system

Abstract

We provide the system. [Solution] A method for obtaining real-time information on the usage status of meeting facilities, searching for available meeting facilities, and suggesting them to users, A means for analyzing legal or human resources documents using natural language processing to identify important sections and generate revision suggestions, A method for collecting financial data, analyzing past spending patterns, and proposing the optimal budget allocation, A means to secure real-time information on the reservation status of public resources from citizens and suggest the optimal usage time, A means of generating feedback to notify citizens of important changes and risks in administrative documents, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a 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 the back-office operations of enterprises, the complexity of the conference room reservation procedure, the time required for the management and review of legal and personnel documents, and the lack of real-time cost management are issues. Due to the inefficient performance of these operations, there is a problem that the productivity of employees decreases and the overall business efficiency deteriorates.

Means for Solving the Problems

[0005] This invention provides a system that includes means for acquiring real-time information on the usage status of meeting rooms, searching for available meeting rooms and suggesting them to users; means for analyzing legal or human resources documents using natural language processing to identify important sections and generate revision suggestions; and means for collecting cost data, analyzing past expenditure patterns, and suggesting optimal budget allocation. This system can improve the overall efficiency of back-office operations through streamlining meeting room reservations, accelerating document reviews, and optimizing cost management.

[0006] "Meeting room usage status" refers to information regarding the reservation status and availability of meeting rooms at a specific time.

[0007] "Real-time acquisition" refers to instantly acquiring and processing the latest data at the current time.

[0008] An "available meeting room" refers to a meeting room that is not booked for a specific time slot and is therefore available for use.

[0009] "Means of suggesting to the user" refers to methods and functions that present the user with the optimal option based on the results of the system's automatic analysis.

[0010] "Natural language processing" is the technology that allows computers to understand and analyze human language.

[0011] "Identifying key points" means determining and extracting sections from documents or information that contain particularly important points or risks.

[0012] "Generating revision suggestions" is the process of creating specific advice on areas that need improvement or correction based on the analysis results.

[0013] "Cost data" refers to information about financial expenditures within a company or organization.

[0014] "Analyzing past spending patterns" refers to the process of analyzing the trends and characteristics of past expenditures and deriving meaningful conclusions from that data.

[0015] "Proposing optimal budget allocation" means providing recommendations for allocating limited budgets most efficiently based on the collected data and analysis results.

Brief Explanation of Drawings

[0016] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It 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] It shows an emotion map to which multiple emotions are mapped. [Figure 10] It shows an emotion map to which multiple emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 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 the 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 the emotion engine is combined.

Mode for Carrying Out the Invention

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

[0018] First, the terms used in the following description will be explained.

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

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

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

[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] The system according to the present invention is designed to improve the efficiency of a company's back-office operations. This system includes features for automating meeting room reservations, document review, and real-time cost management. Detailed embodiments of each function are described below.

[0038] About automating meeting room reservations

[0039] In this function, the server retrieves the availability of meeting rooms in real time and stores it in a database. When a user wishes to reserve a meeting room, they send a request to the server via their terminal. The server compares the user's calendar information with the database and suggests the most suitable available meeting room and time to the user.

[0040] For example, if a user requests to hold a meeting on Monday morning next week, the server immediately checks the availability of all meeting rooms on Monday morning next week and suggests the most suitable room. If the user accepts this suggestion, the reservation is confirmed, and that information is reflected in the database.

[0041] About automating document review

[0042] The AI ​​agent on the device automatically analyzes submitted legal and HR documents. When a user uploads a new document to the device, the AI ​​uses natural language processing to analyze its content and identify important sections and areas where risks may be present. Based on the results, the AI ​​automatically generates revision suggestions and notifies the user.

[0043] As a concrete example, when a user uploads a new contract, the device's AI analyzes the clauses and points out high-risk wording or unclear points. The user can then review this and make any necessary corrections.

[0044] Optimizing cost management

[0045] The server collects and analyzes financial data from across the entire company to support cost management. Users can access a dashboard via their terminal to view current spending and past spending patterns. Based on this, the server presents users with optimal budget allocations and cost reduction strategies.

[0046] For example, if a user aims to reduce costs in a particular business unit, the server analyzes the unit's spending patterns and provides suggestions indicating which items are increasing costs and where reductions are possible.

[0047] In this way, this system significantly improves the efficiency of a company's back-office operations through its functions of meeting room reservation, document review, and cost management.

[0048] The following describes the processing flow.

[0049] Step 1:

[0050] The server monitors the current reservation status of all meeting rooms within the company in real time and records the availability data in a database.

[0051] Step 2:

[0052] The user enters a meeting room reservation request from a terminal. The request includes information such as the desired date and time, the number of participants, and the length of the meeting.

[0053] Step 3:

[0054] The server receives a request from the user, searches the database, and identifies an available meeting room that matches the specified criteria.

[0055] Step 4:

[0056] The server retrieves the user's calendar information, matches the available time slots with the user's free time, and generates the optimal reservation suggestion.

[0057] Step 5:

[0058] The terminal displays suggestions from the server to the user, presenting them with options. The user then decides on the option they deem best and confirms it.

[0059] Step 6:

[0060] The device selected by the user confirms the reservation and sends the information to the server.

[0061] Step 7:

[0062] The server updates the database with reservation confirmation information and changes the meeting room schedule. It then provides other users with the latest availability information.

[0063] The automated meeting room reservation process is completed through steps 1 to 7.

[0064] (Example 1)

[0065] 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."

[0066] Many processes in corporate back-office operations, such as meeting room reservations, document review, and cost management, still rely heavily on manual operations, resulting in significant time and effort. This leads to a compromise in decision-making speed and accuracy, and a decline in overall operational efficiency. Therefore, automating these processes is essential to improve operational efficiency and reduce costs.

[0067] 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.

[0068] This invention includes a server that acquires real-time information on the availability of meeting rooms, selects available meeting rooms using optimization calculations and proposes them to the user, analyzes legal or human resources information using information processing technology, generates revised suggestions and notifies the user, and integrates financial information using data collection technology and applies analysis technology to propose the optimal budget allocation. This enables more efficient meeting room reservations, automated document reviews, and optimized financial cost management.

[0069] A "meeting room" is a dedicated space within a company or organization designated for holding meetings and discussions.

[0070] "Real-time" refers to a state where processing or data acquisition occurs almost instantly, with minimal delay.

[0071] "Optimization computation" is a computational method that finds the most efficient or effective solution under given conditions and constraints.

[0072] A "user" is the entity that utilizes a system or tool, and is typically a human being who performs operations and makes decisions.

[0073] "Information processing technology" is a general term for technologies that collect, analyze, manipulate, store, and manage data.

[0074] "Natural language processing" is a technology that enables computers to understand, interpret, and generate human language.

[0075] A "revision proposal" is a suggestion that outlines specific changes or improvements to address identified problems or areas for improvement.

[0076] "Data collection technology" refers to methods for systematically collecting data from diverse sources and accumulating it in a usable format.

[0077] "Financial information" refers to data related to a company's or organization's accounting, expenses, income, assets, liabilities, etc.

[0078] "Analysis techniques" are techniques for analyzing data in detail and extracting useful information and patterns.

[0079] "Budget allocation" is the process of allocating available funds to various activities and projects.

[0080] This invention is a system for streamlining corporate back-office operations, automating processes such as meeting room reservations, document review, and cost management.

[0081] About automating meeting room reservations

[0082] The server works with sensors to obtain real-time information on meeting room availability and collects data via an API. This allows it to store information on available meeting rooms in a database. Users then submit meeting room reservation requests via their devices. The server performs optimization calculations based on the user's calendar information and suggests the most suitable available meeting room and time. For example, if a user enters "I want to hold a meeting next Monday morning," the server will suggest the most suitable meeting room.

[0083] About automating document review

[0084] Users upload legal and HR documents to the system using a terminal. The terminal is equipped with a generative AI model, which analyzes the uploaded documents using natural language processing technology. It automatically generates revision suggestions for important sections and risky parts and notifies the user. For example, when a user uploads a new contract, they can prompt the AI ​​to "point out high-risk wording," and the AI ​​will present the results.

[0085] Optimizing cost management

[0086] The server collects financial data from across the entire company using APIs and builds an integrated database. This database is analyzed using analytical techniques to visualize current spending and past spending patterns. Users can access a dashboard via their terminal to check appropriate cost reduction measures and budget allocations. For example, if a user inputs "Please suggest cost reduction measures for this department," the server will provide suggestions tailored to that department.

[0087] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0088] Step 1:

[0089] The server acquires real-time information on the usage status of meeting rooms. It receives data from sensors and information from the meeting room reservation system as input. The server analyzes this data and stores it in a database along with meeting room availability information. The output is a database containing the latest meeting room status.

[0090] Step 2:

[0091] Users request meeting room reservations through their devices. The input involves the user entering their desired date and time into a calendar app or a dedicated application. The device sends this information to a server, which then compares the received request against its database. The output is a suggestion of the most suitable available meeting room and time.

[0092] Step 3:

[0093] Users upload documents requiring review to the system using a terminal. The input consists of legal and HR documents specified by the user. A generative AI model installed on the terminal analyzes the documents using natural language processing technology. The output provides suggested revisions regarding important sections and areas where risks may be present.

[0094] Step 4:

[0095] The server collects a company's financial data from external systems. The input consists of multiple financial information sources obtained via APIs. The server integrates this data into a database and analyzes spending patterns using analytical techniques. The output includes visualizations of spending patterns and suggestions for optimal budget allocation.

[0096] Step 5:

[0097] Users access the dashboard from their terminals to review and implement data from the server. Inputs consist of analysis results and suggestions sent from the server. Through the dashboard, users evaluate cost management strategies and select appropriate actions. Outputs show cost allocation and implementation status of control measures within the company.

[0098] (Application Example 1)

[0099] 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."

[0100] In modern cities, the efficient use of public facilities and resources remains a major challenge. In particular, there is a need to improve transparency and efficiency regarding reservations for public facilities and feedback on administrative documents. Furthermore, mechanisms are needed that allow citizens and urban administrators to more intuitively understand budget management and make appropriate decisions.

[0101] 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.

[0102] This invention includes a server that provides real-time access to meeting facilities, searches for available facilities, and suggests them to users; a server that analyzes legal or personnel documents using natural language processing to identify key sections and generate revision suggestions; a server that collects financial data, analyzes past expenditure patterns, and proposes optimal budget allocations; a server that provides real-time access to public resource reservations from citizens and suggests optimal usage times; and a server that generates feedback to notify citizens of significant changes and risks in administrative documents. This enables citizens and administrators to utilize public resources and manage budgets efficiently and transparently.

[0103] "Conference facilities" refer to dedicated spaces used for meetings and gatherings, whether public or private.

[0104] "Usage status" refers to information indicating the extent to which a particular facility or resource is being used or reserved.

[0105] "Users" refer to individuals or organizations that use specific facilities, systems, or resources.

[0106] "Legal or personnel documents" refers to official documents related to legal or human resource management.

[0107] "Natural language processing" is a field of technology that enables computers to understand and process human language.

[0108] "Important sections" refer to parts of specific information or documents that deserve particular attention.

[0109] A "suggested correction" is the provision of content regarding changes or adjustments that are recommended to address a specific problem or for improvement.

[0110] "Financial data" refers to numerical information related to the flow of funds and accounting.

[0111] "Spending patterns" refer to trends in the flow and use of funds in the past.

[0112] "Budget allocation" refers to the planned and systematic allocation of resources and funds to specific purposes or departments.

[0113] "Public resources" refer to facilities, equipment, and services used for the benefit of the local community or its citizens as a whole.

[0114] "Feedback" refers to reactions and opinions regarding the information or results provided.

[0115] The system for realizing this invention consists of a server and multiple terminals. To obtain real-time information on the usage status of meeting facilities and to search for and suggest available slots, the server manages facility availability using a cloud database (e.g., Firebase). Upon receiving a reservation request from a terminal, the server compares it with the user's calendar information and suggests the most suitable meeting facility and time. This function is optimized by a generative AI model.

[0116] When handling legal or HR documents, the terminal analyzes the documents using natural language processing (e.g., Google® Cloud Natural Language) to identify important sections and areas of risk, and generates suggested revisions. This process provides real-time feedback to the user.

[0117] Furthermore, the server collects financial data and analyzes past spending patterns to suggest the optimal budget allocation. Users can check their current spending status and budget suggestions through their terminals. Financial information is visualized intuitively using a dashboard.

[0118] For example, if a user wants to reserve a library meeting room using their smartphone, the reservation system checks the library's reservation status and immediately displays availability information. Simultaneously, when administrative documents are made public to residents, important changes are automatically notified using natural language processing.

[0119] An example of a prompt message for a generating AI model might be: "I am trying to check the reservation status in the following public facility reservation system. Please tell me the best time to reserve a meeting room in the community hall next Thursday afternoon."

[0120] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0121] Step 1:

[0122] The terminal accepts input from the user. The user enters a request to reserve a meeting facility on a specific date. This input includes the desired date and time and the purpose of the meeting. This information is sent to the server in real time.

[0123] Step 2:

[0124] The server accesses a cloud database to retrieve the availability of meeting facilities for a specified date and time. As part of the data processing, it cross-references this information with current reservation data to identify available facilities. This process generates a list of available meeting facilities.

[0125] Step 3:

[0126] The server uses a generated AI model to match the user's calendar information with the obtained list of available facilities and select the optimal meeting facility and time. This process involves data calculations that take into account the user's past booking trends and the importance of the meeting. As a result, the most suitable facility and time are selected.

[0127] Step 4:

[0128] The server returns the selection results to the terminal. The terminal displays a pop-up to the user suggesting the most suitable meeting venue and time. The user is then given the option to review, accept, or modify the suggestion. If the user accepts the suggestion, the final booking information is sent to the server and stored in the database.

[0129] Step 5:

[0130] In financial data analysis, the server collects spending data from across the entire company. This includes analyzing past budget usage and detecting outliers. Based on this data, the server processes it using statistical methods and generates reports that propose optimal budget allocation.

[0131] Step 6:

[0132] The terminal displays a dashboard of the generated report to the user. The report includes specific advice on areas where costs can be reduced and areas where investment should be increased. Based on this information, the user can make financial decisions for the company.

[0133] 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.

[0134] The system according to the present invention is a comprehensive system that automates a company's back-office operations and further improves the quality of proposals and business processes by taking user emotions into consideration. This system combines an emotion engine that analyzes user input, enabling detailed responses based on emotions.

[0135] Automating meeting room reservations and emotion recognition

[0136] In the meeting room reservation function, the server processes reservation requests from users, checks calendar information, and suggests available meeting rooms. This is where the emotion engine comes in; it recognizes emotions from user input data, such as voice or text. The terminal sends this emotion data to the server, which uses this information to adjust the suggested meeting rooms and times. For example, if a user is stressed, the server can prioritize suggesting meeting rooms with a quiet environment.

[0137] Document review and sentiment recognition

[0138] In legal and HR document review functions, the device's AI agent analyzes the documents and generates necessary revision suggestions. Furthermore, an emotion engine understands the user's emotional state and optimizes how review results are communicated. For example, if the user is feeling stressed, the system adjusts the explanation to a gentler tone to reduce stress.

[0139] On cost management optimization and sentiment recognition

[0140] Regarding cost data analysis, the server can reflect user sentiment in the cost dashboard and adjust the way suggestions are presented. If the server's analysis indicates that a user is feeling anxious, it will incorporate features to enhance user confidence by providing more detailed explanations and support.

[0141] In this way, systems that incorporate an emotion engine can take user emotions into consideration, enabling more flexible and user-friendly work support. This approach allows for efficiency improvements that are tailored to the user's psychological state, rather than simply carrying out tasks mechanically.

[0142] The following describes the processing flow.

[0143] Step 1:

[0144] The user enters a request to reserve a meeting room into the terminal. Voice input and text input are available at this stage.

[0145] Step 2:

[0146] The device sends user input data to an emotion engine, which analyzes the user's emotions. The analysis results include various emotional states, such as stress levels and satisfaction levels.

[0147] Step 3:

[0148] The server receives emotional data from the terminal, compares it with a database of meeting room usage, and searches for available meeting rooms. During this process, the server takes the user's emotional state into consideration when selecting the most suitable meeting room and time.

[0149] Step 4:

[0150] The server sends suggested meeting rooms and times to the user's device. The suggestions include explanations that take the user's feelings into consideration. For example, a user who wants a relaxed environment will be offered a suggestion for a quiet meeting room.

[0151] Step 5:

[0152] The user reviews the suggestions on their device and confirms the reservation by selecting the most suitable option.

[0153] Step 6:

[0154] The server updates the database with confirmed reservation information and displays the latest meeting room availability for other users.

[0155] Through this process, the automation of meeting room reservations is implemented in a way that takes user emotions into consideration.

[0156] (Example 2)

[0157] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0158] In modern businesses, efficient operations and reducing employee psychological stress are crucial challenges. While conventional business support systems can improve efficiency and convenience, they often fail to provide suggestions and notifications that consider user emotions, resulting in insufficient support for business processes. Therefore, there is a need for systems that take emotions into account and provide more appropriate business support.

[0159] 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.

[0160] This invention includes a server that acquires the usage status of meeting spaces, searches for available meeting spaces and provides them to users, analyzes documents using natural language processing, extracts important elements, and creates revised proposals, collects cost data, evaluates past expenditure trends and proposes appropriate resource allocation, and utilizes an emotion engine that analyzes user emotion data and adjusts the proposed content. This makes it possible to achieve flexible business support and efficiency while taking user emotions into consideration.

[0161] A "meeting space" refers to a physical location or environment used by a company or organization for meetings and discussions.

[0162] "Usage status" indicates how the meeting space is currently being used, such as whether it is reserved or available.

[0163] "Available meeting spaces" refer to meeting spaces that are not currently booked and are available for use.

[0164] "Users" refers to individuals or organizations that use the system to reserve meeting spaces or upload documents.

[0165] "Natural language processing" refers to the technology that enables machines to understand and analyze human language.

[0166] "Key elements" refer to the aspects or parts that require particular attention based on the analysis results.

[0167] A "revised proposal" refers to suggestions for necessary changes or improvements based on the analysis results.

[0168] "Expense data" refers to information about the expenditures made by companies and organizations in various activities.

[0169] "Past spending trends" refers to trends and patterns that can be seen by analyzing past spending data.

[0170] "Resource allocation" refers to the decision of how to distribute the available funds and physical resources within a company or organization.

[0171] "Emotional data" refers to information that indicates a user's psychological state. This information is typically obtained from verbal and nonverbal cues.

[0172] An "emotion engine" refers to a technology or program that analyzes a user's emotions and adjusts the system's operation based on the results.

[0173] "Proposed content" refers to the solutions or recommendations that the system provides to the user.

[0174] This invention is a system that provides business support while taking user emotions into consideration. The main components of the system consist of a server, terminals, and users. Next, we will explain in detail how these components work together.

[0175] First, the user accesses the system using a terminal. This terminal has a built-in emotion engine that processes the user's speech and text input using built-in speech recognition and text analysis software to generate emotion data. This emotion data is then sent from the terminal to the server.

[0176] The server analyzes the received emotional data and other input data to generate suggestions for optimizing business processes. Specifically, the server utilizes a meeting space reservation system, a document analysis engine, and cost analysis tools to provide information optimized for the user's emotions. For meeting space reservations, it checks availability in conjunction with calendar management software and prioritizes quiet spaces.

[0177] Next, in document analysis, the server uses a natural language processing engine to identify key points and an emotion engine to detect the user's psychological state, generating flexible and gentle feedback. This allows users to proceed with their work with confidence.

[0178] Regarding expense data, the server performs analysis based on past spending data and creates more detailed and reassuring budget proposals that reflect user sentiment. During this process, data analysis tools are used to consider budget allocation.

[0179] As a concrete example, consider a scenario where a user texts, "I'd like to book a meeting for tomorrow, preferably in a quiet and relaxing room." The terminal interprets the user's sentiment from this input and notifies the server. Based on this data, the server cross-references it with calendar information and suggests the most suitable meeting space to the user.

[0180] An example of a prompt for a generative AI model would be, "If the user input indicates a need for calmness, suggest a quiet meeting space." This allows users to receive work support tailored to their emotions, improving work efficiency.

[0181] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0182] Step 1:

[0183] Users access the terminal to reserve meeting rooms and upload documents. Specifically, they input the date, time, and requests through the terminal's interface and upload the necessary files. Input includes date and time information, text requests, and document files.

[0184] Step 2:

[0185] The device receives user input data and activates an emotion engine to analyze the user's emotional state. Specifically, it uses speech recognition software and text analysis software to analyze the input text and audio data. The analysis results are output as emotion data indicating the user's emotions.

[0186] Step 3:

[0187] The terminal sends the acquired emotion data to the server. Specifically, it uses its communication module to send reservation requests and document data to the server in packet format along with the emotion data. This input is the data that initiates server processing.

[0188] Step 4:

[0189] The server analyzes the status of the meeting space and the content of the documents based on the received data. The server queries the company's calendar management system for meeting space availability and simultaneously performs natural language processing using a document analysis engine. This results in outputting information on available meeting spaces and key points of the documents.

[0190] Step 5:

[0191] The server selects the optimal meeting space and feedback content based on the user's emotional data. For example, if the emotional data indicates that the user is seeking relaxation, it prioritizes a quiet and calming meeting space. A generative AI model is used to generate more appropriate suggestions and feedback. This result is output as optimized suggestions.

[0192] Step 6:

[0193] The server sends the final proposal to the terminal. The terminal receives it and presents the results to the user through screen displays and notification functions. The output includes meeting space information and feedback messages that the user can select.

[0194] Step 7:

[0195] Based on the information provided, users can book meeting rooms and review documents. If necessary, they can request further revisions or additional bookings. This feedback loop allows the system to continuously improve.

[0196] (Application Example 2)

[0197] 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 device 14 will be referred to as the "terminal."

[0198] In modern business operations, there is a demand not only for increased efficiency in back-office tasks but also for flexible responses tailored to the psychological state of users. However, conventional systems struggle to understand user emotions and optimize accordingly, making new methods for improving user satisfaction desirable.

[0199] 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.

[0200] This invention includes a server that acquires real-time information on the availability of meeting rooms, searches for available meeting rooms and suggests them to users; a server that analyzes official documents using natural language processing, identifies important parts, and generates revision suggestions; a server that collects expense data, analyzes past spending patterns, and suggests the optimal budget allocation; and a server that uses an emotion recognition engine to determine the user's psychological state and optimize their daily activities. This enables the automation of back-office operations as well as flexible work responses that take into account the user's emotions.

[0201] "Meeting room availability" refers to information indicating whether a meeting room is currently in use or available for use.

[0202] An "available meeting room" refers to a meeting room that is currently not being used and is therefore available for booking.

[0203] "Natural language processing" is a technology that allows computers to process human language, and it is used for document analysis and automatic generation.

[0204] An "official document" is a formal document created and shared within an organization, containing important information and procedures.

[0205] "Expense data" refers to a collection of information about expenditures incurred in a company's financial activities, and this data is used for budget management.

[0206] "Expenditure patterns" refer to trends and patterns that show how expenses have been used in the past.

[0207] An "emotion recognition engine" is a software technology that extracts and analyzes human emotions from voice and text data.

[0208] "Psychological state" refers to an individual's internal state, such as their emotions and mood, which influences their behavior and decision-making.

[0209] "Optimizing daily activities" means streamlining daily work and lifestyle habits and making adjustments to meet individual needs.

[0210] The system for carrying out this invention includes the following elements: The server acquires the usage status of meeting rooms in real time and processes them using natural language processing to analyze official documents. It also collects expense data and analyzes past spending patterns. Furthermore, it uses an emotion recognition engine to determine the user's psychological state and optimize work and daily activities.

[0211] The system analyzes voice and text data using an emotion recognition engine to understand the user's emotions. Based on this analysis, it provides suggestions and environments that help the user feel at ease. For example, if the system detects that a user is stressed when booking a meeting room, it will suggest a quiet and calming room. The specific software used includes a natural language processing platform and an AI model for emotion analysis. By leveraging these technologies, it is possible to provide users with the optimal experience.

[0212] As a concrete example, consider the environment in which a home helper device operates. If the device detects from voice data that someone in the family is actually tired, it will play relaxing music or adjust the lighting. By providing this environment, users can reduce their mental burden and live more comfortably. An example of a prompt using a generative AI model is, "Please suggest support that would be helpful when a family member is tired."

[0213] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0214] Step 1:

[0215] The server receives voice or text data from the user. This input data is passed to an emotion recognition engine, which performs analysis to identify human emotions. As a result, the user's psychological state (e.g., stress or fatigue) is output.

[0216] Step 2:

[0217] Based on the obtained psychological state, the server checks the availability of meeting rooms and retrieves information on available rooms. It then executes a database query to extract real-time meeting room occupancy information and generates a list of matching meeting rooms based on that data. Considering the user's state, quiet meeting rooms are prioritized in the output.

[0218] Step 3:

[0219] The server uses a natural language processing engine to analyze official documents uploaded by users. It identifies key sections from the input document, extracts points requiring correction, and generates suggested revisions. The analysis results are then output in a user-friendly format.

[0220] Step 4:

[0221] Users review suggestions from the server on their devices. Especially for sentiment-based suggestions, they receive situation-appropriate options and next actions, which they then apply to their work and daily activities. For example, they can book a recommended meeting room or accept suggestions for document revisions.

[0222] Step 5:

[0223] The terminal sends expense data to the server, which analyzes past spending patterns to calculate the optimal budget allocation. Based on the analyzed data, an output is generated indicating how the budget should be allocated, and a feasible budget proposal tailored to the user is presented.

[0224] 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.

[0225] 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.

[0226] 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.

[0227] [Second Embodiment]

[0228] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0229] 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.

[0230] 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).

[0231] 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.

[0232] 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.

[0233] 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).

[0234] 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.

[0235] 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.

[0236] 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.

[0237] 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.

[0238] 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.

[0239] 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".

[0240] The system according to the present invention is designed to improve the efficiency of a company's back-office operations. This system includes features for automating meeting room reservations, document review, and real-time cost management. Detailed embodiments of each function are described below.

[0241] About automating meeting room reservations

[0242] In this function, the server retrieves the availability of meeting rooms in real time and stores it in a database. When a user wishes to reserve a meeting room, they send a request to the server via their terminal. The server compares the user's calendar information with the database and suggests the most suitable available meeting room and time to the user.

[0243] For example, if a user requests to hold a meeting on Monday morning next week, the server immediately checks the availability of all meeting rooms on Monday morning next week and suggests the most suitable room. If the user accepts this suggestion, the reservation is confirmed, and that information is reflected in the database.

[0244] About automating document review

[0245] The AI ​​agent on the device automatically analyzes submitted legal and HR documents. When a user uploads a new document to the device, the AI ​​uses natural language processing to analyze its content and identify important sections and areas where risks may be present. Based on the results, the AI ​​automatically generates revision suggestions and notifies the user.

[0246] As a concrete example, when a user uploads a new contract, the device's AI analyzes the clauses and points out high-risk wording or unclear points. The user can then review this and make any necessary corrections.

[0247] Optimizing cost management

[0248] The server collects and analyzes financial data from across the entire company to support cost management. Users can access a dashboard via their terminal to view current spending and past spending patterns. Based on this, the server presents users with optimal budget allocations and cost reduction strategies.

[0249] For example, if a user aims to reduce costs in a particular business unit, the server analyzes the unit's spending patterns and provides suggestions indicating which items are increasing costs and where reductions are possible.

[0250] In this way, this system significantly improves the efficiency of a company's back-office operations through its functions of meeting room reservation, document review, and cost management.

[0251] The following describes the processing flow.

[0252] Step 1:

[0253] The server monitors the current reservation status of all meeting rooms within the company in real time and records the availability data in a database.

[0254] Step 2:

[0255] The user enters a meeting room reservation request from a terminal. The request includes information such as the desired date and time, the number of participants, and the length of the meeting.

[0256] Step 3:

[0257] The server receives a request from the user, searches the database, and identifies an available meeting room that matches the specified criteria.

[0258] Step 4:

[0259] The server retrieves the user's calendar information, matches the available time slots with the user's free time, and generates the optimal reservation suggestion.

[0260] Step 5:

[0261] The terminal displays suggestions from the server to the user, presenting them with options. The user then decides on the option they deem best and confirms it.

[0262] Step 6:

[0263] The device selected by the user confirms the reservation and sends the information to the server.

[0264] Step 7:

[0265] The server updates the database with reservation confirmation information and changes the meeting room schedule. It then provides other users with the latest availability information.

[0266] The automated meeting room reservation process is completed through steps 1 to 7.

[0267] (Example 1)

[0268] 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".

[0269] Many processes in corporate back-office operations, such as meeting room reservations, document review, and cost management, still rely heavily on manual operations, resulting in significant time and effort. This leads to a compromise in decision-making speed and accuracy, and a decline in overall operational efficiency. Therefore, automating these processes is essential to improve operational efficiency and reduce costs.

[0270] 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.

[0271] This invention includes a server that acquires real-time information on the availability of meeting rooms, selects available meeting rooms using optimization calculations and proposes them to the user, analyzes legal or human resources information using information processing technology, generates revised suggestions and notifies the user, and integrates financial information using data collection technology and applies analysis technology to propose the optimal budget allocation. This enables more efficient meeting room reservations, automated document reviews, and optimized financial cost management.

[0272] A "meeting room" is a dedicated space within a company or organization designated for holding meetings and discussions.

[0273] "Real-time" refers to a state where processing or data acquisition occurs almost instantly, with minimal delay.

[0274] "Optimization computation" is a computational method that finds the most efficient or effective solution under given conditions and constraints.

[0275] A "user" is the entity that utilizes a system or tool, and is typically a human being who performs operations and makes decisions.

[0276] "Information processing technology" is a general term for technologies that collect, analyze, manipulate, store, and manage data.

[0277] "Natural language processing" is a technology that enables computers to understand, interpret, and generate human language.

[0278] A "revision proposal" is a suggestion that outlines specific changes or improvements to address identified problems or areas for improvement.

[0279] "Data collection technology" refers to methods for systematically collecting data from diverse sources and accumulating it in a usable format.

[0280] "Financial information" refers to data related to a company's or organization's accounting, expenses, income, assets, liabilities, etc.

[0281] "Analysis techniques" are techniques for analyzing data in detail and extracting useful information and patterns.

[0282] "Budget allocation" is the process of allocating available funds to various activities and projects.

[0283] This invention is a system for streamlining corporate back-office operations, automating processes such as meeting room reservations, document review, and cost management.

[0284] About automating meeting room reservations

[0285] The server collaborates with sensors and collects data through APIs in order to obtain the usage status of meeting rooms in real time. As a result, the information of available meeting rooms can be saved in the database. Subsequently, when a user sends a meeting room reservation request via a terminal, the server performs an optimization calculation based on the user's calendar information and proposes the most suitable available meeting room and time to the user. As a specific example, when the user inputs "I want to hold a meeting on Monday morning next week", the server proposes the most suitable meeting room.

[0286] Regarding the automation of document review

[0287] The user uploads legal and human resources documents to the system using a terminal. The terminal is equipped with a generative AI model, and the documents uploaded by this model are analyzed using natural language processing technology. Automatic correction proposals for important parts and risky parts are generated and notified to the user. For example, when the user uploads a new contract and inputs the prompt "Please point out the high-risk statements", the AI presents the results.

[0288] Regarding the optimization of cost management

[0289] The server collects the financial data of the entire enterprise using APIs and constructs an integrated database. This database is analyzed using analysis techniques to visualize the current expenditure status and past expenditure patterns. The user can access the dashboard through the terminal and confirm appropriate cost reduction measures and budget allocations. As a specific example, when the user inputs "Please propose cost reduction measures for this department", the server makes a proposal according to that department.

[0290] The flow of the specific process in Example 1 will be described using FIG. 11.

[0291] Step 1:

[0292] The server acquires real-time information on the usage status of meeting rooms. It receives data from sensors and information from the meeting room reservation system as input. The server analyzes this data and stores it in a database along with meeting room availability information. The output is a database containing the latest meeting room status.

[0293] Step 2:

[0294] Users request meeting room reservations through their devices. The input involves the user entering their desired date and time into a calendar app or a dedicated application. The device sends this information to a server, which then compares the received request against its database. The output is a suggestion of the most suitable available meeting room and time.

[0295] Step 3:

[0296] Users upload documents requiring review to the system using a terminal. The input consists of legal and HR documents specified by the user. A generative AI model installed on the terminal analyzes the documents using natural language processing technology. The output provides suggested revisions regarding important sections and areas where risks may be present.

[0297] Step 4:

[0298] The server collects a company's financial data from external systems. The input consists of multiple financial information sources obtained via APIs. The server integrates this data into a database and analyzes spending patterns using analytical techniques. The output includes visualizations of spending patterns and suggestions for optimal budget allocation.

[0299] Step 5:

[0300] Users access the dashboard from their terminals to review and implement data from the server. Inputs consist of analysis results and suggestions sent from the server. Through the dashboard, users evaluate cost management strategies and select appropriate actions. Outputs show cost allocation and implementation status of control measures within the company.

[0301] (Application Example 1)

[0302] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[0303] In modern cities, the efficient use of public facilities and resources remains a major issue. In particular, there is a need to improve the transparency and efficiency regarding the reservation of public facilities and the feedback of administrative documents. Also, a mechanism is required that enables citizens and city administrators to intuitively understand budget management and make appropriate decisions.

[0304] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0305] In this invention, the server includes means for obtaining the utilization status of conference facilities in real time, searching for available conference facilities and proposing them to users; means for analyzing legal or personnel documents by natural language processing to identify important parts and generating modification proposals; means for collecting financial data, analyzing past expenditure patterns and proposing optimal budget allocation; means for ensuring the reservation status of public resources from citizens in real time and proposing optimal usage times; and means for generating feedback for notifying citizens of important change points and risks in administrative documents. As a result, citizens and administrators can use public resources and manage budgets efficiently and transparently.

[0306] "Conference facilities" refers to dedicated spaces for meetings and gatherings used in public or private settings.

[0307] "Utilization status" refers to information indicating the state of how much a specific facility or resource is being used or reserved.

[0308] "Users" refers to people or organizations that use specific facilities, systems, or resources.

[0309] "Legal or personnel documents" refers to official documents related to legal or human resource management.

[0310] "Natural language processing" is a field of technology that enables computers to understand and process human language.

[0311] "Important sections" refer to parts of specific information or documents that deserve particular attention.

[0312] A "suggested correction" is the provision of content regarding changes or adjustments that are recommended to address a specific problem or for improvement.

[0313] "Financial data" refers to numerical information related to the flow of funds and accounting.

[0314] "Spending patterns" refer to trends in the flow and use of funds in the past.

[0315] "Budget allocation" refers to the planned and systematic allocation of resources and funds to specific purposes or departments.

[0316] "Public resources" refer to facilities, equipment, and services used for the benefit of the local community or its citizens as a whole.

[0317] "Feedback" refers to reactions and opinions regarding the information or results provided.

[0318] The system for realizing this invention consists of a server and multiple terminals. To obtain real-time information on the usage status of meeting facilities and to search for and suggest available slots, the server manages facility availability using a cloud database (e.g., Firebase). Upon receiving a reservation request from a terminal, the server compares it with the user's calendar information and suggests the most suitable meeting facility and time. This function is optimized by a generative AI model.

[0319] When handling legal or HR documents, the terminal analyzes the documents using natural language processing (e.g., Google Cloud Natural Language) to identify critical sections and areas of risk, and generates suggested revisions. This process provides real-time feedback to the user.

[0320] Furthermore, the server collects financial data and analyzes past spending patterns to suggest the optimal budget allocation. Users can check their current spending status and budget suggestions through their terminals. Financial information is visualized intuitively using a dashboard.

[0321] For example, if a user wants to reserve a library meeting room using their smartphone, the reservation system checks the library's reservation status and immediately displays availability information. Simultaneously, when administrative documents are made public to residents, important changes are automatically notified using natural language processing.

[0322] An example of a prompt message for a generating AI model might be: "I am trying to check the reservation status in the following public facility reservation system. Please tell me the best time to reserve a meeting room in the community hall next Thursday afternoon."

[0323] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0324] Step 1:

[0325] The terminal accepts input from the user. The user enters a request to reserve a meeting facility on a specific date. This input includes the desired date and time and the purpose of the meeting. This information is sent to the server in real time.

[0326] Step 2:

[0327] The server accesses a cloud database to retrieve the availability of meeting facilities for a specified date and time. As part of the data processing, it cross-references this information with current reservation data to identify available facilities. This process generates a list of available meeting facilities.

[0328] Step 3:

[0329] The server uses a generated AI model to match the user's calendar information with the obtained list of available facilities and select the optimal meeting facility and time. This process involves data calculations that take into account the user's past booking trends and the importance of the meeting. As a result, the most suitable facility and time are selected.

[0330] Step 4:

[0331] The server returns the selection results to the terminal. The terminal displays a pop-up to the user suggesting the most suitable meeting venue and time. The user is then given the option to review, accept, or modify the suggestion. If the user accepts the suggestion, the final booking information is sent to the server and stored in the database.

[0332] Step 5:

[0333] In financial data analysis, the server collects spending data from across the entire company. This includes analyzing past budget usage and detecting outliers. Based on this data, the server processes it using statistical methods and generates reports that propose optimal budget allocation.

[0334] Step 6:

[0335] The terminal displays a dashboard of the generated report to the user. The report includes specific advice on areas where costs can be reduced and areas where investment should be increased. Based on this information, the user can make financial decisions for the company.

[0336] 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.

[0337] The system according to the present invention is a comprehensive system that automates a company's back-office operations and further improves the quality of proposals and business processes by taking user emotions into consideration. This system combines an emotion engine that analyzes user input, enabling detailed responses based on emotions.

[0338] Automating meeting room reservations and emotion recognition

[0339] In the meeting room reservation function, the server processes reservation requests from users, checks calendar information, and suggests available meeting rooms. This is where the emotion engine comes in; it recognizes emotions from user input data, such as voice or text. The terminal sends this emotion data to the server, which uses this information to adjust the suggested meeting rooms and times. For example, if a user is stressed, the server can prioritize suggesting meeting rooms with a quiet environment.

[0340] Document review and sentiment recognition

[0341] In legal and HR document review functions, the device's AI agent analyzes the documents and generates necessary revision suggestions. Furthermore, an emotion engine understands the user's emotional state and optimizes how review results are communicated. For example, if the user is feeling stressed, the system adjusts the explanation to a gentler tone to reduce stress.

[0342] On cost management optimization and sentiment recognition

[0343] Regarding cost data analysis, the server can reflect user sentiment in the cost dashboard and adjust the way suggestions are presented. If the server's analysis indicates that a user is feeling anxious, it will incorporate features to enhance user confidence by providing more detailed explanations and support.

[0344] In this way, systems that incorporate an emotion engine can take user emotions into consideration, enabling more flexible and user-friendly work support. This approach allows for efficiency improvements that are tailored to the user's psychological state, rather than simply carrying out tasks mechanically.

[0345] The following describes the processing flow.

[0346] Step 1:

[0347] The user enters a request to reserve a meeting room into the terminal. Voice input and text input are available at this stage.

[0348] Step 2:

[0349] The device sends user input data to an emotion engine, which analyzes the user's emotions. The analysis results include various emotional states, such as stress levels and satisfaction levels.

[0350] Step 3:

[0351] The server receives emotional data from the terminal, compares it with a database of meeting room usage, and searches for available meeting rooms. During this process, the server takes the user's emotional state into consideration when selecting the most suitable meeting room and time.

[0352] Step 4:

[0353] The server sends suggested meeting rooms and times to the user's device. The suggestions include explanations that take the user's feelings into consideration. For example, a user who wants a relaxed environment will be offered a suggestion for a quiet meeting room.

[0354] Step 5:

[0355] The user reviews the suggestions on their device and confirms the reservation by selecting the most suitable option.

[0356] Step 6:

[0357] The server updates the database with confirmed reservation information and displays the latest meeting room availability for other users.

[0358] Through this process, the automation of meeting room reservations is implemented in a way that takes user emotions into consideration.

[0359] (Example 2)

[0360] 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".

[0361] In modern businesses, efficient operations and reducing employee psychological stress are crucial challenges. While conventional business support systems can improve efficiency and convenience, they often fail to provide suggestions and notifications that consider user emotions, resulting in insufficient support for business processes. Therefore, there is a need for systems that take emotions into account and provide more appropriate business support.

[0362] 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.

[0363] This invention includes a server that acquires the usage status of meeting spaces, searches for available meeting spaces and provides them to users, analyzes documents using natural language processing, extracts important elements, and creates revised proposals, collects cost data, evaluates past expenditure trends and proposes appropriate resource allocation, and utilizes an emotion engine that analyzes user emotion data and adjusts the proposed content. This makes it possible to achieve flexible business support and efficiency while taking user emotions into consideration.

[0364] A "meeting space" refers to a physical location or environment used by a company or organization for meetings and discussions.

[0365] "Usage status" indicates how the meeting space is currently being used, such as whether it is reserved or available.

[0366] "Available meeting spaces" refer to meeting spaces that are not currently booked and are available for use.

[0367] "Users" refers to individuals or organizations that use the system to reserve meeting spaces or upload documents.

[0368] "Natural language processing" refers to the technology that enables machines to understand and analyze human language.

[0369] "Key elements" refer to the aspects or parts that require particular attention based on the analysis results.

[0370] A "revised proposal" refers to suggestions for necessary changes or improvements based on the analysis results.

[0371] "Expense data" refers to information about the expenditures made by companies and organizations in various activities.

[0372] "Past spending trends" refers to trends and patterns that can be seen by analyzing past spending data.

[0373] "Resource allocation" refers to the decision of how to distribute the available funds and physical resources within a company or organization.

[0374] "Emotional data" refers to information that indicates a user's psychological state. This information is typically obtained from verbal and nonverbal cues.

[0375] An "emotion engine" refers to a technology or program that analyzes a user's emotions and adjusts the system's operation based on the results.

[0376] "Proposed content" refers to the solutions or recommendations that the system provides to the user.

[0377] This invention is a system that provides business support while taking user emotions into consideration. The main components of the system consist of a server, terminals, and users. Next, we will explain in detail how these components work together.

[0378] First, the user accesses the system using a terminal. This terminal has a built-in emotion engine that processes the user's speech and text input using built-in speech recognition and text analysis software to generate emotion data. This emotion data is then sent from the terminal to the server.

[0379] The server analyzes the received emotional data and other input data to generate suggestions for optimizing business processes. Specifically, the server utilizes a meeting space reservation system, a document analysis engine, and cost analysis tools to provide information optimized for the user's emotions. For meeting space reservations, it checks availability in conjunction with calendar management software and prioritizes quiet spaces.

[0380] Next, in document analysis, the server uses a natural language processing engine to identify key points and an emotion engine to detect the user's psychological state, generating flexible and gentle feedback. This allows users to proceed with their work with confidence.

[0381] Regarding expense data, the server performs analysis based on past spending data and creates more detailed and reassuring budget proposals that reflect user sentiment. During this process, data analysis tools are used to consider budget allocation.

[0382] As a concrete example, consider a scenario where a user texts, "I'd like to book a meeting for tomorrow, preferably in a quiet and relaxing room." The terminal interprets the user's sentiment from this input and notifies the server. Based on this data, the server cross-references it with calendar information and suggests the most suitable meeting space to the user.

[0383] An example of a prompt for a generative AI model would be, "If the user input indicates a need for calmness, suggest a quiet meeting space." This allows users to receive work support tailored to their emotions, improving work efficiency.

[0384] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0385] Step 1:

[0386] Users access the terminal to reserve meeting rooms and upload documents. Specifically, they input the date, time, and requests through the terminal's interface and upload the necessary files. Input includes date and time information, text requests, and document files.

[0387] Step 2:

[0388] The device receives user input data and activates an emotion engine to analyze the user's emotional state. Specifically, it uses speech recognition software and text analysis software to analyze the input text and audio data. The analysis results are output as emotion data indicating the user's emotions.

[0389] Step 3:

[0390] The terminal sends the acquired emotion data to the server. Specifically, it uses its communication module to send reservation requests and document data to the server in packet format along with the emotion data. This input is the data that initiates server processing.

[0391] Step 4:

[0392] The server analyzes the status of the meeting space and the content of the documents based on the received data. The server queries the company's calendar management system for meeting space availability and simultaneously performs natural language processing using a document analysis engine. This results in outputting information on available meeting spaces and key points of the documents.

[0393] Step 5:

[0394] The server selects the optimal meeting space and feedback content based on the user's emotional data. For example, if the emotional data indicates that the user is seeking relaxation, it prioritizes a quiet and calming meeting space. A generative AI model is used to generate more appropriate suggestions and feedback. This result is output as optimized suggestions.

[0395] Step 6:

[0396] The server sends the final proposal to the terminal. The terminal receives it and presents the results to the user through screen displays and notification functions. The output includes meeting space information and feedback messages that the user can select.

[0397] Step 7:

[0398] Based on the information provided, users can book meeting rooms and review documents. If necessary, they can request further revisions or additional bookings. This feedback loop allows the system to continuously improve.

[0399] (Application Example 2)

[0400] 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."

[0401] In modern business operations, there is a demand not only for increased efficiency in back-office tasks but also for flexible responses tailored to the psychological state of users. However, conventional systems struggle to understand user emotions and optimize accordingly, making new methods for improving user satisfaction desirable.

[0402] 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.

[0403] This invention includes a server that acquires real-time information on the availability of meeting rooms, searches for available meeting rooms and suggests them to users; a server that analyzes official documents using natural language processing, identifies important parts, and generates revision suggestions; a server that collects expense data, analyzes past spending patterns, and suggests the optimal budget allocation; and a server that uses an emotion recognition engine to determine the user's psychological state and optimize their daily activities. This enables the automation of back-office operations as well as flexible work responses that take into account the user's emotions.

[0404] "Meeting room availability" refers to information indicating whether a meeting room is currently in use or available for use.

[0405] An "available meeting room" refers to a meeting room that is currently not being used and is therefore available for booking.

[0406] "Natural language processing" is a technology that allows computers to process human language, and it is used for document analysis and automatic generation.

[0407] An "official document" is a formal document created and shared within an organization, containing important information and procedures.

[0408] "Expense data" refers to a collection of information about expenditures incurred in a company's financial activities, and this data is used for budget management.

[0409] "Expenditure patterns" refer to trends and patterns that show how expenses have been used in the past.

[0410] An "emotion recognition engine" is a software technology that extracts and analyzes human emotions from voice and text data.

[0411] "Psychological state" refers to an individual's internal state, such as their emotions and mood, which influences their behavior and decision-making.

[0412] "Optimizing daily activities" means streamlining daily work and lifestyle habits and making adjustments to meet individual needs.

[0413] The system for carrying out this invention includes the following elements: The server acquires the usage status of meeting rooms in real time and processes them using natural language processing to analyze official documents. It also collects expense data and analyzes past spending patterns. Furthermore, it uses an emotion recognition engine to determine the user's psychological state and optimize work and daily activities.

[0414] The system analyzes voice and text data using an emotion recognition engine to understand the user's emotions. Based on this analysis, it provides suggestions and environments that help the user feel at ease. For example, if the system detects that a user is stressed when booking a meeting room, it will suggest a quiet and calming room. The specific software used includes a natural language processing platform and an AI model for emotion analysis. By leveraging these technologies, it is possible to provide users with the optimal experience.

[0415] As a concrete example, consider the environment in which a home helper device operates. If the device detects from voice data that someone in the family is actually tired, it will play relaxing music or adjust the lighting. By providing this environment, users can reduce their mental burden and live more comfortably. An example of a prompt using a generative AI model is, "Please suggest support that would be helpful when a family member is tired."

[0416] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0417] Step 1:

[0418] The server receives voice or text data from the user. This input data is passed to an emotion recognition engine, which performs analysis to identify human emotions. As a result, the user's psychological state (e.g., stress or fatigue) is output.

[0419] Step 2:

[0420] Based on the obtained psychological state, the server checks the availability of meeting rooms and retrieves information on available rooms. It then executes a database query to extract real-time meeting room occupancy information and generates a list of matching meeting rooms based on that data. Considering the user's state, quiet meeting rooms are prioritized in the output.

[0421] Step 3:

[0422] The server uses a natural language processing engine to analyze official documents uploaded by users. It identifies key sections from the input document, extracts points requiring correction, and generates suggested revisions. The analysis results are then output in a user-friendly format.

[0423] Step 4:

[0424] Users review suggestions from the server on their devices. Especially for sentiment-based suggestions, they receive situation-appropriate options and next actions, which they then apply to their work and daily activities. For example, they can book a recommended meeting room or accept suggestions for document revisions.

[0425] Step 5:

[0426] The terminal sends expense data to the server, which analyzes past spending patterns to calculate the optimal budget allocation. Based on the analyzed data, an output is generated indicating how the budget should be allocated, and a feasible budget proposal tailored to the user is presented.

[0427] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0428] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0429] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0430] [Third Embodiment]

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

[0432] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0433] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0434] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0435] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0436] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0437] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0438] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0439] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0440] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0441] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0442] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0443] The system according to the present invention is designed to improve the efficiency of a company's back-office operations. This system includes features for automating meeting room reservations, document review, and real-time cost management. Detailed embodiments of each function are described below.

[0444] About automating meeting room reservations

[0445] In this function, the server retrieves the availability of meeting rooms in real time and stores it in a database. When a user wishes to reserve a meeting room, they send a request to the server via their terminal. The server compares the user's calendar information with the database and suggests the most suitable available meeting room and time to the user.

[0446] For example, if a user requests to hold a meeting on Monday morning next week, the server immediately checks the availability of all meeting rooms on Monday morning next week and suggests the most suitable room. If the user accepts this suggestion, the reservation is confirmed, and that information is reflected in the database.

[0447] About automating document review

[0448] The AI ​​agent on the device automatically analyzes submitted legal and HR documents. When a user uploads a new document to the device, the AI ​​uses natural language processing to analyze its content and identify important sections and areas where risks may be present. Based on the results, the AI ​​automatically generates revision suggestions and notifies the user.

[0449] As a concrete example, when a user uploads a new contract, the device's AI analyzes the clauses and points out high-risk wording or unclear points. The user can then review this and make any necessary corrections.

[0450] Optimizing cost management

[0451] The server collects and analyzes financial data from across the entire company to support cost management. Users can access a dashboard via their terminal to view current spending and past spending patterns. Based on this, the server presents users with optimal budget allocations and cost reduction strategies.

[0452] For example, if a user aims to reduce costs in a particular business unit, the server analyzes the unit's spending patterns and provides suggestions indicating which items are increasing costs and where reductions are possible.

[0453] In this way, this system significantly improves the efficiency of a company's back-office operations through its functions of meeting room reservation, document review, and cost management.

[0454] The following describes the processing flow.

[0455] Step 1:

[0456] The server monitors the current reservation status of all meeting rooms within the company in real time and records the availability data in a database.

[0457] Step 2:

[0458] The user enters a meeting room reservation request from a terminal. The request includes information such as the desired date and time, the number of participants, and the length of the meeting.

[0459] Step 3:

[0460] The server receives a request from the user, searches the database, and identifies an available meeting room that matches the specified criteria.

[0461] Step 4:

[0462] The server retrieves the user's calendar information, matches the available time slots with the user's free time, and generates the optimal reservation suggestion.

[0463] Step 5:

[0464] The terminal displays suggestions from the server to the user, presenting them with options. The user then decides on the option they deem best and confirms it.

[0465] Step 6:

[0466] The device selected by the user confirms the reservation and sends the information to the server.

[0467] Step 7:

[0468] The server updates the database with reservation confirmation information and changes the meeting room schedule. It then provides other users with the latest availability information.

[0469] The automated meeting room reservation process is completed through steps 1 to 7.

[0470] (Example 1)

[0471] 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."

[0472] Many processes in corporate back-office operations, such as meeting room reservations, document review, and cost management, still rely heavily on manual operations, resulting in significant time and effort. This leads to a compromise in decision-making speed and accuracy, and a decline in overall operational efficiency. Therefore, automating these processes is essential to improve operational efficiency and reduce costs.

[0473] 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.

[0474] This invention includes a server that acquires real-time information on the availability of meeting rooms, selects available meeting rooms using optimization calculations and proposes them to the user, analyzes legal or human resources information using information processing technology, generates revised suggestions and notifies the user, and integrates financial information using data collection technology and applies analysis technology to propose the optimal budget allocation. This enables more efficient meeting room reservations, automated document reviews, and optimized financial cost management.

[0475] A "meeting room" is a dedicated space within a company or organization designated for holding meetings and discussions.

[0476] "Real-time" refers to a state where processing or data acquisition occurs almost instantly, with minimal delay.

[0477] "Optimization computation" is a computational method that finds the most efficient or effective solution under given conditions and constraints.

[0478] A "user" is the entity that utilizes a system or tool, and is typically a human being who performs operations and makes decisions.

[0479] "Information processing technology" is a general term for technologies that collect, analyze, manipulate, store, and manage data.

[0480] "Natural language processing" is a technology that enables computers to understand, interpret, and generate human language.

[0481] A "revision proposal" is a suggestion that outlines specific changes or improvements to address identified problems or areas for improvement.

[0482] "Data collection technology" refers to methods for systematically collecting data from diverse sources and accumulating it in a usable format.

[0483] "Financial information" refers to data related to a company's or organization's accounting, expenses, income, assets, liabilities, etc.

[0484] "Analysis techniques" are techniques for analyzing data in detail and extracting useful information and patterns.

[0485] "Budget allocation" is the process of allocating available funds to various activities and projects.

[0486] This invention is a system for streamlining corporate back-office operations, automating processes such as meeting room reservations, document review, and cost management.

[0487] About automating meeting room reservations

[0488] The server works with sensors to obtain real-time information on meeting room availability and collects data via an API. This allows it to store information on available meeting rooms in a database. Users then submit meeting room reservation requests via their devices. The server performs optimization calculations based on the user's calendar information and suggests the most suitable available meeting room and time. For example, if a user enters "I want to hold a meeting next Monday morning," the server will suggest the most suitable meeting room.

[0489] About automating document review

[0490] Users upload legal and HR documents to the system using a terminal. The terminal is equipped with a generative AI model, which analyzes the uploaded documents using natural language processing technology. It automatically generates revision suggestions for important sections and risky parts and notifies the user. For example, when a user uploads a new contract, they can prompt the AI ​​to "point out high-risk wording," and the AI ​​will present the results.

[0491] Optimizing cost management

[0492] The server collects financial data from across the entire company using APIs and builds an integrated database. This database is analyzed using analytical techniques to visualize current spending and past spending patterns. Users can access a dashboard via their terminal to check appropriate cost reduction measures and budget allocations. For example, if a user inputs "Please suggest cost reduction measures for this department," the server will provide suggestions tailored to that department.

[0493] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0494] Step 1:

[0495] The server acquires real-time information on the usage status of meeting rooms. It receives data from sensors and information from the meeting room reservation system as input. The server analyzes this data and stores it in a database along with meeting room availability information. The output is a database containing the latest meeting room status.

[0496] Step 2:

[0497] Users request meeting room reservations through their devices. The input involves the user entering their desired date and time into a calendar app or a dedicated application. The device sends this information to a server, which then compares the received request against its database. The output is a suggestion of the most suitable available meeting room and time.

[0498] Step 3:

[0499] Users upload documents requiring review to the system using a terminal. The input consists of legal and HR documents specified by the user. A generative AI model installed on the terminal analyzes the documents using natural language processing technology. The output provides suggested revisions regarding important sections and areas where risks may be present.

[0500] Step 4:

[0501] The server collects a company's financial data from external systems. The input consists of multiple financial information sources obtained via APIs. The server integrates this data into a database and analyzes spending patterns using analytical techniques. The output includes visualizations of spending patterns and suggestions for optimal budget allocation.

[0502] Step 5:

[0503] Users access the dashboard from their terminals to review and implement data from the server. Inputs consist of analysis results and suggestions sent from the server. Through the dashboard, users evaluate cost management strategies and select appropriate actions. Outputs show cost allocation and implementation status of control measures within the company.

[0504] (Application Example 1)

[0505] 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."

[0506] In modern cities, the efficient use of public facilities and resources remains a major challenge. In particular, there is a need to improve transparency and efficiency regarding reservations for public facilities and feedback on administrative documents. Furthermore, mechanisms are needed that allow citizens and urban administrators to more intuitively understand budget management and make appropriate decisions.

[0507] 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.

[0508] This invention includes a server that provides real-time access to meeting facilities, searches for available facilities, and suggests them to users; a server that analyzes legal or personnel documents using natural language processing to identify key sections and generate revision suggestions; a server that collects financial data, analyzes past expenditure patterns, and proposes optimal budget allocations; a server that provides real-time access to public resource reservations from citizens and suggests optimal usage times; and a server that generates feedback to notify citizens of significant changes and risks in administrative documents. This enables citizens and administrators to utilize public resources and manage budgets efficiently and transparently.

[0509] "Conference facilities" refer to dedicated spaces used for meetings and gatherings, whether public or private.

[0510] "Usage status" refers to information indicating the extent to which a particular facility or resource is being used or reserved.

[0511] "Users" refer to individuals or organizations that use specific facilities, systems, or resources.

[0512] "Legal or personnel documents" refers to official documents related to legal or human resource management.

[0513] "Natural language processing" is a field of technology that enables computers to understand and process human language.

[0514] "Important sections" refer to parts of specific information or documents that deserve particular attention.

[0515] A "suggested correction" is the provision of content regarding changes or adjustments that are recommended to address a specific problem or for improvement.

[0516] "Financial data" refers to numerical information related to the flow of funds and accounting.

[0517] "Spending patterns" refer to trends in the flow and use of funds in the past.

[0518] "Budget allocation" refers to the planned and systematic allocation of resources and funds to specific purposes or departments.

[0519] "Public resources" refer to facilities, equipment, and services used for the benefit of the local community or its citizens as a whole.

[0520] "Feedback" refers to reactions and opinions regarding the information or results provided.

[0521] The system for realizing this invention consists of a server and multiple terminals. To obtain real-time information on the usage status of meeting facilities and to search for and suggest available slots, the server manages facility availability using a cloud database (e.g., Firebase). Upon receiving a reservation request from a terminal, the server compares it with the user's calendar information and suggests the most suitable meeting facility and time. This function is optimized by a generative AI model.

[0522] When handling legal or HR documents, the terminal analyzes the documents using natural language processing (e.g., Google Cloud Natural Language) to identify critical sections and areas of risk, and generates suggested revisions. This process provides real-time feedback to the user.

[0523] Furthermore, the server collects financial data and analyzes past spending patterns to suggest the optimal budget allocation. Users can check their current spending status and budget suggestions through their terminals. Financial information is visualized intuitively using a dashboard.

[0524] For example, if a user wants to reserve a library meeting room using their smartphone, the reservation system checks the library's reservation status and immediately displays availability information. Simultaneously, when administrative documents are made public to residents, important changes are automatically notified using natural language processing.

[0525] An example of a prompt message for a generating AI model might be: "I am trying to check the reservation status in the following public facility reservation system. Please tell me the best time to reserve a meeting room in the community hall next Thursday afternoon."

[0526] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0527] Step 1:

[0528] The terminal accepts input from the user. The user enters a request to reserve a meeting facility on a specific date. This input includes the desired date and time and the purpose of the meeting. This information is sent to the server in real time.

[0529] Step 2:

[0530] The server accesses a cloud database to retrieve the availability of meeting facilities for a specified date and time. As part of the data processing, it cross-references this information with current reservation data to identify available facilities. This process generates a list of available meeting facilities.

[0531] Step 3:

[0532] The server uses a generated AI model to match the user's calendar information with the obtained list of available facilities and select the optimal meeting facility and time. This process involves data calculations that take into account the user's past booking trends and the importance of the meeting. As a result, the most suitable facility and time are selected.

[0533] Step 4:

[0534] The server returns the selection results to the terminal. The terminal displays a pop-up to the user suggesting the most suitable meeting venue and time. The user is then given the option to review, accept, or modify the suggestion. If the user accepts the suggestion, the final booking information is sent to the server and stored in the database.

[0535] Step 5:

[0536] In financial data analysis, the server collects spending data from across the entire company. This includes analyzing past budget usage and detecting outliers. Based on this data, the server processes it using statistical methods and generates reports that propose optimal budget allocation.

[0537] Step 6:

[0538] The terminal displays a dashboard of the generated report to the user. The report includes specific advice on areas where costs can be reduced and areas where investment should be increased. Based on this information, the user can make financial decisions for the company.

[0539] 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.

[0540] The system according to the present invention is a comprehensive system that automates a company's back-office operations and further improves the quality of proposals and business processes by taking user emotions into consideration. This system combines an emotion engine that analyzes user input, enabling detailed responses based on emotions.

[0541] Automating meeting room reservations and emotion recognition

[0542] In the meeting room reservation function, the server processes reservation requests from users, checks calendar information, and suggests available meeting rooms. This is where the emotion engine comes in; it recognizes emotions from user input data, such as voice or text. The terminal sends this emotion data to the server, which uses this information to adjust the suggested meeting rooms and times. For example, if a user is stressed, the server can prioritize suggesting meeting rooms with a quiet environment.

[0543] Document review and sentiment recognition

[0544] In legal and HR document review functions, the device's AI agent analyzes the documents and generates necessary revision suggestions. Furthermore, an emotion engine understands the user's emotional state and optimizes how review results are communicated. For example, if the user is feeling stressed, the system adjusts the explanation to a gentler tone to reduce stress.

[0545] On cost management optimization and sentiment recognition

[0546] Regarding cost data analysis, the server can reflect user sentiment in the cost dashboard and adjust the way suggestions are presented. If the server's analysis indicates that a user is feeling anxious, it will incorporate features to enhance user confidence by providing more detailed explanations and support.

[0547] In this way, systems that incorporate an emotion engine can take user emotions into consideration, enabling more flexible and user-friendly work support. This approach allows for efficiency improvements that are tailored to the user's psychological state, rather than simply carrying out tasks mechanically.

[0548] The following describes the processing flow.

[0549] Step 1:

[0550] The user enters a request to reserve a meeting room into the terminal. Voice input and text input are available at this stage.

[0551] Step 2:

[0552] The device sends user input data to an emotion engine, which analyzes the user's emotions. The analysis results include various emotional states, such as stress levels and satisfaction levels.

[0553] Step 3:

[0554] The server receives emotional data from the terminal, compares it with a database of meeting room usage, and searches for available meeting rooms. During this process, the server takes the user's emotional state into consideration when selecting the most suitable meeting room and time.

[0555] Step 4:

[0556] The server sends suggested meeting rooms and times to the user's device. The suggestions include explanations that take the user's feelings into consideration. For example, a user who wants a relaxed environment will be offered a suggestion for a quiet meeting room.

[0557] Step 5:

[0558] The user reviews the suggestions on their device and confirms the reservation by selecting the most suitable option.

[0559] Step 6:

[0560] The server updates the database with confirmed reservation information and displays the latest meeting room availability for other users.

[0561] Through this process, the automation of meeting room reservations is implemented in a way that takes user emotions into consideration.

[0562] (Example 2)

[0563] 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."

[0564] In modern businesses, efficient operations and reducing employee psychological stress are crucial challenges. While conventional business support systems can improve efficiency and convenience, they often fail to provide suggestions and notifications that consider user emotions, resulting in insufficient support for business processes. Therefore, there is a need for systems that take emotions into account and provide more appropriate business support.

[0565] 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.

[0566] This invention includes a server that acquires the usage status of meeting spaces, searches for available meeting spaces and provides them to users, analyzes documents using natural language processing, extracts important elements, and creates revised proposals, collects cost data, evaluates past expenditure trends and proposes appropriate resource allocation, and utilizes an emotion engine that analyzes user emotion data and adjusts the proposed content. This makes it possible to achieve flexible business support and efficiency while taking user emotions into consideration.

[0567] A "meeting space" refers to a physical location or environment used by a company or organization for meetings and discussions.

[0568] "Usage status" indicates how the meeting space is currently being used, such as whether it is reserved or available.

[0569] "Available meeting spaces" refer to meeting spaces that are not currently booked and are available for use.

[0570] "Users" refers to individuals or organizations that use the system to reserve meeting spaces or upload documents.

[0571] "Natural language processing" refers to the technology that enables machines to understand and analyze human language.

[0572] "Key elements" refer to the aspects or parts that require particular attention based on the analysis results.

[0573] A "revised proposal" refers to suggestions for necessary changes or improvements based on the analysis results.

[0574] "Expense data" refers to information about the expenditures made by companies and organizations in various activities.

[0575] "Past spending trends" refers to trends and patterns that can be seen by analyzing past spending data.

[0576] "Resource allocation" refers to the decision of how to distribute the available funds and physical resources within a company or organization.

[0577] "Emotional data" refers to information that indicates a user's psychological state. This information is typically obtained from verbal and nonverbal cues.

[0578] An "emotion engine" refers to a technology or program that analyzes a user's emotions and adjusts the system's operation based on the results.

[0579] "Proposed content" refers to the solutions or recommendations that the system provides to the user.

[0580] This invention is a system that provides business support while taking user emotions into consideration. The main components of the system consist of a server, terminals, and users. Next, we will explain in detail how these components work together.

[0581] First, the user accesses the system using a terminal. This terminal has a built-in emotion engine that processes the user's speech and text input using built-in speech recognition and text analysis software to generate emotion data. This emotion data is then sent from the terminal to the server.

[0582] The server analyzes the received emotional data and other input data to generate suggestions for optimizing business processes. Specifically, the server utilizes a meeting space reservation system, a document analysis engine, and cost analysis tools to provide information optimized for the user's emotions. For meeting space reservations, it checks availability in conjunction with calendar management software and prioritizes quiet spaces.

[0583] Next, in document analysis, the server uses a natural language processing engine to identify key points and an emotion engine to detect the user's psychological state, generating flexible and gentle feedback. This allows users to proceed with their work with confidence.

[0584] Regarding expense data, the server performs analysis based on past spending data and creates more detailed and reassuring budget proposals that reflect user sentiment. During this process, data analysis tools are used to consider budget allocation.

[0585] As a concrete example, consider a scenario where a user texts, "I'd like to book a meeting for tomorrow, preferably in a quiet and relaxing room." The terminal interprets the user's sentiment from this input and notifies the server. Based on this data, the server cross-references it with calendar information and suggests the most suitable meeting space to the user.

[0586] An example of a prompt for a generative AI model would be, "If the user input indicates a need for calmness, suggest a quiet meeting space." This allows users to receive work support tailored to their emotions, improving work efficiency.

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

[0588] Step 1:

[0589] Users access the terminal to reserve meeting rooms and upload documents. Specifically, they input the date, time, and requests through the terminal's interface and upload the necessary files. Input includes date and time information, text requests, and document files.

[0590] Step 2:

[0591] The device receives user input data and activates an emotion engine to analyze the user's emotional state. Specifically, it uses speech recognition software and text analysis software to analyze the input text and audio data. The analysis results are output as emotion data indicating the user's emotions.

[0592] Step 3:

[0593] The terminal sends the acquired emotion data to the server. Specifically, it uses its communication module to send reservation requests and document data to the server in packet format along with the emotion data. This input is the data that initiates server processing.

[0594] Step 4:

[0595] The server analyzes the status of the meeting space and the content of the documents based on the received data. The server queries the company's calendar management system for meeting space availability and simultaneously performs natural language processing using a document analysis engine. This results in outputting information on available meeting spaces and key points of the documents.

[0596] Step 5:

[0597] The server selects the optimal meeting space and feedback content based on the user's emotional data. For example, if the emotional data indicates that the user is seeking relaxation, it prioritizes a quiet and calming meeting space. A generative AI model is used to generate more appropriate suggestions and feedback. This result is output as optimized suggestions.

[0598] Step 6:

[0599] The server sends the final proposal to the terminal. The terminal receives it and presents the results to the user through screen displays and notification functions. The output includes meeting space information and feedback messages that the user can select.

[0600] Step 7:

[0601] Based on the information provided, users can book meeting rooms and review documents. If necessary, they can request further revisions or additional bookings. This feedback loop allows the system to continuously improve.

[0602] (Application Example 2)

[0603] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0604] In modern business operations, there is a demand not only for increased efficiency in back-office tasks but also for flexible responses tailored to the psychological state of users. However, conventional systems struggle to understand user emotions and optimize accordingly, making new methods for improving user satisfaction desirable.

[0605] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0606] This invention includes a server that acquires real-time information on the availability of meeting rooms, searches for available meeting rooms and suggests them to users; a server that analyzes official documents using natural language processing, identifies important parts, and generates revision suggestions; a server that collects expense data, analyzes past spending patterns, and suggests the optimal budget allocation; and a server that uses an emotion recognition engine to determine the user's psychological state and optimize their daily activities. This enables the automation of back-office operations as well as flexible work responses that take into account the user's emotions.

[0607] "Meeting room availability" refers to information indicating whether a meeting room is currently in use or available for use.

[0608] An "available meeting room" refers to a meeting room that is currently not being used and is therefore available for booking.

[0609] "Natural language processing" is a technology that allows computers to process human language, and it is used for document analysis and automatic generation.

[0610] An "official document" is a formal document created and shared within an organization, containing important information and procedures.

[0611] "Expense data" refers to a collection of information about expenditures incurred in a company's financial activities, and this data is used for budget management.

[0612] "Expenditure patterns" refer to trends and patterns that show how expenses have been used in the past.

[0613] An "emotion recognition engine" is a software technology that extracts and analyzes human emotions from voice and text data.

[0614] "Psychological state" refers to an individual's internal state, such as their emotions and mood, which influences their behavior and decision-making.

[0615] "Optimizing daily activities" means streamlining daily work and lifestyle habits and making adjustments to meet individual needs.

[0616] The system for carrying out this invention includes the following elements: The server acquires the usage status of meeting rooms in real time and processes them using natural language processing to analyze official documents. It also collects expense data and analyzes past spending patterns. Furthermore, it uses an emotion recognition engine to determine the user's psychological state and optimize work and daily activities.

[0617] The system analyzes voice and text data using an emotion recognition engine to understand the user's emotions. Based on this analysis, it provides suggestions and environments that help the user feel at ease. For example, if the system detects that a user is stressed when booking a meeting room, it will suggest a quiet and calming room. The specific software used includes a natural language processing platform and an AI model for emotion analysis. By leveraging these technologies, it is possible to provide users with the optimal experience.

[0618] As a concrete example, consider the environment in which a home helper device operates. If the device detects from voice data that someone in the family is actually tired, it will play relaxing music or adjust the lighting. By providing this environment, users can reduce their mental burden and live more comfortably. An example of a prompt using a generative AI model is, "Please suggest support that would be helpful when a family member is tired."

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

[0620] Step 1:

[0621] The server receives voice or text data from the user. This input data is passed to an emotion recognition engine, which performs analysis to identify human emotions. As a result, the user's psychological state (e.g., stress or fatigue) is output.

[0622] Step 2:

[0623] Based on the obtained psychological state, the server checks the availability of meeting rooms and retrieves information on available rooms. It then executes a database query to extract real-time meeting room occupancy information and generates a list of matching meeting rooms based on that data. Considering the user's state, quiet meeting rooms are prioritized in the output.

[0624] Step 3:

[0625] The server uses a natural language processing engine to analyze official documents uploaded by users. It identifies key sections from the input document, extracts points requiring correction, and generates suggested revisions. The analysis results are then output in a user-friendly format.

[0626] Step 4:

[0627] Users review suggestions from the server on their devices. Especially for sentiment-based suggestions, they receive situation-appropriate options and next actions, which they then apply to their work and daily activities. For example, they can book a recommended meeting room or accept suggestions for document revisions.

[0628] Step 5:

[0629] The terminal sends expense data to the server, which analyzes past spending patterns to calculate the optimal budget allocation. Based on the analyzed data, an output is generated indicating how the budget should be allocated, and a feasible budget proposal tailored to the user is presented.

[0630] 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.

[0631] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0632] 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.

[0633] [Fourth Embodiment]

[0634] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0635] 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.

[0636] 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).

[0637] 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.

[0638] 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.

[0639] 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).

[0640] 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.

[0641] 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.

[0642] 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.

[0643] 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.

[0644] 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.

[0645] 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.

[0646] 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".

[0647] The system according to the present invention is designed to improve the efficiency of a company's back-office operations. This system includes features for automating meeting room reservations, document review, and real-time cost management. Detailed embodiments of each function are described below.

[0648] About automating meeting room reservations

[0649] In this function, the server retrieves the availability of meeting rooms in real time and stores it in a database. When a user wishes to reserve a meeting room, they send a request to the server via their terminal. The server compares the user's calendar information with the database and suggests the most suitable available meeting room and time to the user.

[0650] For example, if a user requests to hold a meeting on Monday morning next week, the server immediately checks the availability of all meeting rooms on Monday morning next week and suggests the most suitable room. If the user accepts this suggestion, the reservation is confirmed, and that information is reflected in the database.

[0651] About automating document review

[0652] The AI ​​agent on the device automatically analyzes submitted legal and HR documents. When a user uploads a new document to the device, the AI ​​uses natural language processing to analyze its content and identify important sections and areas where risks may be present. Based on the results, the AI ​​automatically generates revision suggestions and notifies the user.

[0653] As a concrete example, when a user uploads a new contract, the device's AI analyzes the clauses and points out high-risk wording or unclear points. The user can then review this and make any necessary corrections.

[0654] Optimizing cost management

[0655] The server collects and analyzes financial data from across the entire company to support cost management. Users can access a dashboard via their terminal to view current spending and past spending patterns. Based on this, the server presents users with optimal budget allocations and cost reduction strategies.

[0656] For example, if a user aims to reduce costs in a particular business unit, the server analyzes the unit's spending patterns and provides suggestions indicating which items are increasing costs and where reductions are possible.

[0657] In this way, this system significantly improves the efficiency of a company's back-office operations through its functions of meeting room reservation, document review, and cost management.

[0658] The following describes the processing flow.

[0659] Step 1:

[0660] The server monitors the current reservation status of all meeting rooms within the company in real time and records the availability data in a database.

[0661] Step 2:

[0662] The user enters a meeting room reservation request from a terminal. The request includes information such as the desired date and time, the number of participants, and the length of the meeting.

[0663] Step 3:

[0664] The server receives a request from the user, searches the database, and identifies an available meeting room that matches the specified criteria.

[0665] Step 4:

[0666] The server retrieves the user's calendar information, matches the available time slots with the user's free time, and generates the optimal reservation suggestion.

[0667] Step 5:

[0668] The terminal displays suggestions from the server to the user, presenting them with options. The user then decides on the option they deem best and confirms it.

[0669] Step 6:

[0670] The device selected by the user confirms the reservation and sends the information to the server.

[0671] Step 7:

[0672] The server updates the database with reservation confirmation information and changes the meeting room schedule. It then provides other users with the latest availability information.

[0673] The automated meeting room reservation process is completed through steps 1 to 7.

[0674] (Example 1)

[0675] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0676] Many processes in corporate back-office operations, such as meeting room reservations, document review, and cost management, still rely heavily on manual operations, resulting in significant time and effort. This leads to a compromise in decision-making speed and accuracy, and a decline in overall operational efficiency. Therefore, automating these processes is essential to improve operational efficiency and reduce costs.

[0677] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0678] This invention includes a server that acquires real-time information on the availability of meeting rooms, selects available meeting rooms using optimization calculations and proposes them to the user, analyzes legal or human resources information using information processing technology, generates revised suggestions and notifies the user, and integrates financial information using data collection technology and applies analysis technology to propose the optimal budget allocation. This enables more efficient meeting room reservations, automated document reviews, and optimized financial cost management.

[0679] A "meeting room" is a dedicated space within a company or organization designated for holding meetings and discussions.

[0680] "Real-time" refers to a state where processing or data acquisition occurs almost instantly, with minimal delay.

[0681] "Optimization computation" is a computational method that finds the most efficient or effective solution under given conditions and constraints.

[0682] A "user" is the entity that utilizes a system or tool, and is typically a human being who performs operations and makes decisions.

[0683] "Information processing technology" is a general term for technologies that collect, analyze, manipulate, store, and manage data.

[0684] "Natural language processing" is a technology that enables computers to understand, interpret, and generate human language.

[0685] A "revision proposal" is a suggestion that outlines specific changes or improvements to address identified problems or areas for improvement.

[0686] "Data collection technology" refers to methods for systematically collecting data from diverse sources and accumulating it in a usable format.

[0687] "Financial information" refers to data related to a company's or organization's accounting, expenses, income, assets, liabilities, etc.

[0688] "Analysis techniques" are techniques for analyzing data in detail and extracting useful information and patterns.

[0689] "Budget allocation" is the process of allocating available funds to various activities and projects.

[0690] This invention is a system for streamlining corporate back-office operations, automating processes such as meeting room reservations, document review, and cost management.

[0691] About automating meeting room reservations

[0692] The server works with sensors to obtain real-time information on meeting room availability and collects data via an API. This allows it to store information on available meeting rooms in a database. Users then submit meeting room reservation requests via their devices. The server performs optimization calculations based on the user's calendar information and suggests the most suitable available meeting room and time. For example, if a user enters "I want to hold a meeting next Monday morning," the server will suggest the most suitable meeting room.

[0693] About automating document review

[0694] Users upload legal and HR documents to the system using a terminal. The terminal is equipped with a generative AI model, which analyzes the uploaded documents using natural language processing technology. It automatically generates revision suggestions for important sections and risky parts and notifies the user. For example, when a user uploads a new contract, they can prompt the AI ​​to "point out high-risk wording," and the AI ​​will present the results.

[0695] Optimizing cost management

[0696] The server collects financial data from across the entire company using APIs and builds an integrated database. This database is analyzed using analytical techniques to visualize current spending and past spending patterns. Users can access a dashboard via their terminal to check appropriate cost reduction measures and budget allocations. For example, if a user inputs "Please suggest cost reduction measures for this department," the server will provide suggestions tailored to that department.

[0697] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0698] Step 1:

[0699] The server acquires real-time information on the usage status of meeting rooms. It receives data from sensors and information from the meeting room reservation system as input. The server analyzes this data and stores it in a database along with meeting room availability information. The output is a database containing the latest meeting room status.

[0700] Step 2:

[0701] Users request meeting room reservations through their devices. The input involves the user entering their desired date and time into a calendar app or a dedicated application. The device sends this information to a server, which then compares the received request against its database. The output is a suggestion of the most suitable available meeting room and time.

[0702] Step 3:

[0703] Users upload documents requiring review to the system using a terminal. The input consists of legal and HR documents specified by the user. A generative AI model installed on the terminal analyzes the documents using natural language processing technology. The output provides suggested revisions regarding important sections and areas where risks may be present.

[0704] Step 4:

[0705] The server collects a company's financial data from external systems. The input consists of multiple financial information sources obtained via APIs. The server integrates this data into a database and analyzes spending patterns using analytical techniques. The output includes visualizations of spending patterns and suggestions for optimal budget allocation.

[0706] Step 5:

[0707] Users access the dashboard from their terminals to review and implement data from the server. Inputs consist of analysis results and suggestions sent from the server. Through the dashboard, users evaluate cost management strategies and select appropriate actions. Outputs show cost allocation and implementation status of control measures within the company.

[0708] (Application Example 1)

[0709] 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".

[0710] In modern cities, the efficient use of public facilities and resources remains a major challenge. In particular, there is a need to improve transparency and efficiency regarding reservations for public facilities and feedback on administrative documents. Furthermore, mechanisms are needed that allow citizens and urban administrators to more intuitively understand budget management and make appropriate decisions.

[0711] 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.

[0712] This invention includes a server that provides real-time access to meeting facilities, searches for available facilities, and suggests them to users; a server that analyzes legal or personnel documents using natural language processing to identify key sections and generate revision suggestions; a server that collects financial data, analyzes past expenditure patterns, and proposes optimal budget allocations; a server that provides real-time access to public resource reservations from citizens and suggests optimal usage times; and a server that generates feedback to notify citizens of significant changes and risks in administrative documents. This enables citizens and administrators to utilize public resources and manage budgets efficiently and transparently.

[0713] "Conference facilities" refer to dedicated spaces used for meetings and gatherings, whether public or private.

[0714] "Usage status" refers to information indicating the extent to which a particular facility or resource is being used or reserved.

[0715] "Users" refer to individuals or organizations that use specific facilities, systems, or resources.

[0716] "Legal or personnel documents" refers to official documents related to legal or human resource management.

[0717] "Natural language processing" is a field of technology that enables computers to understand and process human language.

[0718] "Important sections" refer to parts of specific information or documents that deserve particular attention.

[0719] A "suggested correction" is the provision of content regarding changes or adjustments that are recommended to address a specific problem or for improvement.

[0720] "Financial data" refers to numerical information related to the flow of funds and accounting.

[0721] "Spending patterns" refer to trends in the flow and use of funds in the past.

[0722] "Budget allocation" refers to the planned and systematic allocation of resources and funds to specific purposes or departments.

[0723] "Public resources" refer to facilities, equipment, and services used for the benefit of the local community or its citizens as a whole.

[0724] "Feedback" refers to reactions and opinions regarding the information or results provided.

[0725] The system for realizing this invention consists of a server and multiple terminals. To obtain real-time information on the usage status of meeting facilities and to search for and suggest available slots, the server manages facility availability using a cloud database (e.g., Firebase). Upon receiving a reservation request from a terminal, the server compares it with the user's calendar information and suggests the most suitable meeting facility and time. This function is optimized by a generative AI model.

[0726] When handling legal or HR documents, the terminal analyzes the documents using natural language processing (e.g., Google Cloud Natural Language) to identify critical sections and areas of risk, and generates suggested revisions. This process provides real-time feedback to the user.

[0727] Furthermore, the server collects financial data and analyzes past spending patterns to suggest the optimal budget allocation. Users can check their current spending status and budget suggestions through their terminals. Financial information is visualized intuitively using a dashboard.

[0728] For example, if a user wants to reserve a library meeting room using their smartphone, the reservation system checks the library's reservation status and immediately displays availability information. Simultaneously, when administrative documents are made public to residents, important changes are automatically notified using natural language processing.

[0729] An example of a prompt message for a generating AI model might be: "I am trying to check the reservation status in the following public facility reservation system. Please tell me the best time to reserve a meeting room in the community hall next Thursday afternoon."

[0730] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0731] Step 1:

[0732] The terminal accepts input from the user. The user enters a request to reserve a meeting facility on a specific date. This input includes the desired date and time and the purpose of the meeting. This information is sent to the server in real time.

[0733] Step 2:

[0734] The server accesses a cloud database to retrieve the availability of meeting facilities for a specified date and time. As part of the data processing, it cross-references this information with current reservation data to identify available facilities. This process generates a list of available meeting facilities.

[0735] Step 3:

[0736] The server uses a generated AI model to match the user's calendar information with the obtained list of available facilities and select the optimal meeting facility and time. This process involves data calculations that take into account the user's past booking trends and the importance of the meeting. As a result, the most suitable facility and time are selected.

[0737] Step 4:

[0738] The server returns the selection results to the terminal. The terminal displays a pop-up to the user suggesting the most suitable meeting venue and time. The user is then given the option to review, accept, or modify the suggestion. If the user accepts the suggestion, the final booking information is sent to the server and stored in the database.

[0739] Step 5:

[0740] In financial data analysis, the server collects spending data from across the entire company. This includes analyzing past budget usage and detecting outliers. Based on this data, the server processes it using statistical methods and generates reports that propose optimal budget allocation.

[0741] Step 6:

[0742] The terminal displays a dashboard of the generated report to the user. The report includes specific advice on areas where costs can be reduced and areas where investment should be increased. Based on this information, the user can make financial decisions for the company.

[0743] 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.

[0744] The system according to the present invention is a comprehensive system that automates a company's back-office operations and further improves the quality of proposals and business processes by taking user emotions into consideration. This system combines an emotion engine that analyzes user input, enabling detailed responses based on emotions.

[0745] Automating meeting room reservations and emotion recognition

[0746] In the meeting room reservation function, the server processes reservation requests from users, checks calendar information, and suggests available meeting rooms. This is where the emotion engine comes in; it recognizes emotions from user input data, such as voice or text. The terminal sends this emotion data to the server, which uses this information to adjust the suggested meeting rooms and times. For example, if a user is stressed, the server can prioritize suggesting meeting rooms with a quiet environment.

[0747] Document review and sentiment recognition

[0748] In legal and HR document review functions, the device's AI agent analyzes the documents and generates necessary revision suggestions. Furthermore, an emotion engine understands the user's emotional state and optimizes how review results are communicated. For example, if the user is feeling stressed, the system adjusts the explanation to a gentler tone to reduce stress.

[0749] On cost management optimization and sentiment recognition

[0750] Regarding cost data analysis, the server can reflect user sentiment in the cost dashboard and adjust the way suggestions are presented. If the server's analysis indicates that a user is feeling anxious, it will incorporate features to enhance user confidence by providing more detailed explanations and support.

[0751] In this way, systems that incorporate an emotion engine can take user emotions into consideration, enabling more flexible and user-friendly work support. This approach allows for efficiency improvements that are tailored to the user's psychological state, rather than simply carrying out tasks mechanically.

[0752] The following describes the processing flow.

[0753] Step 1:

[0754] The user enters a request to reserve a meeting room into the terminal. Voice input and text input are available at this stage.

[0755] Step 2:

[0756] The device sends user input data to an emotion engine, which analyzes the user's emotions. The analysis results include various emotional states, such as stress levels and satisfaction levels.

[0757] Step 3:

[0758] The server receives emotional data from the terminal, compares it with a database of meeting room usage, and searches for available meeting rooms. During this process, the server takes the user's emotional state into consideration when selecting the most suitable meeting room and time.

[0759] Step 4:

[0760] The server sends suggested meeting rooms and times to the user's device. The suggestions include explanations that take the user's feelings into consideration. For example, a user who wants a relaxed environment will be offered a suggestion for a quiet meeting room.

[0761] Step 5:

[0762] The user reviews the suggestions on their device and confirms the reservation by selecting the most suitable option.

[0763] Step 6:

[0764] The server updates the database with confirmed reservation information and displays the latest meeting room availability for other users.

[0765] Through this process, the automation of meeting room reservations is implemented in a way that takes user emotions into consideration.

[0766] (Example 2)

[0767] 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".

[0768] In modern businesses, efficient operations and reducing employee psychological stress are crucial challenges. While conventional business support systems can improve efficiency and convenience, they often fail to provide suggestions and notifications that consider user emotions, resulting in insufficient support for business processes. Therefore, there is a need for systems that take emotions into account and provide more appropriate business support.

[0769] 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.

[0770] This invention includes a server that acquires the usage status of meeting spaces, searches for available meeting spaces and provides them to users, analyzes documents using natural language processing, extracts important elements, and creates revised proposals, collects cost data, evaluates past expenditure trends and proposes appropriate resource allocation, and utilizes an emotion engine that analyzes user emotion data and adjusts the proposed content. This makes it possible to achieve flexible business support and efficiency while taking user emotions into consideration.

[0771] A "meeting space" refers to a physical location or environment used by a company or organization for meetings and discussions.

[0772] "Usage status" indicates how the meeting space is currently being used, such as whether it is reserved or available.

[0773] "Available meeting spaces" refer to meeting spaces that are not currently booked and are available for use.

[0774] "Users" refers to individuals or organizations that use the system to reserve meeting spaces or upload documents.

[0775] "Natural language processing" refers to the technology that enables machines to understand and analyze human language.

[0776] "Key elements" refer to the aspects or parts that require particular attention based on the analysis results.

[0777] A "revised proposal" refers to suggestions for necessary changes or improvements based on the analysis results.

[0778] "Expense data" refers to information about the expenditures made by companies and organizations in various activities.

[0779] "Past spending trends" refers to trends and patterns that can be seen by analyzing past spending data.

[0780] "Resource allocation" refers to the decision of how to distribute the available funds and physical resources within a company or organization.

[0781] "Emotional data" refers to information that indicates a user's psychological state. This information is typically obtained from verbal and nonverbal cues.

[0782] An "emotion engine" refers to a technology or program that analyzes a user's emotions and adjusts the system's operation based on the results.

[0783] "Proposed content" refers to the solutions or recommendations that the system provides to the user.

[0784] This invention is a system that provides business support while taking user emotions into consideration. The main components of the system consist of a server, terminals, and users. Next, we will explain in detail how these components work together.

[0785] First, the user accesses the system using a terminal. This terminal has a built-in emotion engine that processes the user's speech and text input using built-in speech recognition and text analysis software to generate emotion data. This emotion data is then sent from the terminal to the server.

[0786] The server analyzes the received emotional data and other input data to generate suggestions for optimizing business processes. Specifically, the server utilizes a meeting space reservation system, a document analysis engine, and cost analysis tools to provide information optimized for the user's emotions. For meeting space reservations, it checks availability in conjunction with calendar management software and prioritizes quiet spaces.

[0787] Next, in document analysis, the server uses a natural language processing engine to identify key points and an emotion engine to detect the user's psychological state, generating flexible and gentle feedback. This allows users to proceed with their work with confidence.

[0788] Regarding expense data, the server performs analysis based on past spending data and creates more detailed and reassuring budget proposals that reflect user sentiment. During this process, data analysis tools are used to consider budget allocation.

[0789] As a concrete example, consider a scenario where a user texts, "I'd like to book a meeting for tomorrow, preferably in a quiet and relaxing room." The terminal interprets the user's sentiment from this input and notifies the server. Based on this data, the server cross-references it with calendar information and suggests the most suitable meeting space to the user.

[0790] An example of a prompt for a generative AI model would be, "If the user input indicates a need for calmness, suggest a quiet meeting space." This allows users to receive work support tailored to their emotions, improving work efficiency.

[0791] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0792] Step 1:

[0793] Users access the terminal to reserve meeting rooms and upload documents. Specifically, they input the date, time, and requests through the terminal's interface and upload the necessary files. Input includes date and time information, text requests, and document files.

[0794] Step 2:

[0795] The device receives user input data and activates an emotion engine to analyze the user's emotional state. Specifically, it uses speech recognition software and text analysis software to analyze the input text and audio data. The analysis results are output as emotion data indicating the user's emotions.

[0796] Step 3:

[0797] The terminal sends the acquired emotion data to the server. Specifically, it uses its communication module to send reservation requests and document data to the server in packet format along with the emotion data. This input is the data that initiates server processing.

[0798] Step 4:

[0799] The server analyzes the status of the meeting space and the content of the documents based on the received data. The server queries the company's calendar management system for meeting space availability and simultaneously performs natural language processing using a document analysis engine. This results in outputting information on available meeting spaces and key points of the documents.

[0800] Step 5:

[0801] The server selects the optimal meeting space and feedback content based on the user's emotional data. For example, if the emotional data indicates that the user is seeking relaxation, it prioritizes a quiet and calming meeting space. A generative AI model is used to generate more appropriate suggestions and feedback. This result is output as optimized suggestions.

[0802] Step 6:

[0803] The server sends the final proposal to the terminal. The terminal receives it and presents the results to the user through screen displays and notification functions. The output includes meeting space information and feedback messages that the user can select.

[0804] Step 7:

[0805] Based on the information provided, users can book meeting rooms and review documents. If necessary, they can request further revisions or additional bookings. This feedback loop allows the system to continuously improve.

[0806] (Application Example 2)

[0807] 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".

[0808] In modern business operations, there is a demand not only for increased efficiency in back-office tasks but also for flexible responses tailored to the psychological state of users. However, conventional systems struggle to understand user emotions and optimize accordingly, making new methods for improving user satisfaction desirable.

[0809] 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.

[0810] This invention includes a server that acquires real-time information on the availability of meeting rooms, searches for available meeting rooms and suggests them to users; a server that analyzes official documents using natural language processing, identifies important parts, and generates revision suggestions; a server that collects expense data, analyzes past spending patterns, and suggests the optimal budget allocation; and a server that uses an emotion recognition engine to determine the user's psychological state and optimize their daily activities. This enables the automation of back-office operations as well as flexible work responses that take into account the user's emotions.

[0811] "Meeting room availability" refers to information indicating whether a meeting room is currently in use or available for use.

[0812] An "available meeting room" refers to a meeting room that is currently not being used and is therefore available for booking.

[0813] "Natural language processing" is a technology that allows computers to process human language, and it is used for document analysis and automatic generation.

[0814] An "official document" is a formal document created and shared within an organization, containing important information and procedures.

[0815] "Expense data" refers to a collection of information about expenditures incurred in a company's financial activities, and this data is used for budget management.

[0816] "Expenditure patterns" refer to trends and patterns that show how expenses have been used in the past.

[0817] An "emotion recognition engine" is a software technology that extracts and analyzes human emotions from voice and text data.

[0818] "Psychological state" refers to an individual's internal state, such as their emotions and mood, which influences their behavior and decision-making.

[0819] "Optimizing daily activities" means streamlining daily work and lifestyle habits and making adjustments to meet individual needs.

[0820] The system for carrying out this invention includes the following elements: The server acquires the usage status of meeting rooms in real time and processes them using natural language processing to analyze official documents. It also collects expense data and analyzes past spending patterns. Furthermore, it uses an emotion recognition engine to determine the user's psychological state and optimize work and daily activities.

[0821] The system analyzes voice and text data using an emotion recognition engine to understand the user's emotions. Based on this analysis, it provides suggestions and environments that help the user feel at ease. For example, if the system detects that a user is stressed when booking a meeting room, it will suggest a quiet and calming room. The specific software used includes a natural language processing platform and an AI model for emotion analysis. By leveraging these technologies, it is possible to provide users with the optimal experience.

[0822] As a concrete example, consider the environment in which a home helper device operates. If the device detects from voice data that someone in the family is actually tired, it will play relaxing music or adjust the lighting. By providing this environment, users can reduce their mental burden and live more comfortably. An example of a prompt using a generative AI model is, "Please suggest support that would be helpful when a family member is tired."

[0823] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0824] Step 1:

[0825] The server receives voice or text data from the user. This input data is passed to an emotion recognition engine, which performs analysis to identify human emotions. As a result, the user's psychological state (e.g., stress or fatigue) is output.

[0826] Step 2:

[0827] Based on the obtained psychological state, the server checks the availability of meeting rooms and retrieves information on available rooms. It then executes a database query to extract real-time meeting room occupancy information and generates a list of matching meeting rooms based on that data. Considering the user's state, quiet meeting rooms are prioritized in the output.

[0828] Step 3:

[0829] The server uses a natural language processing engine to analyze official documents uploaded by users. It identifies key sections from the input document, extracts points requiring correction, and generates suggested revisions. The analysis results are then output in a user-friendly format.

[0830] Step 4:

[0831] Users review suggestions from the server on their devices. Especially for sentiment-based suggestions, they receive situation-appropriate options and next actions, which they then apply to their work and daily activities. For example, they can book a recommended meeting room or accept suggestions for document revisions.

[0832] Step 5:

[0833] The terminal sends expense data to the server, which analyzes past spending patterns to calculate the optimal budget allocation. Based on the analyzed data, an output is generated indicating how the budget should be allocated, and a feasible budget proposal tailored to the user is presented.

[0834] 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.

[0835] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0836] 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.

[0837] 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.

[0838] 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.

[0839] 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.

[0840] 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.

[0841] 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.

[0842] 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."

[0843] 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.

[0844] 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.

[0845] 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.

[0846] 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.

[0847] 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.

[0848] 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.

[0849] 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.

[0850] 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.

[0851] 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.

[0852] 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.

[0853] 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.

[0854] 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.

[0855] The following is further disclosed regarding the embodiments described above.

[0856] (Claim 1)

[0857] A method for obtaining real-time information on meeting room usage, searching for available meeting rooms, and suggesting them to users,

[0858] A means of analyzing legal or human resources documents using natural language processing to identify important sections and generate revision suggestions,

[0859] A method for collecting cost data, analyzing past spending patterns, and proposing the optimal budget allocation,

[0860] A system that includes this.

[0861] (Claim 2)

[0862] The system according to claim 1, further comprising means for automatically selecting the most suitable meeting room and time by matching it with the user's calendar information based on a meeting room reservation request.

[0863] (Claim 3)

[0864] The system according to claim 1, further comprising means for analyzing uploaded documents and notifying the user of the generated feedback.

[0865] "Example 1"

[0866] (Claim 1)

[0867] A method for obtaining real-time information on the availability of meeting rooms, selecting available meeting rooms using optimization calculations, and proposing them to users,

[0868] A means of analyzing legal or human resources information using information processing technology, generating proposed revisions, and notifying users;

[0869] A means of integrating financial information using data collection technology and applying analytical technology to propose the optimal budget allocation,

[0870] A system that includes this.

[0871] (Claim 2)

[0872] The system according to claim 1, further comprising means for automatically selecting the optimal available space and time by matching it with the user's schedule information based on a meeting room reservation request.

[0873] (Claim 3)

[0874] The system according to claim 1, further comprising means for analyzing uploaded information and automatically presenting generated feedback.

[0875] "Application Example 1"

[0876] (Claim 1)

[0877] A method for obtaining real-time information on the usage status of meeting facilities, searching for available meeting facilities, and suggesting them to users,

[0878] A means for analyzing legal or human resources documents using natural language processing to identify important sections and generate revision suggestions,

[0879] A method for collecting financial data, analyzing past spending patterns, and proposing the optimal budget allocation,

[0880] A means to secure real-time information on the reservation status of public resources from citizens and suggest the optimal usage time,

[0881] A means of generating feedback to notify citizens of important changes and risks in administrative documents,

[0882] A system that includes this.

[0883] (Claim 2)

[0884] The system according to claim 1, further comprising means for automatically selecting the most suitable meeting facility and time by matching it with the user's schedule information based on a reservation request for a meeting facility.

[0885] (Claim 3)

[0886] The system according to claim 1, further comprising means for analyzing uploaded documents and notifying the user of the generated feedback.

[0887] "Example 2 of combining an emotion engine"

[0888] (Claim 1)

[0889] A means of obtaining the usage status of meeting spaces, searching for available meeting spaces, and providing them to users,

[0890] A method for analyzing documents using natural language processing, extracting key elements, and creating revised proposals,

[0891] A means of collecting cost data, evaluating past spending trends, and proposing appropriate resource allocation,

[0892] A method that utilizes an emotion engine to analyze user emotion data and adjust the suggested content,

[0893] A system that includes this.

[0894] (Claim 2)

[0895] The system according to claim 1, further comprising means for automatically selecting an appropriate meeting space and time by comparing it with the user's time management information in response to a request to reserve a meeting space.

[0896] (Claim 3)

[0897] The system according to claim 1, further comprising means for notifying the user of an optimized response based on the analysis results of the above document and the user's emotional state.

[0898] "Application example 2 when combining with an emotional engine"

[0899] (Claim 1)

[0900] A method for obtaining real-time information on the availability of meeting rooms, searching for available meeting rooms, and suggesting them to users,

[0901] A means of analyzing official documents using natural language processing, identifying important parts, and generating proposed revisions,

[0902] A method for collecting expense data, analyzing past spending patterns, and proposing the optimal budget allocation,

[0903] A means of optimizing daily activities by using an emotion recognition engine to determine the user's psychological state,

[0904] A system that includes this.

[0905] (Claim 2)

[0906] The system according to claim 1, further comprising means for automatically selecting the most suitable meeting room and time based on a meeting room reservation request, matching it with the user's schedule information, and making adjustments based on emotion.

[0907] (Claim 3)

[0908] The system according to claim 1, further comprising means for analyzing uploaded documents, notifying the user of the generated feedback, and adjusting the content of the notification according to the user's emotions. [Explanation of symbols]

[0909] 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 method for obtaining real-time information on the usage status of meeting facilities, searching for available meeting facilities, and suggesting them to users, A means for analyzing legal or human resources documents using natural language processing to identify important sections and generate revision suggestions, A method for collecting financial data, analyzing past spending patterns, and proposing the optimal budget allocation, A means to secure real-time information on the reservation status of public resources from citizens and suggest the optimal usage time, A means of generating feedback to notify citizens of important changes and risks in administrative documents, A system that includes this.

2. The system according to claim 1, further comprising means for automatically selecting the most suitable meeting facility and time by matching it with the user's schedule information based on the reservation request for the meeting facility.

3. The system according to claim 1, further comprising means for analyzing uploaded documents and notifying the user of the generated feedback.

Images