feedback that reflects user emotions is challenging, hindering the development of a positive team atmosphere and improving user satisfaction.

[0737] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0738] In this invention, the server includes data integration means, information provision means, automatic material generation means, and emotion recognition means. This enables the analysis of user emotions, optimization of business processes based on these analyses, provision of materials tailored to emotions, and feedback that takes emotions into consideration.

[0739] A "data integration system" is a mechanism for collecting data from various sources and centrally combining that data.

[0740] An "information provision method" is a system that searches for necessary information based on requests from users and provides it in an appropriate format.

[0741] A "document generation system" is a mechanism that uses a generation model to automatically create documents in a specified format from integrated data and provides them to users.

[0742] A "method for sharing results" is a system for aggregating the work progress and deliverables of multiple users and sharing them within a team.

[0743] An "emotion recognition tool" is a system that analyzes the user's emotions and reflects them in optimizing processes and improving the content of materials.

[0744] The system of this invention uses a smart device, an emotion analysis engine, and a cloud server to provide information and optimize processes based on the user's emotions.

[0745] The server receives data transmitted from smart devices and uses an emotion analysis engine to analyze the user's emotions from voice and facial expressions. Based on the acquired emotion data, it becomes possible to optimize business processes and customize materials. The server processes the data with high accuracy using emotion analysis software such as Microsoft Azure Emotion API.

[0746] The device has the ability to display information on devices such as smart glasses and tablets, providing real-time information tailored to the user's emotions. For example, if the user is feeling stressed, it can display information related to relaxation. This device includes smart wear such as Google Glass.

[0747] Users can obtain information in real time through their devices, thereby improving work efficiency. For example, in customer service, emotion recognition can enable them to provide the most appropriate response.

[0748] By utilizing a generative AI model, automatically generated materials and information are customized to suit individual emotions. Therefore, the materials include positive messages and supportive content, leading to increased user motivation.

[0749] For example, if a customer shows discomfort due to background noise, the system can display a message on the screen using music or sound effects to encourage relaxation. An example of a prompt message in this case would be: "This system uses an emotion analysis engine to provide optimal information and adjust the process based on the user's emotions. Please display relaxation information based on voice and facial expression data."

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

[0751] Step 1:

[0752] The server receives audio and video data collected from smart devices. Here, data acquired via camera and microphone serves as input. This data is transferred to a cloud server and formatted into a format that can be analyzed using emotion analysis software.

[0753] Step 2:

[0754] The server inputs formatted data into an emotion analysis engine to calculate the user's emotional state. Specifically, it analyzes voice pitch and evaluates changes in facial expressions. As a result of the analysis, the user's emotional information (e.g., joy, surprise, anger) is output. Based on this information, prompt sentences are generated for the generative AI model.

[0755] Step 3:

[0756] The terminal receives emotion data and prompt messages sent from the server. Based on this information, it displays information and messages appropriate to the user. Here, the displayed content is dynamically determined according to the input emotion data. Specifically, if the user indicates stress, messages and music related to relaxation will be displayed.

[0757] Step 4:

[0758] Users review the information provided by their devices and adjust their actions as needed. For example, they might take action based on the information provided to shift their emotional state in a positive direction. Finally, user feedback is re-entered into the system and used to improve subsequent analysis and information provision. This cycle continuously optimizes the process.

[0759] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0760] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0761] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0762] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0763] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0764] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0765] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0766] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0767] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0768] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0769] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0770] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0771] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0772] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0773] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0774] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0775] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0776] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0777] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0778] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0779] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0780] The following is further disclosed regarding the embodiments described above.

[0781] (Claim 1)

[0782] A data integration means that collects data from various internal information management tools and integrates said data,

[0783] An information provision means that searches the data in response to a user's request for information and provides information suitable for the request,

[0784] A document generation means that uses a generation model to automatically generate documents in a specified format based on the integrated data and provides such documents,

[0785] A means of sharing results that aggregates and shares the work progress and deliverables of multiple users,

[0786] A business efficiency system that includes this.

[0787] (Claim 2)

[0788] The business efficiency system according to claim 1, characterized in that the automatic data generation means acquires further information from an external data source and reflects said information in said data.

[0789] (Claim 3)

[0790] The business efficiency system according to claim 1, characterized in that the means for sharing results periodically generates progress and results as reports and sends and shares them with team members.

[0791] "Example 1"

[0792] (Claim 1)

[0793] Information integration means that collects information from an information processing device, integrates the information, and removes duplication and corrects inconsistencies,

[0794] An information response means that searches a database in response to information requests from various terminals and provides information that matches the request,

[0795] A document generation means that uses generation AI technology to automatically create a document in a specified format based on integrated information and provides the document,

[0796] A means of sharing results that aggregates the work progress and results of multiple users, and periodically creates and shares reports,

[0797] A system that includes this.

[0798] (Claim 2)

[0799] The system according to claim 1, characterized in that the data generation means acquires additional information from an external information source and incorporates said information into the data.

[0800] (Claim 3)

[0801] The system according to claim 1, characterized in that the means for sharing results periodically generates reports and distributes and shares them with users.

[0802] "Application Example 1"

[0803] (Claim 1)

[0804] A data integration means that collects data from various internal information management devices and integrates said data,

[0805] An information provision means that searches the data in response to a user's request for information and provides information suitable for that request,

[0806] A data generation means that uses a generation model to automatically generate data in a specified format based on the integrated data and provides the data,

[0807] A means of sharing results that aggregates and shares the work progress and deliverables of multiple users,

[0808] An optimization command means that provides work instructions to production equipment in real time and optimizes the work process,

[0809] A system that includes this.

[0810] (Claim 2)

[0811] The system according to claim 1, characterized in that the automatic data generation means acquires further information from an external data source and reflects said information in said data.

[0812] (Claim 3)

[0813] The system according to claim 1, characterized in that the means for sharing results periodically generates progress and results as reports and transmits and shares them with the work group.

[0814] "Example 2 of combining an emotion engine"

[0815] (Claim 1)

[0816] An information integration means that collects data from internal information management means and integrates said data,

[0817] An emotion-adaptive information provision means that searches the data based on the user's emotional state and provides information suitable for the request,

[0818] An emotion-adaptive data generation means that uses a generative model to automatically generate data in a specified format based on the integrated data and provides data that takes emotional states into consideration,

[0819] A means of sharing results that aggregates activity progress and deliverables from multiple users and shares sentiment trends,

[0820] A system that includes this.

[0821] (Claim 2)

[0822] The system according to claim 1, characterized in that the emotion adaptation data automatic generation means acquires further data from an external information source and reflects the data in the data.

[0823] (Claim 3)

[0824] The system according to claim 1, characterized in that the means for sharing results periodically generates progress and results as reports, sends them to team members, and shares sentiment-based feedback.

[0825] "Application example 2 when combining with an emotional engine"

[0826] (Claim 1)

[0827] A data integration means that collects data from internal information management means and integrates said data,

[0828] An information provision means that searches the data in response to a user's request for information and provides information suitable for that request,

[0829] A document generation means that utilizes a generative model to automatically generate documents in a specified format based on the integrated data and provides such documents,

[0830] A means of sharing results that aggregates and shares the work progress and deliverables of multiple users,

[0831] An emotion recognition method that analyzes the user's emotions and optimizes the process,

[0832] A system that includes this.

[0833] (Claim 2)

[0834] The system according to claim 1, characterized in that the automatic data generation means acquires further information from an external information source, reflects the information in the data, and adjusts the content of the data based on the emotion recognition means.

[0835] (Claim 3)

[0836] The system according to claim 1, characterized in that the means for sharing results periodically generates progress and results as reports, sends them to team members, and shares them while reflecting sentiment trends. [Explanation of Symbols]

[0837] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A data integration means that collects data from various internal information management tools and integrates said data, An information provision means that searches the data in response to a user's request for information and provides information suitable for the request, A document generation means that uses a generation model to automatically generate documents in a specified format based on the integrated data and provides such documents, A means of sharing results that aggregates and shares the work progress and deliverables of multiple users, A business efficiency system that includes this.

2. The business efficiency system according to claim 1, characterized in that the automatic data generation means acquires further information from an external data source and reflects said information in said data.

3. The business efficiency system according to claim 1, characterized in that the means for sharing results periodically generates progress and results as reports and sends and shares them with team members.

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