system

Abstract

We provide the system. [Solution] A means for users to input the topics they want to discuss in the meeting, Means for sending the aforementioned agenda to the server, A server provides means for collecting information related to the agenda using generated AI, A means for organizing and analyzing the information collected by the server, A means of generating a report from the information organized and analyzed by the server, A means of sending the report generated by the server to the user's terminal, A system including means for the user to view the aforementioned report.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including 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 a modern business environment, efficient meeting operation is an important issue. Especially in internal company meetings, in many cases, due to insufficient prior information collection and agenda setting, a lot of time is wasted during the meeting. As a result, productivity decreases and efficient decision-making is hindered. Also, it is difficult to quickly collect and analyze the latest information to respond to rapidly changing market trends and trends. Against this background, there is a need for a system that can perform sufficient prior information collection and organization and can be effectively utilized during meetings.

Means for Solving the Problems

[0005] The present invention solves the above-mentioned problems by providing a system that includes means for a user to input an agenda item they wish to discuss in a meeting, means for sending the agenda item to a server, means for the server to collect information related to the agenda item using a generated AI, means for the server to organize and analyze the collected information, means for the server to generate a report from the organized and analyzed information, means for sending the server-generated report to the user's terminal, and means for the user to review the report. This system ensures that sufficient information is available before the meeting, allowing for more time to consider the data and opinions brought to the meeting, and enabling efficient and productive meeting management.

[0006] A "user" refers to an individual or organization that uses the system to input agenda items and receive information.

[0007] "Agenda items" refer to themes such as market trends, new ideas, and issues that users want to discuss in a meeting.

[0008] A "terminal" is a computing device used by users to input agenda items and communicate with the server, and includes personal computers, smartphones, tablets, and other similar devices.

[0009] A "server" refers to a computing system that receives agenda items sent from terminals and uses generative AI to collect, organize, analyze, and generate reports on the information.

[0010] "Generative AI" refers to an artificial intelligence system that uses natural language processing and machine learning techniques to automatically collect and analyze information related to an input topic from the internet or internal databases.

[0011] "Information gathering" refers to the process by which the generating AI acquires relevant text, statistical data, news articles, and other information from the internet and internal databases.

[0012] "Organization and analysis" refers to the process of evaluating collected information based on its reliability, relevance, and importance, and extracting important data while filtering out unnecessary information.

[0013] A "report" refers to a document that compiles organized and analyzed information in a format that is easy for users to understand (such as summaries, graphs, and statistical data).

[0014] "Sending" means sending reports generated by the server to the terminal, and this includes, for example, email and dashboard notifications.

[0015] "Verification" refers to the process of reviewing and checking the content of reports submitted by users. [Brief explanation of the drawing]

[0016] [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] Displays an emotion map on which multiple emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Mode for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0018] [[ID=2S]]First, the terms used in the following description will be explained.

[0019] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0020] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] 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."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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".

[0037] This invention is a system in which a user inputs the topics they wish to discuss in a meeting, and the system collects and organizes the necessary information based on that input and provides it as a report. This enables meetings to be conducted efficiently and productively. Embodiments of this invention are described in detail below.

[0038] Explanation of the program's processing

[0039] User enters agenda item

[0040] Users enter topics they want to discuss during the meeting, such as market trends, new ideas, or challenges, into the interface's text boxes. For example, they might set a specific topic like "Market trends in the IT industry in 2024."

[0041] The terminal sends the agenda to the server.

[0042] The terminal converts the agenda entered by the user into a data format (e.g., JSON format) and sends it to the server using an HTTPS request. The communication is encrypted and secure.

[0043] The server receives the agenda and creates a query for the generating AI.

[0044] The server receives the agenda sent from the terminal and analyzes it. Next, it creates a query for the generating AI based on this agenda. For example, it might set a query in the format of, "Please provide the latest information on market trends in the IT industry in 2024."

[0045] The server uses generated AI to collect information.

[0046] The server sends the generated query to a generating AI (e.g., GPT-3®) to collect relevant information. The generating AI retrieves the necessary information (text, data, news articles, statistics, etc.) from the internet or internal databases.

[0047] The server organizes and analyzes the information it has collected.

[0048] The server receives and analyzes the information returned by the generating AI. Here, the information is filtered and summarized based on criteria such as reliability, relevance, and importance. For example, statistical data may be extracted and graphed, or key points may be listed in bullet points.

[0049] The server generates the report.

[0050] Based on the organized and analyzed information, the server generates a user-friendly report. This report includes summaries, graphs, statistics, and reference links.

[0051] The server sends the generated report to the user's terminal.

[0052] Once a report is generated, the server sends it to the user's device. The report is sent in a digital format such as JSON or PDF, and notifications are sent via email or on the dashboard as needed.

[0053] The user reviews the report.

[0054] Users review the reports they receive on their devices. They then examine the report's contents and use it as material for discussion during meetings. This allows users to prepare thoroughly in advance and effectively consider data and opinions during meetings.

[0055] Specific example

[0056] Example 1: Market Trends Agenda

[0057] User enters topic: The user enters the topic "Market trends in the IT industry in 2024".

[0058] Terminal sends agenda to server: The terminal sends this agenda to the server.

[0059] The server receives the agenda and creates a query for the generating AI: The server creates an appropriate query and sends it to the generating AI.

[0060] The server uses generative AI to gather information: Generative AI collects the latest reports, news articles, and statistical data on market trends.

[0061] Server-generated information organization and analysis: The server organizes the information, extracts important data, and creates a summary.

[0062] The server generates the report: It creates a detailed report based on the organized and analyzed information.

[0063] Send the server-generated report to the user's terminal: The report is sent to the user's terminal.

[0064] User reviews report: The user reviews the report and completes preparations for the meeting.

[0065] This invention enables efficient use of time during meetings by gathering and organizing sufficient information before the meeting, facilitating high-quality discussions and rapid decision-making.

[0066] The following describes the processing flow.

[0067] Step 1:

[0068] User enters agenda item

[0069] Users enter topics they want to discuss in the meeting, such as market trends, new ideas, or challenges, into the interface's text boxes. For example, they might enter "Market trends in the IT industry in 2024."

[0070] Step 2:

[0071] The terminal sends the agenda to the server.

[0072] The terminal converts the agenda entered by the user into an appropriate data format (e.g., JSON) and sends it to the server as an HTTPS request. This communication is encrypted and secure.

[0073] Step 3:

[0074] The server receives the agenda and creates a query for the generating AI.

[0075] The server analyzes the agenda received from the terminal and creates a query for the generating AI. For example, it might prepare a query in the format, "Please provide the latest information on market trends in the IT industry in 2024."

[0076] Step 4:

[0077] The server uses generated AI to collect information.

[0078] The server sends the generated query to the generative AI and collects the relevant information. The generative AI automatically retrieves text, statistical data, news articles, and other information from the internet and internal databases.

[0079] Step 5:

[0080] The server organizes and analyzes the information it has collected.

[0081] The server receives the information returned by the generating AI and organizes and analyzes it based on reliability, relevance, and importance. It filters out unnecessary parts of the data and extracts important data points.

[0082] Step 6:

[0083] The server generates the report.

[0084] The server generates a report based on the organized and analyzed information. This report includes summaries, graphs, statistical data, and reference links, and is provided in a format that is easy for the user to understand.

[0085] Step 7:

[0086] The server sends the generated report to the user's terminal.

[0087] The server converts the generated report into JSON or PDF format and sends it to the user's device. Delivery methods include email and dashboard notifications.

[0088] Step 8:

[0089] The user reviews the report.

[0090] Users review the reports they receive on their devices. They then examine the report's contents and use it as material for discussion during meetings. This allows users to prepare thoroughly in advance and effectively consider data and opinions during the meeting.

[0091] (Example 1)

[0092] 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."

[0093] In modern meetings, a major challenge is the need for a vast amount of information, requiring significant time and effort to collect and organize it beforehand. In particular, a lack of rapid and accurate information gathering can reduce meeting productivity and hinder effective decision-making. Furthermore, given the sheer volume of information, there is a need to efficiently organize and present the necessary information clearly.

[0094] 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.

[0095] In this invention, the server includes means for the user to input an agenda item they wish to discuss in a meeting; means for the terminal to send the agenda item to the server; means for the server to create a query for a generating AI based on the agenda item; means for collecting information related to the agenda item using the generating AI; means for organizing and analyzing the collected information; means for generating the organized and analyzed information as a report; means for sending the generated report to the user's terminal; and means for the user to review the report. This enables the user to efficiently and automatically collect and organize the necessary information and receive it in an easy-to-understand report.

[0096] A "user" is the entity that uses the system to input the topics they want to discuss in a meeting.

[0097] "Agenda items" refer to the themes or topics discussed in a meeting, and are text information entered by the user.

[0098] A "terminal" refers to a device used by a user to input agenda items and send them to the server, and includes, for example, personal computers and smartphones.

[0099] A "server" is a central computer system that receives agenda items submitted by users and uses generating AI to collect, organize, and analyze information.

[0100] "Generative AI" refers to artificial intelligence technology that uses natural language processing techniques to automatically acquire relevant information related to a user's topic.

[0101] A "query" refers to a question created by a server to request information gathering from a generating AI, and is often in natural language format.

[0102] "Information gathering" refers to the process by which a generating AI acquires necessary data from information sources such as the internet and internal databases.

[0103] "Organization and analysis" is the process of evaluating collected information based on its reliability and relevance, selecting the necessary data, and processing it into an easily understandable format.

[0104] A "report" refers to a document that integrates organized and analyzed information and provides it to the user, including summaries, graphs, and statistical information.

[0105] "Transmission" refers to the data transfer process that delivers reports generated by the server to the user's terminal.

[0106] "Verification" refers to the act of carefully examining the contents of reports received by users on their devices and using them as material for meeting preparations and discussions.

[0107] This invention is a system in which a user inputs the topics they wish to discuss in a meeting, and based on that input, the system collects and organizes the necessary information and provides it as a report. This enables meetings to be conducted efficiently and productively. Embodiments of this invention are described in detail below.

[0108] Users enter topics by accessing a dedicated interface. For example, they might access the system's website using a browser, enter "Market Trends in the IT Industry in 2024" into a text box, and click the "Submit" button. This input interface is built using HTML and JavaScript®.

[0109] The terminal first retrieves the agenda entered in the text box and converts it to JSON format. After conversion, it creates an HTTPS POST request and sends it to a specific API endpoint on the server. The communication is encrypted using SSL / TLS, ensuring security. The terminal's communication processing uses libraries such as Python's requests library or JavaScript's fetch API.

[0110] The server receives and analyzes the agenda sent from the terminal. Based on the received agenda, "Market Trends in the IT Industry in 2024," it generates a natural language query. For example, it might create a query such as, "Please provide the latest information on market trends in the IT industry in 2024." An automated natural language processing algorithm is useful for this query generation.

[0111] Next, the server sends the generated query to a generating AI (e.g., GPT-3). The generating AI then collects the necessary information from the internet or internal databases based on the query. For example, it might collect the latest news articles, statistical data, reports, etc.

[0112] The server receives and analyzes the information returned by the generated AI. The information is filtered and summarized based on criteria such as reliability, relevance, and importance. For example, statistical data may be extracted and graphed, or key points may be listed in bullet points. Tools such as Python's pandas library and matplotlib are used for organizing and analyzing this information.

[0113] Based on the organized and analyzed information, the server generates a user-friendly report. This report includes summaries, graphs, statistical data, and reference links. HTML template engines (e.g., Jinja2) and PDF generation libraries (e.g., ReportLab) are used to generate the report.

[0114] The generated report is converted back into JSON or PDF format and sent to the user's device using an HTTPS POST request. After sending, the user receives an email notification or a notification on the dashboard. For email notifications, the SMTP protocol is used, for example.

[0115] Users review the reports received on their devices. They examine the reports displayed in their browsers and scrutinize their contents. If necessary, they can print or download the reports for offline viewing. This allows them to adequately prepare for meetings.

[0116] <Specific example>

[0117] The user enters and submits the topic "Market Trends in the IT Industry in 2024." After being sent from the terminal to the server, the server sends a query to the generating AI asking, "Please provide the latest information on market trends in the IT industry in 2024." The generating AI collects the latest relevant reports and statistical data, and the server analyzes and organizes it to generate a report. This report is sent to the user's terminal, and the user uses it to prepare for the meeting.

[0118] This invention enables users to efficiently and automatically collect and organize necessary information and receive it as an easy-to-understand report.

[0119] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0120] Program processing flow

[0121] Step 1: The user enters the agenda.

[0122] The user accesses the system's website using a browser. They enter a topic into the text box. For example, they might enter the text "Market Trends in the IT Industry in 2024" and click the "Submit" button.

[0123] Input: The user enters text as the agenda item.

[0124] Output: After clicking the send button, the agenda will be received on the device.

[0125] Step 2: The terminal sends the agenda to the server.

[0126] The terminal retrieves the agenda entered in the text box and converts it to JSON format. It then sends the converted data to the server via an HTTPS POST request. This request is secure because it is encrypted using SSL / TLS.

[0127] Input: Agenda text entered by the user

[0128] Output: The agenda, converted to JSON format, is sent to the server.

[0129] Step 3: The server receives the agenda and creates a query for the generating AI.

[0130] The server receives the agenda sent from the terminal. Next, it analyzes the received agenda and generates a query for the generating AI. For example, it might generate a query such as, "Please provide the latest information on market trends in the IT industry in 2024."

[0131] Input: Agenda data in JSON format

[0132] Output: Natural language queries to send to the generating AI

[0133] Step 4: The server uses generated AI to collect information.

[0134] The server sends the generated queries to a generating AI (e.g., GPT-3). The generating AI collects relevant information from external and internal sources. This process gathers the latest news articles, statistics, reports, and so on.

[0135] Input: Natural language query

[0136] Output: Related information returned by the generating AI

[0137] Step 5: Organize and analyze the information collected by the server.

[0138] The server receives information returned by the generating AI and filters it based on reliability and relevance. It then summarizes the information and performs organization and analysis, such as graphing statistical data. For example, it might utilize Python libraries like pandas or matplotlib.

[0139] Input: Information returned by the generating AI

[0140] Output: Organized and analyzed information (summary, graphs, statistical data)

[0141] Step 6: The server generates the report.

[0142] The server generates user reports based on the organized and analyzed information. These reports include summaries, graphs, statistics, and reference links. For example, they can be visually formatted using an HTML template engine.

[0143] Input: Organized and analyzed information

[0144] Output: Completed report (HTML or PDF format)

[0145] Step 7: Send the report generated by the server to the user's terminal.

[0146] The server converts the generated report into an appropriate format (e.g., JSON or PDF) and sends it to the user's device using an HTTPS POST request. Email notifications and dashboard notifications are also provided as needed.

[0147] Input: Completed report

[0148] Output: Report sent to the user's device

[0149] Step 8: User reviews the report

[0150] Users open the received report on their device and review its contents. They can view the report in a browser and examine the data and statistics. If necessary, they can also print or download the report for offline viewing.

[0151] Input: Report sent from the server

[0152] Output: Confirmed report contents (review, print, download)

[0153] The above outlines the specific processing steps of the system. The details of the specific actions performed at each step, along with the associated inputs and outputs, have been described.

[0154] (Application Example 1)

[0155] 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."

[0156] Traditional meeting preparation systems required significant time and effort to gather and organize information for discussion, and lacked concrete tools for virtual store operators to efficiently consider new product lines and market trends. Furthermore, the tools for immediately utilizing the collected information were insufficient, compromising the quality and efficiency of meetings.

[0157] 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.

[0158] In this invention, the server includes means for the virtual store operator to input meeting agendas, means for transmitting agendas entered from a smart device to the server, means for creating and sending queries to a generating AI, means for collecting market research reports, customer reviews, and sales data using the generating AI, means for analyzing the collected data, extracting key points and graphing them, means for creating a detailed report, means for transmitting the generated report to a smart device, and means for reviewing the report. This enables the virtual store operator to prepare meeting materials efficiently and quickly, and to effectively consider data and opinions during the meeting.

[0159] A "user" is the final user who uses the system to input meeting agenda items and review reports.

[0160] A "server" is a central control unit that receives agenda items submitted by users, collects, organizes, and analyzes information using generation AI, generates reports, and sends them to the user's terminal.

[0161] "Generative AI" is artificial intelligence that collects relevant information from the internet or internal databases based on an input query and then analyzes it.

[0162] An "agenda" is a specific theme or topic that users want to discuss in a meeting.

[0163] A "smart device" is an advanced device such as glasses or head-mounted displays that can connect to the internet.

[0164] A "query" is a question or command created by a server to prompt a generating AI to collect information.

[0165] A "market research report" is a document that summarizes the detailed results of a survey on market trends, competitive situations, and other related matters.

[0166] "Customer reviews" are records of customer evaluations and opinions about products and services.

[0167] "Sales data" refers to information regarding the quantity and amount of sales of products over a specific period.

[0168] "Data analysis" is the process of organizing collected information using statistical methods and other techniques to present it in a meaningful form.

[0169] "Key points" refer to particularly important information or indicators within the analyzed data.

[0170] "Graphing" is the process of representing data using shapes to make it easier to understand visually.

[0171] A "report" is a detailed report created based on collected and analyzed information.

[0172] A "meeting" is a gathering of stakeholders to discuss a specific topic and reach a consensus.

[0173] This invention is a system in which a user inputs the topics they wish to discuss in a meeting, and based on that input, the system collects, organizes, and analyzes the necessary information and provides it as a report. A specific embodiment of this system is described below.

[0174] System Configuration

[0175] Hardware:

[0176] Smart glasses (e.g., typical smart glasses)

[0177] Head-mounted display (e.g., typical HMD)

[0178] software:

[0179] Frontend: React Native

[0180] Backend: Node.js, Express.js

[0181] Data analysis: Python, Pandas, Matplotlib

[0182] Generating AI: GPT-3 (OpenAI(registered trademark) API)

[0183] Frontend operation

[0184] Users enter meeting agenda items using smart glasses or head-mounted displays. The agenda items are entered into text boxes, and the data is sent to the server in JSON format. An example of an agenda item a user might enter is "Market Trends in the IT Industry in 2024."

[0185] Data transmission

[0186] The terminal sends the agenda entered by the user to the server. During this process, the data is encrypted and transmitted using HTTPS communication. The server analyzes the received data and creates queries to send to the generating AI to collect the necessary information.

[0187] Information gathering

[0188] The server sends queries to the Generative AI (GPT-3) to collect relevant information. An example query is, "Please provide the latest information on market trends in the IT industry in 2024." The Generative AI retrieves the necessary information from the internet and internal databases. This collected information includes market research reports, customer reviews, and sales data.

[0189] Data Analysis

[0190] The server analyzes the information returned by the generating AI. It filters the information based on criteria such as reliability, relevance, and importance, and extracts summarized and graphed statistical information.

[0191] Report generation

[0192] Based on the analyzed information, the server generates a report in a user-friendly format. The report includes a summary, graphs, statistical data, and reference links.

[0193] Send Report

[0194] The completed report is sent to the user's smart glasses or head-mounted display. The user can then review it and prepare for the meeting.

[0195] Specific example

[0196] Case Study 1: Considering the introduction of a new product line

[0197] The user enters the topic "Effects of introducing a new product line."

[0198] Agenda items entered from smart devices are sent to the server.

[0199] The server sends a query to the generating AI asking, "Please provide information about the effectiveness of introducing the new product."

[0200] The generation AI collects market research reports, customer reviews, sales data, and more.

[0201] The server analyzes the collected data, extracts key points, and graphs them.

[0202] A detailed report is created and sent to your smart device.

[0203] Users review the report and prepare for discussions in the meeting.

[0204] An example of a prompt message would be something like, "Please provide me with the latest information on market trends in the IT industry in 2024."

[0205] This invention enables virtual store operators to efficiently and quickly prepare meeting materials and to effectively review data and opinions during meetings.

[0206] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0207] Step 1:

[0208] The user enters an agenda item into a text box using smart glasses or a head-mounted display. The entered agenda item is in text format, and a specific example of input would be "Market trends in the IT industry in 2024." This text data is sent to the server in the next step.

[0209] Step 2:

[0210] The terminal converts the agenda entered by the user into JSON format and sends it to the server using HTTPS. This ensures that the agenda data is securely communicated to the server. The input is an agenda in text format, and the output is data in JSON format.

[0211] Step 3:

[0212] The server analyzes the received agenda and creates queries for the generating AI. Specifically, it generates queries such as "Please provide the latest information on market trends in the IT industry in 2024" based on the received text data. The input is agenda data in JSON format, and the output is query text to be sent to the generating AI.

[0213] Step 4:

[0214] The server generates queries and sends them to a generative AI like GPT-3 to collect relevant information. The generative AI retrieves market research reports, customer reviews, sales data, etc., by referencing the internet and internal databases. The input is the query text, and the output is the collected relevant information.

[0215] Step 5:

[0216] The server organizes and analyzes the information returned by the generating AI. Specifically, it filters the information based on criteria such as reliability, relevance, and importance, and extracts summaries and statistical data. For example, it uses Python's Pandas and Matplotlib to graph sales data. The input is relevant information from the generating AI, and the output is filtered and summarized information and graph data.

[0217] Step 6:

[0218] The server generates a report based on the information it organizes and analyzes. The report includes a summary, graphs, statistics, and reference links. The generated report is saved in PDF or HTML format. The input is the organized and analyzed information, and the output is the report provided to the user.

[0219] Step 7:

[0220] The server generates a report and sends it to the smart device. Once the report is generated, the server sends it to the user's device in JSON or PDF format. The input is the generated report, and the output is a report viewable on the user's smart device.

[0221] Step 8:

[0222] Users view reports using smart glasses or head-mounted displays. By viewing the reports, users can prepare discussion materials for meetings. The input is the report on the smart device, and the output is the meeting materials the user receives.

[0223] 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.

[0224] This invention is a system in which a user inputs the topics they wish to discuss in a meeting, and based on that input, the system collects and organizes the necessary information and provides it as a report. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it enables prioritization of topics and customization of reports. The configuration for implementing this system is described in detail below.

[0225] Explanation of the program's processing

[0226] User enters agenda item

[0227] Users enter topics they want to discuss in the meeting, such as market trends, new ideas, or challenges, into the interface's text boxes. For example, they might enter "Market trends in the IT industry in 2024."

[0228] The terminal sends the agenda to the server.

[0229] The terminal converts the agenda entered by the user into an appropriate data format (e.g., JSON) and sends it to the server as an HTTPS request. This communication is encrypted and secure.

[0230] The server receives the agenda and creates a query for the generating AI.

[0231] The server analyzes the agenda received from the terminal and creates a query for the generating AI. For example, it might prepare a query in the format, "Please provide the latest information on market trends in the IT industry in 2024."

[0232] The server uses generated AI to collect information.

[0233] The server sends the generated query to the generative AI and collects the relevant information. The generative AI automatically retrieves text, statistical data, news articles, and other information from the internet and internal databases.

[0234] The server organizes and analyzes the information it has collected.

[0235] The server receives the information returned by the generating AI and organizes and analyzes it based on reliability, relevance, and importance. It filters out unnecessary parts of the data and extracts important data points.

[0236] The server uses an emotion engine to recognize the user's emotions.

[0237] The emotion engine analyzes the user's emotions from user input data (e.g., keyboard typing speed and emphasized words). For example, it pays particular attention to areas where the user has a strong interest or concern.

[0238] The server adjusts agenda priorities based on user sentiment.

[0239] The server adjusts the priority of agenda items based on the sentiment analysis results from the sentiment engine. It prioritizes information gathering and organization for agenda items of high interest or urgent issues.

[0240] The server generates the report.

[0241] Based on the organized and analyzed information, the server generates a user-friendly report. This report includes summaries, graphs, statistics, and reference links, and the presentation of information is customized to suit the user's perspective.

[0242] The server sends the generated report to the user's terminal.

[0243] Once a report is generated, the server sends it to the user's device. The transmission format can be digital, such as JSON or PDF, and may also include email or dashboard notifications.

[0244] The user reviews the report.

[0245] Users review reports received on their devices. They prepare for meetings based on agendas prioritized by the emotion engine and customized information. This allows users to be well-prepared in advance and efficiently review data and opinions during meetings.

[0246] Specific example

[0247] Example 1: Market Trends Agenda

[0248] User enters topic: The user enters the topic "Market trends in the IT industry in 2024".

[0249] Terminal sends agenda to server: The terminal sends this agenda to the server.

[0250] The server receives the agenda and creates a query for the generating AI: The server creates an appropriate query and sends it to the generating AI.

[0251] The server uses generative AI to gather information: Generative AI collects the latest reports, news articles, and statistical data on market trends.

[0252] Server-generated information organization and analysis: The server organizes the information, extracts important data, and creates a summary.

[0253] The server uses an emotion engine to recognize the user's emotions: The emotion engine analyzes the user's input to determine their emotions and assess their level of interest.

[0254] The server adjusts agenda priorities based on user sentiment: It adjusts the priority of important agenda items based on sentiment analysis results.

[0255] The server generates reports: Based on the organized and analyzed information, it creates detailed reports and presents information in a way that is sensitive to the user's emotions.

[0256] Send the server-generated report to the user's terminal: The report is sent to the user's terminal.

[0257] Users review the report: Users review the report and prepare for the meeting focusing on topics of high interest to them.

[0258] This system enables information gathering and organization that takes user emotions into consideration, further improving meeting productivity.

[0259] The following describes the processing flow.

[0260] Step 1:

[0261] User enters agenda item

[0262] Users enter topics they want to discuss in the meeting, such as market trends, new ideas, or challenges, into the interface's text box. For example, they might enter "Market trends in the IT industry in 2024."

[0263] Step 2:

[0264] The terminal sends the agenda to the server.

[0265] The terminal converts the agenda entered by the user into JSON format and sends it to the server as an HTTPS request. The communication is encrypted and takes place in a secure environment.

[0266] Step 3:

[0267] The server receives the agenda and creates a query for the generating AI.

[0268] The server analyzes the agenda received from the terminal and generates appropriate queries for the AI. For example, it might create a query in the format of, "Please provide the latest information on market trends in the IT industry in 2024."

[0269] Step 4:

[0270] The server uses generated AI to collect information.

[0271] The server sends queries to the generative AI to collect relevant information. The generative AI retrieves text, statistics, news articles, reports, and other data from the internet and internal databases.

[0272] Step 5:

[0273] The server organizes and analyzes the information it has collected.

[0274] The server receives the information returned by the generating AI and organizes and analyzes it based on reliability, relevance, and importance. If there is too much information, it filters out unnecessary data and extracts the important information.

[0275] Step 6:

[0276] The server uses an emotion engine to recognize the user's emotions.

[0277] The emotion engine analyzes user input data and user activity history (e.g., typing speed and vocabulary selection) to infer the user's emotions. For example, it analyzes emotions based on keywords that the user emphasizes when typing.

[0278] Step 7:

[0279] The server adjusts agenda priorities based on user sentiment.

[0280] The server adjusts the priority of agenda items based on the sentiment analysis results obtained from the sentiment engine. Topics of high interest and urgent issues are prioritized for information gathering and organization.

[0281] Step 8:

[0282] The server generates the report.

[0283] The server generates a report based on the organized and analyzed information. This report includes a summary, graphs, statistical data, reference links, etc. Customize the way of presenting information according to the user's sentiment.

[0284] Step 9:

[0285] Send the report generated by the server to the user's terminal

[0286] The server sends the generated report to the user's terminal in JSON or PDF format. The sending methods include email and dashboard notifications.

[0287] Step 10:

[0288] The user checks the report

[0289] The user checks the report received on the terminal. Based on the issues with adjusted priorities and customized information by the sentiment engine, prepare for the meeting.

[0290] This system enables information collection and organization considering the user's sentiment, and further improves the productivity of the meeting. For example, for topics that the user is highly interested in, they can be placed at the top of the report, and important information can be highlighted.

[0291] (Example 2)

[0292] Next, Example 2 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart device 14 is referred to as the "terminal".

[0293] Conventional meeting preparation systems lacked sufficient automation in gathering and organizing information for agenda items, requiring users to manually search for and compile necessary information. Furthermore, the lack of information customization based on user sentiment and interests hindered efficient meeting preparation. This invention aims to solve these problems by providing a system that automatically collects and organizes information based on user input and delivers reports that reflect user sentiment.

[0294] 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.

[0295] In this invention, the server includes means for collecting information related to the agenda using generative AI, means for organizing and analyzing the collected information, and means for analyzing the user's emotions using an emotion analysis engine. This allows the prioritization of agenda items to be adjusted based on the user's emotions, and enables the provision of customized reports to the user.

[0296] A "user" is defined as the entity that utilizes the present invention, and is the person who inputs agenda items and reviews reports.

[0297] A "terminal" is a device used by users to input agenda items or to receive and review reports sent from a server. Specifically, this includes personal computers, smartphones, and tablets.

[0298] A "server" is a computer system that processes data sent from users or terminals, and collects, organizes, analyzes, generates, and transmits information.

[0299] "Generative AI" refers to artificial intelligence technology that collects relevant information in response to user queries, and is used to retrieve information from the internet or internal databases.

[0300] The "Emotion Analysis Engine" is a technology for analyzing emotions from the user's input data and extracting information related to the user's degree of interest and emotions.

[0301] The "topic" refers to the topic or theme that the user wants to discuss in a meeting and is sent to the server through the input interface.

[0302] "Information collection" is a process in which the generative AI obtains relevant data from the Internet or an internal database based on the user's query.

[0303] "Sorting and analyzing information" is a process of filtering the collected data based on reliability, relevance, and importance, and extracting important data points.

[0304] A "report" is a document or data generated in a user-friendly format based on the sorted and analyzed information, and may include summaries, graphs, statistical data, reference links, etc.

[0305] "Adjusting priorities" is a process of re-evaluating the importance of topics and information based on the results of the emotion analysis engine and changing the order of collection and sorting.

[0306] The "JSON format" is short for JavaScript Object Notation and is a format for representing data in a lightweight and compact manner.

[0307] "TLS" is short for Transport Layer Security and is a protocol for encrypting data communication via the Internet to ensure security.

[0308] This invention is a system in which a user inputs the topics they wish to discuss in a meeting, and based on that input, the system collects and organizes the necessary information and provides it as a report. By combining this invention with a sentiment analysis engine, the system enables prioritization of topics and customization of reports. A detailed embodiment of this system is described below.

[0309] Hardware and software to be used

[0310] User's device: This is the device on which the user enters agenda items and reviews reports. This includes personal computers, smartphones, and tablets.

[0311] Server: A computer system that receives, processes, and generates data, sends queries to AI, collects and analyzes information, performs sentiment analysis, and generates and sends reports.

[0312] Generative AI models: These are artificial intelligence technologies that collect relevant information based on user queries, and for example, large-scale language models (such as GPT-3) are used.

[0313] Sentiment analysis engine: This technology analyzes emotions from user input data and uses it to prioritize agenda items and customize information.

[0314] Data processing and calculations

[0315] 1. The user enters the agenda item.

[0316] The user enters the topic they want to discuss in the meeting into the interface's text box. For example, they might enter "Market trends in the IT industry in 2024."

[0317] 2. The terminal sends the agenda to the server.

[0318] The terminal converts the agenda entered by the user into JSON format and sends it to the server as an HTTPS request.

[0319] 3. The server creates and sends a query to the generated AI.

[0320] The server analyzes the agenda received from the terminal and creates a query for the generating AI. For example, it might generate a query in the format of, "Please provide the latest information on market trends in the IT industry in 2024."

[0321] 4. Generative AI collects information

[0322] The server sends queries to the generative AI, which then collects relevant information (text, statistical data, news articles, etc.) from the internet and internal databases.

[0323] 5. The server organizes and analyzes the information.

[0324] The server analyzes the information obtained from the generated AI and filters and summarizes it based on reliability, relevance, and importance. For example, it extracts important data points and statistical information.

[0325] 6. The server performs sentiment analysis.

[0326] The server's sentiment analysis engine analyzes user input data (for example, keyboard input speed and emphasized words) to understand the user's level of interest and emotions.

[0327] 7. The server adjusts the priority of the agenda items.

[0328] Based on the sentiment analysis results, the importance of each agenda item will be re-evaluated, and the order of information gathering and organization will be adjusted as needed.

[0329] 8. The server generates the report.

[0330] Based on the organized and analyzed information, a report is generated in a user-friendly format. This report includes summaries, graphs, statistical data, and reference links.

[0331] 9. The server sends the report to the user's terminal.

[0332] The completed report is sent from the server to the user's terminal. The report may be sent in JSON or PDF format, and may also include email and dashboard notifications.

[0333] 10. The user reviews the report.

[0334] Users review reports received on their devices and prepare for meetings focusing on topics of high interest. This improves meeting productivity.

[0335] Specific example

[0336] Example 1: Market Trends Agenda

[0337] User enters topic: The user enters the topic "Market trends in the IT industry in 2024".

[0338] The terminal sends the agenda to the server: The terminal converts this agenda into JSON format and sends it as an HTTPS request.

[0339] The server receives the agenda and creates a query for the generating AI: The server creates an appropriate query and sends it to the generating AI.

[0340] The server uses generative AI to gather information: Generative AI collects the latest reports, news articles, and statistical data on market trends.

[0341] Server-generated information organization and analysis: The server organizes the information, extracts important data, and creates a summary.

[0342] The server uses an emotion engine to recognize the user's emotions: The emotion engine analyzes the user's input to determine their emotions and assess their level of interest.

[0343] The server adjusts agenda priorities based on user sentiment: It adjusts the priority of important agenda items based on sentiment analysis results.

[0344] The server generates reports: Based on the organized and analyzed information, it creates detailed reports and presents information in a way that is sensitive to the user's emotions.

[0345] Send the server-generated report to the user's terminal: The report is sent to the user's terminal.

[0346] Users review the report: Users review the report and prepare for the meeting focusing on topics of high interest to them.

[0347] This system enables information gathering and organization that takes user emotions into consideration, further improving meeting productivity.

[0348] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0349] Step 1:

[0350] The user enters the topics they want to discuss in the meeting.

[0351] Input: The user enters a topic, such as "Market trends in the IT industry in 2024," into the interface's text box.

[0352] Output: The agenda text is obtained as user input.

[0353] Specific action: The user enters an agenda item into a text box and clicks the submit button.

[0354] Step 2:

[0355] The terminal sends the agenda to the server.

[0356] Input: The agenda text entered by the user in Step 1.

[0357] Output: The agenda text is sent to the server in JSON format.

[0358] Specific operation: The terminal converts the agenda into a JSON format like the one below and sends it to the server via an HTTPS request.

[0359] json

[0360] {

[0361] "Topic": "Market Trends in the IT Industry in 2024"

[0362] }

[0363] Step 3:

[0364] The server receives the agenda and creates a query for the generating AI.

[0365] Input: Agenda JSON data sent from the terminal.

[0366] Output: A query for the generating AI is created.

[0367] Specific operation: The server analyzes the agenda JSON data and creates a query for the generating AI: "Please provide the latest information on market trends in the IT industry in 2024."

[0368] Step 4:

[0369] The server uses generated AI to collect information.

[0370] Input: A query created for the generating AI.

[0371] Output: Relevant information collected by the generating AI (text, statistical data, news articles, etc.).

[0372] Specific operation: The server sends a query to the generating AI, which then collects information from the internet and internal databases.

[0373] Step 5:

[0374] The server organizes and analyzes the information it has collected.

[0375] Input: Relevant information returned by the generating AI.

[0376] Output: Organized and analyzed information.

[0377] Specific operation: The server filters information based on reliability, relevance, and importance, extracts key data points, and creates a summary.

[0378] Step 6:

[0379] The server uses an emotion analysis engine to recognize the user's emotions.

[0380] Input: User input data (e.g., input speed and emphasized words).

[0381] Output: User sentiment analysis results.

[0382] Specific operation: The server's sentiment analysis engine analyzes the highlighted parts and input speed of the entered text to understand the user's level of interest and emotions.

[0383] Step 7:

[0384] The server adjusts the priority of agenda items based on the user's sentiment.

[0385] Input: Sentiment analysis results and organized / analyzed information.

[0386] Output: Prioritized agenda items.

[0387] Specific operation: Based on the sentiment analysis results, the server resets the agenda priorities to display information of high interest.

[0388] Step 8:

[0389] The server generates the report.

[0390] Input: Organized and analyzed information, prioritizing agenda items.

[0391] Output: Generated report (summary, graphs, statistics, reference links, etc.).

[0392] Specific operation: The server generates customized reports and formats them in a user-friendly format.

[0393] Step 9:

[0394] The server sends the generated report to the user's terminal.

[0395] Input: Generated report.

[0396] Output: Report sent to the user's terminal.

[0397] Specific operation: The server generates a report in JSON or PDF format and sends it to the user's terminal via HTTPS.

[0398] Step 10:

[0399] The user reviews the report.

[0400] Input: Report sent from the server.

[0401] Output: Report contents confirmed by the user.

[0402] Specific action: The user downloads the report to their device and reviews its contents. The report includes customized information based on the user's sentiment analysis results, allowing the user to prepare for meetings efficiently.

[0403] (Application Example 2)

[0404] 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".

[0405] When proposing improvements to factory production lines, there is a need to effectively and quickly gather problem identifications and new ideas, and then organize and analyze the information based on them. However, with conventional methods, it was difficult to select appropriate data from a vast amount of information and to prioritize it in a way that reflected the intentions and feelings of managers. Furthermore, the process of generating reports based on the collected information and providing them to managers was cumbersome, hindering rapid decision-making for productivity improvement.

[0406] 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.

[0407] In this invention, the server includes means for the user to input an agenda item for a production line they wish to improve; means for transmitting the agenda item to the server; means for the server to collect information related to the agenda item using a generated AI; means for the server to organize and analyze the collected information; means for the server to recognize the user's emotions using an emotion engine; means for the server to adjust the priority of the agenda item based on the user's emotions recognized by the server; means for the server to generate a report from the organized and analyzed information; means for the server to transmit the report generated by the server to the user's terminal; and means for the user to review the report. This enables the administrator to automatically prioritize improvement measures of interest and to provide efficiently customized information in a short amount of time.

[0408] Creating a definition

[0409] A "user" is a person or organization that uses the system to input production line agendas and review reports.

[0410] A "topic" refers to the content of a discussion that outlines areas for improvement or new ideas for the factory's production line.

[0411] A "server" is a computer system that receives agenda items, collects, organizes, and analyzes information using a generation AI and emotion engine, and generates reports.

[0412] "Generative AI" is artificial intelligence that collects information from the internet or internal databases and analyzes that information.

[0413] "Information gathering" refers to the process by which the generating AI obtains data related to the topic from the internet or an internal database.

[0414] "Information organization" involves categorizing collected information and rearranging the data based on its relevance and reliability.

[0415] "Information analysis" is the process of extracting important data points based on organized information and generating statistical data and graphs.

[0416] An "emotion engine" is software that analyzes emotions from user input data and evaluates the importance and urgency of agenda items.

[0417] "Emotion recognition" is the process by which an emotion engine determines the level of interest and urgency of a user's input data.

[0418] "Priority adjustment" refers to changing the priority of information gathering and data organization based on the importance and urgency of the agenda items, using the results of the emotion engine's analysis.

[0419] "Report generation" refers to creating a report that includes summaries, graphs, and statistical data based on organized and analyzed information.

[0420] A "report" is a generated document containing information that users refer to when considering improvements to the production line.

[0421] A "terminal" refers to a device (such as a smartphone, tablet, or computer) that a user uses to input agenda items and review reports.

[0422] This invention is a system for streamlining factory production line improvements. The user inputs the topics they wish to improve, and based on those topics, a generative AI is used to collect, organize, and analyze information to generate a report. Furthermore, an emotion engine is used to recognize the user's emotions and adjust the prioritization of topics, providing a customized report.

[0423] User-submitted agenda items

[0424] Users input topics related to production line improvements into the terminal interface. This is done in text box format and includes examples such as "improving production line efficiency" and "cost reduction methods."

[0425] Sending the agenda to the server

[0426] The terminal converts the agenda entered by the user into JSON format and sends it to the server as an HTTPS request. This process ensures that data related to the agenda is transferred securely.

[0427] Information gathering by generating AI

[0428] The server analyzes the received agenda and generates queries for the generative AI. For example, a prompt such as "Please provide the latest information on improving production line efficiency" might be used. The generative AI collects relevant information from the internet and internal databases. The generative AI model used is GPT-4® or a similar generative model.

[0429] Information organization and analysis

[0430] The server analyzes and organizes the collected information. The data is filtered based on reliability and relevance, and organized into summaries, graphs, and statistical data. For example, data on the latest efficiency technologies and success stories are prioritized.

[0431] Emotion recognition by an emotion engine

[0432] The server uses an emotion engine to recognize emotions from user input data. For example, it analyzes emotions based on the emphasis and typing speed of the words the user enters, and adjusts the priority of topics accordingly. Software used for this process includes libraries such as the EmotionAnalyzer library.

[0433] Priority adjustment

[0434] Based on the analysis results from the emotion engine, the server automatically adjusts the priority of agenda items. Topics of high interest and urgent issues are given priority.

[0435] Report generation and submission

[0436] The server generates a report based on the organized and analyzed information, providing it to the user in the most useful format. This report includes summaries, graphs, and statistical data, and is sent to the user's device in PDF or JSON format.

[0437] User-confirmed report

[0438] Users review reports generated on their terminals. Based on the customized information, they can quickly consider ways to improve the production line.

[0439] Specific example

[0440] For example, if you input a prompt like, "Please provide the latest information on optimizing production lines," into the AI ​​generator, it will collect data on the latest efficiency technologies and success stories. Furthermore, if a manager expresses a strong interest in "efficiency" or "cost reduction," that topic will be prioritized, and more detailed information will be provided.

[0441] In this way, the system for implementing the invention supports the rapid and efficient proposal of improvements to factory production lines.

[0442] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0443] System program processing flow

[0444] Step 1:

[0445] The user inputs the production line improvement topics they want to address into the terminal's interface.

[0446] Input: Production line agenda (e.g., "Improving production line efficiency")

[0447] Output: User input data

[0448] Specific action: The user uses the application for factory administrators to enter the agenda item into a text box.

[0449] Step 2:

[0450] The terminal converts the agenda entered by the user into JSON format and sends it to the server using an HTTPS request.

[0451] Input: User input data

[0452] Output: Agenda data in JSON format

[0453] Specific operation: The client-side program converts the text data into JSON format and sends it to the server using the HTTPS protocol.

[0454] Step 3:

[0455] The server analyzes the received agenda data and generates queries for the AI.

[0456] Input: Agenda data in JSON format

[0457] Output: Prompt text for the generated AI (Example: "Please provide the latest information on optimizing production lines.")

[0458] Specific operation: The server uses a programming language such as Python to analyze the received data and generate prompt messages.

[0459] Step 4:

[0460] The server uses generated AI to collect information related to the agenda.

[0461] Input: Prompt message

[0462] Output: Collected information (e.g., latest production technologies, best practices, statistical data, etc.)

[0463] Specific operation: The server uses a generated AI model (e.g., GPT-4) to collect relevant information from the internet or an internal database.

[0464] Step 5:

[0465] The server organizes and analyzes the information it has collected.

[0466] Input: Collected information

[0467] Output: Organized and analyzed data (e.g., in the form of summaries, graphs, and statistical data)

[0468] Specific actions: Categorize collected information, sort data based on relevance and reliability, and create summaries and graphs.

[0469] Step 6:

[0470] The server uses an emotion engine to recognize the user's emotions.

[0471] Input: User input data, collected information

[0472] Output: Sentiment analysis results (e.g., evaluation of level of interest and urgency)

[0473] Specific operation: The server uses the EmotionAnalyzer library to analyze emotions from the user's input data.

[0474] Step 7:

[0475] The server adjusts agenda priorities based on the user's perceived emotions.

[0476] Input: Sentiment analysis results, organized information

[0477] Output: Adjusted and prioritized data

[0478] Specific operation: The server automatically readjusts the priority of relevant information based on the output of the emotion engine.

[0479] Step 8:

[0480] The server generates reports based on the organized and analyzed information, providing it to users in a useful format.

[0481] Input: Adjusted, prioritized data

[0482] Output: Generated report (e.g., PDF or JSON format including summary, graphs, and statistical data)

[0483] Specific actions: Use the report generation tool to format the data into a report format and create a file.

[0484] Step 9:

[0485] The server sends the generated report to the user's terminal.

[0486] Input: Report file

[0487] Output: Report sent to the user's terminal

[0488] Specific operation: The server uses a file transfer protocol (e.g., email, dashboard notification) to send the generated report to the user's device.

[0489] Step 10:

[0490] Users review reports generated on their devices and consider ways to improve the production line.

[0491] Input: Report file

[0492] Output: Review results, improvement measures

[0493] Specific actions: The user opens the submitted report, reviews its contents, and develops improvement measures for the production line.

[0494] 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.

[0495] 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.

[0496] 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.

[0497] [Second Embodiment]

[0498] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0499] 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.

[0500] 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).

[0501] 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.

[0502] 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.

[0503] 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).

[0504] 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.

[0505] 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.

[0506] 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.

[0507] 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.

[0508] 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.

[0509] 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".

[0510] This invention is a system in which a user inputs the topics they wish to discuss in a meeting, and the system collects and organizes the necessary information based on that input and provides it as a report. This enables meetings to be conducted efficiently and productively. Embodiments of this invention are described in detail below.

[0511] Explanation of the program's processing

[0512] User enters agenda item

[0513] Users enter topics they want to discuss during the meeting, such as market trends, new ideas, or challenges, into the interface's text boxes. For example, they might set a specific topic like "Market trends in the IT industry in 2024."

[0514] The terminal sends the agenda to the server.

[0515] The terminal converts the agenda entered by the user into a data format (e.g., JSON format) and sends it to the server using an HTTPS request. The communication is encrypted and secure.

[0516] The server receives the agenda and creates a query for the generating AI.

[0517] The server receives the agenda sent from the terminal and analyzes it. Next, it creates a query for the generating AI based on this agenda. For example, it might set a query in the format of, "Please provide the latest information on market trends in the IT industry in 2024."

[0518] The server uses generated AI to collect information.

[0519] The server sends the generated query to a generating AI (e.g., GPT-3) to collect relevant information. The generating AI retrieves the necessary information (text, data, news articles, statistics, etc.) from the internet or internal databases.

[0520] The server organizes and analyzes the information it has collected.

[0521] The server receives and analyzes the information returned by the generating AI. Here, the information is filtered and summarized based on criteria such as reliability, relevance, and importance. For example, statistical data may be extracted and graphed, or key points may be listed in bullet points.

[0522] The server generates the report.

[0523] Based on the organized and analyzed information, the server generates a user-friendly report. This report includes summaries, graphs, statistics, and reference links.

[0524] The server sends the generated report to the user's terminal.

[0525] Once a report is generated, the server sends it to the user's device. The report is sent in a digital format such as JSON or PDF, and notifications are sent via email or on the dashboard as needed.

[0526] The user reviews the report.

[0527] Users review the reports they receive on their devices. They then examine the report's contents and use it as material for discussion during meetings. This allows users to prepare thoroughly in advance and effectively consider data and opinions during meetings.

[0528] Specific example

[0529] Example 1: Market Trends Agenda

[0530] User enters topic: The user enters the topic "Market trends in the IT industry in 2024".

[0531] Terminal sends agenda to server: The terminal sends this agenda to the server.

[0532] The server receives the agenda and creates a query for the generating AI: The server creates an appropriate query and sends it to the generating AI.

[0533] The server uses generative AI to gather information: Generative AI collects the latest reports, news articles, and statistical data on market trends.

[0534] Server-generated information organization and analysis: The server organizes the information, extracts important data, and creates a summary.

[0535] The server generates the report: It creates a detailed report based on the organized and analyzed information.

[0536] Send the server-generated report to the user's terminal: The report is sent to the user's terminal.

[0537] User reviews report: The user reviews the report and completes preparations for the meeting.

[0538] This invention enables efficient use of time during meetings by gathering and organizing sufficient information before the meeting, facilitating high-quality discussions and rapid decision-making.

[0539] The following describes the processing flow.

[0540] Step 1:

[0541] User enters agenda item

[0542] Users enter topics they want to discuss in the meeting, such as market trends, new ideas, or challenges, into the interface's text boxes. For example, they might enter "Market trends in the IT industry in 2024."

[0543] Step 2:

[0544] The terminal sends the agenda to the server.

[0545] The terminal converts the agenda entered by the user into an appropriate data format (e.g., JSON) and sends it to the server as an HTTPS request. This communication is encrypted and secure.

[0546] Step 3:

[0547] The server receives the agenda and creates a query for the generating AI.

[0548] The server analyzes the agenda received from the terminal and creates a query for the generating AI. For example, it might prepare a query in the format, "Please provide the latest information on market trends in the IT industry in 2024."

[0549] Step 4:

[0550] The server uses generated AI to collect information.

[0551] The server sends the generated query to the generative AI and collects the relevant information. The generative AI automatically retrieves text, statistical data, news articles, and other information from the internet and internal databases.

[0552] Step 5:

[0553] The server organizes and analyzes the information it has collected.

[0554] The server receives the information returned by the generating AI and organizes and analyzes it based on reliability, relevance, and importance. It filters out unnecessary parts of the data and extracts important data points.

[0555] Step 6:

[0556] The server generates the report.

[0557] The server generates a report based on the organized and analyzed information. This report includes summaries, graphs, statistical data, and reference links, and is provided in a format that is easy for the user to understand.

[0558] Step 7:

[0559] The server sends the generated report to the user's terminal.

[0560] The server converts the generated report into JSON or PDF format and sends it to the user's device. Delivery methods include email and dashboard notifications.

[0561] Step 8:

[0562] The user reviews the report.

[0563] Users review the reports they receive on their devices. They then examine the report's contents and use it as material for discussion during meetings. This allows users to prepare thoroughly in advance and effectively consider data and opinions during the meeting.

[0564] (Example 1)

[0565] 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."

[0566] In modern meetings, a major challenge is the need for a vast amount of information, requiring significant time and effort to collect and organize it beforehand. In particular, a lack of rapid and accurate information gathering can reduce meeting productivity and hinder effective decision-making. Furthermore, given the sheer volume of information, there is a need to efficiently organize and present the necessary information clearly.

[0567] 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.

[0568] In this invention, the server includes means for the user to input an agenda item they wish to discuss in a meeting; means for the terminal to send the agenda item to the server; means for the server to create a query for a generating AI based on the agenda item; means for collecting information related to the agenda item using the generating AI; means for organizing and analyzing the collected information; means for generating the organized and analyzed information as a report; means for sending the generated report to the user's terminal; and means for the user to review the report. This enables the user to efficiently and automatically collect and organize the necessary information and receive it in an easy-to-understand report.

[0569] A "user" is the entity that uses the system to input the topics they want to discuss in a meeting.

[0570] "Agenda items" refer to the themes or topics discussed in a meeting, and are text information entered by the user.

[0571] A "terminal" refers to a device used by a user to input agenda items and send them to the server, and includes, for example, personal computers and smartphones.

[0572] A "server" is a central computer system that receives agenda items submitted by users and uses generating AI to collect, organize, and analyze information.

[0573] "Generative AI" refers to artificial intelligence technology that uses natural language processing techniques to automatically acquire relevant information related to a user's topic.

[0574] A "query" refers to a question created by a server to request information gathering from a generating AI, and is often in natural language format.

[0575] "Information gathering" refers to the process by which a generating AI acquires necessary data from information sources such as the internet and internal databases.

[0576] "Organization and analysis" is the process of evaluating collected information based on its reliability and relevance, selecting the necessary data, and processing it into an easily understandable format.

[0577] A "report" refers to a document that integrates organized and analyzed information and provides it to the user, including summaries, graphs, and statistical information.

[0578] "Transmission" refers to the data transfer process that delivers reports generated by the server to the user's terminal.

[0579] "Verification" refers to the act of carefully examining the contents of reports received by users on their devices and using them as material for meeting preparations and discussions.

[0580] This invention is a system in which a user inputs the topics they wish to discuss in a meeting, and based on that input, the system collects and organizes the necessary information and provides it as a report. This enables meetings to be conducted efficiently and productively. Embodiments of this invention are described in detail below.

[0581] Users access a dedicated interface to input topics. For example, they might use a browser to access the system's website, enter "Market Trends in the IT Industry in 2024" into a text box, and click the "Submit" button. This input interface is built using HTML and JavaScript.

[0582] The terminal first retrieves the agenda entered in the text box and converts it to JSON format. After conversion, it creates an HTTPS POST request and sends it to a specific API endpoint on the server. The communication is encrypted using SSL / TLS, ensuring security. The terminal's communication processing uses libraries such as Python's requests library or JavaScript's fetch API.

[0583] The server receives and analyzes the agenda sent from the terminal. Based on the received agenda, "Market Trends in the IT Industry in 2024," it generates a natural language query. For example, it might create a query such as, "Please provide the latest information on market trends in the IT industry in 2024." An automated natural language processing algorithm is useful for this query generation.

[0584] Next, the server sends the generated query to a generating AI (e.g., GPT-3). The generating AI then collects the necessary information from the internet or internal databases based on the query. For example, it might collect the latest news articles, statistical data, reports, etc.

[0585] The server receives and analyzes the information returned by the generated AI. The information is filtered and summarized based on criteria such as reliability, relevance, and importance. For example, statistical data may be extracted and graphed, or key points may be listed in bullet points. Tools such as Python's pandas library and matplotlib are used for organizing and analyzing this information.

[0586] Based on the organized and analyzed information, the server generates a user-friendly report. This report includes summaries, graphs, statistical data, and reference links. HTML template engines (e.g., Jinja2) and PDF generation libraries (e.g., ReportLab) are used to generate the report.

[0587] The generated report is converted back into JSON or PDF format and sent to the user's device using an HTTPS POST request. After sending, the user receives an email notification or a notification on the dashboard. For email notifications, the SMTP protocol is used, for example.

[0588] Users review the reports received on their devices. They examine the reports displayed in their browsers and scrutinize their contents. If necessary, they can print or download the reports for offline viewing. This allows them to adequately prepare for meetings.

[0589] <Specific example>

[0590] The user enters and submits the topic "Market Trends in the IT Industry in 2024." After being sent from the terminal to the server, the server sends a query to the generating AI asking, "Please provide the latest information on market trends in the IT industry in 2024." The generating AI collects the latest relevant reports and statistical data, and the server analyzes and organizes it to generate a report. This report is sent to the user's terminal, and the user uses it to prepare for the meeting.

[0591] This invention enables users to efficiently and automatically collect and organize necessary information and receive it as an easy-to-understand report.

[0592] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0593] Program processing flow

[0594] Step 1: The user enters the agenda.

[0595] The user accesses the system's website using a browser. They enter a topic into the text box. For example, they might enter the text "Market Trends in the IT Industry in 2024" and click the "Submit" button.

[0596] Input: The user enters text as the agenda item.

[0597] Output: After clicking the send button, the agenda will be received on the device.

[0598] Step 2: The terminal sends the agenda to the server.

[0599] The terminal retrieves the agenda entered in the text box and converts it to JSON format. It then sends the converted data to the server via an HTTPS POST request. This request is secure because it is encrypted using SSL / TLS.

[0600] Input: Agenda text entered by the user

[0601] Output: The agenda, converted to JSON format, is sent to the server.

[0602] Step 3: The server receives the agenda and creates a query for the generating AI.

[0603] The server receives the agenda sent from the terminal. Next, it analyzes the received agenda and generates a query for the generating AI. For example, it might generate a query such as, "Please provide the latest information on market trends in the IT industry in 2024."

[0604] Input: Agenda data in JSON format

[0605] Output: Natural language queries to send to the generating AI

[0606] Step 4: The server uses generated AI to collect information.

[0607] The server sends the generated queries to a generating AI (e.g., GPT-3). The generating AI collects relevant information from external and internal sources. This process gathers the latest news articles, statistics, reports, and so on.

[0608] Input: Natural language query

[0609] Output: Related information returned by the generating AI

[0610] Step 5: Organize and analyze the information collected by the server.

[0611] The server receives information returned by the generating AI and filters it based on reliability and relevance. It then summarizes the information and performs organization and analysis, such as graphing statistical data. For example, it might utilize Python libraries like pandas or matplotlib.

[0612] Input: Information returned by the generating AI

[0613] Output: Organized and analyzed information (summary, graphs, statistical data)

[0614] Step 6: The server generates the report.

[0615] The server generates user reports based on the organized and analyzed information. These reports include summaries, graphs, statistics, and reference links. For example, they can be visually formatted using an HTML template engine.

[0616] Input: Organized and analyzed information

[0617] Output: Completed report (HTML or PDF format)

[0618] Step 7: Send the report generated by the server to the user's terminal.

[0619] The server converts the generated report into an appropriate format (e.g., JSON or PDF) and sends it to the user's device using an HTTPS POST request. Email notifications and dashboard notifications are also provided as needed.

[0620] Input: Completed report

[0621] Output: Report sent to the user's device

[0622] Step 8: User reviews the report

[0623] Users open the received report on their device and review its contents. They can view the report in a browser and examine the data and statistics. If necessary, they can also print or download the report for offline viewing.

[0624] Input: Report sent from the server

[0625] Output: Confirmed report contents (review, print, download)

[0626] The above outlines the specific processing steps of the system. The details of the specific actions performed at each step, along with the associated inputs and outputs, have been described.

[0627] (Application Example 1)

[0628] 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."

[0629] Traditional meeting preparation systems required significant time and effort to gather and organize information for discussion, and lacked concrete tools for virtual store operators to efficiently consider new product lines and market trends. Furthermore, the tools for immediately utilizing the collected information were insufficient, compromising the quality and efficiency of meetings.

[0630] 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.

[0631] In this invention, the server includes means for the virtual store operator to input meeting agendas, means for transmitting agendas entered from a smart device to the server, means for creating and sending queries to a generating AI, means for collecting market research reports, customer reviews, and sales data using the generating AI, means for analyzing the collected data, extracting key points and graphing them, means for creating a detailed report, means for transmitting the generated report to a smart device, and means for reviewing the report. This enables the virtual store operator to prepare meeting materials efficiently and quickly, and to effectively consider data and opinions during the meeting.

[0632] A "user" is the final user who uses the system to input meeting agenda items and review reports.

[0633] A "server" is a central control unit that receives agenda items submitted by users, collects, organizes, and analyzes information using generation AI, generates reports, and sends them to the user's terminal.

[0634] "Generative AI" is artificial intelligence that collects relevant information from the internet or internal databases based on an input query and then analyzes it.

[0635] An "agenda" is a specific theme or topic that users want to discuss in a meeting.

[0636] A "smart device" is an advanced device such as glasses or head-mounted displays that can connect to the internet.

[0637] A "query" is a question or command created by a server to prompt a generating AI to collect information.

[0638] A "market research report" is a document that summarizes the detailed results of a survey on market trends, competitive situations, and other related matters.

[0639] "Customer reviews" are records of customer evaluations and opinions about products and services.

[0640] "Sales data" refers to information regarding the quantity and amount of sales of products over a specific period.

[0641] "Data analysis" is the process of organizing collected information using statistical methods and other techniques to present it in a meaningful form.

[0642] "Key points" refer to particularly important information or indicators within the analyzed data.

[0643] "Graphing" is the process of representing data using shapes to make it easier to understand visually.

[0644] A "report" is a detailed report created based on collected and analyzed information.

[0645] A "meeting" is a gathering of stakeholders to discuss a specific topic and reach a consensus.

[0646] This invention is a system in which a user inputs the topics they wish to discuss in a meeting, and based on that input, the system collects, organizes, and analyzes the necessary information and provides it as a report. A specific embodiment of this system is described below.

[0647] System Configuration

[0648] Hardware:

[0649] Smart glasses (e.g., typical smart glasses)

[0650] Head-mounted display (e.g., typical HMD)

[0651] software:

[0652] Frontend: React Native

[0653] Backend: Node.js, Express.js

[0654] Data analysis: Python, Pandas, Matplotlib

[0655] Generation AI: GPT-3 (OpenAI API)

[0656] Frontend operation

[0657] Users enter meeting agenda items using smart glasses or head-mounted displays. The agenda items are entered into text boxes, and the data is sent to the server in JSON format. An example of an agenda item a user might enter is "Market Trends in the IT Industry in 2024."

[0658] Data transmission

[0659] The terminal sends the agenda entered by the user to the server. During this process, the data is encrypted and transmitted using HTTPS communication. The server analyzes the received data and creates queries to send to the generating AI to collect the necessary information.

[0660] Information gathering

[0661] The server sends queries to the Generative AI (GPT-3) to collect relevant information. An example query is, "Please provide the latest information on market trends in the IT industry in 2024." The Generative AI retrieves the necessary information from the internet and internal databases. This collected information includes market research reports, customer reviews, and sales data.

[0662] Data Analysis

[0663] The server analyzes the information returned by the generating AI. It filters the information based on criteria such as reliability, relevance, and importance, and extracts summarized and graphed statistical information.

[0664] Report generation

[0665] Based on the analyzed information, the server generates a report in a user-friendly format. The report includes a summary, graphs, statistical data, and reference links.

[0666] Send Report

[0667] The completed report is sent to the user's smart glasses or head-mounted display. The user can then review it and prepare for the meeting.

[0668] Specific example

[0669] Case Study 1: Considering the introduction of a new product line

[0670] The user enters the topic "Effects of introducing a new product line."

[0671] Agenda items entered from smart devices are sent to the server.

[0672] The server sends a query to the generating AI asking, "Please provide information about the effectiveness of introducing the new product."

[0673] The generation AI collects market research reports, customer reviews, sales data, and more.

[0674] The server analyzes the collected data, extracts key points, and graphs them.

[0675] A detailed report is created and sent to your smart device.

[0676] Users review the report and prepare for discussions in the meeting.

[0677] An example of a prompt message would be something like, "Please provide me with the latest information on market trends in the IT industry in 2024."

[0678] This invention enables virtual store operators to efficiently and quickly prepare meeting materials and to effectively review data and opinions during meetings.

[0679] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0680] Step 1:

[0681] The user enters an agenda item into a text box using smart glasses or a head-mounted display. The entered agenda item is in text format, and a specific example of input would be "Market trends in the IT industry in 2024." This text data is sent to the server in the next step.

[0682] Step 2:

[0683] The terminal converts the agenda entered by the user into JSON format and sends it to the server using HTTPS. This ensures that the agenda data is securely communicated to the server. The input is an agenda in text format, and the output is data in JSON format.

[0684] Step 3:

[0685] The server analyzes the received agenda and creates queries for the generating AI. Specifically, it generates queries such as "Please provide the latest information on market trends in the IT industry in 2024" based on the received text data. The input is agenda data in JSON format, and the output is query text to be sent to the generating AI.

[0686] Step 4:

[0687] The server generates queries and sends them to a generative AI like GPT-3 to collect relevant information. The generative AI retrieves market research reports, customer reviews, sales data, etc., by referencing the internet and internal databases. The input is the query text, and the output is the collected relevant information.

[0688] Step 5:

[0689] The server organizes and analyzes the information returned by the generating AI. Specifically, it filters the information based on criteria such as reliability, relevance, and importance, and extracts summaries and statistical data. For example, it uses Python's Pandas and Matplotlib to graph sales data. The input is relevant information from the generating AI, and the output is filtered and summarized information and graph data.

[0690] Step 6:

[0691] The server generates a report based on the information it organizes and analyzes. The report includes a summary, graphs, statistics, and reference links. The generated report is saved in PDF or HTML format. The input is the organized and analyzed information, and the output is the report provided to the user.

[0692] Step 7:

[0693] The server generates a report and sends it to the smart device. Once the report is generated, the server sends it to the user's device in JSON or PDF format. The input is the generated report, and the output is a report viewable on the user's smart device.

[0694] Step 8:

[0695] Users view reports using smart glasses or head-mounted displays. By viewing the reports, users can prepare discussion materials for meetings. The input is the report on the smart device, and the output is the meeting materials the user receives.

[0696] 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.

[0697] This invention is a system in which a user inputs the topics they wish to discuss in a meeting, and based on that input, the system collects and organizes the necessary information and provides it as a report. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it enables prioritization of topics and customization of reports. The configuration for implementing this system is described in detail below.

[0698] Explanation of the program's processing

[0699] User enters agenda item

[0700] Users enter topics they want to discuss in the meeting, such as market trends, new ideas, or challenges, into the interface's text boxes. For example, they might enter "Market trends in the IT industry in 2024."

[0701] The terminal sends the agenda to the server.

[0702] The terminal converts the agenda entered by the user into an appropriate data format (e.g., JSON) and sends it to the server as an HTTPS request. This communication is encrypted and secure.

[0703] The server receives the agenda and creates a query for the generating AI.

[0704] The server analyzes the agenda received from the terminal and creates a query for the generating AI. For example, it might prepare a query in the format, "Please provide the latest information on market trends in the IT industry in 2024."

[0705] The server uses generated AI to collect information.

[0706] The server sends the generated query to the generative AI and collects the relevant information. The generative AI automatically retrieves text, statistical data, news articles, and other information from the internet and internal databases.

[0707] The server organizes and analyzes the information it has collected.

[0708] The server receives the information returned by the generating AI and organizes and analyzes it based on reliability, relevance, and importance. It filters out unnecessary parts of the data and extracts important data points.

[0709] The server uses an emotion engine to recognize the user's emotions.

[0710] The emotion engine analyzes the user's emotions from user input data (e.g., keyboard typing speed and emphasized words). For example, it pays particular attention to areas where the user has a strong interest or concern.

[0711] The server adjusts agenda priorities based on user sentiment.

[0712] The server adjusts the priority of agenda items based on the sentiment analysis results from the sentiment engine. It prioritizes information gathering and organization for agenda items of high interest or urgent issues.

[0713] The server generates the report.

[0714] Based on the organized and analyzed information, the server generates a user-friendly report. This report includes summaries, graphs, statistics, and reference links, and the presentation of information is customized to suit the user's perspective.

[0715] The server sends the generated report to the user's terminal.

[0716] Once a report is generated, the server sends it to the user's device. The transmission format can be digital, such as JSON or PDF, and may also include email or dashboard notifications.

[0717] The user reviews the report.

[0718] Users review reports received on their devices. They prepare for meetings based on agendas prioritized by the emotion engine and customized information. This allows users to be well-prepared in advance and efficiently review data and opinions during meetings.

[0719] Specific example

[0720] Example 1: Market Trends Agenda

[0721] User enters topic: The user enters the topic "Market trends in the IT industry in 2024".

[0722] Terminal sends agenda to server: The terminal sends this agenda to the server.

[0723] The server receives the agenda and creates a query for the generating AI: The server creates an appropriate query and sends it to the generating AI.

[0724] The server uses generative AI to gather information: Generative AI collects the latest reports, news articles, and statistical data on market trends.

[0725] Server-generated information organization and analysis: The server organizes the information, extracts important data, and creates a summary.

[0726] The server uses an emotion engine to recognize the user's emotions: The emotion engine analyzes the user's input to determine their emotions and assess their level of interest.

[0727] The server adjusts agenda priorities based on user sentiment: It adjusts the priority of important agenda items based on sentiment analysis results.

[0728] The server generates reports: Based on the organized and analyzed information, it creates detailed reports and presents information in a way that is sensitive to the user's emotions.

[0729] Send the server-generated report to the user's terminal: The report is sent to the user's terminal.

[0730] Users review the report: Users review the report and prepare for the meeting focusing on topics of high interest to them.

[0731] This system enables information gathering and organization that takes user emotions into consideration, further improving meeting productivity.

[0732] The following describes the processing flow.

[0733] Step 1:

[0734] User enters agenda item

[0735] Users enter topics they want to discuss in the meeting, such as market trends, new ideas, or challenges, into the interface's text box. For example, they might enter "Market trends in the IT industry in 2024."

[0736] Step 2:

[0737] The terminal sends the agenda to the server.

[0738] The terminal converts the agenda entered by the user into JSON format and sends it to the server as an HTTPS request. The communication is encrypted and takes place in a secure environment.

[0739] Step 3:

[0740] The server receives the agenda and creates a query for the generating AI.

[0741] The server analyzes the agenda received from the terminal and generates appropriate queries for the AI. For example, it might create a query in the format of, "Please provide the latest information on market trends in the IT industry in 2024."

[0742] Step 4:

[0743] The server uses generated AI to collect information.

[0744] The server sends queries to the generative AI to collect relevant information. The generative AI retrieves text, statistics, news articles, reports, and other data from the internet and internal databases.

[0745] Step 5:

[0746] The server organizes and analyzes the information it has collected.

[0747] The server receives the information returned by the generating AI and organizes and analyzes it based on reliability, relevance, and importance. If there is too much information, it filters out unnecessary data and extracts the important information.

[0748] Step 6:

[0749] The server uses an emotion engine to recognize the user's emotions.

[0750] The emotion engine analyzes user input data and user activity history (e.g., typing speed and vocabulary selection) to infer the user's emotions. For example, it analyzes emotions based on keywords that the user emphasizes when typing.

[0751] Step 7:

[0752] The server adjusts agenda priorities based on user sentiment.

[0753] The server adjusts the priority of agenda items based on the sentiment analysis results obtained from the sentiment engine. Topics of high interest and urgent issues are prioritized for information gathering and organization.

[0754] Step 8:

[0755] The server generates the report.

[0756] The server generates a report based on the organized and analyzed information. This report includes summaries, graphs, statistics, and reference links. The way information is presented is customized to suit the user's emotions.

[0757] Step 9:

[0758] The server sends the generated report to the user's terminal.

[0759] The server sends the generated report to the user's device in JSON or PDF format. Delivery methods include email and dashboard notifications.

[0760] Step 10:

[0761] The user reviews the report.

[0762] Users review reports received on their devices. They then prepare for meetings based on agendas prioritized by the sentiment engine and customized information.

[0763] This system enables information gathering and organization that takes user emotions into consideration, further improving meeting productivity. For example, it allows for features such as placing topics of strong user interest at the beginning of a report and highlighting important information.

[0764] (Example 2)

[0765] 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".

[0766] Conventional meeting preparation systems lacked sufficient automation in gathering and organizing information for agenda items, requiring users to manually search for and compile necessary information. Furthermore, the lack of information customization based on user sentiment and interests hindered efficient meeting preparation. This invention aims to solve these problems by providing a system that automatically collects and organizes information based on user input and delivers reports that reflect user sentiment.

[0767] 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.

[0768] In this invention, the server includes means for collecting information related to the agenda using generative AI, means for organizing and analyzing the collected information, and means for analyzing the user's emotions using an emotion analysis engine. This allows the prioritization of agenda items to be adjusted based on the user's emotions, and enables the provision of customized reports to the user.

[0769] A "user" is defined as the entity that utilizes the present invention, and is the person who inputs agenda items and reviews reports.

[0770] A "terminal" is a device used by users to input agenda items or to receive and review reports sent from a server. Specifically, this includes personal computers, smartphones, and tablets.

[0771] A "server" is a computer system that processes data sent from users or terminals, and collects, organizes, analyzes, generates, and transmits information.

[0772] "Generative AI" refers to artificial intelligence technology that collects relevant information in response to user queries, and is used to retrieve information from the internet or internal databases.

[0773] An "emotion analysis engine" is a technology that analyzes emotions from user input data and extracts information about the user's level of interest and emotions.

[0774] An "agenda" refers to a topic or theme that a user wants to discuss in a meeting, and it is sent to the server through the input interface.

[0775] "Information gathering" is the process by which the generating AI retrieves relevant data from the internet or internal databases based on the user's queries.

[0776] "Information organization and analysis" is the process of filtering collected data based on reliability, relevance, and importance, and extracting key data points.

[0777] A "report" is a document or data generated in a user-friendly format based on organized and analyzed information, and may include summaries, graphs, statistical data, and reference links.

[0778] "Prioritizing" is the process of re-evaluating the importance of topics and information based on the results of the sentiment analysis engine, and changing the order in which they are collected and organized.

[0779] "JSON format" is an abbreviation for JavaScript Object Notation, and it is a format for representing data in a lightweight and compact manner.

[0780] "TLS" stands for Transport Layer Security, and it is a protocol used to encrypt and secure data communications over the internet.

[0781] This invention is a system in which a user inputs the topics they wish to discuss in a meeting, and based on that input, the system collects and organizes the necessary information and provides it as a report. By combining this invention with a sentiment analysis engine, the system enables prioritization of topics and customization of reports. A detailed embodiment of this system is described below.

[0782] Hardware and software to be used

[0783] User's device: This is the device on which the user enters agenda items and reviews reports. This includes personal computers, smartphones, and tablets.

[0784] Server: A computer system that receives, processes, and generates data, sends queries to AI, collects and analyzes information, performs sentiment analysis, and generates and sends reports.

[0785] Generative AI models: These are artificial intelligence technologies that collect relevant information based on user queries, and for example, large-scale language models (such as GPT-3) are used.

[0786] Sentiment analysis engine: This technology analyzes emotions from user input data and uses it to prioritize agenda items and customize information.

[0787] Data processing and calculations

[0788] 1. The user enters the agenda item.

[0789] The user enters the topic they want to discuss in the meeting into the interface's text box. For example, they might enter "Market trends in the IT industry in 2024."

[0790] 2. The terminal sends the agenda to the server.

[0791] The terminal converts the agenda entered by the user into JSON format and sends it to the server as an HTTPS request.

[0792] 3. The server creates and sends a query to the generated AI.

[0793] The server analyzes the agenda received from the terminal and creates a query for the generating AI. For example, it might generate a query in the format of, "Please provide the latest information on market trends in the IT industry in 2024."

[0794] 4. Generative AI collects information

[0795] The server sends queries to the generative AI, which then collects relevant information (text, statistical data, news articles, etc.) from the internet and internal databases.

[0796] 5. The server organizes and analyzes the information.

[0797] The server analyzes the information obtained from the generated AI and filters and summarizes it based on reliability, relevance, and importance. For example, it extracts important data points and statistical information.

[0798] 6. The server performs sentiment analysis.

[0799] The server's sentiment analysis engine analyzes user input data (for example, keyboard input speed and emphasized words) to understand the user's level of interest and emotions.

[0800] 7. The server adjusts the priority of the agenda items.

[0801] Based on the sentiment analysis results, the importance of each agenda item will be re-evaluated, and the order of information gathering and organization will be adjusted as needed.

[0802] 8. The server generates the report.

[0803] Based on the organized and analyzed information, a report is generated in a user-friendly format. This report includes summaries, graphs, statistical data, and reference links.

[0804] 9. The server sends the report to the user's terminal.

[0805] The completed report is sent from the server to the user's terminal. The report may be sent in JSON or PDF format, and may also include email and dashboard notifications.

[0806] 10. The user reviews the report.

[0807] Users review reports received on their devices and prepare for meetings focusing on topics of high interest. This improves meeting productivity.

[0808] Specific example

[0809] Example 1: Market Trends Agenda

[0810] User enters topic: The user enters the topic "Market trends in the IT industry in 2024".

[0811] The terminal sends the agenda to the server: The terminal converts this agenda into JSON format and sends it as an HTTPS request.

[0812] The server receives the agenda and creates a query for the generating AI: The server creates an appropriate query and sends it to the generating AI.

[0813] The server uses generative AI to gather information: Generative AI collects the latest reports, news articles, and statistical data on market trends.

[0814] Server-generated information organization and analysis: The server organizes the information, extracts important data, and creates a summary.

[0815] The server uses an emotion engine to recognize the user's emotions: The emotion engine analyzes the user's input to determine their emotions and assess their level of interest.

[0816] The server adjusts agenda priorities based on user sentiment: It adjusts the priority of important agenda items based on sentiment analysis results.

[0817] The server generates reports: Based on the organized and analyzed information, it creates detailed reports and presents information in a way that is sensitive to the user's emotions.

[0818] Send the server-generated report to the user's terminal: The report is sent to the user's terminal.

[0819] Users review the report: Users review the report and prepare for the meeting focusing on topics of high interest to them.

[0820] This system enables information gathering and organization that takes user emotions into consideration, further improving meeting productivity.

[0821] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0822] Step 1:

[0823] The user enters the topics they want to discuss in the meeting.

[0824] Input: The user enters a topic, such as "Market trends in the IT industry in 2024," into the interface's text box.

[0825] Output: The agenda text is obtained as user input.

[0826] Specific action: The user enters an agenda item into a text box and clicks the submit button.

[0827] Step 2:

[0828] The terminal sends the agenda to the server.

[0829] Input: The agenda text entered by the user in Step 1.

[0830] Output: The agenda text is sent to the server in JSON format.

[0831] Specific operation: The terminal converts the agenda into a JSON format like the one below and sends it to the server via an HTTPS request.

[0832] json

[0833] {

[0834] "Topic": "Market Trends in the IT Industry in 2024"

[0835] }

[0836] Step 3:

[0837] The server receives the agenda and creates a query for the generating AI.

[0838] Input: Agenda JSON data sent from the terminal.

[0839] Output: A query for the generating AI is created.

[0840] Specific operation: The server analyzes the agenda JSON data and creates a query for the generating AI: "Please provide the latest information on market trends in the IT industry in 2024."

[0841] Step 4:

[0842] The server uses generated AI to collect information.

[0843] Input: A query created for the generating AI.

[0844] Output: Relevant information collected by the generating AI (text, statistical data, news articles, etc.).

[0845] Specific operation: The server sends a query to the generating AI, which then collects information from the internet and internal databases.

[0846] Step 5:

[0847] The server organizes and analyzes the information it has collected.

[0848] Input: Relevant information returned by the generating AI.

[0849] Output: Organized and analyzed information.

[0850] Specific operation: The server filters information based on reliability, relevance, and importance, extracts key data points, and creates a summary.

[0851] Step 6:

[0852] The server uses an emotion analysis engine to recognize the user's emotions.

[0853] Input: User input data (e.g., input speed and emphasized words).

[0854] Output: User sentiment analysis results.

[0855] Specific operation: The server's sentiment analysis engine analyzes the highlighted parts and input speed of the entered text to understand the user's level of interest and emotions.

[0856] Step 7:

[0857] The server adjusts the priority of agenda items based on the user's sentiment.

[0858] Input: Sentiment analysis results and organized / analyzed information.

[0859] Output: Prioritized agenda items.

[0860] Specific operation: Based on the sentiment analysis results, the server resets the agenda priorities to display information of high interest.

[0861] Step 8:

[0862] The server generates the report.

[0863] Input: Organized and analyzed information, prioritizing agenda items.

[0864] Output: Generated report (summary, graphs, statistics, reference links, etc.).

[0865] Specific operation: The server generates customized reports and formats them in a user-friendly format.

[0866] Step 9:

[0867] The server sends the generated report to the user's terminal.

[0868] Input: Generated report.

[0869] Output: Report sent to the user's terminal.

[0870] Specific operation: The server generates a report in JSON or PDF format and sends it to the user's terminal via HTTPS.

[0871] Step 10:

[0872] The user reviews the report.

[0873] Input: Report sent from the server.

[0874] Output: Report contents confirmed by the user.

[0875] Specific action: The user downloads the report to their device and reviews its contents. The report includes customized information based on the user's sentiment analysis results, allowing the user to prepare for meetings efficiently.

[0876] (Application Example 2)

[0877] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0878] When proposing improvements to factory production lines, there is a need to effectively and quickly gather problem identifications and new ideas, and then organize and analyze the information based on them. However, with conventional methods, it was difficult to select appropriate data from a vast amount of information and to prioritize it in a way that reflected the intentions and feelings of managers. Furthermore, the process of generating reports based on the collected information and providing them to managers was cumbersome, hindering rapid decision-making for productivity improvement.

[0879] 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.

[0880] In this invention, the server includes means for the user to input an agenda item for a production line they wish to improve; means for transmitting the agenda item to the server; means for the server to collect information related to the agenda item using a generated AI; means for the server to organize and analyze the collected information; means for the server to recognize the user's emotions using an emotion engine; means for the server to adjust the priority of the agenda item based on the user's emotions recognized by the server; means for the server to generate a report from the organized and analyzed information; means for the server to transmit the report generated by the server to the user's terminal; and means for the user to review the report. This enables the administrator to automatically prioritize improvement measures of interest and to provide efficiently customized information in a short amount of time.

[0881] Creating a definition

[0882] A "user" is a person or organization that uses the system to input production line agendas and review reports.

[0883] A "topic" refers to the content of a discussion that outlines areas for improvement or new ideas for the factory's production line.

[0884] A "server" is a computer system that receives agenda items, collects, organizes, and analyzes information using a generation AI and emotion engine, and generates reports.

[0885] "Generative AI" is artificial intelligence that collects information from the internet or internal databases and analyzes that information.

[0886] "Information gathering" refers to the process by which the generating AI obtains data related to the topic from the internet or an internal database.

[0887] "Information organization" involves categorizing collected information and rearranging the data based on its relevance and reliability.

[0888] "Information analysis" is the process of extracting important data points based on organized information and generating statistical data and graphs.

[0889] An "emotion engine" is software that analyzes emotions from user input data and evaluates the importance and urgency of agenda items.

[0890] "Emotion recognition" is the process by which an emotion engine determines the level of interest and urgency of a user's input data.

[0891] "Priority adjustment" refers to changing the priority of information gathering and data organization based on the importance and urgency of the agenda items, using the results of the emotion engine's analysis.

[0892] "Report generation" refers to creating a report that includes summaries, graphs, and statistical data based on organized and analyzed information.

[0893] A "report" is a generated document containing information that users refer to when considering improvements to the production line.

[0894] A "terminal" refers to a device (such as a smartphone, tablet, or computer) that a user uses to input agenda items and review reports.

[0895] This invention is a system for streamlining factory production line improvements. The user inputs the topics they wish to improve, and based on those topics, a generative AI is used to collect, organize, and analyze information to generate a report. Furthermore, an emotion engine is used to recognize the user's emotions and adjust the prioritization of topics, providing a customized report.

[0896] User-submitted agenda items

[0897] Users input topics related to production line improvements into the terminal interface. This is done in text box format and includes examples such as "improving production line efficiency" and "cost reduction methods."

[0898] Sending the agenda to the server

[0899] The terminal converts the agenda entered by the user into JSON format and sends it to the server as an HTTPS request. This process ensures that data related to the agenda is transferred securely.

[0900] Information gathering by generating AI

[0901] The server analyzes the received agenda and generates queries for the generative AI. For example, a prompt such as "Please provide the latest information on optimizing production lines" might be used. The generative AI collects relevant information from the internet and internal databases. The generative AI model used is GPT-4 or a similar generative model.

[0902] Information organization and analysis

[0903] The server analyzes and organizes the collected information. The data is filtered based on reliability and relevance, and organized into summaries, graphs, and statistical data. For example, data on the latest efficiency technologies and success stories are prioritized.

[0904] Emotion recognition by an emotion engine

[0905] The server uses an emotion engine to recognize emotions from user input data. For example, it analyzes emotions based on the emphasis and typing speed of the words the user enters, and adjusts the priority of topics accordingly. Software used for this process includes libraries such as the EmotionAnalyzer library.

[0906] Priority adjustment

[0907] Based on the analysis results from the emotion engine, the server automatically adjusts the priority of agenda items. Topics of high interest and urgent issues are given priority.

[0908] Report generation and submission

[0909] The server generates a report based on the organized and analyzed information, providing it to the user in the most useful format. This report includes summaries, graphs, and statistical data, and is sent to the user's device in PDF or JSON format.

[0910] User-confirmed report

[0911] Users review reports generated on their terminals. Based on the customized information, they can quickly consider ways to improve the production line.

[0912] Specific example

[0913] For example, if you input a prompt like, "Please provide the latest information on optimizing production lines," into the AI ​​generator, it will collect data on the latest efficiency technologies and success stories. Furthermore, if a manager expresses a strong interest in "efficiency" or "cost reduction," that topic will be prioritized, and more detailed information will be provided.

[0914] In this way, the system for implementing the invention supports the rapid and efficient proposal of improvements to factory production lines.

[0915] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0916] System program processing flow

[0917] Step 1:

[0918] The user inputs the production line improvement topics they want to address into the terminal's interface.

[0919] Input: Production line agenda (e.g., "Improving production line efficiency")

[0920] Output: User input data

[0921] Specific action: The user uses the application for factory administrators to enter the agenda item into a text box.

[0922] Step 2:

[0923] The terminal converts the agenda entered by the user into JSON format and sends it to the server using an HTTPS request.

[0924] Input: User input data

[0925] Output: Agenda data in JSON format

[0926] Specific operation: The client-side program converts the text data into JSON format and sends it to the server using the HTTPS protocol.

[0927] Step 3:

[0928] The server analyzes the received agenda data and generates queries for the AI.

[0929] Input: Agenda data in JSON format

[0930] Output: Prompt text for the generated AI (Example: "Please provide the latest information on optimizing production lines.")

[0931] Specific operation: The server uses a programming language such as Python to analyze the received data and generate prompt messages.

[0932] Step 4:

[0933] The server uses generated AI to collect information related to the agenda.

[0934] Input: Prompt message

[0935] Output: Collected information (e.g., latest production technologies, best practices, statistical data, etc.)

[0936] Specific operation: The server uses a generated AI model (e.g., GPT-4) to collect relevant information from the internet or an internal database.

[0937] Step 5:

[0938] The server organizes and analyzes the information it has collected.

[0939] Input: Collected information

[0940] Output: Organized and analyzed data (e.g., in the form of summaries, graphs, and statistical data)

[0941] Specific actions: Categorize collected information, sort data based on relevance and reliability, and create summaries and graphs.

[0942] Step 6:

[0943] The server uses an emotion engine to recognize the user's emotions.

[0944] Input: User input data, collected information

[0945] Output: Sentiment analysis results (e.g., evaluation of level of interest and urgency)

[0946] Specific operation: The server uses the EmotionAnalyzer library to analyze emotions from the user's input data.

[0947] Step 7:

[0948] The server adjusts agenda priorities based on the user's perceived emotions.

[0949] Input: Sentiment analysis results, organized information

[0950] Output: Adjusted and prioritized data

[0951] Specific operation: The server automatically readjusts the priority of relevant information based on the output of the emotion engine.

[0952] Step 8:

[0953] The server generates reports based on the organized and analyzed information, providing it to users in a useful format.

[0954] Input: Adjusted, prioritized data

[0955] Output: Generated report (e.g., PDF or JSON format including summary, graphs, and statistical data)

[0956] Specific actions: Use the report generation tool to format the data into a report format and create a file.

[0957] Step 9:

[0958] The server sends the generated report to the user's terminal.

[0959] Input: Report file

[0960] Output: Report sent to the user's terminal

[0961] Specific operation: The server uses a file transfer protocol (e.g., email, dashboard notification) to send the generated report to the user's device.

[0962] Step 10:

[0963] Users review reports generated on their devices and consider ways to improve the production line.

[0964] Input: Report file

[0965] Output: Review results, improvement measures

[0966] Specific actions: The user opens the submitted report, reviews its contents, and develops improvement measures for the production line.

[0967] 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.

[0968] The data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of the 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.

[0969] 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.

[0970] [Third Embodiment]

[0971] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0972] 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.

[0973] 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).

[0974] 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.

[0975] 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.

[0976] 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).

[0977] 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.

[0978] 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.

[0979] 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.

[0980] 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.

[0981] 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.

[0982] 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".

[0983] This invention is a system in which a user inputs the topics they wish to discuss in a meeting, and the system collects and organizes the necessary information based on that input and provides it as a report. This enables meetings to be conducted efficiently and productively. Embodiments of this invention are described in detail below.

[0984] Explanation of the program's processing

[0985] User enters agenda item

[0986] Users enter topics they want to discuss during the meeting, such as market trends, new ideas, or challenges, into the interface's text boxes. For example, they might set a specific topic like "Market trends in the IT industry in 2024."

[0987] The terminal sends the agenda to the server.

[0988] The terminal converts the agenda entered by the user into a data format (e.g., JSON format) and sends it to the server using an HTTPS request. The communication is encrypted and secure.

[0989] The server receives the agenda and creates a query for the generating AI.

[0990] The server receives the agenda sent from the terminal and analyzes it. Next, it creates a query for the generating AI based on this agenda. For example, it might set a query in the format of, "Please provide the latest information on market trends in the IT industry in 2024."

[0991] The server uses generated AI to collect information.

[0992] The server sends the generated query to a generating AI (e.g., GPT-3) to collect relevant information. The generating AI retrieves the necessary information (text, data, news articles, statistics, etc.) from the internet or internal databases.

[0993] The server organizes and analyzes the information it has collected.

[0994] The server receives and analyzes the information returned by the generating AI. Here, the information is filtered and summarized based on criteria such as reliability, relevance, and importance. For example, statistical data may be extracted and graphed, or key points may be listed in bullet points.

[0995] The server generates the report.

[0996] Based on the organized and analyzed information, the server generates a user-friendly report. This report includes summaries, graphs, statistics, and reference links.

[0997] The server sends the generated report to the user's terminal.

[0998] Once a report is generated, the server sends it to the user's device. The report is sent in a digital format such as JSON or PDF, and notifications are sent via email or on the dashboard as needed.

[0999] The user reviews the report.

[1000] Users review the reports they receive on their devices. They then examine the report's contents and use it as material for discussion during meetings. This allows users to prepare thoroughly in advance and effectively consider data and opinions during meetings.

[1001] Specific example

[1002] Example 1: Market Trends Agenda

[1003] User enters topic: The user enters the topic "Market trends in the IT industry in 2024".

[1004] Terminal sends agenda to server: The terminal sends this agenda to the server.

[1005] The server receives the agenda and creates a query for the generating AI: The server creates an appropriate query and sends it to the generating AI.

[1006] The server uses generative AI to gather information: Generative AI collects the latest reports, news articles, and statistical data on market trends.

[1007] Server-generated information organization and analysis: The server organizes the information, extracts important data, and creates a summary.

[1008] The server generates the report: It creates a detailed report based on the organized and analyzed information.

[1009] Send the server-generated report to the user's terminal: The report is sent to the user's terminal.

[1010] User reviews report: The user reviews the report and completes preparations for the meeting.

[1011] This invention enables efficient use of time during meetings by gathering and organizing sufficient information before the meeting, facilitating high-quality discussions and rapid decision-making.

[1012] The following describes the processing flow.

[1013] Step 1:

[1014] User enters agenda item

[1015] Users enter topics they want to discuss in the meeting, such as market trends, new ideas, or challenges, into the interface's text boxes. For example, they might enter "Market trends in the IT industry in 2024."

[1016] Step 2:

[1017] The terminal sends the agenda to the server.

[1018] The terminal converts the agenda entered by the user into an appropriate data format (e.g., JSON) and sends it to the server as an HTTPS request. This communication is encrypted and secure.

[1019] Step 3:

[1020] The server receives the agenda and creates a query for the generating AI.

[1021] The server analyzes the agenda received from the terminal and creates a query for the generating AI. For example, it might prepare a query in the format, "Please provide the latest information on market trends in the IT industry in 2024."

[1022] Step 4:

[1023] The server uses generated AI to collect information.

[1024] The server sends the generated query to the generative AI and collects the relevant information. The generative AI automatically retrieves text, statistical data, news articles, and other information from the internet and internal databases.

[1025] Step 5:

[1026] The server organizes and analyzes the information it has collected.

[1027] The server receives the information returned by the generating AI and organizes and analyzes it based on reliability, relevance, and importance. It filters out unnecessary parts of the data and extracts important data points.

[1028] Step 6:

[1029] The server generates the report.

[1030] The server generates a report based on the organized and analyzed information. This report includes summaries, graphs, statistical data, and reference links, and is provided in a format that is easy for the user to understand.

[1031] Step 7:

[1032] The server sends the generated report to the user's terminal.

[1033] The server converts the generated report into JSON or PDF format and sends it to the user's device. Delivery methods include email and dashboard notifications.

[1034] Step 8:

[1035] The user reviews the report.

[1036] Users review the reports they receive on their devices. They then examine the report's contents and use it as material for discussion during meetings. This allows users to prepare thoroughly in advance and effectively consider data and opinions during the meeting.

[1037] (Example 1)

[1038] 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."

[1039] In modern meetings, a major challenge is the need for a vast amount of information, requiring significant time and effort to collect and organize it beforehand. In particular, a lack of rapid and accurate information gathering can reduce meeting productivity and hinder effective decision-making. Furthermore, given the sheer volume of information, there is a need to efficiently organize and present the necessary information clearly.

[1040] 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.

[1041] In this invention, the server includes means for the user to input an agenda item they wish to discuss in a meeting; means for the terminal to send the agenda item to the server; means for the server to create a query for a generating AI based on the agenda item; means for collecting information related to the agenda item using the generating AI; means for organizing and analyzing the collected information; means for generating the organized and analyzed information as a report; means for sending the generated report to the user's terminal; and means for the user to review the report. This enables the user to efficiently and automatically collect and organize the necessary information and receive it in an easy-to-understand report.

[1042] A "user" is the entity that uses the system to input the topics they want to discuss in a meeting.

[1043] "Agenda items" refer to the themes or topics discussed in a meeting, and are text information entered by the user.

[1044] A "terminal" refers to a device used by a user to input agenda items and send them to the server, and includes, for example, personal computers and smartphones.

[1045] A "server" is a central computer system that receives agenda items submitted by users and uses generating AI to collect, organize, and analyze information.

[1046] "Generative AI" refers to artificial intelligence technology that uses natural language processing techniques to automatically acquire relevant information related to a user's topic.

[1047] A "query" refers to a question created by a server to request information gathering from a generating AI, and is often in natural language format.

[1048] "Information gathering" refers to the process by which a generating AI acquires necessary data from information sources such as the internet and internal databases.

[1049] "Organization and analysis" is the process of evaluating collected information based on its reliability and relevance, selecting the necessary data, and processing it into an easily understandable format.

[1050] A "report" refers to a document that integrates organized and analyzed information and provides it to the user, including summaries, graphs, and statistical information.

[1051] "Transmission" refers to the data transfer process that delivers reports generated by the server to the user's terminal.

[1052] "Verification" refers to the act of carefully examining the contents of reports received by users on their devices and using them as material for meeting preparations and discussions.

[1053] This invention is a system in which a user inputs the topics they wish to discuss in a meeting, and based on that input, the system collects and organizes the necessary information and provides it as a report. This enables meetings to be conducted efficiently and productively. Embodiments of this invention are described in detail below.

[1054] Users access a dedicated interface to input topics. For example, they might use a browser to access the system's website, enter "Market Trends in the IT Industry in 2024" into a text box, and click the "Submit" button. This input interface is built using HTML and JavaScript.

[1055] The terminal first retrieves the agenda entered in the text box and converts it to JSON format. After conversion, it creates an HTTPS POST request and sends it to a specific API endpoint on the server. The communication is encrypted using SSL / TLS, ensuring security. The terminal's communication processing uses libraries such as Python's requests library or JavaScript's fetch API.

[1056] The server receives and analyzes the agenda sent from the terminal. Based on the received agenda, "Market Trends in the IT Industry in 2024," it generates a natural language query. For example, it might create a query such as, "Please provide the latest information on market trends in the IT industry in 2024." An automated natural language processing algorithm is useful for this query generation.

[1057] Next, the server sends the generated query to a generating AI (e.g., GPT-3). The generating AI then collects the necessary information from the internet or internal databases based on the query. For example, it might collect the latest news articles, statistical data, reports, etc.

[1058] The server receives and analyzes the information returned by the generated AI. The information is filtered and summarized based on criteria such as reliability, relevance, and importance. For example, statistical data may be extracted and graphed, or key points may be listed in bullet points. Tools such as Python's pandas library and matplotlib are used for organizing and analyzing this information.

[1059] Based on the organized and analyzed information, the server generates a user-friendly report. This report includes summaries, graphs, statistical data, and reference links. HTML template engines (e.g., Jinja2) and PDF generation libraries (e.g., ReportLab) are used to generate the report.

[1060] The generated report is converted back into JSON or PDF format and sent to the user's device using an HTTPS POST request. After sending, the user receives an email notification or a notification on the dashboard. For email notifications, the SMTP protocol is used, for example.

[1061] Users review the reports received on their devices. They examine the reports displayed in their browsers and scrutinize their contents. If necessary, they can print or download the reports for offline viewing. This allows them to adequately prepare for meetings.

[1062] <Specific example>

[1063] The user enters and submits the topic "Market Trends in the IT Industry in 2024." After being sent from the terminal to the server, the server sends a query to the generating AI asking, "Please provide the latest information on market trends in the IT industry in 2024." The generating AI collects the latest relevant reports and statistical data, and the server analyzes and organizes it to generate a report. This report is sent to the user's terminal, and the user uses it to prepare for the meeting.

[1064] This invention enables users to efficiently and automatically collect and organize necessary information and receive it as an easy-to-understand report.

[1065] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1066] Program processing flow

[1067] Step 1: The user enters the agenda.

[1068] The user accesses the system's website using a browser. They enter a topic into the text box. For example, they might enter the text "Market Trends in the IT Industry in 2024" and click the "Submit" button.

[1069] Input: The user enters text as the agenda item.

[1070] Output: After clicking the send button, the agenda will be received on the device.

[1071] Step 2: The terminal sends the agenda to the server.

[1072] The terminal retrieves the agenda entered in the text box and converts it to JSON format. It then sends the converted data to the server via an HTTPS POST request. This request is secure because it is encrypted using SSL / TLS.

[1073] Input: Agenda text entered by the user

[1074] Output: The agenda, converted to JSON format, is sent to the server.

[1075] Step 3: The server receives the agenda and creates a query for the generating AI.

[1076] The server receives the agenda sent from the terminal. Next, it analyzes the received agenda and generates a query for the generating AI. For example, it might generate a query such as, "Please provide the latest information on market trends in the IT industry in 2024."

[1077] Input: Agenda data in JSON format

[1078] Output: Natural language queries to send to the generating AI

[1079] Step 4: The server uses generated AI to collect information.

[1080] The server sends the generated queries to a generating AI (e.g., GPT-3). The generating AI collects relevant information from external and internal sources. This process gathers the latest news articles, statistics, reports, and so on.

[1081] Input: Natural language query

[1082] Output: Related information returned by the generating AI

[1083] Step 5: Organize and analyze the information collected by the server.

[1084] The server receives information returned by the generating AI and filters it based on reliability and relevance. It then summarizes the information and performs organization and analysis, such as graphing statistical data. For example, it might utilize Python libraries like pandas or matplotlib.

[1085] Input: Information returned by the generating AI

[1086] Output: Organized and analyzed information (summary, graphs, statistical data)

[1087] Step 6: The server generates the report.

[1088] The server generates user reports based on the organized and analyzed information. These reports include summaries, graphs, statistics, and reference links. For example, they can be visually formatted using an HTML template engine.

[1089] Input: Organized and analyzed information

[1090] Output: Completed report (HTML or PDF format)

[1091] Step 7: Send the report generated by the server to the user's terminal.

[1092] The server converts the generated report into an appropriate format (e.g., JSON or PDF) and sends it to the user's device using an HTTPS POST request. Email notifications and dashboard notifications are also provided as needed.

[1093] Input: Completed report

[1094] Output: Report sent to the user's device

[1095] Step 8: User reviews the report

[1096] Users open the received report on their device and review its contents. They can view the report in a browser and examine the data and statistics. If necessary, they can also print or download the report for offline viewing.

[1097] Input: Report sent from the server

[1098] Output: Confirmed report contents (review, print, download)

[1099] The above outlines the specific processing steps of the system. The details of the specific actions performed at each step, along with the associated inputs and outputs, have been described.

[1100] (Application Example 1)

[1101] 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."

[1102] Traditional meeting preparation systems required significant time and effort to gather and organize information for discussion, and lacked concrete tools for virtual store operators to efficiently consider new product lines and market trends. Furthermore, the tools for immediately utilizing the collected information were insufficient, compromising the quality and efficiency of meetings.

[1103] 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.

[1104] In this invention, the server includes means for the virtual store operator to input meeting agendas, means for transmitting agendas entered from a smart device to the server, means for creating and sending queries to a generating AI, means for collecting market research reports, customer reviews, and sales data using the generating AI, means for analyzing the collected data, extracting key points and graphing them, means for creating a detailed report, means for transmitting the generated report to a smart device, and means for reviewing the report. This enables the virtual store operator to prepare meeting materials efficiently and quickly, and to effectively consider data and opinions during the meeting.

[1105] A "user" is the final user who uses the system to input meeting agenda items and review reports.

[1106] A "server" is a central control unit that receives agenda items submitted by users, collects, organizes, and analyzes information using generation AI, generates reports, and sends them to the user's terminal.

[1107] "Generative AI" is artificial intelligence that collects relevant information from the internet or internal databases based on an input query and then analyzes it.

[1108] An "agenda" is a specific theme or topic that users want to discuss in a meeting.

[1109] A "smart device" is an advanced device such as glasses or head-mounted displays that can connect to the internet.

[1110] A "query" is a question or command created by a server to prompt a generating AI to collect information.

[1111] A "market research report" is a document that summarizes the detailed results of a survey on market trends, competitive situations, and other related matters.

[1112] "Customer reviews" are records of customer evaluations and opinions about products and services.

[1113] "Sales data" refers to information regarding the quantity and amount of sales of products over a specific period.

[1114] "Data analysis" is the process of organizing collected information using statistical methods and other techniques to present it in a meaningful form.

[1115] "Key points" refer to particularly important information or indicators within the analyzed data.

[1116] "Graphing" is the process of representing data using shapes to make it easier to understand visually.

[1117] A "report" is a detailed report created based on collected and analyzed information.

[1118] A "meeting" is a gathering of stakeholders to discuss a specific topic and reach a consensus.

[1119] This invention is a system in which a user inputs the topics they wish to discuss in a meeting, and based on that input, the system collects, organizes, and analyzes the necessary information and provides it as a report. A specific embodiment of this system is described below.

[1120] System Configuration

[1121] Hardware:

[1122] Smart glasses (e.g., typical smart glasses)

[1123] Head-mounted display (e.g., typical HMD)

[1124] software:

[1125] Frontend: React Native

[1126] Backend: Node.js, Express.js

[1127] Data analysis: Python, Pandas, Matplotlib

[1128] Generation AI: GPT-3 (OpenAI API)

[1129] Frontend operation

[1130] Users enter meeting agenda items using smart glasses or head-mounted displays. The agenda items are entered into text boxes, and the data is sent to the server in JSON format. An example of an agenda item a user might enter is "Market Trends in the IT Industry in 2024."

[1131] Data transmission

[1132] The terminal sends the agenda entered by the user to the server. During this process, the data is encrypted and transmitted using HTTPS communication. The server analyzes the received data and creates queries to send to the generating AI to collect the necessary information.

[1133] Information gathering

[1134] The server sends queries to the Generative AI (GPT-3) to collect relevant information. An example query is, "Please provide the latest information on market trends in the IT industry in 2024." The Generative AI retrieves the necessary information from the internet and internal databases. This collected information includes market research reports, customer reviews, and sales data.

[1135] Data Analysis

[1136] The server analyzes the information returned by the generating AI. It filters the information based on criteria such as reliability, relevance, and importance, and extracts summarized and graphed statistical information.

[1137] Report generation

[1138] Based on the analyzed information, the server generates a report in a user-friendly format. The report includes a summary, graphs, statistical data, and reference links.

[1139] Send Report

[1140] The completed report is sent to the user's smart glasses or head-mounted display. The user can then review it and prepare for the meeting.

[1141] Specific example

[1142] Case Study 1: Considering the introduction of a new product line

[1143] The user enters the topic "Effects of introducing a new product line."

[1144] Agenda items entered from smart devices are sent to the server.

[1145] The server sends a query to the generating AI asking, "Please provide information about the effectiveness of introducing the new product."

[1146] The generation AI collects market research reports, customer reviews, sales data, and more.

[1147] The server analyzes the collected data, extracts key points, and graphs them.

[1148] A detailed report is created and sent to your smart device.

[1149] Users review the report and prepare for discussions in the meeting.

[1150] An example of a prompt message would be something like, "Please provide me with the latest information on market trends in the IT industry in 2024."

[1151] This invention enables virtual store operators to efficiently and quickly prepare meeting materials and to effectively review data and opinions during meetings.

[1152] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1153] Step 1:

[1154] The user enters an agenda item into a text box using smart glasses or a head-mounted display. The entered agenda item is in text format, and a specific example of input would be "Market trends in the IT industry in 2024." This text data is sent to the server in the next step.

[1155] Step 2:

[1156] The terminal converts the agenda entered by the user into JSON format and sends it to the server using HTTPS. This ensures that the agenda data is securely communicated to the server. The input is an agenda in text format, and the output is data in JSON format.

[1157] Step 3:

[1158] The server analyzes the received agenda and creates queries for the generating AI. Specifically, it generates queries such as "Please provide the latest information on market trends in the IT industry in 2024" based on the received text data. The input is agenda data in JSON format, and the output is query text to be sent to the generating AI.

[1159] Step 4:

[1160] The server generates queries and sends them to a generative AI like GPT-3 to collect relevant information. The generative AI retrieves market research reports, customer reviews, sales data, etc., by referencing the internet and internal databases. The input is the query text, and the output is the collected relevant information.

[1161] Step 5:

[1162] The server organizes and analyzes the information returned by the generating AI. Specifically, it filters the information based on criteria such as reliability, relevance, and importance, and extracts summaries and statistical data. For example, it uses Python's Pandas and Matplotlib to graph sales data. The input is relevant information from the generating AI, and the output is filtered and summarized information and graph data.

[1163] Step 6:

[1164] The server generates a report based on the information it organizes and analyzes. The report includes a summary, graphs, statistics, and reference links. The generated report is saved in PDF or HTML format. The input is the organized and analyzed information, and the output is the report provided to the user.

[1165] Step 7:

[1166] The server generates a report and sends it to the smart device. Once the report is generated, the server sends it to the user's device in JSON or PDF format. The input is the generated report, and the output is a report viewable on the user's smart device.

[1167] Step 8:

[1168] Users view reports using smart glasses or head-mounted displays. By viewing the reports, users can prepare discussion materials for meetings. The input is the report on the smart device, and the output is the meeting materials the user receives.

[1169] 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.

[1170] This invention is a system in which a user inputs the topics they wish to discuss in a meeting, and based on that input, the system collects and organizes the necessary information and provides it as a report. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it enables prioritization of topics and customization of reports. The configuration for implementing this system is described in detail below.

[1171] Explanation of the program's processing

[1172] User enters agenda item

[1173] Users enter topics they want to discuss in the meeting, such as market trends, new ideas, or challenges, into the interface's text boxes. For example, they might enter "Market trends in the IT industry in 2024."

[1174] The terminal sends the agenda to the server.

[1175] The terminal converts the agenda entered by the user into an appropriate data format (e.g., JSON) and sends it to the server as an HTTPS request. This communication is encrypted and secure.

[1176] The server receives the agenda and creates a query for the generating AI.

[1177] The server analyzes the agenda received from the terminal and creates a query for the generating AI. For example, it might prepare a query in the format, "Please provide the latest information on market trends in the IT industry in 2024."

[1178] The server uses generated AI to collect information.

[1179] The server sends the generated query to the generative AI and collects the relevant information. The generative AI automatically retrieves text, statistical data, news articles, and other information from the internet and internal databases.

[1180] The server organizes and analyzes the information it has collected.

[1181] The server receives the information returned by the generating AI and organizes and analyzes it based on reliability, relevance, and importance. It filters out unnecessary parts of the data and extracts important data points.

[1182] The server uses an emotion engine to recognize the user's emotions.

[1183] The emotion engine analyzes the user's emotions from user input data (e.g., keyboard typing speed and emphasized words). For example, it pays particular attention to areas where the user has a strong interest or concern.

[1184] The server adjusts agenda priorities based on user sentiment.

[1185] The server adjusts the priority of agenda items based on the sentiment analysis results from the sentiment engine. It prioritizes information gathering and organization for agenda items of high interest or urgent issues.

[1186] The server generates the report.

[1187] Based on the organized and analyzed information, the server generates a user-friendly report. This report includes summaries, graphs, statistics, and reference links, and the presentation of information is customized to suit the user's perspective.

[1188] The server sends the generated report to the user's terminal.

[1189] Once a report is generated, the server sends it to the user's device. The transmission format can be digital, such as JSON or PDF, and may also include email or dashboard notifications.

[1190] The user reviews the report.

[1191] Users review reports received on their devices. They prepare for meetings based on agendas prioritized by the emotion engine and customized information. This allows users to be well-prepared in advance and efficiently review data and opinions during meetings.

[1192] Specific example

[1193] Example 1: Market Trends Agenda

[1194] User enters topic: The user enters the topic "Market trends in the IT industry in 2024".

[1195] Terminal sends agenda to server: The terminal sends this agenda to the server.

[1196] The server receives the agenda and creates a query for the generating AI: The server creates an appropriate query and sends it to the generating AI.

[1197] The server uses generative AI to gather information: Generative AI collects the latest reports, news articles, and statistical data on market trends.

[1198] Server-generated information organization and analysis: The server organizes the information, extracts important data, and creates a summary.

[1199] The server uses an emotion engine to recognize the user's emotions: The emotion engine analyzes the user's input to determine their emotions and assess their level of interest.

[1200] The server adjusts agenda priorities based on user sentiment: It adjusts the priority of important agenda items based on sentiment analysis results.

[1201] The server generates reports: Based on the organized and analyzed information, it creates detailed reports and presents information in a way that is sensitive to the user's emotions.

[1202] Send the server-generated report to the user's terminal: The report is sent to the user's terminal.

[1203] Users review the report: Users review the report and prepare for the meeting focusing on topics of high interest to them.

[1204] This system enables information gathering and organization that takes user emotions into consideration, further improving meeting productivity.

[1205] The following describes the processing flow.

[1206] Step 1:

[1207] User enters agenda item

[1208] Users enter topics they want to discuss in the meeting, such as market trends, new ideas, or challenges, into the interface's text box. For example, they might enter "Market trends in the IT industry in 2024."

[1209] Step 2:

[1210] The terminal sends the agenda to the server.

[1211] The terminal converts the agenda entered by the user into JSON format and sends it to the server as an HTTPS request. The communication is encrypted and takes place in a secure environment.

[1212] Step 3:

[1213] The server receives the agenda and creates a query for the generating AI.

[1214] The server analyzes the agenda received from the terminal and generates appropriate queries for the AI. For example, it might create a query in the format of, "Please provide the latest information on market trends in the IT industry in 2024."

[1215] Step 4:

[1216] The server uses generated AI to collect information.

[1217] The server sends queries to the generative AI to collect relevant information. The generative AI retrieves text, statistics, news articles, reports, and other data from the internet and internal databases.

[1218] Step 5:

[1219] The server organizes and analyzes the information it has collected.

[1220] The server receives the information returned by the generating AI and organizes and analyzes it based on reliability, relevance, and importance. If there is too much information, it filters out unnecessary data and extracts the important information.

[1221] Step 6:

[1222] The server uses an emotion engine to recognize the user's emotions.

[1223] The emotion engine analyzes user input data and user activity history (e.g., typing speed and vocabulary selection) to infer the user's emotions. For example, it analyzes emotions based on keywords that the user emphasizes when typing.

[1224] Step 7:

[1225] The server adjusts agenda priorities based on user sentiment.

[1226] The server adjusts the priority of agenda items based on the sentiment analysis results obtained from the sentiment engine. Topics of high interest and urgent issues are prioritized for information gathering and organization.

[1227] Step 8:

[1228] The server generates the report.

[1229] The server generates a report based on the organized and analyzed information. This report includes summaries, graphs, statistics, and reference links. The way information is presented is customized to suit the user's emotions.

[1230] Step 9:

[1231] The server sends the generated report to the user's terminal.

[1232] The server sends the generated report to the user's device in JSON or PDF format. Delivery methods include email and dashboard notifications.

[1233] Step 10:

[1234] The user reviews the report.

[1235] Users review reports received on their devices. They then prepare for meetings based on agendas prioritized by the sentiment engine and customized information.

[1236] This system enables information gathering and organization that takes user emotions into consideration, further improving meeting productivity. For example, it allows for features such as placing topics of strong user interest at the beginning of a report and highlighting important information.

[1237] (Example 2)

[1238] 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."

[1239] Conventional meeting preparation systems lacked sufficient automation in gathering and organizing information for agenda items, requiring users to manually search for and compile necessary information. Furthermore, the lack of information customization based on user sentiment and interests hindered efficient meeting preparation. This invention aims to solve these problems by providing a system that automatically collects and organizes information based on user input and delivers reports that reflect user sentiment.

[1240] 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.

[1241] In this invention, the server includes means for collecting information related to the agenda using generative AI, means for organizing and analyzing the collected information, and means for analyzing the user's emotions using an emotion analysis engine. This allows the prioritization of agenda items to be adjusted based on the user's emotions, and enables the provision of customized reports to the user.

[1242] A "user" is defined as the entity that utilizes the present invention, and is the person who inputs agenda items and reviews reports.

[1243] A "terminal" is a device used by users to input agenda items or to receive and review reports sent from a server. Specifically, this includes personal computers, smartphones, and tablets.

[1244] A "server" is a computer system that processes data sent from users or terminals, and collects, organizes, analyzes, generates, and transmits information.

[1245] "Generative AI" refers to artificial intelligence technology that collects relevant information in response to user queries, and is used to retrieve information from the internet or internal databases.

[1246] An "emotion analysis engine" is a technology that analyzes emotions from user input data and extracts information about the user's level of interest and emotions.

[1247] An "agenda" refers to a topic or theme that a user wants to discuss in a meeting, and it is sent to the server through the input interface.

[1248] "Information gathering" is the process by which the generating AI retrieves relevant data from the internet or internal databases based on the user's queries.

[1249] "Information organization and analysis" is the process of filtering collected data based on reliability, relevance, and importance, and extracting key data points.

[1250] A "report" is a document or data generated in a user-friendly format based on organized and analyzed information, and may include summaries, graphs, statistical data, and reference links.

[1251] "Prioritizing" is the process of re-evaluating the importance of topics and information based on the results of the sentiment analysis engine, and changing the order in which they are collected and organized.

[1252] "JSON format" is an abbreviation for JavaScript Object Notation, and it is a format for representing data in a lightweight and compact manner.

[1253] "TLS" stands for Transport Layer Security, and it is a protocol used to encrypt and secure data communications over the internet.

[1254] This invention is a system in which a user inputs the topics they wish to discuss in a meeting, and based on that input, the system collects and organizes the necessary information and provides it as a report. By combining this invention with a sentiment analysis engine, the system enables prioritization of topics and customization of reports. A detailed embodiment of this system is described below.

[1255] Hardware and software to be used

[1256] User's device: This is the device on which the user enters agenda items and reviews reports. This includes personal computers, smartphones, and tablets.

[1257] Server: A computer system that receives, processes, and generates data, sends queries to AI, collects and analyzes information, performs sentiment analysis, and generates and sends reports.

[1258] Generative AI models: These are artificial intelligence technologies that collect relevant information based on user queries, and for example, large-scale language models (such as GPT-3) are used.

[1259] Sentiment analysis engine: This technology analyzes emotions from user input data and uses it to prioritize agenda items and customize information.

[1260] Data processing and calculations

[1261] 1. The user enters the agenda item.

[1262] The user enters the topic they want to discuss in the meeting into the interface's text box. For example, they might enter "Market trends in the IT industry in 2024."

[1263] 2. The terminal sends the agenda to the server.

[1264] The terminal converts the agenda entered by the user into JSON format and sends it to the server as an HTTPS request.

[1265] 3. The server creates and sends a query to the generated AI.

[1266] The server analyzes the agenda received from the terminal and creates a query for the generating AI. For example, it might generate a query in the format of, "Please provide the latest information on market trends in the IT industry in 2024."

[1267] 4. Generative AI collects information

[1268] The server sends queries to the generative AI, which then collects relevant information (text, statistical data, news articles, etc.) from the internet and internal databases.

[1269] 5. The server organizes and analyzes the information.

[1270] The server analyzes the information obtained from the generated AI and filters and summarizes it based on reliability, relevance, and importance. For example, it extracts important data points and statistical information.

[1271] 6. The server performs sentiment analysis.

[1272] The server's sentiment analysis engine analyzes user input data (for example, keyboard input speed and emphasized words) to understand the user's level of interest and emotions.

[1273] 7. The server adjusts the priority of the agenda items.

[1274] Based on the sentiment analysis results, the importance of each agenda item will be re-evaluated, and the order of information gathering and organization will be adjusted as needed.

[1275] 8. The server generates the report.

[1276] Based on the organized and analyzed information, a report is generated in a user-friendly format. This report includes summaries, graphs, statistical data, and reference links.

[1277] 9. The server sends the report to the user's terminal.

[1278] The completed report is sent from the server to the user's terminal. The report may be sent in JSON or PDF format, and may also include email and dashboard notifications.

[1279] 10. The user reviews the report.

[1280] Users review reports received on their devices and prepare for meetings focusing on topics of high interest. This improves meeting productivity.

[1281] Specific example

[1282] Example 1: Market Trends Agenda

[1283] User enters topic: The user enters the topic "Market trends in the IT industry in 2024".

[1284] The terminal sends the agenda to the server: The terminal converts this agenda into JSON format and sends it as an HTTPS request.

[1285] The server receives the agenda and creates a query for the generating AI: The server creates an appropriate query and sends it to the generating AI.

[1286] The server uses generative AI to gather information: Generative AI collects the latest reports, news articles, and statistical data on market trends.

[1287] Server-generated information organization and analysis: The server organizes the information, extracts important data, and creates a summary.

[1288] The server uses an emotion engine to recognize the user's emotions: The emotion engine analyzes the user's input to determine their emotions and assess their level of interest.

[1289] The server adjusts agenda priorities based on user sentiment: It adjusts the priority of important agenda items based on sentiment analysis results.

[1290] The server generates reports: Based on the organized and analyzed information, it creates detailed reports and presents information in a way that is sensitive to the user's emotions.

[1291] Send the server-generated report to the user's terminal: The report is sent to the user's terminal.

[1292] Users review the report: Users review the report and prepare for the meeting focusing on topics of high interest to them.

[1293] This system enables information gathering and organization that takes user emotions into consideration, further improving meeting productivity.

[1294] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1295] Step 1:

[1296] The user enters the topics they want to discuss in the meeting.

[1297] Input: The user enters a topic, such as "Market trends in the IT industry in 2024," into the interface's text box.

[1298] Output: The agenda text is obtained as user input.

[1299] Specific action: The user enters an agenda item into a text box and clicks the submit button.

[1300] Step 2:

[1301] The terminal sends the agenda to the server.

[1302] Input: The agenda text entered by the user in Step 1.

[1303] Output: The agenda text is sent to the server in JSON format.

[1304] Specific operation: The terminal converts the agenda into a JSON format like the one below and sends it to the server via an HTTPS request.

[1305] json

[1306] {

[1307] "Topic": "Market Trends in the IT Industry in 2024"

[1308] }

[1309] Step 3:

[1310] The server receives the agenda and creates a query for the generating AI.

[1311] Input: Agenda JSON data sent from the terminal.

[1312] Output: A query for the generating AI is created.

[1313] Specific operation: The server analyzes the agenda JSON data and creates a query for the generating AI: "Please provide the latest information on market trends in the IT industry in 2024."

[1314] Step 4:

[1315] The server uses generated AI to collect information.

[1316] Input: A query created for the generating AI.

[1317] Output: Relevant information collected by the generating AI (text, statistical data, news articles, etc.).

[1318] Specific operation: The server sends a query to the generating AI, which then collects information from the internet and internal databases.

[1319] Step 5:

[1320] The server organizes and analyzes the information it has collected.

[1321] Input: Relevant information returned by the generating AI.

[1322] Output: Organized and analyzed information.

[1323] Specific operation: The server filters information based on reliability, relevance, and importance, extracts key data points, and creates a summary.

[1324] Step 6:

[1325] The server uses an emotion analysis engine to recognize the user's emotions.

[1326] Input: User input data (e.g., input speed and emphasized words).

[1327] Output: User sentiment analysis results.

[1328] Specific operation: The server's sentiment analysis engine analyzes the highlighted parts and input speed of the entered text to understand the user's level of interest and emotions.

[1329] Step 7:

[1330] The server adjusts the priority of agenda items based on the user's sentiment.

[1331] Input: Sentiment analysis results and organized / analyzed information.

[1332] Output: Prioritized agenda items.

[1333] Specific operation: Based on the sentiment analysis results, the server resets the agenda priorities to display information of high interest.

[1334] Step 8:

[1335] The server generates the report.

[1336] Input: Organized and analyzed information, prioritizing agenda items.

[1337] Output: Generated report (summary, graphs, statistics, reference links, etc.).

[1338] Specific operation: The server generates customized reports and formats them in a user-friendly format.

[1339] Step 9:

[1340] The server sends the generated report to the user's terminal.

[1341] Input: Generated report.

[1342] Output: Report sent to the user's terminal.

[1343] Specific operation: The server generates a report in JSON or PDF format and sends it to the user's terminal via HTTPS.

[1344] Step 10:

[1345] The user reviews the report.

[1346] Input: Report sent from the server.

[1347] Output: Report contents confirmed by the user.

[1348] Specific action: The user downloads the report to their device and reviews its contents. The report includes customized information based on the user's sentiment analysis results, allowing the user to prepare for meetings efficiently.

[1349] (Application Example 2)

[1350] 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."

[1351] When proposing improvements to factory production lines, there is a need to effectively and quickly gather problem identifications and new ideas, and then organize and analyze the information based on them. However, with conventional methods, it was difficult to select appropriate data from a vast amount of information and to prioritize it in a way that reflected the intentions and feelings of managers. Furthermore, the process of generating reports based on the collected information and providing them to managers was cumbersome, hindering rapid decision-making for productivity improvement.

[1352] 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.

[1353] In this invention, the server includes means for the user to input an agenda item for a production line they wish to improve; means for transmitting the agenda item to the server; means for the server to collect information related to the agenda item using a generated AI; means for the server to organize and analyze the collected information; means for the server to recognize the user's emotions using an emotion engine; means for the server to adjust the priority of the agenda item based on the user's emotions recognized by the server; means for the server to generate a report from the organized and analyzed information; means for the server to transmit the report generated by the server to the user's terminal; and means for the user to review the report. This enables the administrator to automatically prioritize improvement measures of interest and to provide efficiently customized information in a short amount of time.

[1354] Creating a definition

[1355] A "user" is a person or organization that uses the system to input production line agendas and review reports.

[1356] A "topic" refers to the content of a discussion that outlines areas for improvement or new ideas for the factory's production line.

[1357] A "server" is a computer system that receives agenda items, collects, organizes, and analyzes information using a generation AI and emotion engine, and generates reports.

[1358] "Generative AI" is artificial intelligence that collects information from the internet or internal databases and analyzes that information.

[1359] "Information gathering" refers to the process by which the generating AI obtains data related to the topic from the internet or an internal database.

[1360] "Information organization" involves categorizing collected information and rearranging the data based on its relevance and reliability.

[1361] "Information analysis" is the process of extracting important data points based on organized information and generating statistical data and graphs.

[1362] An "emotion engine" is software that analyzes emotions from user input data and evaluates the importance and urgency of agenda items.

[1363] "Emotion recognition" is the process by which an emotion engine determines the level of interest and urgency of a user's input data.

[1364] "Priority adjustment" refers to changing the priority of information gathering and data organization based on the importance and urgency of the agenda items, using the results of the emotion engine's analysis.

[1365] "Report generation" refers to creating a report that includes summaries, graphs, and statistical data based on organized and analyzed information.

[1366] A "report" is a generated document containing information that users refer to when considering improvements to the production line.

[1367] A "terminal" refers to a device (such as a smartphone, tablet, or computer) that a user uses to input agenda items and review reports.

[1368] This invention is a system for streamlining factory production line improvements. The user inputs the topics they wish to improve, and based on those topics, a generative AI is used to collect, organize, and analyze information to generate a report. Furthermore, an emotion engine is used to recognize the user's emotions and adjust the prioritization of topics, providing a customized report.

[1369] User-submitted agenda items

[1370] Users input topics related to production line improvements into the terminal interface. This is done in text box format and includes examples such as "improving production line efficiency" and "cost reduction methods."

[1371] Sending the agenda to the server

[1372] The terminal converts the agenda entered by the user into JSON format and sends it to the server as an HTTPS request. This process ensures that data related to the agenda is transferred securely.

[1373] Information gathering by generating AI

[1374] The server analyzes the received agenda and generates queries for the generative AI. For example, a prompt such as "Please provide the latest information on optimizing production lines" might be used. The generative AI collects relevant information from the internet and internal databases. The generative AI model used is GPT-4 or a similar generative model.

[1375] Information organization and analysis

[1376] The server analyzes and organizes the collected information. The data is filtered based on reliability and relevance, and organized into summaries, graphs, and statistical data. For example, data on the latest efficiency technologies and success stories are prioritized.

[1377] Emotion recognition by an emotion engine

[1378] The server uses an emotion engine to recognize emotions from user input data. For example, it analyzes emotions based on the emphasis and typing speed of the words the user enters, and adjusts the priority of topics accordingly. Software used for this process includes libraries such as the EmotionAnalyzer library.

[1379] Priority adjustment

[1380] Based on the analysis results from the emotion engine, the server automatically adjusts the priority of agenda items. Topics of high interest and urgent issues are given priority.

[1381] Report generation and submission

[1382] The server generates a report based on the organized and analyzed information, providing it to the user in the most useful format. This report includes summaries, graphs, and statistical data, and is sent to the user's device in PDF or JSON format.

[1383] User-confirmed report

[1384] Users review reports generated on their terminals. Based on the customized information, they can quickly consider ways to improve the production line.

[1385] Specific example

[1386] For example, if you input a prompt like, "Please provide the latest information on optimizing production lines," into the AI ​​generator, it will collect data on the latest efficiency technologies and success stories. Furthermore, if a manager expresses a strong interest in "efficiency" or "cost reduction," that topic will be prioritized, and more detailed information will be provided.

[1387] In this way, the system for implementing the invention supports the rapid and efficient proposal of improvements to factory production lines.

[1388] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1389] System program processing flow

[1390] Step 1:

[1391] The user inputs the production line improvement topics they want to address into the terminal's interface.

[1392] Input: Production line agenda (e.g., "Improving production line efficiency")

[1393] Output: User input data

[1394] Specific action: The user uses the application for factory administrators to enter the agenda item into a text box.

[1395] Step 2:

[1396] The terminal converts the agenda entered by the user into JSON format and sends it to the server using an HTTPS request.

[1397] Input: User input data

[1398] Output: Agenda data in JSON format

[1399] Specific operation: The client-side program converts the text data into JSON format and sends it to the server using the HTTPS protocol.

[1400] Step 3:

[1401] The server analyzes the received agenda data and generates queries for the AI.

[1402] Input: Agenda data in JSON format

[1403] Output: Prompt text for the generated AI (Example: "Please provide the latest information on optimizing production lines.")

[1404] Specific operation: The server uses a programming language such as Python to analyze the received data and generate prompt messages.

[1405] Step 4:

[1406] The server uses generated AI to collect information related to the agenda.

[1407] Input: Prompt message

[1408] Output: Collected information (e.g., latest production technologies, best practices, statistical data, etc.)

[1409] Specific operation: The server uses a generated AI model (e.g., GPT-4) to collect relevant information from the internet or an internal database.

[1410] Step 5:

[1411] The server organizes and analyzes the information it has collected.

[1412] Input: Collected information

[1413] Output: Organized and analyzed data (e.g., in the form of summaries, graphs, and statistical data)

[1414] Specific actions: Categorize collected information, sort data based on relevance and reliability, and create summaries and graphs.

[1415] Step 6:

[1416] The server uses an emotion engine to recognize the user's emotions.

[1417] Input: User input data, collected information

[1418] Output: Sentiment analysis results (e.g., evaluation of level of interest and urgency)

[1419] Specific operation: The server uses the EmotionAnalyzer library to analyze emotions from the user's input data.

[1420] Step 7:

[1421] The server adjusts agenda priorities based on the user's perceived emotions.

[1422] Input: Sentiment analysis results, organized information

[1423] Output: Adjusted and prioritized data

[1424] Specific operation: The server automatically readjusts the priority of relevant information based on the output of the emotion engine.

[1425] Step 8:

[1426] The server generates reports based on the organized and analyzed information, providing it to users in a useful format.

[1427] Input: Adjusted, prioritized data

[1428] Output: Generated report (e.g., PDF or JSON format including summary, graphs, and statistical data)

[1429] Specific actions: Use the report generation tool to format the data into a report format and create a file.

[1430] Step 9:

[1431] The server sends the generated report to the user's terminal.

[1432] Input: Report file

[1433] Output: Report sent to the user's terminal

[1434] Specific operation: The server uses a file transfer protocol (e.g., email, dashboard notification) to send the generated report to the user's device.

[1435] Step 10:

[1436] Users review reports generated on their devices and consider ways to improve the production line.

[1437] Input: Report file

[1438] Output: Review results, improvement measures

[1439] Specific actions: The user opens the submitted report, reviews its contents, and develops improvement measures for the production line.

[1440] 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.

[1441] The data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of the 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.

[1442] 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.

[1443] [Fourth Embodiment]

[1444] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1445] 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.

[1446] 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).

[1447] 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.

[1448] 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.

[1449] 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).

[1450] 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.

[1451] 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.

[1452] 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.

[1453] 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.

[1454] 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.

[1455] 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.

[1456] 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".

[1457] This invention is a system in which a user inputs the topics they wish to discuss in a meeting, and the system collects and organizes the necessary information based on that input and provides it as a report. This enables meetings to be conducted efficiently and productively. Embodiments of this invention are described in detail below.

[1458] Explanation of the program's processing

[1459] User enters agenda item

[1460] Users enter topics they want to discuss during the meeting, such as market trends, new ideas, or challenges, into the interface's text boxes. For example, they might set a specific topic like "Market trends in the IT industry in 2024."

[1461] The terminal sends the agenda to the server.

[1462] The terminal converts the agenda entered by the user into a data format (e.g., JSON format) and sends it to the server using an HTTPS request. The communication is encrypted and secure.

[1463] The server receives the agenda and creates a query for the generating AI.

[1464] The server receives the agenda sent from the terminal and analyzes it. Next, it creates a query for the generating AI based on this agenda. For example, it might set a query in the format of, "Please provide the latest information on market trends in the IT industry in 2024."

[1465] The server uses generated AI to collect information.

[1466] The server sends the generated query to a generating AI (e.g., GPT-3) to collect relevant information. The generating AI retrieves the necessary information (text, data, news articles, statistics, etc.) from the internet or internal databases.

[1467] The server organizes and analyzes the information it has collected.

[1468] The server receives and analyzes the information returned by the generating AI. Here, the information is filtered and summarized based on criteria such as reliability, relevance, and importance. For example, statistical data may be extracted and graphed, or key points may be listed in bullet points.

[1469] The server generates the report.

[1470] Based on the organized and analyzed information, the server generates a user-friendly report. This report includes summaries, graphs, statistics, and reference links.

[1471] The server sends the generated report to the user's terminal.

[1472] Once a report is generated, the server sends it to the user's device. The report is sent in a digital format such as JSON or PDF, and notifications are sent via email or on the dashboard as needed.

[1473] The user reviews the report.

[1474] Users review the reports they receive on their devices. They then examine the report's contents and use it as material for discussion during meetings. This allows users to prepare thoroughly in advance and effectively consider data and opinions during meetings.

[1475] Specific example

[1476] Example 1: Market Trends Agenda

[1477] User enters topic: The user enters the topic "Market trends in the IT industry in 2024".

[1478] Terminal sends agenda to server: The terminal sends this agenda to the server.

[1479] The server receives the agenda and creates a query for the generating AI: The server creates an appropriate query and sends it to the generating AI.

[1480] The server uses generative AI to gather information: Generative AI collects the latest reports, news articles, and statistical data on market trends.

[1481] Server-generated information organization and analysis: The server organizes the information, extracts important data, and creates a summary.

[1482] The server generates the report: It creates a detailed report based on the organized and analyzed information.

[1483] Send the server-generated report to the user's terminal: The report is sent to the user's terminal.

[1484] User reviews report: The user reviews the report and completes preparations for the meeting.

[1485] This invention enables efficient use of time during meetings by gathering and organizing sufficient information before the meeting, facilitating high-quality discussions and rapid decision-making.

[1486] The following describes the processing flow.

[1487] Step 1:

[1488] User enters agenda item

[1489] Users enter topics they want to discuss in the meeting, such as market trends, new ideas, or challenges, into the interface's text boxes. For example, they might enter "Market trends in the IT industry in 2024."

[1490] Step 2:

[1491] The terminal sends the agenda to the server.

[1492] The terminal converts the agenda entered by the user into an appropriate data format (e.g., JSON) and sends it to the server as an HTTPS request. This communication is encrypted and secure.

[1493] Step 3:

[1494] The server receives the agenda and creates a query for the generating AI.

[1495] The server analyzes the agenda received from the terminal and creates a query for the generating AI. For example, it might prepare a query in the format, "Please provide the latest information on market trends in the IT industry in 2024."

[1496] Step 4:

[1497] The server uses generated AI to collect information.

[1498] The server sends the generated query to the generative AI and collects the relevant information. The generative AI automatically retrieves text, statistical data, news articles, and other information from the internet and internal databases.

[1499] Step 5:

[1500] The server organizes and analyzes the information it has collected.

[1501] The server receives the information returned by the generating AI and organizes and analyzes it based on reliability, relevance, and importance. It filters out unnecessary parts of the data and extracts important data points.

[1502] Step 6:

[1503] The server generates the report.

[1504] The server generates a report based on the organized and analyzed information. This report includes summaries, graphs, statistical data, and reference links, and is provided in a format that is easy for the user to understand.

[1505] Step 7:

[1506] The server sends the generated report to the user's terminal.

[1507] The server converts the generated report into JSON or PDF format and sends it to the user's device. Delivery methods include email and dashboard notifications.

[1508] Step 8:

[1509] The user reviews the report.

[1510] Users review the reports they receive on their devices. They then examine the report's contents and use it as material for discussion during meetings. This allows users to prepare thoroughly in advance and effectively consider data and opinions during the meeting.

[1511] (Example 1)

[1512] 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".

[1513] In modern meetings, a major challenge is the need for a vast amount of information, requiring significant time and effort to collect and organize it beforehand. In particular, a lack of rapid and accurate information gathering can reduce meeting productivity and hinder effective decision-making. Furthermore, given the sheer volume of information, there is a need to efficiently organize and present the necessary information clearly.

[1514] 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.

[1515] In this invention, the server includes means for the user to input an agenda item they wish to discuss in a meeting; means for the terminal to send the agenda item to the server; means for the server to create a query for a generating AI based on the agenda item; means for collecting information related to the agenda item using the generating AI; means for organizing and analyzing the collected information; means for generating the organized and analyzed information as a report; means for sending the generated report to the user's terminal; and means for the user to review the report. This enables the user to efficiently and automatically collect and organize the necessary information and receive it in an easy-to-understand report.

[1516] A "user" is the entity that uses the system to input the topics they want to discuss in a meeting.

[1517] "Agenda items" refer to the themes or topics discussed in a meeting, and are text information entered by the user.

[1518] A "terminal" refers to a device used by a user to input agenda items and send them to the server, and includes, for example, personal computers and smartphones.

[1519] A "server" is a central computer system that receives agenda items submitted by users and uses generating AI to collect, organize, and analyze information.

[1520] "Generative AI" refers to artificial intelligence technology that uses natural language processing techniques to automatically acquire relevant information related to a user's topic.

[1521] A "query" refers to a question created by a server to request information gathering from a generating AI, and is often in natural language format.

[1522] "Information gathering" refers to the process by which a generating AI acquires necessary data from information sources such as the internet and internal databases.

[1523] "Organization and analysis" is the process of evaluating collected information based on its reliability and relevance, selecting the necessary data, and processing it into an easily understandable format.

[1524] A "report" refers to a document that integrates organized and analyzed information and provides it to the user, including summaries, graphs, and statistical information.

[1525] "Transmission" refers to the data transfer process that delivers reports generated by the server to the user's terminal.

[1526] "Verification" refers to the act of carefully examining the contents of reports received by users on their devices and using them as material for meeting preparations and discussions.

[1527] This invention is a system in which a user inputs the topics they wish to discuss in a meeting, and based on that input, the system collects and organizes the necessary information and provides it as a report. This enables meetings to be conducted efficiently and productively. Embodiments of this invention are described in detail below.

[1528] Users access a dedicated interface to input topics. For example, they might use a browser to access the system's website, enter "Market Trends in the IT Industry in 2024" into a text box, and click the "Submit" button. This input interface is built using HTML and JavaScript.

[1529] The terminal first retrieves the agenda entered in the text box and converts it to JSON format. After conversion, it creates an HTTPS POST request and sends it to a specific API endpoint on the server. The communication is encrypted using SSL / TLS, ensuring security. The terminal's communication processing uses libraries such as Python's requests library or JavaScript's fetch API.

[1530] The server receives and analyzes the agenda sent from the terminal. Based on the received agenda, "Market Trends in the IT Industry in 2024," it generates a natural language query. For example, it might create a query such as, "Please provide the latest information on market trends in the IT industry in 2024." An automated natural language processing algorithm is useful for this query generation.

[1531] Next, the server sends the generated query to a generating AI (e.g., GPT-3). The generating AI then collects the necessary information from the internet or internal databases based on the query. For example, it might collect the latest news articles, statistical data, reports, etc.

[1532] The server receives and analyzes the information returned by the generated AI. The information is filtered and summarized based on criteria such as reliability, relevance, and importance. For example, statistical data may be extracted and graphed, or key points may be listed in bullet points. Tools such as Python's pandas library and matplotlib are used for organizing and analyzing this information.

[1533] Based on the organized and analyzed information, the server generates a user-friendly report. This report includes summaries, graphs, statistical data, and reference links. HTML template engines (e.g., Jinja2) and PDF generation libraries (e.g., ReportLab) are used to generate the report.

[1534] The generated report is converted back into JSON or PDF format and sent to the user's device using an HTTPS POST request. After sending, the user receives an email notification or a notification on the dashboard. For email notifications, the SMTP protocol is used, for example.

[1535] Users review the reports received on their devices. They examine the reports displayed in their browsers and scrutinize their contents. If necessary, they can print or download the reports for offline viewing. This allows them to adequately prepare for meetings.

[1536] <Specific example>

[1537] The user enters and submits the topic "Market Trends in the IT Industry in 2024." After being sent from the terminal to the server, the server sends a query to the generating AI asking, "Please provide the latest information on market trends in the IT industry in 2024." The generating AI collects the latest relevant reports and statistical data, and the server analyzes and organizes it to generate a report. This report is sent to the user's terminal, and the user uses it to prepare for the meeting.

[1538] This invention enables users to efficiently and automatically collect and organize necessary information and receive it as an easy-to-understand report.

[1539] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1540] Program processing flow

[1541] Step 1: The user enters the agenda.

[1542] The user accesses the system's website using a browser. They enter a topic into the text box. For example, they might enter the text "Market Trends in the IT Industry in 2024" and click the "Submit" button.

[1543] Input: The user enters text as the agenda item.

[1544] Output: After clicking the send button, the agenda will be received on the device.

[1545] Step 2: The terminal sends the agenda to the server.

[1546] The terminal retrieves the agenda entered in the text box and converts it to JSON format. It then sends the converted data to the server via an HTTPS POST request. This request is secure because it is encrypted using SSL / TLS.

[1547] Input: Agenda text entered by the user

[1548] Output: The agenda, converted to JSON format, is sent to the server.

[1549] Step 3: The server receives the agenda and creates a query for the generating AI.

[1550] The server receives the agenda sent from the terminal. Next, it analyzes the received agenda and generates a query for the generating AI. For example, it might generate a query such as, "Please provide the latest information on market trends in the IT industry in 2024."

[1551] Input: Agenda data in JSON format

[1552] Output: Natural language queries to send to the generating AI

[1553] Step 4: The server uses generated AI to collect information.

[1554] The server sends the generated queries to a generating AI (e.g., GPT-3). The generating AI collects relevant information from external and internal sources. This process gathers the latest news articles, statistics, reports, and so on.

[1555] Input: Natural language query

[1556] Output: Related information returned by the generating AI

[1557] Step 5: Organize and analyze the information collected by the server.

[1558] The server receives information returned by the generating AI and filters it based on reliability and relevance. It then summarizes the information and performs organization and analysis, such as graphing statistical data. For example, it might utilize Python libraries like pandas or matplotlib.

[1559] Input: Information returned by the generating AI

[1560] Output: Organized and analyzed information (summary, graphs, statistical data)

[1561] Step 6: The server generates the report.

[1562] The server generates user reports based on the organized and analyzed information. These reports include summaries, graphs, statistics, and reference links. For example, they can be visually formatted using an HTML template engine.

[1563] Input: Organized and analyzed information

[1564] Output: Completed report (HTML or PDF format)

[1565] Step 7: Send the report generated by the server to the user's terminal.

[1566] The server converts the generated report into an appropriate format (e.g., JSON or PDF) and sends it to the user's device using an HTTPS POST request. Email notifications and dashboard notifications are also provided as needed.

[1567] Input: Completed report

[1568] Output: Report sent to the user's device

[1569] Step 8: User reviews the report

[1570] Users open the received report on their device and review its contents. They can view the report in a browser and examine the data and statistics. If necessary, they can also print or download the report for offline viewing.

[1571] Input: Report sent from the server

[1572] Output: Confirmed report contents (review, print, download)

[1573] The above outlines the specific processing steps of the system. The details of the specific actions performed at each step, along with the associated inputs and outputs, have been described.

[1574] (Application Example 1)

[1575] 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".

[1576] Traditional meeting preparation systems required significant time and effort to gather and organize information for discussion, and lacked concrete tools for virtual store operators to efficiently consider new product lines and market trends. Furthermore, the tools for immediately utilizing the collected information were insufficient, compromising the quality and efficiency of meetings.

[1577] 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.

[1578] In this invention, the server includes means for the virtual store operator to input meeting agendas, means for transmitting agendas entered from a smart device to the server, means for creating and sending queries to a generating AI, means for collecting market research reports, customer reviews, and sales data using the generating AI, means for analyzing the collected data, extracting key points and graphing them, means for creating a detailed report, means for transmitting the generated report to a smart device, and means for reviewing the report. This enables the virtual store operator to prepare meeting materials efficiently and quickly, and to effectively consider data and opinions during the meeting.

[1579] A "user" is the final user who uses the system to input meeting agenda items and review reports.

[1580] A "server" is a central control unit that receives agenda items submitted by users, collects, organizes, and analyzes information using generation AI, generates reports, and sends them to the user's terminal.

[1581] "Generative AI" is artificial intelligence that collects relevant information from the internet or internal databases based on an input query and then analyzes it.

[1582] An "agenda" is a specific theme or topic that users want to discuss in a meeting.

[1583] A "smart device" is an advanced device such as glasses or head-mounted displays that can connect to the internet.

[1584] A "query" is a question or command created by a server to prompt a generating AI to collect information.

[1585] A "market research report" is a document that summarizes the detailed results of a survey on market trends, competitive situations, and other related matters.

[1586] "Customer reviews" are records of customer evaluations and opinions about products and services.

[1587] "Sales data" refers to information regarding the quantity and amount of sales of products over a specific period.

[1588] "Data analysis" is the process of organizing collected information using statistical methods and other techniques to present it in a meaningful form.

[1589] "Key points" refer to particularly important information or indicators within the analyzed data.

[1590] "Graphing" is the process of representing data using shapes to make it easier to understand visually.

[1591] A "report" is a detailed report created based on collected and analyzed information.

[1592] A "meeting" is a gathering of stakeholders to discuss a specific topic and reach a consensus.

[1593] This invention is a system in which a user inputs the topics they wish to discuss in a meeting, and based on that input, the system collects, organizes, and analyzes the necessary information and provides it as a report. A specific embodiment of this system is described below.

[1594] System Configuration

[1595] Hardware:

[1596] Smart glasses (e.g., typical smart glasses)

[1597] Head-mounted display (e.g., typical HMD)

[1598] software:

[1599] Frontend: React Native

[1600] Backend: Node.js, Express.js

[1601] Data analysis: Python, Pandas, Matplotlib

[1602] Generation AI: GPT-3 (OpenAI API)

[1603] Frontend operation

[1604] Users enter meeting agenda items using smart glasses or head-mounted displays. The agenda items are entered into text boxes, and the data is sent to the server in JSON format. An example of an agenda item a user might enter is "Market Trends in the IT Industry in 2024."

[1605] Data transmission

[1606] The terminal sends the agenda entered by the user to the server. During this process, the data is encrypted and transmitted using HTTPS communication. The server analyzes the received data and creates queries to send to the generating AI to collect the necessary information.

[1607] Information gathering

[1608] The server sends queries to the Generative AI (GPT-3) to collect relevant information. An example query is, "Please provide the latest information on market trends in the IT industry in 2024." The Generative AI retrieves the necessary information from the internet and internal databases. This collected information includes market research reports, customer reviews, and sales data.

[1609] Data Analysis

[1610] The server analyzes the information returned by the generating AI. It filters the information based on criteria such as reliability, relevance, and importance, and extracts summarized and graphed statistical information.

[1611] Report generation

[1612] Based on the analyzed information, the server generates a report in a user-friendly format. The report includes a summary, graphs, statistical data, and reference links.

[1613] Send Report

[1614] The completed report is sent to the user's smart glasses or head-mounted display. The user can then review it and prepare for the meeting.

[1615] Specific example

[1616] Case Study 1: Considering the introduction of a new product line

[1617] The user enters the topic "Effects of introducing a new product line."

[1618] Agenda items entered from smart devices are sent to the server.

[1619] The server sends a query to the generating AI asking, "Please provide information about the effectiveness of introducing the new product."

[1620] The generation AI collects market research reports, customer reviews, sales data, and more.

[1621] The server analyzes the collected data, extracts key points, and graphs them.

[1622] A detailed report is created and sent to your smart device.

[1623] Users review the report and prepare for discussions in the meeting.

[1624] An example of a prompt message would be something like, "Please provide me with the latest information on market trends in the IT industry in 2024."

[1625] This invention enables virtual store operators to efficiently and quickly prepare meeting materials and to effectively review data and opinions during meetings.

[1626] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1627] Step 1:

[1628] The user enters an agenda item into a text box using smart glasses or a head-mounted display. The entered agenda item is in text format, and a specific example of input would be "Market trends in the IT industry in 2024." This text data is sent to the server in the next step.

[1629] Step 2:

[1630] The terminal converts the agenda entered by the user into JSON format and sends it to the server using HTTPS. This ensures that the agenda data is securely communicated to the server. The input is an agenda in text format, and the output is data in JSON format.

[1631] Step 3:

[1632] The server analyzes the received agenda and creates queries for the generating AI. Specifically, it generates queries such as "Please provide the latest information on market trends in the IT industry in 2024" based on the received text data. The input is agenda data in JSON format, and the output is query text to be sent to the generating AI.

[1633] Step 4:

[1634] The server generates queries and sends them to a generative AI like GPT-3 to collect relevant information. The generative AI retrieves market research reports, customer reviews, sales data, etc., by referencing the internet and internal databases. The input is the query text, and the output is the collected relevant information.

[1635] Step 5:

[1636] The server organizes and analyzes the information returned by the generating AI. Specifically, it filters the information based on criteria such as reliability, relevance, and importance, and extracts summaries and statistical data. For example, it uses Python's Pandas and Matplotlib to graph sales data. The input is relevant information from the generating AI, and the output is filtered and summarized information and graph data.

[1637] Step 6:

[1638] The server generates a report based on the information it organizes and analyzes. The report includes a summary, graphs, statistics, and reference links. The generated report is saved in PDF or HTML format. The input is the organized and analyzed information, and the output is the report provided to the user.

[1639] Step 7:

[1640] The server generates a report and sends it to the smart device. Once the report is generated, the server sends it to the user's device in JSON or PDF format. The input is the generated report, and the output is a report viewable on the user's smart device.

[1641] Step 8:

[1642] Users view reports using smart glasses or head-mounted displays. By viewing the reports, users can prepare discussion materials for meetings. The input is the report on the smart device, and the output is the meeting materials the user receives.

[1643] 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.

[1644] This invention is a system in which a user inputs the topics they wish to discuss in a meeting, and based on that input, the system collects and organizes the necessary information and provides it as a report. Furthermore, by incorporating an emotion engine that recognizes the user's emotions, it enables prioritization of topics and customization of reports. The configuration for implementing this system is described in detail below.

[1645] Explanation of the program's processing

[1646] User enters agenda item

[1647] Users enter topics they want to discuss in the meeting, such as market trends, new ideas, or challenges, into the interface's text boxes. For example, they might enter "Market trends in the IT industry in 2024."

[1648] The terminal sends the agenda to the server.

[1649] The terminal converts the agenda entered by the user into an appropriate data format (e.g., JSON) and sends it to the server as an HTTPS request. This communication is encrypted and secure.

[1650] The server receives the agenda and creates a query for the generating AI.

[1651] The server analyzes the agenda received from the terminal and creates a query for the generating AI. For example, it might prepare a query in the format, "Please provide the latest information on market trends in the IT industry in 2024."

[1652] The server uses generated AI to collect information.

[1653] The server sends the generated query to the generative AI and collects the relevant information. The generative AI automatically retrieves text, statistical data, news articles, and other information from the internet and internal databases.

[1654] The server organizes and analyzes the information it has collected.

[1655] The server receives the information returned by the generating AI and organizes and analyzes it based on reliability, relevance, and importance. It filters out unnecessary parts of the data and extracts important data points.

[1656] The server uses an emotion engine to recognize the user's emotions.

[1657] The emotion engine analyzes the user's emotions from user input data (e.g., keyboard typing speed and emphasized words). For example, it pays particular attention to areas where the user has a strong interest or concern.

[1658] The server adjusts agenda priorities based on user sentiment.

[1659] The server adjusts the priority of agenda items based on the sentiment analysis results from the sentiment engine. It prioritizes information gathering and organization for agenda items of high interest or urgent issues.

[1660] The server generates the report.

[1661] Based on the organized and analyzed information, the server generates a user-friendly report. This report includes summaries, graphs, statistics, and reference links, and the presentation of information is customized to suit the user's perspective.

[1662] The server sends the generated report to the user's terminal.

[1663] Once a report is generated, the server sends it to the user's device. The transmission format can be digital, such as JSON or PDF, and may also include email or dashboard notifications.

[1664] The user reviews the report.

[1665] Users review reports received on their devices. They prepare for meetings based on agendas prioritized by the emotion engine and customized information. This allows users to be well-prepared in advance and efficiently review data and opinions during meetings.

[1666] Specific example

[1667] Example 1: Market Trends Agenda

[1668] User enters topic: The user enters the topic "Market trends in the IT industry in 2024".

[1669] Terminal sends agenda to server: The terminal sends this agenda to the server.

[1670] The server receives the agenda and creates a query for the generating AI: The server creates an appropriate query and sends it to the generating AI.

[1671] The server uses generative AI to gather information: Generative AI collects the latest reports, news articles, and statistical data on market trends.

[1672] Server-generated information organization and analysis: The server organizes the information, extracts important data, and creates a summary.

[1673] The server uses an emotion engine to recognize the user's emotions: The emotion engine analyzes the user's input to determine their emotions and assess their level of interest.

[1674] The server adjusts agenda priorities based on user sentiment: It adjusts the priority of important agenda items based on sentiment analysis results.

[1675] The server generates reports: Based on the organized and analyzed information, it creates detailed reports and presents information in a way that is sensitive to the user's emotions.

[1676] Send the server-generated report to the user's terminal: The report is sent to the user's terminal.

[1677] Users review the report: Users review the report and prepare for the meeting focusing on topics of high interest to them.

[1678] This system enables information gathering and organization that takes user emotions into consideration, further improving meeting productivity.

[1679] The following describes the processing flow.

[1680] Step 1:

[1681] User enters agenda item

[1682] Users enter topics they want to discuss in the meeting, such as market trends, new ideas, or challenges, into the interface's text box. For example, they might enter "Market trends in the IT industry in 2024."

[1683] Step 2:

[1684] The terminal sends the agenda to the server.

[1685] The terminal converts the agenda entered by the user into JSON format and sends it to the server as an HTTPS request. The communication is encrypted and takes place in a secure environment.

[1686] Step 3:

[1687] The server receives the agenda and creates a query for the generating AI.

[1688] The server analyzes the agenda received from the terminal and generates appropriate queries for the AI. For example, it might create a query in the format of, "Please provide the latest information on market trends in the IT industry in 2024."

[1689] Step 4:

[1690] The server uses generated AI to collect information.

[1691] The server sends queries to the generative AI to collect relevant information. The generative AI retrieves text, statistics, news articles, reports, and other data from the internet and internal databases.

[1692] Step 5:

[1693] The server organizes and analyzes the information it has collected.

[1694] The server receives the information returned by the generating AI and organizes and analyzes it based on reliability, relevance, and importance. If there is too much information, it filters out unnecessary data and extracts the important information.

[1695] Step 6:

[1696] The server uses an emotion engine to recognize the user's emotions.

[1697] The emotion engine analyzes user input data and user activity history (e.g., typing speed and vocabulary selection) to infer the user's emotions. For example, it analyzes emotions based on keywords that the user emphasizes when typing.

[1698] Step 7:

[1699] The server adjusts agenda priorities based on user sentiment.

[1700] The server adjusts the priority of agenda items based on the sentiment analysis results obtained from the sentiment engine. Topics of high interest and urgent issues are prioritized for information gathering and organization.

[1701] Step 8:

[1702] The server generates the report.

[1703] The server generates a report based on the organized and analyzed information. This report includes summaries, graphs, statistics, and reference links. The way information is presented is customized to suit the user's emotions.

[1704] Step 9:

[1705] The server sends the generated report to the user's terminal.

[1706] The server sends the generated report to the user's device in JSON or PDF format. Delivery methods include email and dashboard notifications.

[1707] Step 10:

[1708] The user reviews the report.

[1709] Users review reports received on their devices. They then prepare for meetings based on agendas prioritized by the sentiment engine and customized information.

[1710] This system enables information gathering and organization that takes user emotions into consideration, further improving meeting productivity. For example, it allows for features such as placing topics of strong user interest at the beginning of a report and highlighting important information.

[1711] (Example 2)

[1712] 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".

[1713] Conventional meeting preparation systems lacked sufficient automation in gathering and organizing information for agenda items, requiring users to manually search for and compile necessary information. Furthermore, the lack of information customization based on user sentiment and interests hindered efficient meeting preparation. This invention aims to solve these problems by providing a system that automatically collects and organizes information based on user input and delivers reports that reflect user sentiment.

[1714] 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.

[1715] In this invention, the server includes means for collecting information related to the agenda using generative AI, means for organizing and analyzing the collected information, and means for analyzing the user's emotions using an emotion analysis engine. This allows the prioritization of agenda items to be adjusted based on the user's emotions, and enables the provision of customized reports to the user.

[1716] A "user" is defined as the entity that utilizes the present invention, and is the person who inputs agenda items and reviews reports.

[1717] A "terminal" is a device used by users to input agenda items or to receive and review reports sent from a server. Specifically, this includes personal computers, smartphones, and tablets.

[1718] A "server" is a computer system that processes data sent from users or terminals, and collects, organizes, analyzes, generates, and transmits information.

[1719] "Generative AI" refers to artificial intelligence technology that collects relevant information in response to user queries, and is used to retrieve information from the internet or internal databases.

[1720] An "emotion analysis engine" is a technology that analyzes emotions from user input data and extracts information about the user's level of interest and emotions.

[1721] An "agenda" refers to a topic or theme that a user wants to discuss in a meeting, and it is sent to the server through the input interface.

[1722] "Information gathering" is the process by which the generating AI retrieves relevant data from the internet or internal databases based on the user's queries.

[1723] "Information organization and analysis" is the process of filtering collected data based on reliability, relevance, and importance, and extracting key data points.

[1724] A "report" is a document or data generated in a user-friendly format based on organized and analyzed information, and may include summaries, graphs, statistical data, and reference links.

[1725] "Prioritizing" is the process of re-evaluating the importance of topics and information based on the results of the sentiment analysis engine, and changing the order in which they are collected and organized.

[1726] "JSON format" is an abbreviation for JavaScript Object Notation, and it is a format for representing data in a lightweight and compact manner.

[1727] "TLS" stands for Transport Layer Security, and it is a protocol used to encrypt and secure data communications over the internet.

[1728] This invention is a system in which a user inputs the topics they wish to discuss in a meeting, and based on that input, the system collects and organizes the necessary information and provides it as a report. By combining this invention with a sentiment analysis engine, the system enables prioritization of topics and customization of reports. A detailed embodiment of this system is described below.

[1729] Hardware and software to be used

[1730] User's device: This is the device on which the user enters agenda items and reviews reports. This includes personal computers, smartphones, and tablets.

[1731] Server: A computer system that receives, processes, and generates data, sends queries to AI, collects and analyzes information, performs sentiment analysis, and generates and sends reports.

[1732] Generative AI models: These are artificial intelligence technologies that collect relevant information based on user queries, and for example, large-scale language models (such as GPT-3) are used.

[1733] Sentiment analysis engine: This technology analyzes emotions from user input data and uses it to prioritize agenda items and customize information.

[1734] Data processing and calculations

[1735] 1. The user enters the agenda item.

[1736] The user enters the topic they want to discuss in the meeting into the interface's text box. For example, they might enter "Market trends in the IT industry in 2024."

[1737] 2. The terminal sends the agenda to the server.

[1738] The terminal converts the agenda entered by the user into JSON format and sends it to the server as an HTTPS request.

[1739] 3. The server creates and sends a query to the generated AI.

[1740] The server analyzes the agenda received from the terminal and creates a query for the generating AI. For example, it might generate a query in the format of, "Please provide the latest information on market trends in the IT industry in 2024."

[1741] 4. Generative AI collects information

[1742] The server sends queries to the generative AI, which then collects relevant information (text, statistical data, news articles, etc.) from the internet and internal databases.

[1743] 5. The server organizes and analyzes the information.

[1744] The server analyzes the information obtained from the generated AI and filters and summarizes it based on reliability, relevance, and importance. For example, it extracts important data points and statistical information.

[1745] 6. The server performs sentiment analysis.

[1746] The server's sentiment analysis engine analyzes user input data (for example, keyboard input speed and emphasized words) to understand the user's level of interest and emotions.

[1747] 7. The server adjusts the priority of the agenda items.

[1748] Based on the sentiment analysis results, the importance of each agenda item will be re-evaluated, and the order of information gathering and organization will be adjusted as needed.

[1749] 8. The server generates the report.

[1750] Based on the organized and analyzed information, a report is generated in a user-friendly format. This report includes summaries, graphs, statistical data, and reference links.

[1751] 9. The server sends the report to the user's terminal.

[1752] The completed report is sent from the server to the user's terminal. The report may be sent in JSON or PDF format, and may also include email and dashboard notifications.

[1753] 10. The user reviews the report.

[1754] Users review reports received on their devices and prepare for meetings focusing on topics of high interest. This improves meeting productivity.

[1755] Specific example

[1756] Example 1: Market Trends Agenda

[1757] User enters topic: The user enters the topic "Market trends in the IT industry in 2024".

[1758] The terminal sends the agenda to the server: The terminal converts this agenda into JSON format and sends it as an HTTPS request.

[1759] The server receives the agenda and creates a query for the generating AI: The server creates an appropriate query and sends it to the generating AI.

[1760] The server uses generative AI to gather information: Generative AI collects the latest reports, news articles, and statistical data on market trends.

[1761] Server-generated information organization and analysis: The server organizes the information, extracts important data, and creates a summary.

[1762] The server uses an emotion engine to recognize the user's emotions: The emotion engine analyzes the user's input to determine their emotions and assess their level of interest.

[1763] The server adjusts agenda priorities based on user sentiment: It adjusts the priority of important agenda items based on sentiment analysis results.

[1764] The server generates reports: Based on the organized and analyzed information, it creates detailed reports and presents information in a way that is sensitive to the user's emotions.

[1765] Send the server-generated report to the user's terminal: The report is sent to the user's terminal.

[1766] Users review the report: Users review the report and prepare for the meeting focusing on topics of high interest to them.

[1767] This system enables information gathering and organization that takes user emotions into consideration, further improving meeting productivity.

[1768] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1769] Step 1:

[1770] The user enters the topics they want to discuss in the meeting.

[1771] Input: The user enters a topic, such as "Market trends in the IT industry in 2024," into the interface's text box.

[1772] Output: The agenda text is obtained as user input.

[1773] Specific action: The user enters an agenda item into a text box and clicks the submit button.

[1774] Step 2:

[1775] The terminal sends the agenda to the server.

[1776] Input: The agenda text entered by the user in Step 1.

[1777] Output: The agenda text is sent to the server in JSON format.

[1778] Specific operation: The terminal converts the agenda into a JSON format like the one below and sends it to the server via an HTTPS request.

[1779] json

[1780] {

[1781] "Topic": "Market Trends in the IT Industry in 2024"

[1782] }

[1783] Step 3:

[1784] The server receives the agenda and creates a query for the generating AI.

[1785] Input: Agenda JSON data sent from the terminal.

[1786] Output: A query for the generating AI is created.

[1787] Specific operation: The server analyzes the agenda JSON data and creates a query for the generating AI: "Please provide the latest information on market trends in the IT industry in 2024."

[1788] Step 4:

[1789] The server uses generated AI to collect information.

[1790] Input: A query created for the generating AI.

[1791] Output: Relevant information collected by the generating AI (text, statistical data, news articles, etc.).

[1792] Specific operation: The server sends a query to the generating AI, which then collects information from the internet and internal databases.

[1793] Step 5:

[1794] The server organizes and analyzes the information it has collected.

[1795] Input: Relevant information returned by the generating AI.

[1796] Output: Organized and analyzed information.

[1797] Specific operation: The server filters information based on reliability, relevance, and importance, extracts key data points, and creates a summary.

[1798] Step 6:

[1799] The server uses an emotion analysis engine to recognize the user's emotions.

[1800] Input: User input data (e.g., input speed and emphasized words).

[1801] Output: User sentiment analysis results.

[1802] Specific operation: The server's sentiment analysis engine analyzes the highlighted parts and input speed of the entered text to understand the user's level of interest and emotions.

[1803] Step 7:

[1804] The server adjusts the priority of agenda items based on the user's sentiment.

[1805] Input: Sentiment analysis results and organized / analyzed information.

[1806] Output: Prioritized agenda items.

[1807] Specific operation: Based on the sentiment analysis results, the server resets the agenda priorities to display information of high interest.

[1808] Step 8:

[1809] The server generates the report.

[1810] Input: Organized and analyzed information, prioritizing agenda items.

[1811] Output: Generated report (summary, graphs, statistics, reference links, etc.).

[1812] Specific operation: The server generates customized reports and formats them in a user-friendly format.

[1813] Step 9:

[1814] The server sends the generated report to the user's terminal.

[1815] Input: Generated report.

[1816] Output: Report sent to the user's terminal.

[1817] Specific operation: The server generates a report in JSON or PDF format and sends it to the user's terminal via HTTPS.

[1818] Step 10:

[1819] The user reviews the report.

[1820] Input: Report sent from the server.

[1821] Output: Report contents confirmed by the user.

[1822] Specific action: The user downloads the report to their device and reviews its contents. The report includes customized information based on the user's sentiment analysis results, allowing the user to prepare for meetings efficiently.

[1823] (Application Example 2)

[1824] 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".

[1825] When proposing improvements to factory production lines, there is a need to effectively and quickly gather problem identifications and new ideas, and then organize and analyze the information based on them. However, with conventional methods, it was difficult to select appropriate data from a vast amount of information and to prioritize it in a way that reflected the intentions and feelings of managers. Furthermore, the process of generating reports based on the collected information and providing them to managers was cumbersome, hindering rapid decision-making for productivity improvement.

[1826] 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.

[1827] In this invention, the server includes means for the user to input an agenda item for a production line they wish to improve; means for transmitting the agenda item to the server; means for the server to collect information related to the agenda item using a generated AI; means for the server to organize and analyze the collected information; means for the server to recognize the user's emotions using an emotion engine; means for the server to adjust the priority of the agenda item based on the user's emotions recognized by the server; means for the server to generate a report from the organized and analyzed information; means for the server to transmit the report generated by the server to the user's terminal; and means for the user to review the report. This enables the administrator to automatically prioritize improvement measures of interest and to provide efficiently customized information in a short amount of time.

[1828] Creating a definition

[1829] A "user" is a person or organization that uses the system to input production line agendas and review reports.

[1830] A "topic" refers to the content of a discussion that outlines areas for improvement or new ideas for the factory's production line.

[1831] A "server" is a computer system that receives agenda items, collects, organizes, and analyzes information using a generation AI and emotion engine, and generates reports.

[1832] "Generative AI" is artificial intelligence that collects information from the internet or internal databases and analyzes that information.

[1833] "Information gathering" refers to the process by which the generating AI obtains data related to the topic from the internet or an internal database.

[1834] "Information organization" involves categorizing collected information and rearranging the data based on its relevance and reliability.

[1835] "Information analysis" is the process of extracting important data points based on organized information and generating statistical data and graphs.

[1836] An "emotion engine" is software that analyzes emotions from user input data and evaluates the importance and urgency of agenda items.

[1837] "Emotion recognition" is the process by which an emotion engine determines the level of interest and urgency of a user's input data.

[1838] "Priority adjustment" refers to changing the priority of information gathering and data organization based on the importance and urgency of the agenda items, using the results of the emotion engine's analysis.

[1839] "Report generation" refers to creating a report that includes summaries, graphs, and statistical data based on organized and analyzed information.

[1840] A "report" is a generated document containing information that users refer to when considering improvements to the production line.

[1841] A "terminal" refers to a device (such as a smartphone, tablet, or computer) that a user uses to input agenda items and review reports.

[1842] This invention is a system for streamlining factory production line improvements. The user inputs the topics they wish to improve, and based on those topics, a generative AI is used to collect, organize, and analyze information to generate a report. Furthermore, an emotion engine is used to recognize the user's emotions and adjust the prioritization of topics, providing a customized report.

[1843] User-submitted agenda items

[1844] Users input topics related to production line improvements into the terminal interface. This is done in text box format and includes examples such as "improving production line efficiency" and "cost reduction methods."

[1845] Sending the agenda to the server

[1846] The terminal converts the agenda entered by the user into JSON format and sends it to the server as an HTTPS request. This process ensures that data related to the agenda is transferred securely.

[1847] Information gathering by generating AI

[1848] The server analyzes the received agenda and generates queries for the generative AI. For example, a prompt such as "Please provide the latest information on optimizing production lines" might be used. The generative AI collects relevant information from the internet and internal databases. The generative AI model used is GPT-4 or a similar generative model.

[1849] Information organization and analysis

[1850] The server analyzes and organizes the collected information. The data is filtered based on reliability and relevance, and organized into summaries, graphs, and statistical data. For example, data on the latest efficiency technologies and success stories are prioritized.

[1851] Emotion recognition by an emotion engine

[1852] The server uses an emotion engine to recognize emotions from user input data. For example, it analyzes emotions based on the emphasis and typing speed of the words the user enters, and adjusts the priority of topics accordingly. Software used for this process includes libraries such as the EmotionAnalyzer library.

[1853] Priority adjustment

[1854] Based on the analysis results from the emotion engine, the server automatically adjusts the priority of agenda items. Topics of high interest and urgent issues are given priority.

[1855] Report generation and submission

[1856] The server generates a report based on the organized and analyzed information, providing it to the user in the most useful format. This report includes summaries, graphs, and statistical data, and is sent to the user's device in PDF or JSON format.

[1857] User-confirmed report

[1858] Users review reports generated on their terminals. Based on the customized information, they can quickly consider ways to improve the production line.

[1859] Specific example

[1860] For example, if you input a prompt like, "Please provide the latest information on optimizing production lines," into the AI ​​generator, it will collect data on the latest efficiency technologies and success stories. Furthermore, if a manager expresses a strong interest in "efficiency" or "cost reduction," that topic will be prioritized, and more detailed information will be provided.

[1861] In this way, the system for implementing the invention supports the rapid and efficient proposal of improvements to factory production lines.

[1862] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1863] System program processing flow

[1864] Step 1:

[1865] The user inputs the production line improvement topics they want to address into the terminal's interface.

[1866] Input: Production line agenda (e.g., "Improving production line efficiency")

[1867] Output: User input data

[1868] Specific action: The user uses the application for factory administrators to enter the agenda item into a text box.

[1869] Step 2:

[1870] The terminal converts the agenda entered by the user into JSON format and sends it to the server using an HTTPS request.

[1871] Input: User input data

[1872] Output: Agenda data in JSON format

[1873] Specific operation: The client-side program converts the text data into JSON format and sends it to the server using the HTTPS protocol.

[1874] Step 3:

[1875] The server analyzes the received agenda data and generates queries for the AI.

[1876] Input: Agenda data in JSON format

[1877] Output: Prompt text for the generated AI (Example: "Please provide the latest information on optimizing production lines.")

[1878] Specific operation: The server uses a programming language such as Python to analyze the received data and generate prompt messages.

[1879] Step 4:

[1880] The server uses generated AI to collect information related to the agenda.

[1881] Input: Prompt message

[1882] Output: Collected information (e.g., latest production technologies, best practices, statistical data, etc.)

[1883] Specific operation: The server uses a generated AI model (e.g., GPT-4) to collect relevant information from the internet or an internal database.

[1884] Step 5:

[1885] The server organizes and analyzes the information it has collected.

[1886] Input: Collected information

[1887] Output: Organized and analyzed data (e.g., in the form of summaries, graphs, and statistical data)

[1888] Specific actions: Categorize collected information, sort data based on relevance and reliability, and create summaries and graphs.

[1889] Step 6:

[1890] The server uses an emotion engine to recognize the user's emotions.

[1891] Input: User input data, collected information

[1892] Output: Sentiment analysis results (e.g., evaluation of level of interest and urgency)

[1893] Specific operation: The server uses the EmotionAnalyzer library to analyze emotions from the user's input data.

[1894] Step 7:

[1895] The server adjusts agenda priorities based on the user's perceived emotions.

[1896] Input: Sentiment analysis results, organized information

[1897] Output: Adjusted and prioritized data

[1898] Specific operation: The server automatically readjusts the priority of relevant information based on the output of the emotion engine.

[1899] Step 8:

[1900] The server generates reports based on the organized and analyzed information, providing it to users in a useful format.

[1901] Input: Adjusted, prioritized data

[1902] Output: Generated report (e.g., PDF or JSON format including summary, graphs, and statistical data)

[1903] Specific actions: Use the report generation tool to format the data into a report format and create a file.

[1904] Step 9:

[1905] The server sends the generated report to the user's terminal.

[1906] Input: Report file

[1907] Output: Report sent to the user's terminal

[1908] Specific operation: The server uses a file transfer protocol (e.g., email, dashboard notification) to send the generated report to the user's device.

[1909] Step 10:

[1910] Users review reports generated on their devices and consider ways to improve the production line.

[1911] Input: Report file

[1912] Output: Review results, improvement measures

[1913] Specific actions: The user opens the submitted report, reviews its contents, and develops improvement measures for the production line.

[1914] 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.

[1915] The data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of the 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.

[1916] 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.

[1917] 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.

[1918] 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.

[1919] 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.

[1920] 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.

[1921] 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.

[1922] 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."

[1923] 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.

[1924] 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.

[1925] 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.

[1926] 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.

[1927] 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.

[1928] 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.

[1929] 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.

[1930] 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.

[1931] 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.

[1932] 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.

[1933] 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.

[1934] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[1935] The following is further disclosed regarding the embodiments described above.

[1936] (Claim 1)

[1937] A means for users to input the topics they want to discuss in the meeting,

[1938] Means for sending the aforementioned agenda to the server,

[1939] A server provides means for collecting information related to the agenda using generated AI,

[1940] A means for organizing and analyzing the information collected by the server,

[1941] A means of generating a report from the information organized and analyzed by the server,

[1942] A means of sending the report generated by the server to the user's terminal,

[1943] A system including means for the user to view the aforementioned report.

[1944] (Claim 2)

[1945] The system according to claim 1, wherein the generating AI collects information from the internet or an internal database.

[1946] (Claim 3)

[1947] The system according to claim 1, wherein the report is generated in a format including a summary, graphs, and statistical data.

[1948] "Example 1"

[1949] (Claim 1)

[1950] A means for users to input the topics they want to discuss in the meeting,

[1951] A means for transmitting the aforementioned agenda from the terminal to the server,

[1952] A server provides means for creating queries for the generating AI based on the aforementioned agenda,

[1953] A server provides means for collecting information related to the agenda using generated AI,

[1954] A means for organizing and analyzing the information collected by the server,

[1955] A means of generating a report from the information organized and analyzed by the server,

[1956] A means of sending the report generated by the server to the user's terminal,

[1957] A system including means for the user to view the aforementioned report.

[1958] (Claim 2)

[1959] The system according to claim 1, wherein the generating AI collects information from an external or internal information source.

[1960] (Claim 3)

[1961] The system according to claim 1, wherein the report is generated in a format including an abstract, figures, tables, and statistical information.

[1962] "Application Example 1"

[1963] (Claim 1)

[1964] A means for users to input the topics they want to discuss in the meeting,

[1965] Means for sending the aforementioned agenda to the server,

[1966] A server provides means for collecting information related to the agenda using generated AI,

[1967] A means for organizing and analyzing the information collected by the server,

[1968] A means of generating a report from the information organized and analyzed by the server,

[1969] A means of sending the report generated by the server to the user's terminal,

[1970] A means for the user to view the aforementioned report,

[1971] A means for the operator of a virtual store to input meeting agenda items,

[1972] A means of sending agenda items entered from a smart device to a server,

[1973] A means of creating and sending queries to the generating AI,

[1974] A means of collecting market research reports, customer reviews, and sales data using generative AI,

[1975] A method for analyzing collected data, extracting key points, and graphing them,

[1976] Means for creating a detailed report,

[1977] A means of sending the generated report to a smart device,

[1978] A system including means for verifying the aforementioned report.

[1979] (Claim 2)

[1980] The system according to claim 1, wherein the generating AI collects information from the internet or an internal database.

[1981] (Claim 3)

[1982] The system according to claim 1, wherein the report is generated in a format including a summary, graphs, and statistical data.

[1983] "Example 2 of combining an emotion engine"

[1984] (Claim 1)

[1985] A means for users to input the topics they want to discuss in the meeting,

[1986] Means for sending the aforementioned agenda to the server,

[1987] A server provides means for collecting information related to the agenda using generated AI,

[1988] A means for organizing and analyzing the information collected by the server,

[1989] A means by which the server analyzes the user's emotions using an emotion analysis engine,

[1990] A means by which the server adjusts agenda priorities based on user sentiment,

[1991] A means of generating a report from the information organized and analyzed by the server,

[1992] A means of sending the report generated by the server to the user's terminal,

[1993] A system including means for the user to view the aforementioned report.

[1994] (Claim 2)

[1995] The system according to claim 1, wherein the generating AI collects information from the internet or an internal database.

[1996] (Claim 3)

[1997] The system according to claim 1, wherein the report is generated in a format including a summary, graphs, and statistical data.

[1998] "Application example 2 when combining with an emotional engine"

[1999] Rewrite according to the procedure

[2000] (Claim 1)

[2001] A means for users to input the topics they want to discuss in the meeting,

[2002] Means for sending the aforementioned agenda to the server,

[2003] A server provides means for collecting information related to the agenda using generated AI,

[2004] A means for organizing and analyzing the information collected by the server,

[2005] A means of generating a report from the information organized and analyzed by the server,

[2006] A means of sending the report generated by the server to the user's terminal,

[2007] A system including means for the user to view the aforementioned report.

[2008] (Claim 2)

[2009] The system according to claim 1, wherein the generating AI collects information from the internet or an internal database.

[2010] (Claim 3)

[2011] The system according to claim 1, wherein the report is generated in a format including a summary, graphs, and statistical data.

[2012] Rewriting to match the content of the new invention.

[2013] (Claim 1)

[2014] A means for users to input topics for production line improvements they want to make,

[2015] Means for sending the aforementioned agenda to the server,

[2016] A server provides means for collecting information related to the agenda using generated AI,

[2017] A means for organizing and analyzing the information collected by the server,

[2018] A means by which the server uses an emotion engine to recognize the user's emotions,

[2019] A means of adjusting agenda priorities based on the user's sentiment as perceived by the server,

[2020] A means of generating a report from the information organized and analyzed by the server,

[2021] A means of sending the report generated by the server to the user's terminal,

[2022] A system including means for the user to view the aforementioned report.

[2023] (Claim 2)

[2024] The system according to claim 1, wherein the generating AI collects information from the internet or an internal database.

[2025] (Claim 3)

[2026] The system according to claim 1, wherein the report is generated in a format including a summary, graphs, and statistical data. [Explanation of symbols]

[2027] 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 means for users to input the topics they want to discuss in the meeting, Means for sending the aforementioned agenda to the server, A server provides means for collecting information related to the agenda using generated AI, A means for organizing and analyzing the information collected by the server, A means of generating a report from the information organized and analyzed by the server, A means of sending the report generated by the server to the user's terminal, A system including means for the user to view the aforementioned report.

2. The system according to claim 1, wherein the generating AI collects information from the internet or an internal database.

3. The system according to claim 1, wherein the report is generated in a format including a summary, graphs, and statistical data.

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