system

Abstract

We provide the system. [Solution] Means of collecting business data, A means of analyzing collected business data and evaluating the effectiveness of each meeting, A means of determining the necessity of a meeting based on evaluation, A means of generating and presenting improvement plans to optimize business workflows, A means of visualizing the learning progress of individual users, 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 method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Currently, many companies are facing the problem of reduced productivity due to excessive meetings and inefficient business processes. In such a situation, it is difficult for new employees to smoothly adapt to the organization and improve work efficiency. In addition, the lack of communication within the organization leads to insufficient visualization of work progress and knowledge sharing, and a high workload is likely to occur. The purpose of this invention is to overcome these problems and improve the harmony of productivity across the organization.

Means for Solving the Problems

[0005] This invention employs a means of collecting business data and analyzing the collected data to evaluate the effectiveness of meetings. Furthermore, it reduces excessive meetings and improves operational efficiency by determining the necessity of meetings based on the evaluation and generating and presenting improvement plans to optimize the workflow. It also provides a means of visualizing the learning progress of individual users, enabling everyone, including new employees, to efficiently share knowledge and promote skill improvement. This results in a system that improves communication within the organization and increases productivity.

[0006] "Business data" refers to information related to the execution of business operations within a company, including schedules, communication history, and task details.

[0007] "Meeting effectiveness" is a measure used to evaluate whether a meeting achieved its objectives and was valuable to the participants.

[0008] A "business process flow" is a series of processes and procedures for efficiently carrying out business operations, and its purpose is to improve productivity through optimization.

[0009] An "improvement plan" is a document that analyzes the current business processes and structure and presents specific proposals and action plans aimed at improving efficiency and solving problems.

[0010] "Learning progress" is an indicator that shows an individual's degree of achievement or progress toward a specific learning goal, and it visualizes the degree to which skills and knowledge are improving. [Brief explanation of the drawing]

[0011] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0012] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0013] First, let's explain the terminology used in the following explanation.

[0014] In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0015] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0016] In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs, various parameters, and the like. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0017] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor, an antenna, and the like. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0018] 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."

[0019] [First Embodiment]

[0020] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0021] 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.

[0022] 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).

[0023] 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.

[0024] 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.

[0025] 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.

[0026] 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.

[0027] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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".

[0032] The system of the present invention consists of a series of processes in which a server, terminals, and users work together to improve operational efficiency within a company. Specific embodiments are shown below.

[0033] The server first collects work data from each user's calendar and messaging tools. This stores the schedules of meetings that users regularly attend and their communication history in a database. This data forms the basis for subsequent analytical processing.

[0034] After data is collected, the server uses an AI algorithm to evaluate the effectiveness of each meeting. This evaluation includes the meeting's purpose, duration, participants' roles, and outcomes achieved. For meetings deemed ineffective, suggestions for improvement are provided to participants and their supervisors. This promotes reduced attendance and more efficient meeting management.

[0035] Furthermore, the server analyzes each user's workflow based on the collected business data and generates an optimization plan. This streamlines business processes and improves productivity. The optimization plan is displayed on the user's dashboard via their terminal, allowing users to directly refer to it in their daily work.

[0036] Users can visualize their work and learning progress through the provided dashboard. This visualization includes information such as completed tasks, unfinished tasks, and new skills to acquire, making it easier for users to understand directions for skill improvement and work efficiency. For example, new employees can use this feature as a benchmark to quickly adapt to the organization during their orientation period.

[0037] The server also analyzes communication between teams and departments and provides improvement measures as needed. For example, if there is a lack of communication between departments, specific advice on recommended communication methods and information to share will be automatically provided. The terminal organizes this information and sends timely alerts to the user.

[0038] As described above, the system of the present invention helps to improve the efficiency of operations through the collection and analysis of business data, optimizes the importance of meetings and the adaptation process for new employees, and achieves improved productivity throughout the organization.

[0039] The following describes the processing flow.

[0040] Step 1:

[0041] The server periodically collects schedule and communication data from each user's calendar and messaging tools within the company. This includes the date and time of each meeting, participants, purpose, and message sending and receiving history.

[0042] Step 2:

[0043] The server analyzes the collected data using an AI algorithm to evaluate the effectiveness of each meeting. Specifically, it examines whether the meeting's objectives were achieved, whether the participants were appropriate, and whether the duration was practical. Based on these results, it calculates an effectiveness score.

[0044] Step 3:

[0045] The server identifies meetings that are unnecessary or need improvement based on their effectiveness score. Based on this information, it creates a list of potential meetings to be cut, reports it to supervisors and relevant departments, and sends improvement suggestions.

[0046] Step 4:

[0047] The server analyzes the user's business processes and generates an optimization plan for the workflow based on the collected data. This plan includes specific steps on how to improve particular business processes.

[0048] Step 5:

[0049] The device displays the generated optimization plan on the user's dashboard. Based on this information, users can improve the prioritization and methods of their daily tasks.

[0050] Step 6:

[0051] The device displays each user's skill assessment and uncompleted tasks on a dashboard to visualize their learning progress. This allows users to understand their areas of growth and the challenges they should focus on.

[0052] Step 7:

[0053] The server analyzes the state of communication between departments and identifies common problems. Based on this, it automatically generates improvement suggestions and specific action plans and notifies the relevant departments.

[0054] Through these processes, users can leverage the system to improve their own work efficiency and strengthen collaboration across the entire organization.

[0055] (Example 1)

[0056] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0057] In modern businesses, improving operational efficiency and productivity are crucial challenges. However, effective meetings and optimized business processes are often insufficient, leading to wasted resources. Furthermore, the learning progress of individual employees is unclear, and insufficient information sharing across the organization easily creates communication gaps between departments. Addressing these challenges and improving overall organizational efficiency is essential.

[0058] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0059] In this invention, the server includes means for collecting business information, means for analyzing the collected business information and evaluating the efficiency of each meeting, and means for proposing improvements to the meetings based on the evaluation. This enables transparency and optimization of business processes, effective operation of meetings, and visualization of the learning progress of individual employees.

[0060] "Business information" refers to data related to various activities within a company, including information such as meeting schedules, communication history, and task progress.

[0061] "Evaluating efficiency" is the process of measuring how effective tasks and meetings are in achieving goals, using indicators such as purpose, time required, and results.

[0062] "Suggesting improvements" means analyzing current business processes and meeting procedures, and presenting specific methods for achieving better results.

[0063] "Optimizing business processes" means reviewing the flow of work, eliminating waste, and improving processes to efficiently achieve goals.

[0064] "Visualizing learning progress" means clarifying and visually displaying the learning progress and skill improvement status of individual employees.

[0065] A "digital device" is a device that has the ability to process and display digital data, and includes personal computers, smartphones, tablets, and other similar devices.

[0066] The system of this invention is designed to improve operational efficiency within a company, and operates through the cooperation of a server, terminals, and users. The server plays a central role, collecting and analyzing business information and generating improvement proposals. Specifically, the server uses APIs to collect data and retrieve information from various digital sources. This includes schedule information from calendar applications (e.g., Google® Calendar, Microsoft® Outlook) and communication history from messaging tools.

[0067] The server utilizes a generative AI model to analyze the collected information. This AI model applies natural language processing technology to analyze the content and progress of meetings and evaluate the efficiency of each meeting. Furthermore, based on the analysis results, it automatically generates specific improvement suggestions using prompt sentences. For example, by asking the AI ​​questions such as, "How can we narrow down the agenda for the next meeting?", practical suggestions can be elicited.

[0068] The terminal functions as a device that presents the user with optimization plans and improvement suggestions generated by the server. Personal computers and smartphones are used for this purpose. This allows users to check their work progress and learning status in real time through a dashboard. Based on the information displayed on the dashboard, users can review their work priorities and make improvements.

[0069] As a concrete example, consider the case where new employees use this system during their orientation period. The server analyzes business information and presents efficient workflows, making it easier for new employees to quickly adapt to the organization's culture and processes. An example of a prompt message could be, "Please suggest a recommended task management method for new employees."

[0070] Thus, the present invention improves organizational productivity by efficiently analyzing business information and providing improvement suggestions to users.

[0071] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0072] Step 1:

[0073] The server collects business information from various digital sources. It receives calendar information and communication history as input via APIs and stores this information in a database. Specifically, it uses APIs from Google Calendar and messaging apps to periodically retrieve schedules and messages.

[0074] Step 2:

[0075] The server inputs the collected business information into an AI model for data analysis. Based on this information, the AI ​​model uses natural language processing technology to analyze meeting minutes and communication content. The output is a report that evaluates the efficiency of each meeting and identifies areas for improvement.

[0076] Step 3:

[0077] The server generates prompts based on the analysis results and creates improvement suggestions. For example, it might ask the AI ​​model a question using a prompt like, "What are the key points for narrowing the agenda at the next meeting?" Based on this, it obtains specific improvement suggestions as output and passes them on to the next process.

[0078] Step 4:

[0079] The terminal displays optimization plans and improvement suggestions received from the server on the user's dashboard. This step involves updating the user interface to allow users to intuitively access information. The input begins with receiving improvement suggestions, and the output presents visually organized information.

[0080] Step 5:

[0081] Users refer to the presented dashboard information to check their work progress and important tasks. They also provide feedback to the server and evaluate the effectiveness of improvement suggestions. This feedback serves as input for the next analysis step and acts as output that contributes to further system improvement.

[0082] (Application Example 1)

[0083] 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."

[0084] Improving operational efficiency within companies presents challenges such as evaluating the effectiveness of meetings and optimizing workflows. However, existing systems are insufficient in optimizing the operation schedules of machinery and equipment using work history and communication information, making efficient business operations difficult. Therefore, new methods are needed to more effectively optimize work schedules and improve business processes.

[0085] 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.

[0086] In this invention, the server includes means for collecting business information, means for evaluating the effectiveness of each consultation based on the collected information, means for generating and presenting improvement proposals to optimize business processes, and means for analyzing work history and communication information to optimize the operation schedule of machinery and business processes. This makes the operation of machinery within the company more efficient and enables the optimization of work schedules.

[0087] "Business information" is a general term for data and records related to various business operations within a company.

[0088] "Means of collection" refers to methods and equipment for importing necessary data into devices such as servers and terminals.

[0089] "Means of analysis" refer to methods and equipment for analyzing collected data and determining its meaning and value.

[0090] "Means of evaluating effectiveness" refers to methods and equipment for measuring the outcomes of activities and processes and determining their value.

[0091] "Means of judgment" refer to the methods and equipment used to determine appropriate responses based on the analysis results.

[0092] "Business process" refers to a series of work processes or flows carried out within an organization.

[0093] An "improvement proposal" is a suggestion or plan to make the current process more efficient.

[0094] "Means of presentation" refers to methods and equipment for clearly displaying analysis results and improvement proposals to users.

[0095] "Work history" refers to a record of the work performed by machinery, equipment, or people in the past.

[0096] "Communication information" refers to the records and content of data exchanges that occur between digital devices.

[0097] "Mechanical equipment" refers to devices or robots designed to perform specific tasks.

[0098] An "operation schedule" refers to the planned tasks that a machine or device should perform within a certain period of time.

[0099] "Optimization" means adjusting and improving a process or system to make it as efficient as possible.

[0100] The system in this invention is designed to improve operational efficiency within a company. A server acts as the central hub, collecting and analyzing operational information and providing plans aimed at effective business improvement. Specifically, the server collects each user's schedule information and communication history, and analyzes this data from multiple perspectives. AI models such as TENSORFLOW® are used for the analysis, interpreting the meaning of the data and evaluating the effectiveness of the operations.

[0101] The terminal displays the generated improvement suggestions on the user's dashboard. This dashboard utilizes ReactJS for its user interface, providing a clear and easy-to-understand graphical display. Based on the displayed information, users can check their work progress and learning progress and work to improve their work.

[0102] The server also optimizes operating schedules and work processes by collecting and analyzing the operating history and communication information of machinery and equipment. This allows for more efficient and effective machine operation on a company's manufacturing line.

[0103] Specifically, robots in the manufacturing process generate efficient operation schedules based on motion data obtained from sensors. For example, it analyzes when and what tasks a robot should perform, enabling operation that eliminates delays and waste. In this process, an optimized plan is generated on a server using a generation AI model.

[0104] An example of a prompt message is: "Create an AI model to generate efficient schedules and workflows for robot operations on a manufacturing line. Use work logs, communication history, utilization rate data, etc., as datasets to enable optimization suggestions."

[0105] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0106] Step 1:

[0107] The server collects users' schedule information and communication history. This provides input data for business use. Specifically, it extracts information from each user's digital calendar and messaging application via APIs and stores it in a database.

[0108] Step 2:

[0109] The server analyzes the collected business information using an AI algorithm. In this process, the effectiveness of each meeting is evaluated using a generative AI model based on TensorFlow. Calendar information and communication logs are referenced as input, and a report on the meeting's effectiveness and areas for improvement is generated as output. Specifically, the data is preprocessed and then fed into the analysis model.

[0110] Step 3:

[0111] The server generates improvement proposals to optimize business processes based on the analysis results. Here, prompts are generated, and the AI ​​proposes optimization suggestions. These generated improvement proposals are then obtained as output. The improvement proposals identify bottlenecks in the business process and include recommendations for efficiency improvements.

[0112] Step 4:

[0113] The terminal displays improvement suggestions received from the server on the user's dashboard. The input consists of specific improvement suggestions sent from the server, and the output is displayed in a visually easy-to-understand format for the user. Specifically, the improvement suggestions are presented as graphs and lists through an interface using ReactJS.

[0114] Step 5:

[0115] The server collects and analyzes the operation history and communication information of the machinery and equipment to optimize the operation schedule. Inputs include sensor recordings and log information from the machinery. After processing the data, an optimal operation schedule is generated and provided as output. Specifically, the server analyzes the time required for each task of the machinery and equipment, designing an efficient work sequence.

[0116] 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.

[0117] The system of the present invention aims to improve operational efficiency within companies. In addition to collecting and analyzing operational data, it combines this with an emotion engine to monitor the emotional state of users and support business improvement based on that data. The following describes specific embodiments of the present invention.

[0118] First, the server collects business data such as each user's calendar information and message history. This business data is used as foundational data to evaluate the effectiveness of meetings. Separately, the server uses an emotion engine to recognize the user's emotional state from their voice and text. The emotion engine uses natural language processing and speech analysis technology to analyze the words and tone of conversation spoken by the user in real time and identify their emotional state.

[0119] Next, the server evaluates the effectiveness of each meeting and determines its necessity based on the collected business data and the user's emotional state. Meetings with significant emotional fluctuations or frequent negative emotions are analyzed in particular, and suggestions for improvement are provided to the user. For example, specific suggestions may be offered, such as reducing the frequency of meetings, changing participants, or revising the agenda.

[0120] Furthermore, the server generates improvement plans to optimize the workflow. These plans include stress reduction measures and workload adjustments tailored to the user's emotional state. The terminal displays these improvement plans on the user's dashboard for easy visual understanding.

[0121] Furthermore, the device provides users with a function that visualizes their emotional state. This allows users to understand their own mental health and adaptation to the work environment. For example, if the system determines that a user is accumulating work-related stress, it can send a notification suggesting a break or provide information on relaxation techniques.

[0122] This invention enables users to improve their own work efficiency, take emotional states into consideration, and build a better collaborative system across the entire organization. This system goes beyond a mere task management tool, providing comprehensive work support that includes emotional aspects.

[0123] The following describes the processing flow.

[0124] Step 1:

[0125] The server collects work data from each user's calendar and messaging tools. At this stage, meeting dates and times, participant lists, and agenda details are retrieved and stored in the database.

[0126] Step 2:

[0127] The server uses AI algorithms to evaluate the effectiveness of meetings based on collected business data. Specifically, it analyzes whether the meeting's objectives are appropriate, the duration is reasonable, and the roles of the participants are clear. An effectiveness score is calculated based on the evaluation results.

[0128] Step 3:

[0129] The emotion engine accesses the user's calls and chats, recognizing their emotional state from the voice data and text. It analyzes the user's tone of voice and word choice using natural language processing technology to determine whether the emotion is positive or negative.

[0130] Step 4:

[0131] The server combines the output of the emotion engine to re-evaluate the effectiveness of the meeting. In particular, meetings where negative emotions were frequently observed are deemed to have a high need for improvement and undergo a detailed analysis.

[0132] Step 5:

[0133] The server generates an optimization plan for the workflow. The plan includes suggestions for improving meetings and proposes specific steps such as participant adjustments and agenda restructuring. It also incorporates work adjustment proposals that take user emotions into consideration.

[0134] Step 6:

[0135] The device provides an optimization plan and a dashboard that visualizes the user's emotional state. Through this, users can check their current work challenges and their own emotional state.

[0136] Step 7:

[0137] Users adjust their work based on the dashboard. For example, if the system analyzes that they are experiencing stress, they can choose actions such as taking appropriate breaks or assigning tasks more efficiently.

[0138] Step 8:

[0139] The server continuously monitors inter-departmental communication and, as needed, utilizes feedback from the emotion engine to formulate improvement suggestions. Based on this, the system continuously supports smooth communication within the organization.

[0140] (Example 2)

[0141] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0142] In today's work environment, there is a challenge in properly managing and evaluating the effectiveness of meetings and the emotional state of operators. This challenge leads to unnecessary meetings, decreased work efficiency, and increased mental burden on operators. Furthermore, there is a need to propose work improvement plans that take operators' emotional states into consideration, but doing so manually requires a great deal of time and effort.

[0143] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0144] In this invention, the server includes means for collecting business information, means for analyzing the collected business information and evaluating the effectiveness of meetings, and means for determining the necessity of meetings based on the analysis. This makes it possible to efficiently evaluate the effectiveness of meetings and automatically generate and present necessary improvement plans. Furthermore, by providing means for analyzing the emotional state of the operator, it is possible to propose appropriate workload reduction measures according to the operator's emotions, thereby simultaneously improving work efficiency and mental health.

[0145] "Business information" refers to all data related to activities within a company or organization, including schedule information and dialogue history.

[0146] A "meeting" refers to a conference or meeting held for the purpose of sharing information and making decisions necessary for the progress of work or projects.

[0147] "Operators" refer to end-users and employees who utilize this system, and are the entities whose individual work data and emotional states influence the system.

[0148] "Emotional state" refers to information that indicates the operator's psychological state, and is recognized through the analysis of voice and text data.

[0149] "Evaluation" is the act of judging the effectiveness of a meeting or the efficiency of operations based on specific criteria or indicators.

[0150] An "improvement plan" is a proposal for optimizing business processes generated by the system, and includes suggestions aimed at improving the structure of meetings and reducing the workload of operators.

[0151] "Load reduction measures" refer to specific methods and action plans proposed to reduce work-related stress and workload, taking into account the emotional state of the operator.

[0152] A "display device" refers to a device or interface used to provide information to an operator, with dashboards being a concrete example.

[0153] The embodiments for carrying out the present invention will now be described. This system supports business management within a company by considering both the user's work efficiency and emotional state. The entire system is mainly composed of three elements: a server, a terminal, and a user, which work together in cooperation with each other.

[0154] First, the server uses APIs to retrieve schedule information and conversation history to collect business information. For this, it utilizes a common API platform, such as MySQL as the database system and Python for data analysis. The server also performs natural language processing and speech analysis to analyze emotional states. Specifically, it uses Python's NLTK library and TensorFlow to estimate the user's emotional state from speech and text data.

[0155] Based on the analyzed information, the server evaluates the effectiveness of each meeting and generates improvement plans as needed. These improvement plans are generated using a generative AI model. An example of a prompt for the generative AI model is, "Create business improvement proposals."

[0156] Next, the device visually presents the improvement plan sent from the server to the user. The device is equipped with a dashboard using a JavaScript® framework (e.g., React), through which the user can view the information. The device also visualizes the user's emotional state and provides stress reduction measures based on that information.

[0157] Based on this improvement plan, users will review their work processes and adjust the meeting structure and workload. For example, based on the results of sentiment analysis, they might implement changes such as "reconsidering participants for the next meeting."

[0158] This allows users to improve their work efficiency and implement effective work improvements that take their emotional state into consideration. This system comprehensively supports work management and emotional care.

[0159] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0160] Step 1:

[0161] The server collects business information. Inputs include schedule information and interaction history via API. Outputs include the collected data being stored in an internal database. Specifically, the server periodically sends API requests to retrieve new business information and update the database.

[0162] Step 2:

[0163] The server analyzes the collected data to identify emotional states. Inputs include audio data and text logs. Based on this data, natural language processing and speech analysis are performed to calculate the user's emotional score. The output is stored in a database as numerical values ​​and categories representing each user's emotional state. Specifically, the server first transcribes the audio data and then uses natural language processing techniques to identify emotions.

[0164] Step 3:

[0165] The server evaluates the effectiveness of meetings based on emotional states and operational information. Inputs include emotional scores, meeting dates, and participant lists. It performs data analysis and calculates metrics to evaluate the effectiveness of the meetings. The output is a report on the effectiveness of the meetings, which is recorded in the database. Specifically, the server analyzes fluctuations in emotional scores and performs an efficiency evaluation for each meeting.

[0166] Step 4:

[0167] The server creates a business improvement plan using a generative AI model. Effectiveness reports and sentiment data from meetings are used as input. The generative AI model is prompted with the command "Create business improvement proposals," and generates specific improvement proposals. The output is an improvement plan, which is presented to the user. Specifically, the server adjusts the generated improvement proposals based on predefined criteria and organizes the proposals for the user.

[0168] Step 5:

[0169] The terminal presents the improvement plan to the user's display device. The input is the improvement plan sent from the server. This plan is displayed visually to make it easily understandable to the user. The output is a dashboard that the user can view, which is displayed on the terminal. Specifically, the terminal uses a JavaScript framework to build an interactive UI and effectively display information from the server.

[0170] Step 6:

[0171] The user accepts the proposed improvement plan and adjusts their work procedures. The input is the improvement plan displayed on the terminal. The output is the adjusted workflow and the new meeting schedule. Specifically, the user follows the instructions in the improvement plan to restructure the meeting frequency and participants, and perform operations to improve work efficiency.

[0172] (Application Example 2)

[0173] 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."

[0174] In modern manufacturing environments, worker efficiency and safety can be significantly influenced by their emotional state. However, existing systems lacked the technology to monitor workers' emotional states in real time and respond appropriately. This resulted in insufficient work adjustments and adequate worker health management, making it difficult to improve production efficiency and the work environment.

[0175] 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.

[0176] In this invention, the server includes means for collecting work information, means for analyzing the collected work information and evaluating the effectiveness of each meeting, and means for monitoring the emotional state of workers and making appropriate work adjustments. This makes it possible to grasp the emotional state of workers in real time and to suggest appropriate breaks and adjust the work process.

[0177] "Business information" refers to all data generated within a company, and specifically includes schedule information and communication history.

[0178] "Means of collection" refers to systems and methods for effectively acquiring necessary business information.

[0179] "Means of analysis" refers to the process of identifying the effectiveness and areas for improvement of information based on collected data.

[0180] "Meeting effectiveness" is an indicator used to evaluate how much a meeting or discussion contributes to achieving its goals.

[0181] A "business process" refers to a series of steps related to production or service provision, and is the subject of optimization.

[0182] An "improvement plan" is a collection of specific improvement measures proposed to enhance operational efficiency.

[0183] "Users" refer to individuals or organizations that use this system and benefit from it.

[0184] "Worker emotional state" refers to the emotional aspects related to a worker's mental health and well-being, and is a factor that affects work performance.

[0185] "Information processing equipment" refers to electronic devices and software used to analyze data and present results.

[0186] This invention is a system for improving work efficiency and safety in production sites. Specifically, a server plays a central role in collecting and analyzing work information and evaluating the emotional state of workers. The server is composed of multiple modules and uses a system that efficiently acquires work information for data collection. Specifically, it can collect work information including schedule information and communication history.

[0187] The server uses a generative AI model to analyze the emotional state of workers in real time based on the collected data. For example, software called EmotionEngine analyzes voice and text data to understand the emotional state of workers. This data is useful for optimizing work processes and generating improvement plans. Based on this information, the server creates improvement plans and proposes them to users.

[0188] The terminal is equipped with an information processing device that visually displays the generated improvement plan. Specifically, it has a function to notify users of appropriate work adjustments and break suggestions. This allows users to improve productivity while monitoring their own health status. For example, if a worker's stress level is high, the terminal can send a break notification and provide relaxation techniques.

[0189] As a concrete example, in an automotive parts factory, the introduction of this system enabled a quick and appropriate response to problems that arose when a new assembly line was installed.

[0190] An example of a prompt sentence to input into the generating AI model is: "Design an application for smart glasses that monitors the emotional state of workers in real time to improve work efficiency in an automotive parts factory."

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

[0192] Step 1:

[0193] The server collects business information. Specifically, it retrieves information from databases such as schedule information and communication history. The inputs used are each user's calendar information and communication history. The output is the collected business information. The server stores this data in a processing queue.

[0194] Step 2:

[0195] The server evaluates the effectiveness of each meeting based on the collected data. It uses a generative AI model to perform data analysis. The input is the business information obtained in Step 1. The output is the evaluation results regarding the effectiveness of each meeting. The server generates these results as an evaluation report.

[0196] Step 3:

[0197] The server analyzes the worker's voice and text data to identify their emotional state. It utilizes EmotionEngine for emotion analysis. Inputs include real-time collected voice and text data. Outputs provide information about the worker's emotional state. The server uses this information to update the emotional profile.

[0198] Step 4:

[0199] The server generates optimization proposals for business processes based on the analysis results. It uses a generating AI model to create the optimal improvement plan. Inputs include evaluation results from steps 2 and 3, and emotional state information. The output is an optimized business process plan. The server prepares this plan as a proposal document.

[0200] Step 5:

[0201] The terminal visually presents the generated improvement plan. The user can view the plan through the information processing device. The input is the improvement plan prepared in step 4. The output is the visually displayed suggestion information. The terminal notifies the user of this.

[0202] Step 6:

[0203] The user receives notifications on their device and selects the appropriate action. Inputs include improvement plans and notification information. Output is the action selected by the user. The user then utilizes the suggested break or relaxation techniques.

[0204] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0205] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0206] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0207] [Second Embodiment]

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

[0209] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0210] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0211] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0212] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0213] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0214] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0215] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0216] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0217] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0218] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0219] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0220] The system of the present invention consists of a series of processes in which a server, terminals, and users work together to improve operational efficiency within a company. Specific embodiments are shown below.

[0221] The server first collects work data from each user's calendar and messaging tools. This stores the schedules of meetings that users regularly attend and their communication history in a database. This data forms the basis for subsequent analytical processing.

[0222] After data is collected, the server uses an AI algorithm to evaluate the effectiveness of each meeting. This evaluation includes the meeting's purpose, duration, participants' roles, and outcomes achieved. For meetings deemed ineffective, suggestions for improvement are provided to participants and their supervisors. This promotes reduced attendance and more efficient meeting management.

[0223] Furthermore, the server analyzes each user's workflow based on the collected business data and generates an optimization plan. This streamlines business processes and improves productivity. The optimization plan is displayed on the user's dashboard via their terminal, allowing users to directly refer to it in their daily work.

[0224] Users can visualize their work and learning progress through the provided dashboard. This visualization includes information such as completed tasks, unfinished tasks, and new skills to acquire, making it easier for users to understand directions for skill improvement and work efficiency. For example, new employees can use this feature as a benchmark to quickly adapt to the organization during their orientation period.

[0225] The server also analyzes communication between teams and departments and provides improvement measures as needed. For example, if there is a lack of communication between departments, specific advice on recommended communication methods and information to share will be automatically provided. The terminal organizes this information and sends timely alerts to the user.

[0226] As described above, the system of the present invention helps to improve the efficiency of operations through the collection and analysis of business data, optimizes the importance of meetings and the adaptation process for new employees, and achieves improved productivity throughout the organization.

[0227] The following describes the processing flow.

[0228] Step 1:

[0229] The server periodically collects schedule and communication data from each user's calendar and messaging tools within the company. This includes the date and time of each meeting, participants, purpose, and message sending and receiving history.

[0230] Step 2:

[0231] The server analyzes the collected data using an AI algorithm to evaluate the effectiveness of each meeting. Specifically, it examines whether the meeting's objectives were achieved, whether the participants were appropriate, and whether the duration was practical. Based on these results, it calculates an effectiveness score.

[0232] Step 3:

[0233] The server identifies meetings that are unnecessary or need improvement based on their effectiveness score. Based on this information, it creates a list of potential meetings to be cut, reports it to supervisors and relevant departments, and sends improvement suggestions.

[0234] Step 4:

[0235] The server analyzes the user's business processes and generates an optimization plan for the workflow based on the collected data. This plan includes specific steps on how to improve particular business processes.

[0236] Step 5:

[0237] The device displays the generated optimization plan on the user's dashboard. Based on this information, users can improve the prioritization and methods of their daily tasks.

[0238] Step 6:

[0239] The device displays each user's skill assessment and uncompleted tasks on a dashboard to visualize their learning progress. This allows users to understand their areas of growth and the challenges they should focus on.

[0240] Step 7:

[0241] The server analyzes the state of communication between departments and identifies common problems. Based on this, it automatically generates improvement suggestions and specific action plans and notifies the relevant departments.

[0242] Through these processes, users can leverage the system to improve their own work efficiency and strengthen collaboration across the entire organization.

[0243] (Example 1)

[0244] 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."

[0245] In modern businesses, improving operational efficiency and productivity are crucial challenges. However, effective meetings and optimized business processes are often insufficient, leading to wasted resources. Furthermore, the learning progress of individual employees is unclear, and insufficient information sharing across the organization easily creates communication gaps between departments. Addressing these challenges and improving overall organizational efficiency is essential.

[0246] 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.

[0247] In this invention, the server includes means for collecting business information, means for analyzing the collected business information and evaluating the efficiency of each meeting, and means for proposing improvements to the meetings based on the evaluation. This enables transparency and optimization of business processes, effective operation of meetings, and visualization of the learning progress of individual employees.

[0248] "Business information" refers to data related to various activities within a company, including information such as meeting schedules, communication history, and task progress.

[0249] "Evaluating efficiency" is the process of measuring how effective tasks and meetings are in achieving goals, using indicators such as purpose, time required, and results.

[0250] "Suggesting improvements" means analyzing current business processes and meeting procedures, and presenting specific methods for achieving better results.

[0251] "Optimizing business processes" means reviewing the flow of work, eliminating waste, and improving processes to efficiently achieve goals.

[0252] "Visualizing learning progress" means clarifying and visually displaying the learning progress and skill improvement status of individual employees.

[0253] A "digital device" is a device that has the ability to process and display digital data, and includes personal computers, smartphones, tablets, and other similar devices.

[0254] The system of this invention is designed to improve operational efficiency within a company, and operates through the cooperation of a server, terminals, and users. The server plays a central role, collecting and analyzing business information and generating improvement proposals. Specifically, the server uses APIs to collect data and retrieve information from various digital sources. This includes schedule information from calendar applications (e.g., Google Calendar, Microsoft Outlook) and communication history from messaging tools.

[0255] The server utilizes a generative AI model to analyze the collected information. This AI model applies natural language processing technology to analyze the content and progress of meetings and evaluate the efficiency of each meeting. Furthermore, based on the analysis results, it automatically generates specific improvement suggestions using prompt sentences. For example, by asking the AI ​​questions such as, "How can we narrow down the agenda for the next meeting?", practical suggestions can be elicited.

[0256] The terminal functions as a device that presents the user with optimization plans and improvement suggestions generated by the server. Personal computers and smartphones are used for this purpose. This allows users to check their work progress and learning status in real time through a dashboard. Based on the information displayed on the dashboard, users can review their work priorities and make improvements.

[0257] As a concrete example, consider the case where new employees use this system during their orientation period. The server analyzes business information and presents efficient workflows, making it easier for new employees to quickly adapt to the organization's culture and processes. An example of a prompt message could be, "Please suggest a recommended task management method for new employees."

[0258] Thus, the present invention improves organizational productivity by efficiently analyzing business information and providing improvement suggestions to users.

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

[0260] Step 1:

[0261] The server collects business information from various digital sources. It receives calendar information and communication history as input via APIs and stores this information in a database. Specifically, it uses APIs from Google Calendar and messaging apps to periodically retrieve schedules and messages.

[0262] Step 2:

[0263] The server inputs the collected business information into an AI model for data analysis. Based on this information, the AI ​​model uses natural language processing technology to analyze meeting minutes and communication content. The output is a report that evaluates the efficiency of each meeting and identifies areas for improvement.

[0264] Step 3:

[0265] The server generates prompts based on the analysis results and creates improvement suggestions. For example, it might ask the AI ​​model a question using a prompt like, "What are the key points for narrowing the agenda at the next meeting?" Based on this, it obtains specific improvement suggestions as output and passes them on to the next process.

[0266] Step 4:

[0267] The terminal displays optimization plans and improvement suggestions received from the server on the user's dashboard. This step involves updating the user interface to allow users to intuitively access information. The input begins with receiving improvement suggestions, and the output presents visually organized information.

[0268] Step 5:

[0269] Users refer to the presented dashboard information to check their work progress and important tasks. They also provide feedback to the server and evaluate the effectiveness of improvement suggestions. This feedback serves as input for the next analysis step and acts as output that contributes to further system improvement.

[0270] (Application Example 1)

[0271] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0272] Improving operational efficiency within companies presents challenges such as evaluating the effectiveness of meetings and optimizing workflows. However, existing systems are insufficient in optimizing the operation schedules of machinery and equipment using work history and communication information, making efficient business operations difficult. Therefore, new methods are needed to more effectively optimize work schedules and improve business processes.

[0273] 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.

[0274] In this invention, the server includes means for collecting business information, means for evaluating the effectiveness of each consultation based on the collected information, means for generating and presenting improvement proposals to optimize business processes, and means for analyzing work history and communication information to optimize the operation schedule of machinery and business processes. This makes the operation of machinery within the company more efficient and enables the optimization of work schedules.

[0275] "Business information" is a general term for data and records related to various business operations within a company.

[0276] "Means of collection" refers to methods and equipment for importing necessary data into devices such as servers and terminals.

[0277] "Means of analysis" refer to methods and equipment for analyzing collected data and determining its meaning and value.

[0278] "Means of evaluating effectiveness" refers to methods and equipment for measuring the outcomes of activities and processes and determining their value.

[0279] "Means of judgment" refer to the methods and equipment used to determine appropriate responses based on the analysis results.

[0280] "Business process" refers to a series of work processes or flows carried out within an organization.

[0281] An "improvement proposal" is a suggestion or plan to make the current process more efficient.

[0282] "Means of presentation" refers to methods and equipment for clearly displaying analysis results and improvement proposals to users.

[0283] "Work history" refers to the records of the work performed by mechanical devices or people in the past.

[0284] "Communication information" refers to the records and content regarding the exchange of data between digital devices.

[0285] "Mechanical device" refers to a device or robot designed to perform a specific task.

[0286] "Operation schedule" refers to the plan or schedule of the work that a mechanical device should execute within a certain period.

[0287] "Optimize" means to adjust and improve a process or system to make it as efficient as possible.

[0288] The system in this invention is designed to improve the business efficiency within an enterprise. Centered around a server, it collects and analyzes business information and provides a plan aimed at effective business improvement. Specifically, the server collects the schedule information and communication history of each user, and analyzes these data from multiple perspectives. For the analysis, AI models such as TensorFlow are used to analyze the meaning of the data and evaluate the effectiveness of the business.

[0289] The terminal presents the generated improvement plan to the user's dashboard. In this dashboard, ReactJS is utilized for the user interface to provide an understandable graphical display. Based on the displayed information, the user can confirm their business progress and learning progress and attempt to improve their business.

[0290] The server also collects and analyzes the operation history and communication information of mechanical devices to optimize the operation schedule and business process. Thereby, it can effectively improve the operation of machines in the enterprise's manufacturing line.

[0291] Specifically, robots in the manufacturing process generate efficient operation schedules based on motion data obtained from sensors. For example, it analyzes when and what tasks a robot should perform, enabling operation that eliminates delays and waste. In this process, an optimized plan is generated on a server using a generation AI model.

[0292] An example of a prompt message is: "Create an AI model to generate efficient schedules and workflows for robot operations on a manufacturing line. Use work logs, communication history, utilization rate data, etc., as datasets to enable optimization suggestions."

[0293] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0294] Step 1:

[0295] The server collects users' schedule information and communication history. This provides input data for business use. Specifically, it extracts information from each user's digital calendar and messaging application via APIs and stores it in a database.

[0296] Step 2:

[0297] The server analyzes the collected business information using an AI algorithm. In this process, the effectiveness of each meeting is evaluated using a generative AI model based on TensorFlow. Calendar information and communication logs are referenced as input, and a report on the meeting's effectiveness and areas for improvement is generated as output. Specifically, the data is preprocessed and then fed into the analysis model.

[0298] Step 3:

[0299] The server generates improvement proposals to optimize business processes based on the analysis results. Here, prompts are generated, and the AI ​​proposes optimization suggestions. These generated improvement proposals are then obtained as output. The improvement proposals identify bottlenecks in the business process and include recommendations for efficiency improvements.

[0300] Step 4:

[0301] The terminal displays improvement suggestions received from the server on the user's dashboard. The input consists of specific improvement suggestions sent from the server, and the output is displayed in a visually easy-to-understand format for the user. Specifically, the improvement suggestions are presented as graphs and lists through an interface using ReactJS.

[0302] Step 5:

[0303] The server collects and analyzes the operation history and communication information of the machinery and equipment to optimize the operation schedule. Inputs include sensor recordings and log information from the machinery. After processing the data, an optimal operation schedule is generated and provided as output. Specifically, the server analyzes the time required for each task of the machinery and equipment, designing an efficient work sequence.

[0304] 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.

[0305] The system of the present invention aims to improve operational efficiency within companies. In addition to collecting and analyzing operational data, it combines this with an emotion engine to monitor the emotional state of users and support business improvement based on that data. The following describes specific embodiments of the present invention.

[0306] First, the server collects business data such as each user's calendar information and message history. This business data is used as the basic data for evaluating the effectiveness of meetings. Separately, the server uses an emotion engine to recognize the emotional state of the user from the user's voice and text. The emotion engine analyzes the words and conversation tones uttered by the user in real time by means of natural language processing and speech analysis technologies to identify the emotional state.

[0307] Next, the server evaluates the effectiveness of each meeting based on the collected business data and the user's emotional state, and determines the necessity of the meeting. At this time, for meetings with large fluctuations in emotions or meetings with frequent negative emotions, particularly detailed analysis is carried out, and suggestions are proposed to the user on how to improve. For example, specific proposals such as reducing the frequency of meetings, changing the participants, or reviewing the agenda are presented.

[0308] Furthermore, the server generates an improvement plan for optimizing the business process. This plan also includes stress relief measures and business load adjustment plans according to the user's emotional state. The terminal displays this improvement plan on the user's dashboard to make it easier to visually grasp.

[0309] In addition, the terminal provides a function for visualizing the emotional state to the user. Thereby, the user can utilize it to grasp their own mental health and workplace environment adaptation. As a specific example, when it is determined that the user has accumulated work stress, the system can send a notification proposing a break or provide information on relaxation techniques.

[0310] According to the present invention, the user can improve their own work efficiency and build a better cooperation system across the organization while considering the emotional situation. This system goes beyond the framework of a mere business management tool and realizes comprehensive business support including emotional aspects.

[0311] The following describes the processing flow.

[0312] Step 1:

[0313] The server collects work data from each user's calendar and messaging tools. At this stage, meeting dates and times, participant lists, and agenda details are retrieved and stored in the database.

[0314] Step 2:

[0315] The server uses AI algorithms to evaluate the effectiveness of meetings based on collected business data. Specifically, it analyzes whether the meeting's objectives are appropriate, the duration is reasonable, and the roles of the participants are clear. An effectiveness score is calculated based on the evaluation results.

[0316] Step 3:

[0317] The emotion engine accesses the user's calls and chats, recognizing their emotional state from the voice data and text. It analyzes the user's tone of voice and word choice using natural language processing technology to determine whether the emotion is positive or negative.

[0318] Step 4:

[0319] The server combines the output of the emotion engine to re-evaluate the effectiveness of the meeting. In particular, meetings where negative emotions were frequently observed are deemed to have a high need for improvement and undergo a detailed analysis.

[0320] Step 5:

[0321] The server generates an optimization plan for the workflow. The plan includes suggestions for improving meetings and proposes specific steps such as participant adjustments and agenda restructuring. It also incorporates work adjustment proposals that take user emotions into consideration.

[0322] Step 6:

[0323] The device provides an optimization plan and a dashboard that visualizes the user's emotional state. Through this, users can check their current work challenges and their own emotional state.

[0324] Step 7:

[0325] Users adjust their work based on the dashboard. For example, if the system analyzes that they are experiencing stress, they can choose actions such as taking appropriate breaks or assigning tasks more efficiently.

[0326] Step 8:

[0327] The server continuously monitors inter-departmental communication and, as needed, utilizes feedback from the emotion engine to formulate improvement suggestions. Based on this, the system continuously supports smooth communication within the organization.

[0328] (Example 2)

[0329] 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".

[0330] In today's work environment, there is a challenge in properly managing and evaluating the effectiveness of meetings and the emotional state of operators. This challenge leads to unnecessary meetings, decreased work efficiency, and increased mental burden on operators. Furthermore, there is a need to propose work improvement plans that take operators' emotional states into consideration, but doing so manually requires a great deal of time and effort.

[0331] 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.

[0332] In this invention, the server includes means for collecting business information, means for analyzing the collected business information and evaluating the effectiveness of meetings, and means for determining the necessity of meetings based on the analysis. This makes it possible to efficiently evaluate the effectiveness of meetings and automatically generate and present necessary improvement plans. Furthermore, by providing means for analyzing the emotional state of the operator, it is possible to propose appropriate workload reduction measures according to the operator's emotions, thereby simultaneously improving work efficiency and mental health.

[0333] "Business information" refers to all data related to activities within a company or organization, including schedule information and dialogue history.

[0334] A "meeting" refers to a conference or meeting held for the purpose of sharing information and making decisions necessary for the progress of work or projects.

[0335] "Operators" refer to end-users and employees who utilize this system, and are the entities whose individual work data and emotional states influence the system.

[0336] "Emotional state" refers to information that indicates the operator's psychological state, and is recognized through the analysis of voice and text data.

[0337] "Evaluation" is the act of judging the effectiveness of a meeting or the efficiency of operations based on specific criteria or indicators.

[0338] An "improvement plan" is a proposal for optimizing business processes generated by the system, and includes suggestions aimed at improving the structure of meetings and reducing the workload of operators.

[0339] "Load reduction measures" refer to specific methods and action plans proposed to reduce work-related stress and workload, taking into account the emotional state of the operator.

[0340] A "display device" refers to a device or interface used to provide information to an operator, with dashboards being a concrete example.

[0341] The embodiments for carrying out the present invention will now be described. This system supports business management within a company by considering both the user's work efficiency and emotional state. The entire system is mainly composed of three elements: a server, a terminal, and a user, which work together in cooperation with each other.

[0342] First, the server uses APIs to retrieve schedule information and conversation history to collect business information. For this, it utilizes a common API platform, for example, using MySQL as the database system and Python for data analysis. The server also performs natural language processing and speech analysis to analyze emotional states. Specifically, it uses Python's NLTK library and TensorFlow to estimate the user's emotional state from speech and text data.

[0343] Based on the analyzed information, the server evaluates the effectiveness of each meeting and generates improvement plans as needed. These improvement plans are generated using a generative AI model. An example of a prompt for the generative AI model is, "Create business improvement proposals."

[0344] Next, the device visually presents the improvement plan sent from the server to the user. The device is equipped with a dashboard using a JavaScript framework (e.g., React), through which the user can view the information. The device also visualizes the user's emotional state and provides stress reduction measures based on that information.

[0345] Based on this improvement plan, users will review their work processes and adjust the meeting structure and workload. For example, based on the results of sentiment analysis, they might implement changes such as "reconsidering participants for the next meeting."

[0346] This allows users to improve their work efficiency and implement effective work improvements that take their emotional state into consideration. This system comprehensively supports work management and emotional care.

[0347] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0348] Step 1:

[0349] The server collects business information. Inputs include schedule information and interaction history via API. Outputs include the collected data being stored in an internal database. Specifically, the server periodically sends API requests to retrieve new business information and update the database.

[0350] Step 2:

[0351] The server analyzes the collected data to identify emotional states. Inputs include audio data and text logs. Based on this data, natural language processing and speech analysis are performed to calculate the user's emotional score. The output is stored in a database as numerical values ​​and categories representing each user's emotional state. Specifically, the server first transcribes the audio data and then uses natural language processing techniques to identify emotions.

[0352] Step 3:

[0353] The server evaluates the effectiveness of meetings based on emotional states and operational information. Inputs include emotional scores, meeting dates, and participant lists. It performs data analysis and calculates metrics to evaluate the effectiveness of the meetings. The output is a report on the effectiveness of the meetings, which is recorded in the database. Specifically, the server analyzes fluctuations in emotional scores and performs an efficiency evaluation for each meeting.

[0354] Step 4:

[0355] The server creates a business improvement plan using a generative AI model. Effectiveness reports and sentiment data from meetings are used as input. The generative AI model is prompted with the command "Create business improvement proposals," and generates specific improvement proposals. The output is an improvement plan, which is presented to the user. Specifically, the server adjusts the generated improvement proposals based on predefined criteria and organizes the proposals for the user.

[0356] Step 5:

[0357] The terminal presents the improvement plan to the user's display device. The input is the improvement plan sent from the server. This plan is displayed visually to make it easily understandable to the user. The output is a dashboard that the user can view, which is displayed on the terminal. Specifically, the terminal uses a JavaScript framework to build an interactive UI and effectively display information from the server.

[0358] Step 6:

[0359] The user accepts the proposed improvement plan and adjusts their work procedures. The input is the improvement plan displayed on the terminal. The output is the adjusted workflow and the new meeting schedule. Specifically, the user follows the instructions in the improvement plan to restructure the meeting frequency and participants, and perform operations to improve work efficiency.

[0360] (Application Example 2)

[0361] 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."

[0362] In modern manufacturing environments, worker efficiency and safety can be significantly influenced by their emotional state. However, existing systems lacked the technology to monitor workers' emotional states in real time and respond appropriately. This resulted in insufficient work adjustments and adequate worker health management, making it difficult to improve production efficiency and the work environment.

[0363] 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.

[0364] In this invention, the server includes means for collecting work information, means for analyzing the collected work information and evaluating the effectiveness of each meeting, and means for monitoring the emotional state of workers and making appropriate work adjustments. This makes it possible to grasp the emotional state of workers in real time and to suggest appropriate breaks and adjust the work process.

[0365] "Business information" refers to all data generated within a company, and specifically includes schedule information and communication history.

[0366] "Means of collection" refers to systems and methods for effectively acquiring necessary business information.

[0367] "Means of analysis" refers to the process of identifying the effectiveness and areas for improvement of information based on collected data.

[0368] "Meeting effectiveness" is an indicator used to evaluate how much a meeting or discussion contributes to achieving its goals.

[0369] A "business process" refers to a series of steps related to production or service provision, and is the subject of optimization.

[0370] An "improvement plan" is a collection of specific improvement measures proposed to enhance operational efficiency.

[0371] "Users" refer to individuals or organizations that use this system and benefit from it.

[0372] "Worker emotional state" refers to the emotional aspects related to a worker's mental health and well-being, and is a factor that affects work performance.

[0373] "Information processing equipment" refers to electronic devices and software used to analyze data and present results.

[0374] This invention is a system for improving work efficiency and safety in production sites. Specifically, a server plays a central role in collecting and analyzing work information and evaluating the emotional state of workers. The server is composed of multiple modules and uses a system that efficiently acquires work information for data collection. Specifically, it can collect work information including schedule information and communication history.

[0375] The server uses a generative AI model to analyze the emotional state of workers in real time based on the collected data. For example, software called EmotionEngine analyzes voice and text data to understand the emotional state of workers. This data is useful for optimizing work processes and generating improvement plans. Based on this information, the server creates improvement plans and proposes them to users.

[0376] The terminal is equipped with an information processing device that visually displays the generated improvement plan. Specifically, it has a function to notify users of appropriate work adjustments and break suggestions. This allows users to improve productivity while monitoring their own health status. For example, if a worker's stress level is high, the terminal can send a break notification and provide relaxation techniques.

[0377] As a concrete example, in an automotive parts factory, the introduction of this system enabled a quick and appropriate response to problems that arose when a new assembly line was installed.

[0378] An example of a prompt sentence to input into the generating AI model is: "Design an application for smart glasses that monitors the emotional state of workers in real time to improve work efficiency in an automotive parts factory."

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

[0380] Step 1:

[0381] The server collects business information. Specifically, it retrieves information from databases such as schedule information and communication history. The inputs used are each user's calendar information and communication history. The output is the collected business information. The server stores this data in a processing queue.

[0382] Step 2:

[0383] The server evaluates the effectiveness of each meeting based on the collected data. It uses a generative AI model to perform data analysis. The input is the business information obtained in Step 1. The output is the evaluation results regarding the effectiveness of each meeting. The server generates these results as an evaluation report.

[0384] Step 3:

[0385] The server analyzes the worker's voice and text data to identify their emotional state. It utilizes EmotionEngine for emotion analysis. Inputs include real-time collected voice and text data. Outputs provide information about the worker's emotional state. The server uses this information to update the emotional profile.

[0386] Step 4:

[0387] The server generates optimization proposals for business processes based on the analysis results. It uses a generating AI model to create the optimal improvement plan. Inputs include evaluation results from steps 2 and 3, and emotional state information. The output is an optimized business process plan. The server prepares this plan as a proposal document.

[0388] Step 5:

[0389] The terminal visually presents the generated improvement plan. The user can view the plan through the information processing device. The input is the improvement plan prepared in step 4. The output is the visually displayed suggestion information. The terminal notifies the user of this.

[0390] Step 6:

[0391] The user receives notifications on their device and selects the appropriate action. Inputs include improvement plans and notification information. Output is the action selected by the user. The user then utilizes the suggested break or relaxation techniques.

[0392] 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.

[0393] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0394] 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.

[0395] [Third Embodiment]

[0396] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0397] 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.

[0398] 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).

[0399] 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.

[0400] 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.

[0401] 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).

[0402] 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.

[0403] 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.

[0404] 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.

[0405] 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.

[0406] 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.

[0407] 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".

[0408] The system of the present invention consists of a series of processes in which a server, terminals, and users work together to improve operational efficiency within a company. Specific embodiments are shown below.

[0409] The server first collects work data from each user's calendar and messaging tools. This stores the schedules of meetings that users regularly attend and their communication history in a database. This data forms the basis for subsequent analytical processing.

[0410] After data is collected, the server uses an AI algorithm to evaluate the effectiveness of each meeting. This evaluation includes the meeting's purpose, duration, participants' roles, and outcomes achieved. For meetings deemed ineffective, suggestions for improvement are provided to participants and their supervisors. This promotes reduced attendance and more efficient meeting management.

[0411] Furthermore, the server analyzes each user's workflow based on the collected business data and generates an optimization plan. This streamlines business processes and improves productivity. The optimization plan is displayed on the user's dashboard via their terminal, allowing users to directly refer to it in their daily work.

[0412] Users can visualize their work and learning progress through the provided dashboard. This visualization includes information such as completed tasks, unfinished tasks, and new skills to acquire, making it easier for users to understand directions for skill improvement and work efficiency. For example, new employees can use this feature as a benchmark to quickly adapt to the organization during their orientation period.

[0413] The server also analyzes communication between teams and departments and provides improvement measures as needed. For example, if there is a lack of communication between departments, specific advice on recommended communication methods and information to share will be automatically provided. The terminal organizes this information and sends timely alerts to the user.

[0414] As described above, the system of the present invention helps to improve the efficiency of operations through the collection and analysis of business data, optimizes the importance of meetings and the adaptation process for new employees, and achieves improved productivity throughout the organization.

[0415] The following describes the processing flow.

[0416] Step 1:

[0417] The server periodically collects schedule and communication data from each user's calendar and messaging tools within the company. This includes the date and time of each meeting, participants, purpose, and message sending and receiving history.

[0418] Step 2:

[0419] The server analyzes the collected data using an AI algorithm to evaluate the effectiveness of each meeting. Specifically, it examines whether the meeting's objectives were achieved, whether the participants were appropriate, and whether the duration was practical. Based on these results, it calculates an effectiveness score.

[0420] Step 3:

[0421] The server identifies meetings that are unnecessary or need improvement based on their effectiveness score. Based on this information, it creates a list of potential meetings to be cut, reports it to supervisors and relevant departments, and sends improvement suggestions.

[0422] Step 4:

[0423] The server analyzes the user's business processes and generates an optimization plan for the workflow based on the collected data. This plan includes specific steps on how to improve particular business processes.

[0424] Step 5:

[0425] The device displays the generated optimization plan on the user's dashboard. Based on this information, users can improve the prioritization and methods of their daily tasks.

[0426] Step 6:

[0427] The device displays each user's skill assessment and uncompleted tasks on a dashboard to visualize their learning progress. This allows users to understand their areas of growth and the challenges they should focus on.

[0428] Step 7:

[0429] The server analyzes the state of communication between departments and identifies common problems. Based on this, it automatically generates improvement suggestions and specific action plans and notifies the relevant departments.

[0430] Through these processes, users can leverage the system to improve their own work efficiency and strengthen collaboration across the entire organization.

[0431] (Example 1)

[0432] 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."

[0433] In modern businesses, improving operational efficiency and productivity are crucial challenges. However, effective meetings and optimized business processes are often insufficient, leading to wasted resources. Furthermore, the learning progress of individual employees is unclear, and insufficient information sharing across the organization easily creates communication gaps between departments. Addressing these challenges and improving overall organizational efficiency is essential.

[0434] 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.

[0435] In this invention, the server includes means for collecting business information, means for analyzing the collected business information and evaluating the efficiency of each meeting, and means for proposing improvements to the meetings based on the evaluation. This enables transparency and optimization of business processes, effective operation of meetings, and visualization of the learning progress of individual employees.

[0436] "Business information" refers to data related to various activities within a company, including information such as meeting schedules, communication history, and task progress.

[0437] "Evaluating efficiency" is the process of measuring how effective tasks and meetings are in achieving goals, using indicators such as purpose, time required, and results.

[0438] "Suggesting improvements" means analyzing current business processes and meeting procedures, and presenting specific methods for achieving better results.

[0439] "Optimizing business processes" means reviewing the flow of work, eliminating waste, and improving processes to efficiently achieve goals.

[0440] "Visualizing learning progress" means clarifying and visually displaying the learning progress and skill improvement status of individual employees.

[0441] A "digital device" is a device that has the ability to process and display digital data, and includes personal computers, smartphones, tablets, and other similar devices.

[0442] The system of this invention is designed to improve operational efficiency within a company, and operates through the cooperation of a server, terminals, and users. The server plays a central role, collecting and analyzing business information and generating improvement proposals. Specifically, the server uses APIs to collect data and retrieve information from various digital sources. This includes schedule information from calendar applications (e.g., Google Calendar, Microsoft Outlook) and communication history from messaging tools.

[0443] The server utilizes a generative AI model to analyze the collected information. This AI model applies natural language processing technology to analyze the content and progress of meetings and evaluate the efficiency of each meeting. Furthermore, based on the analysis results, it automatically generates specific improvement suggestions using prompt sentences. For example, by asking the AI ​​questions such as, "How can we narrow down the agenda for the next meeting?", practical suggestions can be elicited.

[0444] The terminal functions as a device that presents the user with optimization plans and improvement suggestions generated by the server. Personal computers and smartphones are used for this purpose. This allows users to check their work progress and learning status in real time through a dashboard. Based on the information displayed on the dashboard, users can review their work priorities and make improvements.

[0445] As a concrete example, consider the case where new employees use this system during their orientation period. The server analyzes business information and presents efficient workflows, making it easier for new employees to quickly adapt to the organization's culture and processes. An example of a prompt message could be, "Please suggest a recommended task management method for new employees."

[0446] Thus, the present invention improves organizational productivity by efficiently analyzing business information and providing improvement suggestions to users.

[0447] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0448] Step 1:

[0449] The server collects business information from various digital sources. It receives calendar information and communication history as input via APIs and stores this information in a database. Specifically, it uses APIs from Google Calendar and messaging apps to periodically retrieve schedules and messages.

[0450] Step 2:

[0451] The server inputs the collected business information into an AI model for data analysis. Based on this information, the AI ​​model uses natural language processing technology to analyze meeting minutes and communication content. The output is a report that evaluates the efficiency of each meeting and identifies areas for improvement.

[0452] Step 3:

[0453] The server generates prompts based on the analysis results and creates improvement suggestions. For example, it might ask the AI ​​model a question using a prompt like, "What are the key points for narrowing the agenda at the next meeting?" Based on this, it obtains specific improvement suggestions as output and passes them on to the next process.

[0454] Step 4:

[0455] The terminal displays optimization plans and improvement suggestions received from the server on the user's dashboard. This step involves updating the user interface to allow users to intuitively access information. The input begins with receiving improvement suggestions, and the output presents visually organized information.

[0456] Step 5:

[0457] Users refer to the presented dashboard information to check their work progress and important tasks. They also provide feedback to the server and evaluate the effectiveness of improvement suggestions. This feedback serves as input for the next analysis step and acts as output that contributes to further system improvement.

[0458] (Application Example 1)

[0459] 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."

[0460] Improving operational efficiency within companies presents challenges such as evaluating the effectiveness of meetings and optimizing workflows. However, existing systems are insufficient in optimizing the operation schedules of machinery and equipment using work history and communication information, making efficient business operations difficult. Therefore, new methods are needed to more effectively optimize work schedules and improve business processes.

[0461] 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.

[0462] In this invention, the server includes means for collecting business information, means for evaluating the effectiveness of each consultation based on the collected information, means for generating and presenting improvement proposals to optimize business processes, and means for analyzing work history and communication information to optimize the operation schedule of machinery and business processes. This makes the operation of machinery within the company more efficient and enables the optimization of work schedules.

[0463] "Business information" is a general term for data and records related to various business operations within a company.

[0464] "Means of collection" refers to methods and equipment for importing necessary data into devices such as servers and terminals.

[0465] "Means of analysis" refer to methods and equipment for analyzing collected data and determining its meaning and value.

[0466] "Means of evaluating effectiveness" refers to methods and equipment for measuring the outcomes of activities and processes and determining their value.

[0467] "Means of judgment" refer to the methods and equipment used to determine appropriate responses based on the analysis results.

[0468] "Business process" refers to a series of work processes or flows carried out within an organization.

[0469] An "improvement proposal" is a suggestion or plan to make the current process more efficient.

[0470] "Means of presentation" refers to methods and equipment for clearly displaying analysis results and improvement proposals to users.

[0471] "Work history" refers to a record of the work performed by machinery, equipment, or people in the past.

[0472] "Communication information" refers to the records and content of data exchanges that occur between digital devices.

[0473] "Mechanical equipment" refers to devices or robots designed to perform specific tasks.

[0474] An "operation schedule" refers to the planned tasks that a machine or device should perform within a certain period of time.

[0475] "Optimization" means adjusting and improving a process or system to make it as efficient as possible.

[0476] The system in this invention is designed to improve operational efficiency within a company. A server acts as the central hub, collecting and analyzing operational information and providing plans aimed at effective business improvement. Specifically, the server collects each user's schedule information and communication history, and analyzes this data from multiple perspectives. AI models such as TensorFlow are used for the analysis, interpreting the meaning of the data and evaluating the effectiveness of the operations.

[0477] The terminal displays the generated improvement suggestions on the user's dashboard. This dashboard utilizes ReactJS for its user interface, providing a clear and easy-to-understand graphical display. Based on the displayed information, users can check their work progress and learning progress and work to improve their work.

[0478] The server also optimizes operating schedules and work processes by collecting and analyzing the operating history and communication information of machinery and equipment. This allows for more efficient and effective machine operation on a company's manufacturing line.

[0479] Specifically, robots in the manufacturing process generate efficient operation schedules based on motion data obtained from sensors. For example, it analyzes when and what tasks a robot should perform, enabling operation that eliminates delays and waste. In this process, an optimized plan is generated on a server using a generation AI model.

[0480] An example of a prompt message is: "Create an AI model to generate efficient schedules and workflows for robot operations on a manufacturing line. Use work logs, communication history, utilization rate data, etc., as datasets to enable optimization suggestions."

[0481] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0482] Step 1:

[0483] The server collects users' schedule information and communication history. This provides input data for business use. Specifically, it extracts information from each user's digital calendar and messaging application via APIs and stores it in a database.

[0484] Step 2:

[0485] The server analyzes the collected business information using an AI algorithm. In this process, the effectiveness of each meeting is evaluated using a generative AI model based on TensorFlow. Calendar information and communication logs are referenced as input, and a report on the meeting's effectiveness and areas for improvement is generated as output. Specifically, the data is preprocessed and then fed into the analysis model.

[0486] Step 3:

[0487] The server generates improvement proposals to optimize business processes based on the analysis results. Here, prompts are generated, and the AI ​​proposes optimization suggestions. These generated improvement proposals are then obtained as output. The improvement proposals identify bottlenecks in the business process and include recommendations for efficiency improvements.

[0488] Step 4:

[0489] The terminal displays improvement suggestions received from the server on the user's dashboard. The input consists of specific improvement suggestions sent from the server, and the output is displayed in a visually easy-to-understand format for the user. Specifically, the improvement suggestions are presented as graphs and lists through an interface using ReactJS.

[0490] Step 5:

[0491] The server collects and analyzes the operation history and communication information of the machinery and equipment to optimize the operation schedule. Inputs include sensor recordings and log information from the machinery. After processing the data, an optimal operation schedule is generated and provided as output. Specifically, the server analyzes the time required for each task of the machinery and equipment, designing an efficient work sequence.

[0492] 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.

[0493] The system of the present invention aims to improve operational efficiency within companies. In addition to collecting and analyzing operational data, it combines this with an emotion engine to monitor the emotional state of users and support business improvement based on that data. The following describes specific embodiments of the present invention.

[0494] First, the server collects business data such as each user's calendar information and message history. This business data is used as foundational data to evaluate the effectiveness of meetings. Separately, the server uses an emotion engine to recognize the user's emotional state from their voice and text. The emotion engine uses natural language processing and speech analysis technology to analyze the words and tone of conversation spoken by the user in real time and identify their emotional state.

[0495] Next, the server evaluates the effectiveness of each meeting and determines its necessity based on the collected business data and the user's emotional state. Meetings with significant emotional fluctuations or frequent negative emotions are analyzed in particular, and suggestions for improvement are provided to the user. For example, specific suggestions may be offered, such as reducing the frequency of meetings, changing participants, or revising the agenda.

[0496] Furthermore, the server generates improvement plans to optimize the workflow. These plans include stress reduction measures and workload adjustments tailored to the user's emotional state. The terminal displays these improvement plans on the user's dashboard for easy visual understanding.

[0497] Furthermore, the device provides users with a function that visualizes their emotional state. This allows users to understand their own mental health and adaptation to the work environment. For example, if the system determines that a user is accumulating work-related stress, it can send a notification suggesting a break or provide information on relaxation techniques.

[0498] This invention enables users to improve their own work efficiency, take emotional states into consideration, and build a better collaborative system across the entire organization. This system goes beyond a mere task management tool, providing comprehensive work support that includes emotional aspects.

[0499] The following describes the processing flow.

[0500] Step 1:

[0501] The server collects work data from each user's calendar and messaging tools. At this stage, meeting dates and times, participant lists, and agenda details are retrieved and stored in the database.

[0502] Step 2:

[0503] The server uses AI algorithms to evaluate the effectiveness of meetings based on collected business data. Specifically, it analyzes whether the meeting's objectives are appropriate, the duration is reasonable, and the roles of the participants are clear. An effectiveness score is calculated based on the evaluation results.

[0504] Step 3:

[0505] The emotion engine accesses the user's calls and chats, recognizing their emotional state from the voice data and text. It analyzes the user's tone of voice and word choice using natural language processing technology to determine whether the emotion is positive or negative.

[0506] Step 4:

[0507] The server combines the output of the emotion engine to re-evaluate the effectiveness of the meeting. In particular, meetings where negative emotions were frequently observed are deemed to have a high need for improvement and undergo a detailed analysis.

[0508] Step 5:

[0509] The server generates an optimization plan for the workflow. The plan includes suggestions for improving meetings and proposes specific steps such as participant adjustments and agenda restructuring. It also incorporates work adjustment proposals that take user emotions into consideration.

[0510] Step 6:

[0511] The device provides an optimization plan and a dashboard that visualizes the user's emotional state. Through this, users can check their current work challenges and their own emotional state.

[0512] Step 7:

[0513] Users adjust their work based on the dashboard. For example, if the system analyzes that they are experiencing stress, they can choose actions such as taking appropriate breaks or assigning tasks more efficiently.

[0514] Step 8:

[0515] The server continuously monitors inter-departmental communication and, as needed, utilizes feedback from the emotion engine to formulate improvement suggestions. Based on this, the system continuously supports smooth communication within the organization.

[0516] (Example 2)

[0517] 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."

[0518] In today's work environment, there is a challenge in properly managing and evaluating the effectiveness of meetings and the emotional state of operators. This challenge leads to unnecessary meetings, decreased work efficiency, and increased mental burden on operators. Furthermore, there is a need to propose work improvement plans that take operators' emotional states into consideration, but doing so manually requires a great deal of time and effort.

[0519] 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.

[0520] In this invention, the server includes means for collecting business information, means for analyzing the collected business information and evaluating the effectiveness of meetings, and means for determining the necessity of meetings based on the analysis. This makes it possible to efficiently evaluate the effectiveness of meetings and automatically generate and present necessary improvement plans. Furthermore, by providing means for analyzing the emotional state of the operator, it is possible to propose appropriate workload reduction measures according to the operator's emotions, thereby simultaneously improving work efficiency and mental health.

[0521] "Business information" refers to all data related to activities within a company or organization, including schedule information and dialogue history.

[0522] A "meeting" refers to a conference or meeting held for the purpose of sharing information and making decisions necessary for the progress of work or projects.

[0523] "Operators" refer to end-users and employees who utilize this system, and are the entities whose individual work data and emotional states influence the system.

[0524] "Emotional state" refers to information that indicates the operator's psychological state, and is recognized through the analysis of voice and text data.

[0525] "Evaluation" is the act of judging the effectiveness of a meeting or the efficiency of operations based on specific criteria or indicators.

[0526] An "improvement plan" is a proposal for optimizing business processes generated by the system, and includes suggestions aimed at improving the structure of meetings and reducing the workload of operators.

[0527] "Load reduction measures" refer to specific methods and action plans proposed to reduce work-related stress and workload, taking into account the emotional state of the operator.

[0528] A "display device" refers to a device or interface used to provide information to an operator, with dashboards being a concrete example.

[0529] The embodiments for carrying out the present invention will now be described. This system supports business management within a company by considering both the user's work efficiency and emotional state. The entire system is mainly composed of three elements: a server, a terminal, and a user, which work together in cooperation with each other.

[0530] First, the server uses APIs to retrieve schedule information and conversation history to collect business information. For this, it utilizes a common API platform, for example, using MySQL as the database system and Python for data analysis. The server also performs natural language processing and speech analysis to analyze emotional states. Specifically, it uses Python's NLTK library and TensorFlow to estimate the user's emotional state from speech and text data.

[0531] Based on the analyzed information, the server evaluates the effectiveness of each meeting and generates improvement plans as needed. These improvement plans are generated using a generative AI model. An example of a prompt for the generative AI model is, "Create business improvement proposals."

[0532] Next, the device visually presents the improvement plan sent from the server to the user. The device is equipped with a dashboard using a JavaScript framework (e.g., React), through which the user can view the information. The device also visualizes the user's emotional state and provides stress reduction measures based on that information.

[0533] Based on this improvement plan, users will review their work processes and adjust the meeting structure and workload. For example, based on the results of sentiment analysis, they might implement changes such as "reconsidering participants for the next meeting."

[0534] This allows users to improve their work efficiency and implement effective work improvements that take their emotional state into consideration. This system comprehensively supports work management and emotional care.

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

[0536] Step 1:

[0537] The server collects business information. Inputs include schedule information and interaction history via API. Outputs include the collected data being stored in an internal database. Specifically, the server periodically sends API requests to retrieve new business information and update the database.

[0538] Step 2:

[0539] The server analyzes the collected data to identify emotional states. Inputs include audio data and text logs. Based on this data, natural language processing and speech analysis are performed to calculate the user's emotional score. The output is stored in a database as numerical values ​​and categories representing each user's emotional state. Specifically, the server first transcribes the audio data and then uses natural language processing techniques to identify emotions.

[0540] Step 3:

[0541] The server evaluates the effectiveness of meetings based on emotional states and operational information. Inputs include emotional scores, meeting dates, and participant lists. It performs data analysis and calculates metrics to evaluate the effectiveness of the meetings. The output is a report on the effectiveness of the meetings, which is recorded in the database. Specifically, the server analyzes fluctuations in emotional scores and performs an efficiency evaluation for each meeting.

[0542] Step 4:

[0543] The server creates a business improvement plan using a generative AI model. Effectiveness reports and sentiment data from meetings are used as input. The generative AI model is prompted with the command "Create business improvement proposals," and generates specific improvement proposals. The output is an improvement plan, which is presented to the user. Specifically, the server adjusts the generated improvement proposals based on predefined criteria and organizes the proposals for the user.

[0544] Step 5:

[0545] The terminal presents the improvement plan to the user's display device. The input is the improvement plan sent from the server. This plan is displayed visually to make it easily understandable to the user. The output is a dashboard that the user can view, which is displayed on the terminal. Specifically, the terminal uses a JavaScript framework to build an interactive UI and effectively display information from the server.

[0546] Step 6:

[0547] The user accepts the proposed improvement plan and adjusts their work procedures. The input is the improvement plan displayed on the terminal. The output is the adjusted workflow and the new meeting schedule. Specifically, the user follows the instructions in the improvement plan to restructure the meeting frequency and participants, and perform operations to improve work efficiency.

[0548] (Application Example 2)

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

[0550] In modern manufacturing environments, worker efficiency and safety can be significantly influenced by their emotional state. However, existing systems lacked the technology to monitor workers' emotional states in real time and respond appropriately. This resulted in insufficient work adjustments and adequate worker health management, making it difficult to improve production efficiency and the work environment.

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

[0552] In this invention, the server includes means for collecting work information, means for analyzing the collected work information and evaluating the effectiveness of each meeting, and means for monitoring the emotional state of workers and making appropriate work adjustments. This makes it possible to grasp the emotional state of workers in real time and to suggest appropriate breaks and adjust the work process.

[0553] "Business information" refers to all data generated within a company, and specifically includes schedule information and communication history.

[0554] "Means of collection" refers to systems and methods for effectively acquiring necessary business information.

[0555] "Means of analysis" refers to the process of identifying the effectiveness and areas for improvement of information based on collected data.

[0556] "Meeting effectiveness" is an indicator used to evaluate how much a meeting or discussion contributes to achieving its goals.

[0557] A "business process" refers to a series of steps related to production or service provision, and is the subject of optimization.

[0558] An "improvement plan" is a collection of specific improvement measures proposed to enhance operational efficiency.

[0559] "Users" refer to individuals or organizations that use this system and benefit from it.

[0560] "Worker emotional state" refers to the emotional aspects related to a worker's mental health and well-being, and is a factor that affects work performance.

[0561] "Information processing equipment" refers to electronic devices and software used to analyze data and present results.

[0562] This invention is a system for improving work efficiency and safety in production sites. Specifically, a server plays a central role in collecting and analyzing work information and evaluating the emotional state of workers. The server is composed of multiple modules and uses a system that efficiently acquires work information for data collection. Specifically, it can collect work information including schedule information and communication history.

[0563] The server uses a generative AI model to analyze the emotional state of workers in real time based on the collected data. For example, software called EmotionEngine analyzes voice and text data to understand the emotional state of workers. This data is useful for optimizing work processes and generating improvement plans. Based on this information, the server creates improvement plans and proposes them to users.

[0564] The terminal is equipped with an information processing device that visually displays the generated improvement plan. Specifically, it has a function to notify users of appropriate work adjustments and break suggestions. This allows users to improve productivity while monitoring their own health status. For example, if a worker's stress level is high, the terminal can send a break notification and provide relaxation techniques.

[0565] As a concrete example, in an automotive parts factory, the introduction of this system enabled a quick and appropriate response to problems that arose when a new assembly line was installed.

[0566] An example of a prompt sentence to input into the generating AI model is: "Design an application for smart glasses that monitors the emotional state of workers in real time to improve work efficiency in an automotive parts factory."

[0567] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0568] Step 1:

[0569] The server collects business information. Specifically, it retrieves information from databases such as schedule information and communication history. The inputs used are each user's calendar information and communication history. The output is the collected business information. The server stores this data in a processing queue.

[0570] Step 2:

[0571] The server evaluates the effectiveness of each meeting based on the collected data. It uses a generative AI model to perform data analysis. The input is the business information obtained in Step 1. The output is the evaluation results regarding the effectiveness of each meeting. The server generates these results as an evaluation report.

[0572] Step 3:

[0573] The server analyzes the worker's voice and text data to identify their emotional state. It utilizes EmotionEngine for emotion analysis. Inputs include real-time collected voice and text data. Outputs provide information about the worker's emotional state. The server uses this information to update the emotional profile.

[0574] Step 4:

[0575] The server generates optimization proposals for business processes based on the analysis results. It uses a generating AI model to create the optimal improvement plan. Inputs include evaluation results from steps 2 and 3, and emotional state information. The output is an optimized business process plan. The server prepares this plan as a proposal document.

[0576] Step 5:

[0577] The terminal visually presents the generated improvement plan. The user can view the plan through the information processing device. The input is the improvement plan prepared in step 4. The output is the visually displayed suggestion information. The terminal notifies the user of this.

[0578] Step 6:

[0579] The user receives notifications on their device and selects the appropriate action. Inputs include improvement plans and notification information. Output is the action selected by the user. The user then utilizes the suggested break or relaxation techniques.

[0580] 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.

[0581] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0582] 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.

[0583] [Fourth Embodiment]

[0584] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0585] 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.

[0586] 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).

[0587] 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.

[0588] 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.

[0589] 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).

[0590] 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.

[0591] 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.

[0592] 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.

[0593] 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.

[0594] 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.

[0595] 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.

[0596] 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".

[0597] The system of the present invention consists of a series of processes in which a server, terminals, and users work together to improve operational efficiency within a company. Specific embodiments are shown below.

[0598] The server first collects work data from each user's calendar and messaging tools. This stores the schedules of meetings that users regularly attend and their communication history in a database. This data forms the basis for subsequent analytical processing.

[0599] After data is collected, the server uses an AI algorithm to evaluate the effectiveness of each meeting. This evaluation includes the meeting's purpose, duration, participants' roles, and outcomes achieved. For meetings deemed ineffective, suggestions for improvement are provided to participants and their supervisors. This promotes reduced attendance and more efficient meeting management.

[0600] Furthermore, the server analyzes each user's workflow based on the collected business data and generates an optimization plan. This streamlines business processes and improves productivity. The optimization plan is displayed on the user's dashboard via their terminal, allowing users to directly refer to it in their daily work.

[0601] Users can visualize their work and learning progress through the provided dashboard. This visualization includes information such as completed tasks, unfinished tasks, and new skills to acquire, making it easier for users to understand directions for skill improvement and work efficiency. For example, new employees can use this feature as a benchmark to quickly adapt to the organization during their orientation period.

[0602] The server also analyzes communication between teams and departments and provides improvement measures as needed. For example, if there is a lack of communication between departments, specific advice on recommended communication methods and information to share will be automatically provided. The terminal organizes this information and sends timely alerts to the user.

[0603] As described above, the system of the present invention helps to improve the efficiency of operations through the collection and analysis of business data, optimizes the importance of meetings and the adaptation process for new employees, and achieves improved productivity throughout the organization.

[0604] The following describes the processing flow.

[0605] Step 1:

[0606] The server periodically collects schedule and communication data from each user's calendar and messaging tools within the company. This includes the date and time of each meeting, participants, purpose, and message sending and receiving history.

[0607] Step 2:

[0608] The server analyzes the collected data using an AI algorithm to evaluate the effectiveness of each meeting. Specifically, it examines whether the meeting's objectives were achieved, whether the participants were appropriate, and whether the duration was practical. Based on these results, it calculates an effectiveness score.

[0609] Step 3:

[0610] The server identifies meetings that are unnecessary or need improvement based on their effectiveness score. Based on this information, it creates a list of potential meetings to be cut, reports it to supervisors and relevant departments, and sends improvement suggestions.

[0611] Step 4:

[0612] The server analyzes the user's business processes and generates an optimization plan for the workflow based on the collected data. This plan includes specific steps on how to improve particular business processes.

[0613] Step 5:

[0614] The device displays the generated optimization plan on the user's dashboard. Based on this information, users can improve the prioritization and methods of their daily tasks.

[0615] Step 6:

[0616] The device displays each user's skill assessment and uncompleted tasks on a dashboard to visualize their learning progress. This allows users to understand their areas of growth and the challenges they should focus on.

[0617] Step 7:

[0618] The server analyzes the state of communication between departments and identifies common problems. Based on this, it automatically generates improvement suggestions and specific action plans and notifies the relevant departments.

[0619] Through these processes, users can leverage the system to improve their own work efficiency and strengthen collaboration across the entire organization.

[0620] (Example 1)

[0621] 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".

[0622] In modern businesses, improving operational efficiency and productivity are crucial challenges. However, effective meetings and optimized business processes are often insufficient, leading to wasted resources. Furthermore, the learning progress of individual employees is unclear, and insufficient information sharing across the organization easily creates communication gaps between departments. Addressing these challenges and improving overall organizational efficiency is essential.

[0623] 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.

[0624] In this invention, the server includes means for collecting business information, means for analyzing the collected business information and evaluating the efficiency of each meeting, and means for proposing improvements to the meetings based on the evaluation. This enables transparency and optimization of business processes, effective operation of meetings, and visualization of the learning progress of individual employees.

[0625] "Business information" refers to data related to various activities within a company, including information such as meeting schedules, communication history, and task progress.

[0626] "Evaluating efficiency" is the process of measuring how effective tasks and meetings are in achieving goals, using indicators such as purpose, time required, and results.

[0627] "Suggesting improvements" means analyzing current business processes and meeting procedures, and presenting specific methods for achieving better results.

[0628] "Optimizing business processes" means reviewing the flow of work, eliminating waste, and improving processes to efficiently achieve goals.

[0629] "Visualizing learning progress" means clarifying and visually displaying the learning progress and skill improvement status of individual employees.

[0630] A "digital device" is a device that has the ability to process and display digital data, and includes personal computers, smartphones, tablets, and other similar devices.

[0631] The system of this invention is designed to improve operational efficiency within a company, and operates through the cooperation of a server, terminals, and users. The server plays a central role, collecting and analyzing business information and generating improvement proposals. Specifically, the server uses APIs to collect data and retrieve information from various digital sources. This includes schedule information from calendar applications (e.g., Google Calendar, Microsoft Outlook) and communication history from messaging tools.

[0632] The server utilizes a generative AI model to analyze the collected information. This AI model applies natural language processing technology to analyze the content and progress of meetings and evaluate the efficiency of each meeting. Furthermore, based on the analysis results, it automatically generates specific improvement suggestions using prompt sentences. For example, by asking the AI ​​questions such as, "How can we narrow down the agenda for the next meeting?", practical suggestions can be elicited.

[0633] The terminal functions as a device that presents the user with optimization plans and improvement suggestions generated by the server. Personal computers and smartphones are used for this purpose. This allows users to check their work progress and learning status in real time through a dashboard. Based on the information displayed on the dashboard, users can review their work priorities and make improvements.

[0634] As a concrete example, consider the case where new employees use this system during their orientation period. The server analyzes business information and presents efficient workflows, making it easier for new employees to quickly adapt to the organization's culture and processes. An example of a prompt message could be, "Please suggest a recommended task management method for new employees."

[0635] Thus, the present invention improves organizational productivity by efficiently analyzing business information and providing improvement suggestions to users.

[0636] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0637] Step 1:

[0638] The server collects business information from various digital sources. It receives calendar information and communication history as input via APIs and stores this information in a database. Specifically, it uses APIs from Google Calendar and messaging apps to periodically retrieve schedules and messages.

[0639] Step 2:

[0640] The server inputs the collected business information into an AI model for data analysis. Based on this information, the AI ​​model uses natural language processing technology to analyze meeting minutes and communication content. The output is a report that evaluates the efficiency of each meeting and identifies areas for improvement.

[0641] Step 3:

[0642] The server generates prompts based on the analysis results and creates improvement suggestions. For example, it might ask the AI ​​model a question using a prompt like, "What are the key points for narrowing the agenda at the next meeting?" Based on this, it obtains specific improvement suggestions as output and passes them on to the next process.

[0643] Step 4:

[0644] The terminal displays optimization plans and improvement suggestions received from the server on the user's dashboard. This step involves updating the user interface to allow users to intuitively access information. The input begins with receiving improvement suggestions, and the output presents visually organized information.

[0645] Step 5:

[0646] Users refer to the presented dashboard information to check their work progress and important tasks. They also provide feedback to the server and evaluate the effectiveness of improvement suggestions. This feedback serves as input for the next analysis step and acts as output that contributes to further system improvement.

[0647] (Application Example 1)

[0648] 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".

[0649] Improving operational efficiency within companies presents challenges such as evaluating the effectiveness of meetings and optimizing workflows. However, existing systems are insufficient in optimizing the operation schedules of machinery and equipment using work history and communication information, making efficient business operations difficult. Therefore, new methods are needed to more effectively optimize work schedules and improve business processes.

[0650] 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.

[0651] In this invention, the server includes means for collecting business information, means for evaluating the effectiveness of each consultation based on the collected information, means for generating and presenting improvement proposals to optimize business processes, and means for analyzing work history and communication information to optimize the operation schedule of machinery and business processes. This makes the operation of machinery within the company more efficient and enables the optimization of work schedules.

[0652] "Business information" is a general term for data and records related to various business operations within a company.

[0653] "Means of collection" refers to methods and equipment for importing necessary data into devices such as servers and terminals.

[0654] "Means of analysis" refer to methods and equipment for analyzing collected data and determining its meaning and value.

[0655] "Means of evaluating effectiveness" refers to methods and equipment for measuring the outcomes of activities and processes and determining their value.

[0656] "Means of judgment" refer to the methods and equipment used to determine appropriate responses based on the analysis results.

[0657] "Business process" refers to a series of work processes or flows carried out within an organization.

[0658] An "improvement proposal" is a suggestion or plan to make the current process more efficient.

[0659] "Means of presentation" refers to methods and equipment for clearly displaying analysis results and improvement proposals to users.

[0660] "Work history" refers to a record of the work performed by machinery, equipment, or people in the past.

[0661] "Communication information" refers to the records and content of data exchanges that occur between digital devices.

[0662] "Mechanical equipment" refers to devices or robots designed to perform specific tasks.

[0663] An "operation schedule" refers to the planned tasks that a machine or device should perform within a certain period of time.

[0664] "Optimization" means adjusting and improving a process or system to make it as efficient as possible.

[0665] The system in this invention is designed to improve operational efficiency within a company. A server acts as the central hub, collecting and analyzing operational information and providing plans aimed at effective business improvement. Specifically, the server collects each user's schedule information and communication history, and analyzes this data from multiple perspectives. AI models such as TensorFlow are used for the analysis, interpreting the meaning of the data and evaluating the effectiveness of the operations.

[0666] The terminal displays the generated improvement suggestions on the user's dashboard. This dashboard utilizes ReactJS for its user interface, providing a clear and easy-to-understand graphical display. Based on the displayed information, users can check their work progress and learning progress and work to improve their work.

[0667] The server also optimizes operating schedules and work processes by collecting and analyzing the operating history and communication information of machinery and equipment. This allows for more efficient and effective machine operation on a company's manufacturing line.

[0668] Specifically, robots in the manufacturing process generate efficient operation schedules based on motion data obtained from sensors. For example, it analyzes when and what tasks a robot should perform, enabling operation that eliminates delays and waste. In this process, an optimized plan is generated on a server using a generation AI model.

[0669] An example of a prompt message is: "Create an AI model to generate efficient schedules and workflows for robot operations on a manufacturing line. Use work logs, communication history, utilization rate data, etc., as datasets to enable optimization suggestions."

[0670] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0671] Step 1:

[0672] The server collects users' schedule information and communication history. This provides input data for business use. Specifically, it extracts information from each user's digital calendar and messaging application via APIs and stores it in a database.

[0673] Step 2:

[0674] The server analyzes the collected business information using an AI algorithm. In this process, the effectiveness of each meeting is evaluated using a generative AI model based on TensorFlow. Calendar information and communication logs are referenced as input, and a report on the meeting's effectiveness and areas for improvement is generated as output. Specifically, the data is preprocessed and then fed into the analysis model.

[0675] Step 3:

[0676] The server generates improvement proposals to optimize business processes based on the analysis results. Here, prompts are generated, and the AI ​​proposes optimization suggestions. These generated improvement proposals are then obtained as output. The improvement proposals identify bottlenecks in the business process and include recommendations for efficiency improvements.

[0677] Step 4:

[0678] The terminal displays improvement suggestions received from the server on the user's dashboard. The input consists of specific improvement suggestions sent from the server, and the output is displayed in a visually easy-to-understand format for the user. Specifically, the improvement suggestions are presented as graphs and lists through an interface using ReactJS.

[0679] Step 5:

[0680] The server collects and analyzes the operation history and communication information of the machinery and equipment to optimize the operation schedule. Inputs include sensor recordings and log information from the machinery. After processing the data, an optimal operation schedule is generated and provided as output. Specifically, the server analyzes the time required for each task of the machinery and equipment, designing an efficient work sequence.

[0681] 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.

[0682] The system of the present invention aims to improve operational efficiency within companies. In addition to collecting and analyzing operational data, it combines this with an emotion engine to monitor the emotional state of users and support business improvement based on that data. The following describes specific embodiments of the present invention.

[0683] First, the server collects business data such as each user's calendar information and message history. This business data is used as foundational data to evaluate the effectiveness of meetings. Separately, the server uses an emotion engine to recognize the user's emotional state from their voice and text. The emotion engine uses natural language processing and speech analysis technology to analyze the words and tone of conversation spoken by the user in real time and identify their emotional state.

[0684] Next, the server evaluates the effectiveness of each meeting and determines its necessity based on the collected business data and the user's emotional state. Meetings with significant emotional fluctuations or frequent negative emotions are analyzed in particular, and suggestions for improvement are provided to the user. For example, specific suggestions may be offered, such as reducing the frequency of meetings, changing participants, or revising the agenda.

[0685] Furthermore, the server generates improvement plans to optimize the workflow. These plans include stress reduction measures and workload adjustments tailored to the user's emotional state. The terminal displays these improvement plans on the user's dashboard for easy visual understanding.

[0686] Furthermore, the device provides users with a function that visualizes their emotional state. This allows users to understand their own mental health and adaptation to the work environment. For example, if the system determines that a user is accumulating work-related stress, it can send a notification suggesting a break or provide information on relaxation techniques.

[0687] This invention enables users to improve their own work efficiency, take emotional states into consideration, and build a better collaborative system across the entire organization. This system goes beyond a mere task management tool, providing comprehensive work support that includes emotional aspects.

[0688] The following describes the processing flow.

[0689] Step 1:

[0690] The server collects work data from each user's calendar and messaging tools. At this stage, meeting dates and times, participant lists, and agenda details are retrieved and stored in the database.

[0691] Step 2:

[0692] The server uses AI algorithms to evaluate the effectiveness of meetings based on collected business data. Specifically, it analyzes whether the meeting's objectives are appropriate, the duration is reasonable, and the roles of the participants are clear. An effectiveness score is calculated based on the evaluation results.

[0693] Step 3:

[0694] The emotion engine accesses the user's calls and chats, recognizing their emotional state from the voice data and text. It analyzes the user's tone of voice and word choice using natural language processing technology to determine whether the emotion is positive or negative.

[0695] Step 4:

[0696] The server combines the output of the emotion engine to re-evaluate the effectiveness of the meeting. In particular, meetings where negative emotions were frequently observed are deemed to have a high need for improvement and undergo a detailed analysis.

[0697] Step 5:

[0698] The server generates an optimization plan for the workflow. The plan includes suggestions for improving meetings and proposes specific steps such as participant adjustments and agenda restructuring. It also incorporates work adjustment proposals that take user emotions into consideration.

[0699] Step 6:

[0700] The device provides an optimization plan and a dashboard that visualizes the user's emotional state. Through this, users can check their current work challenges and their own emotional state.

[0701] Step 7:

[0702] Users adjust their work based on the dashboard. For example, if the system analyzes that they are experiencing stress, they can choose actions such as taking appropriate breaks or assigning tasks more efficiently.

[0703] Step 8:

[0704] The server continuously monitors inter-departmental communication and, as needed, utilizes feedback from the emotion engine to formulate improvement suggestions. Based on this, the system continuously supports smooth communication within the organization.

[0705] (Example 2)

[0706] 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".

[0707] In today's work environment, there is a challenge in properly managing and evaluating the effectiveness of meetings and the emotional state of operators. This challenge leads to unnecessary meetings, decreased work efficiency, and increased mental burden on operators. Furthermore, there is a need to propose work improvement plans that take operators' emotional states into consideration, but doing so manually requires a great deal of time and effort.

[0708] 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.

[0709] In this invention, the server includes means for collecting business information, means for analyzing the collected business information and evaluating the effectiveness of meetings, and means for determining the necessity of meetings based on the analysis. This makes it possible to efficiently evaluate the effectiveness of meetings and automatically generate and present necessary improvement plans. Furthermore, by providing means for analyzing the emotional state of the operator, it is possible to propose appropriate workload reduction measures according to the operator's emotions, thereby simultaneously improving work efficiency and mental health.

[0710] "Business information" refers to all data related to activities within a company or organization, including schedule information and dialogue history.

[0711] A "meeting" refers to a conference or meeting held for the purpose of sharing information and making decisions necessary for the progress of work or projects.

[0712] "Operators" refer to end-users and employees who utilize this system, and are the entities whose individual work data and emotional states influence the system.

[0713] "Emotional state" refers to information that indicates the operator's psychological state, and is recognized through the analysis of voice and text data.

[0714] "Evaluation" is the act of judging the effectiveness of a meeting or the efficiency of operations based on specific criteria or indicators.

[0715] An "improvement plan" is a proposal for optimizing business processes generated by the system, and includes suggestions aimed at improving the structure of meetings and reducing the workload of operators.

[0716] "Load reduction measures" refer to specific methods and action plans proposed to reduce work-related stress and workload, taking into account the emotional state of the operator.

[0717] A "display device" refers to a device or interface used to provide information to an operator, with dashboards being a concrete example.

[0718] The embodiments for carrying out the present invention will now be described. This system supports business management within a company by considering both the user's work efficiency and emotional state. The entire system is mainly composed of three elements: a server, a terminal, and a user, which work together in cooperation with each other.

[0719] First, the server uses APIs to retrieve schedule information and conversation history to collect business information. For this, it utilizes a common API platform, for example, using MySQL as the database system and Python for data analysis. The server also performs natural language processing and speech analysis to analyze emotional states. Specifically, it uses Python's NLTK library and TensorFlow to estimate the user's emotional state from speech and text data.

[0720] Based on the analyzed information, the server evaluates the effectiveness of each meeting and generates improvement plans as needed. These improvement plans are generated using a generative AI model. An example of a prompt for the generative AI model is, "Create business improvement proposals."

[0721] Next, the device visually presents the improvement plan sent from the server to the user. The device is equipped with a dashboard using a JavaScript framework (e.g., React), through which the user can view the information. The device also visualizes the user's emotional state and provides stress reduction measures based on that information.

[0722] Based on this improvement plan, users will review their work processes and adjust the meeting structure and workload. For example, based on the results of sentiment analysis, they might implement changes such as "reconsidering participants for the next meeting."

[0723] This allows users to improve their work efficiency and implement effective work improvements that take their emotional state into consideration. This system comprehensively supports work management and emotional care.

[0724] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0725] Step 1:

[0726] The server collects business information. Inputs include schedule information and interaction history via API. Outputs include the collected data being stored in an internal database. Specifically, the server periodically sends API requests to retrieve new business information and update the database.

[0727] Step 2:

[0728] The server analyzes the collected data to identify emotional states. Inputs include audio data and text logs. Based on this data, natural language processing and speech analysis are performed to calculate the user's emotional score. The output is stored in a database as numerical values ​​and categories representing each user's emotional state. Specifically, the server first transcribes the audio data and then uses natural language processing techniques to identify emotions.

[0729] Step 3:

[0730] The server evaluates the effectiveness of meetings based on emotional states and operational information. Inputs include emotional scores, meeting dates, and participant lists. It performs data analysis and calculates metrics to evaluate the effectiveness of the meetings. The output is a report on the effectiveness of the meetings, which is recorded in the database. Specifically, the server analyzes fluctuations in emotional scores and performs an efficiency evaluation for each meeting.

[0731] Step 4:

[0732] The server creates a business improvement plan using a generative AI model. Effectiveness reports and sentiment data from meetings are used as input. The generative AI model is prompted with the command "Create business improvement proposals," and generates specific improvement proposals. The output is an improvement plan, which is presented to the user. Specifically, the server adjusts the generated improvement proposals based on predefined criteria and organizes the proposals for the user.

[0733] Step 5:

[0734] The terminal presents the improvement plan to the user's display device. The input is the improvement plan sent from the server. This plan is displayed visually to make it easily understandable to the user. The output is a dashboard that the user can view, which is displayed on the terminal. Specifically, the terminal uses a JavaScript framework to build an interactive UI and effectively display information from the server.

[0735] Step 6:

[0736] The user accepts the proposed improvement plan and adjusts their work procedures. The input is the improvement plan displayed on the terminal. The output is the adjusted workflow and the new meeting schedule. Specifically, the user follows the instructions in the improvement plan to restructure the meeting frequency and participants, and perform operations to improve work efficiency.

[0737] (Application Example 2)

[0738] 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".

[0739] In modern manufacturing environments, worker efficiency and safety can be significantly influenced by their emotional state. However, existing systems lacked the technology to monitor workers' emotional states in real time and respond appropriately. This resulted in insufficient work adjustments and adequate worker health management, making it difficult to improve production efficiency and the work environment.

[0740] 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.

[0741] In this invention, the server includes means for collecting work information, means for analyzing the collected work information and evaluating the effectiveness of each meeting, and means for monitoring the emotional state of workers and making appropriate work adjustments. This makes it possible to grasp the emotional state of workers in real time and to suggest appropriate breaks and adjust the work process.

[0742] "Business information" refers to all data generated within a company, and specifically includes schedule information and communication history.

[0743] "Means of collection" refers to systems and methods for effectively acquiring necessary business information.

[0744] "Means of analysis" refers to the process of identifying the effectiveness and areas for improvement of information based on collected data.

[0745] "Meeting effectiveness" is an indicator used to evaluate how much a meeting or discussion contributes to achieving its goals.

[0746] A "business process" refers to a series of steps related to production or service provision, and is the subject of optimization.

[0747] An "improvement plan" is a collection of specific improvement measures proposed to enhance operational efficiency.

[0748] "Users" refer to individuals or organizations that use this system and benefit from it.

[0749] "Worker emotional state" refers to the emotional aspects related to a worker's mental health and well-being, and is a factor that affects work performance.

[0750] "Information processing equipment" refers to electronic devices and software used to analyze data and present results.

[0751] This invention is a system for improving work efficiency and safety in production sites. Specifically, a server plays a central role in collecting and analyzing work information and evaluating the emotional state of workers. The server is composed of multiple modules and uses a system that efficiently acquires work information for data collection. Specifically, it can collect work information including schedule information and communication history.

[0752] The server uses a generative AI model to analyze the emotional state of workers in real time based on the collected data. For example, software called EmotionEngine analyzes voice and text data to understand the emotional state of workers. This data is useful for optimizing work processes and generating improvement plans. Based on this information, the server creates improvement plans and proposes them to users.

[0753] The terminal is equipped with an information processing device that visually displays the generated improvement plan. Specifically, it has a function to notify users of appropriate work adjustments and break suggestions. This allows users to improve productivity while monitoring their own health status. For example, if a worker's stress level is high, the terminal can send a break notification and provide relaxation techniques.

[0754] As a concrete example, in an automotive parts factory, the introduction of this system enabled a quick and appropriate response to problems that arose when a new assembly line was installed.

[0755] An example of a prompt sentence to input into the generating AI model is: "Design an application for smart glasses that monitors the emotional state of workers in real time to improve work efficiency in an automotive parts factory."

[0756] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0757] Step 1:

[0758] The server collects business information. Specifically, it retrieves information from databases such as schedule information and communication history. The inputs used are each user's calendar information and communication history. The output is the collected business information. The server stores this data in a processing queue.

[0759] Step 2:

[0760] The server evaluates the effectiveness of each meeting based on the collected data. It uses a generative AI model to perform data analysis. The input is the business information obtained in Step 1. The output is the evaluation results regarding the effectiveness of each meeting. The server generates these results as an evaluation report.

[0761] Step 3:

[0762] The server analyzes the worker's voice and text data to identify their emotional state. It utilizes EmotionEngine for emotion analysis. Inputs include real-time collected voice and text data. Outputs provide information about the worker's emotional state. The server uses this information to update the emotional profile.

[0763] Step 4:

[0764] The server generates optimization proposals for business processes based on the analysis results. It uses a generating AI model to create the optimal improvement plan. Inputs include evaluation results from steps 2 and 3, and emotional state information. The output is an optimized business process plan. The server prepares this plan as a proposal document.

[0765] Step 5:

[0766] The terminal visually presents the generated improvement plan. The user can view the plan through the information processing device. The input is the improvement plan prepared in step 4. The output is the visually displayed suggestion information. The terminal notifies the user of this.

[0767] Step 6:

[0768] The user receives notifications on their device and selects the appropriate action. Inputs include improvement plans and notification information. Output is the action selected by the user. The user then utilizes the suggested break or relaxation techniques.

[0769] 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.

[0770] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0771] 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 robot 414.

[0772] 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.

[0773] 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.

[0774] 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.

[0775] 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.

[0776] 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.

[0777] 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."

[0778] 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.

[0779] 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.

[0780] 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.

[0781] 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.

[0782] 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.

[0783] 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.

[0784] 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.

[0785] 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.

[0786] 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.

[0787] 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.

[0788] 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.

[0789] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0790] The following is further disclosed regarding the embodiments described above.

[0791] (Claim 1)

[0792] Means of collecting business data,

[0793] A means of analyzing collected business data and evaluating the effectiveness of each meeting,

[0794] A means of determining the necessity of a meeting based on evaluation,

[0795] A means of generating and presenting improvement plans to optimize business workflows,

[0796] A means of visualizing the learning progress of individual users,

[0797] A system that includes this.

[0798] (Claim 2)

[0799] The system according to claim 1, wherein the data collection means acquires calendar information and communication history.

[0800] (Claim 3)

[0801] The system according to claim 1, which presents the generated improvement plan to the user's terminal.

[0802] "Example 1"

[0803] (Claim 1)

[0804] Means of collecting business information,

[0805] A means of analyzing collected business information and evaluating the efficiency of each meeting,

[0806] A means of proposing improvements to meetings based on evaluations,

[0807] A means for generating and displaying improvement proposals to optimize business processes,

[0808] A means of visualizing the learning progress of individual users,

[0809] A means of notifying alerts in cooperation with multiple digital devices,

[0810] A system that includes this.

[0811] (Claim 2)

[0812] The system according to claim 1, wherein the information gathering means incorporates scheduled information and dialogue history.

[0813] (Claim 3)

[0814] The system according to claim 1, which presents the generated improvement proposals to the user's digital device.

[0815] "Application Example 1"

[0816] (Claim 1)

[0817] Means of collecting business information,

[0818] A means of analyzing collected business information and evaluating the effectiveness of each consultation,

[0819] A means of determining the need for consultation based on the evaluation,

[0820] A means of generating and presenting improvement proposals to optimize business processes,

[0821] A means of visualizing the learning progress of individual users,

[0822] A means for analyzing work history and communication information to optimize the operating schedule and work processes of machinery and equipment,

[0823] A system that includes this.

[0824] (Claim 2)

[0825] The system according to claim 1, wherein the data collection means acquires scheduled information and communication history.

[0826] (Claim 3)

[0827] The system according to claim 1, which presents the generated improvement proposals to the user's display device.

[0828] "Example 2 of combining an emotion engine"

[0829] (Claim 1)

[0830] Means of collecting business information,

[0831] A means of analyzing collected operational information and evaluating the effectiveness of the meeting,

[0832] A means of determining the necessity of a meeting based on analysis,

[0833] A means of generating and presenting improvement plans to optimize business procedures,

[0834] A means of analyzing the emotional state of individual operators,

[0835] A means of proposing burden reduction measures according to emotional state,

[0836] A means for displaying the generated improvement plan on the operator's display device,

[0837] A system that includes this.

[0838] (Claim 2)

[0839] The system according to claim 1, wherein the data collection means collects scheduled information and dialogue history.

[0840] (Claim 3)

[0841] The system according to claim 1, wherein the emotion analysis targets voice and text data.

[0842] "Application example 2 of combining emotional engines"

[0843] (Claim 1)

[0844] Means of collecting business information,

[0845] A means of analyzing collected operational information and evaluating the effectiveness of each meeting,

[0846] A means of determining the necessity of a meeting based on evaluation,

[0847] A means of generating and presenting improvement plans to optimize business processes,

[0848] A means of visualizing the learning progress of individual users,

[0849] A means of monitoring the emotional state of workers and making appropriate work adjustments,

[0850] A system that includes this.

[0851] (Claim 2)

[0852] The system according to claim 1, wherein the data collection means acquires schedule information and communication history.

[0853] (Claim 3)

[0854] The system according to claim 1, which presents the generated improvement plan to the user's information processing device. [Explanation of Symbols]

[0855] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. Means of collecting business data, A means of analyzing collected business data and evaluating the effectiveness of each meeting, A means of determining the necessity of a meeting based on evaluation, A means of generating and presenting improvement plans to optimize business workflows, A means of visualizing the learning progress of individual users, A system that includes this.

2. The system according to claim 1, wherein the data collection means acquires calendar information and communication history.

3. The system according to claim 1, which presents the generated improvement plan to the user's terminal.

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