System

Abstract

A system is provided.SOLUTION: A system comprising: means for collecting corporate information, personnel data, and goal setting data; means for analyzing the collected data and generating customized goals for each employee; means for setting evaluation criteria based on the generated goals; means for storing the goals and evaluation criteria in a database; means for inputting goals and progress by an employee through a user interface; and means for processing the progress data in real time and providing feedback.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional goal management systems have the problem that it is difficult for employees to feel satisfied or fair, and the evaluator requires a lot of time and effort, while the satisfaction of the person being evaluated is low. Furthermore, goal setting is vague, making it difficult to accurately evaluate the degree of achievement, which leads to a decrease in motivation and dissatisfaction. The purpose of this invention is to solve these problems and improve the sense of satisfaction and fairness of evaluations. [Means for solving the problem]

[0005] The goal management system of the present invention includes the following means: a means for collecting company information, personnel data, and goal setting data; a means for analyzing the collected data and generating customized goals for each employee; a means for setting evaluation criteria based on the generated goals; a means for saving the goals and evaluation criteria in a database; a means for employees to input their goals and progress through a user interface; and a means for processing progress data in real time and providing feedback. This makes it possible to improve the sense of satisfaction and fairness of the evaluation system and reduce the burden on evaluators. Furthermore, by including a means for setting evaluation criteria by integrating quantitative and qualitative evaluations and a means for periodically collecting progress data and feedback data and providing it to both evaluators and evaluatees, the efficiency and quality of the overall evaluation process can be improved.

[0006] "Company information" refers to the company's organizational structure, department information, management policy, corporate culture, and other basic data related to the company.

[0007] "Human Resources Data" means information about an employee's role, position, rank, background, skills, evaluation history, and other personnel-related information.

[0008] "Goal Setting Data" means the specific business goals, achievement criteria, progress, and other goal-related information set for each employee.

[0009] "User interface" refers to an interface through which a user interacts with the goal management system, and includes an input form, a feedback display screen, and the like.

[0010] "Database" means a system for storing and managing collected goal setting data, assessment data, progress data, and other related information.

[0011] "Progress data" is regularly updated information that shows how well an employee is achieving their goals.

[0012] "Feedback" refers to evaluations and comments provided to employees on progress data they enter, often in real time.

[0013] "Customized goals" are specific work goals that are set individually for each employee based on collected data.

[0014] "Evaluation criteria" are standards for measuring the degree of achievement of set goals, and can include quantitative and qualitative elements.

[0015] "Real-time processing" refers to a process in which data entered by a user is processed immediately and the results are fed back to the user. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

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

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

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

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

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

[0022] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0024] [First embodiment]

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

[0026] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0029] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0033] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0036] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0037] This invention relates to a system and method for improving the efficiency of the target management system implemented by a company and for improving the sense of satisfaction and fairness among employees. This invention is realized through the cooperation of three components: a server, a terminal, and a user.

[0038] Server Operation

[0039] The server receives and analyzes company information, personnel data, and goal setting data provided by the company. First, the server acquires various data via APIs and database connections. The acquired data is analyzed and processed by AI algorithms to generate customized goal settings for each employee.

[0040] As a specific example, the server uses information from the sales department to analyze the past sales performance and achievement level of sales department employees, and sets the next period's sales target to increase by 15%. At the same time, the server also calculates evaluation criteria for the set target and stores them in the database. For example, it can rank employees according to their achievement level of the sales target, setting criteria such as high evaluation for achievement of 80% or more and low evaluation for achievement of less than 50%.

[0041] Device behavior

[0042] The terminal provides an interface for setting goals and inputting progress through a user interface. Users (employees) can check their own goals and periodically input their progress through the terminal.

[0043] For example, a sales manager logs in to a terminal and checks the target provided by the server (e.g., a 15% increase in sales). Next, at the end of each month, the manager enters the sales progress and sends it to the server. At this time, the terminal sends the entered data to the server in real time, allowing the manager to receive feedback.

[0044] User Actions

[0045] Users (employees and evaluators) use the interface provided by the server and terminal to understand their goals and periodically enter their progress. Users also perform self-evaluations and confirm and accept the feedback provided by the server.

[0046] For example, after a sales manager inputs monthly sales figures, he or she can receive feedback from the server, such as "Current achievement rate is 60%. Improvement plan for the next quarter: Strengthen approach to specific customer segments." This feedback is provided in real time, making it possible to take prompt improvement measures.

[0047] Overall system operation

[0048] This system streamlines company-wide goal management, improves employee motivation, and reduces the burden on evaluators. In addition, by integrating qualitative and quantitative evaluations, the evaluation process becomes more transparent and fair, leading to overall performance improvements.

[0049] The present invention provides an intuitive and easy-to-use interface for both employees and raters, and significantly improves the quality and efficiency of appraisals through real-time feedback and advice.

[0050] The processing flow will be explained below.

[0051] Step 1:

[0052] The server collects company information, personnel data, and goal setting data provided by the company. This data is obtained via API and database connection.

[0053] Step 2:

[0054] The server preprocesses the collected data, maintaining its integrity and converting it into a format suitable for analysis.

[0055] Step 3:

[0056] The server uses AI algorithms to analyze the data and generate customized goals for each employee.

[0057] Step 4:

[0058] The server sets evaluation criteria based on the generated goals, and the specific evaluation criteria include quantitative and qualitative elements.

[0059] Step 5:

[0060] The server stores the goals and evaluation criteria in a database, which allows for consistent management of the data.

[0061] Step 6:

[0062] The terminal provides the user with a login interface, prompting them to enter their username and password, and then sends the authentication information to the server.

[0063] Step 7:

[0064] The terminal displays the goal settings and evaluation criteria obtained from the server to the user, allowing the user to confirm their own goals.

[0065] Step 8:

[0066] The user periodically inputs progress information via the terminal, and the input data is sent to the server in real time.

[0067] Step 9:

[0068] The server analyzes the received progress data and generates real-time feedback, which is then sent to the device.

[0069] Step 10:

[0070] The device displays feedback to the user, allowing them to receive advice based on their progress.

[0071] Step 11:

[0072] The user inputs their self-evaluation and sends it to the server via their terminal, where the input data is saved.

[0073] Step 12:

[0074] The server generates the final assessment, which is provided to both the user and the assessor.

[0075] Step 13:

[0076] The device displays the final evaluation results to the user, and suggests areas for improvement and future goals based on the evaluation.

[0077] Step 14:

[0078] The user checks the final evaluation results and considers improvement measures for the next period, completing the entire evaluation process.

[0079] The above steps realize a system that integrates goal setting, progress management, and evaluation.

[0080] Example 1

[0081] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0082] With conventional goal management systems, employees often lack a sense of satisfaction or fairness regarding the goals set within the company, making efficient goal management difficult. Furthermore, because evaluation criteria are not clear, evaluations can lack transparency and fairness. Furthermore, progress cannot be entered and feedback cannot be provided in real time, which can delay rapid responses and the implementation of improvement measures.

[0083] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0084] In this invention, the server includes means for collecting company information, personnel information, and goal data, means for analyzing the collected data using an AI algorithm and generating goals customized for each employee, means for setting evaluation criteria based on the generated goals, means for saving the goals and evaluation criteria in a data storage device, means for employees to input their goals and progress through a user interface, and means for processing progress data in real time and providing feedback. This enables efficient and transparent goal management within a company, increases employees' sense of satisfaction and fairness, and enables prompt feedback and the implementation of improvement measures.

[0085] "Company information" refers to data about a company's basic information and organizational structure.

[0086] "Human resources information" refers to data about employees' individual attributes, job duties, and past performance.

[0087] "Goal Data" refers to data relating to goals to be achieved set for a company or individual employees.

[0088] "AI algorithm" refers to a computational method that uses artificial intelligence technology to analyze data and generate specific patterns or predictions.

[0089] "Customized goals" refer to individual goals set based on each employee's characteristics and past performance.

[0090] "Evaluation criteria" refers to the indicators and standards used to evaluate an employee's level of goal achievement.

[0091] "Data storage device" refers to a system or database for storing data.

[0092] "User interface" refers to the screen or interface through which a user interacts with a system.

[0093] "Progress Data" refers to data relating to the current achievement or progress towards a goal.

[0094] "Real-time processing" refers to the immediate collection and analysis of progress data.

[0095] "Feedback" refers to notification and advice regarding evaluation results and improvement measures based on progress.

[0096] This invention relates to a system and method for improving the efficiency of the target management system adopted by companies and enhancing employees' sense of satisfaction and fairness. This system is realized through the cooperation of three components: a server, a terminal, and a user.

[0097] Server Operation

[0098] The server receives company information, personnel information, and goal data provided by the company and analyzes this data. First, the server obtains various data via APIs and database connections. Specifically, the server uses the following hardware and software:

[0099] Database: MySQL, PostgreSQL

[0100] AI algorithms: Python, TensorFlow, Scikit-learn

[0101] API frameworks: Flask, Django

[0102] The acquired data is analyzed and processed by an AI algorithm to generate customized goals for each employee. For example, the server uses information from the sales department to analyze the sales department's past sales performance and achievement level, and sets the next period's sales target to increase by 15%. At the same time, the server also calculates evaluation criteria for the set target and stores them in the database. For example, it can rank employees according to their level of achievement of the sales target, setting criteria such as a high evaluation for achievement of 80% or more and a low evaluation for achievement of less than 50%.

[0103] Device behavior

[0104] The terminal provides an interface for goal setting and progress input through a user interface. Users (employees) check their goals and periodically input their progress through the terminal. Specifically, the terminal uses the following hardware and software:

[0105] Frontend: React, Vue.js

[0106] Backend: Node.js (Express)

[0107] For example, a sales manager logs in to a terminal and checks the target provided by the server (e.g., a 15% increase in sales). Then, at the end of each month, the manager enters the sales progress and sends it to the server. At this time, the terminal sends the entered data to the server in real time, allowing the manager to receive feedback.

[0108] User Actions

[0109] Users (employees and evaluators) use the interface provided by the server and terminal to understand their own goals and periodically enter their progress. Users also perform self-evaluations and confirm and accept the feedback provided by the server. For example, after a sales manager enters monthly sales figures, the server can provide feedback with specific advice, such as "Current achievement rate is 60%. Improvement plan for the next quarter: Strengthen approach to specific customer segments." This feedback is provided in real time, enabling prompt improvement measures to be implemented.

[0110] Examples of specific examples and prompts

[0111] After logging in to their device, the sales manager checks the next quarter's sales target (e.g., a 15% increase) provided by the server. At the end of each month, the manager enters the monthly sales and presses the "Send" button on the device to send the data to the server. The server receives this data, analyzes it in real time, and calculates the achievement rate. The calculation results are displayed as, for example, "Current achievement rate is 60%." Furthermore, the server uses an AI model to generate feedback such as "Improvement measures for the next quarter: Strengthen approach to specific customer segments," and immediately sends this to the device. The manager can receive this feedback and make an action plan for the next quarter.

[0112] Prompt Sentence Examples

[0113] By inputting the following prompt sentence into the generative AI model, the processing of the above program can be explained in natural language.

[0114] Please explain how a corporate goal management system works. The system consists of three components: a server, a terminal, and a user. The server analyzes data and sets customized goals, while the terminal displays goal settings and provides progress input. The user checks goals and inputs progress. Please explain how the entire system works using specific examples.

[0115] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0116] Step 1:

[0117] Data collection

[0118] The server obtains company information, personnel information, and goal data provided by the company. Specifically, the server collects this data using APIs and database connections. The input is data obtained from the company's personnel system and goal management system. For example, the server periodically sends an HTTP request to an API endpoint and receives JSON-formatted data as a response. The received data is then stored in a database.

[0119] Step 2:

[0120] Data analysis and goal setting

[0121] The server analyzes the collected data using an AI algorithm. The input here is the data collected in step 1. Specifically, it uses Python's TensorFlow library to analyze past performance data and set customized goals for each employee. For example, for employees in the sales department, it sets a sales goal for the next fiscal year to increase by 15% based on past sales data. The analysis results are stored in a database.

[0122] Step 3:

[0123] Setting evaluation criteria

[0124] The server sets evaluation criteria based on the generated goals. The input for this step is the customized goals generated in step 2. Specifically, it ranks the sales goals according to their achievement level. For example, it sets criteria such as high evaluation for achievement of 80% or more and low evaluation for achievement of less than 50%, and saves this in the database.

[0125] Step 4:

[0126] Providing a goal presentation and progress input interface

[0127] The terminal presents goals to employees through a user interface and provides an interface for them to input their progress. The input is goal setting information sent from the server. For example, a dashboard built using React displays each employee's goal (e.g., 15% increase in sales). The user inputs their progress here, and the data is sent to the server in real time.

[0128] Step 5:

[0129] Progress data collection and analysis

[0130] The server receives the progress data sent from the terminal and analyzes it in real time. The input is the progress data entered by the user in step 4. Specifically, the server receives the progress data (e.g., monthly sales) via the Node.js backend API and analyzes it using a Python script. The output is the calculated achievement level for each employee (e.g., current achievement level is 60%).

[0131] Step 6:

[0132] Generating and Providing Feedback

[0133] The server generates feedback based on the results of analyzing the progress data and sends it to the device. The input is the calculation result of the achievement level obtained in step 5. Specifically, an AI model is used to generate optimal feedback based on the evaluation results of each employee. This feedback might be something like, "Improvement plan for the next quarter: Strengthen approach to specific customer segments." The generated feedback is sent to the device in real time and can be viewed by the user.

[0134] This series of processes will improve the efficiency of goal management across the entire company, improve employee motivation, and reduce the burden on evaluators.

[0135] (Application example 1)

[0136] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0137] Conventional goal management systems make it difficult to set employee goals and monitor progress, and they tend to be out of sync with actual work, especially in factories and other workplaces. Real-time feedback is also difficult, making it difficult to implement rapid improvement measures to achieve goals. This leads to a lack of transparency and fairness in evaluations, which can lead to lower motivation and increased burdens on evaluators.

[0138] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0139] In this invention, the server includes a means for collecting company information, personnel data, and goal setting data, a means for analyzing the collected data and generating customized goals for each employee, and a means for setting evaluation criteria based on the generated goals. This allows employees to view their goals and feedback through smart glasses, collect progress data during actual work, and receive feedback in real time. This improves the efficiency of goal management and improves employees' sense of satisfaction and fairness.

[0140] "Company Information" means information including organizational structure, performance, department information, and other company-related data.

[0141] "Human Resources Data" means data related to employee names, job titles, evaluation history, skill sets, and working hours.

[0142] "Goal setting data" refers to data regarding the specific performance and production goals that each employee or department must achieve.

[0143] "Collection means" refers to the software or hardware components that collect the required data through a database or API.

[0144] "Means of analysis" refers to AI algorithms and machine learning models that analyze the collected data and extract relevant information.

[0145] "Customized goals" are individual goals set for each employee based on their skills, past performance, and current situation.

[0146] "Evaluation criteria" are standards for evaluating the degree of achievement of set goals, and include specific evaluation indicators and ranking methods.

[0147] "Means for storing data in a database" means a database management system for securely storing collected data and generated goals and evaluation criteria.

[0148] "User interface" refers to the software screens or applications that allow employees to enter and review goals and progress.

[0149] "Progress data" is specific data that shows how an employee is progressing toward their goals.

[0150] "Real-time processing means" means a high-speed computing mechanism that instantly analyzes received data and provides feedback.

[0151] "Means for providing feedback" is a function for providing advice and suggestions for improvement to employees based on progress data.

[0152] "Smart glasses" are devices that provide visual information to the wearer and assist them in real-world tasks.

[0153] "Means for displaying goals and feedback" means software functionality for displaying set goals and real-time feedback through the display of the smart glasses.

[0154] "Means for collecting progress data" refers to an input function for collecting specific work progress from employees through the smart glasses.

[0155] This invention aims to improve the efficiency of goal management in factories, and describes a system in which employees use smart glasses to set goals, manage progress, and receive real-time feedback.

[0156] Server Operation

[0157] The server first collects company information, personnel data, and goal setting data provided by the company. This data, obtained through existing database management systems or APIs, is then analyzed using AI algorithms. For example, it takes into account an employee's past production performance and skill set to customize goals appropriate for each employee. The generated goals are then stored in a database along with evaluation criteria.

[0158] Smart glasses terminal operation

[0159] A dedicated application is installed on the smart glasses used as terminals. This application allows employees to visually check their goals and progress through a user interface. Employees can check their goals in real time and enter their progress directly through the smart glasses while working. This allows progress data to be sent to a server in real time, and feedback is provided immediately as an analysis result.

[0160] User Actions

[0161] By wearing the smart glasses, employees can check their set goals and progress in real time while they work. They can also input progress data and receive prompt feedback from the server, enabling employees to take prompt action to improve their work.

[0162] System operation example

[0163] For example, when a factory worker puts on the smart glasses, the production target for the current month is displayed. The worker inputs their progress as they work, and the server analyzes this in real time and provides feedback. This feedback suggests specific improvement measures, such as "Please reevaluate next week's production plan."

[0164] Prompt Sentence Examples

[0165] Examples of specific prompts that smart glasses applications might provide to users include:

[0166] "How close are you to achieving your goal this month? Please give me some specific numbers."

[0167] "What should we improve next?"

[0168] "Please enter your progress data."

[0169] This will improve the efficiency and transparency of goal management. In particular, by allowing employees to receive feedback in real time, it is possible to take prompt corrective measures, which is expected to improve overall production efficiency and fairness in evaluations.

[0170] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0171] Step 1:

[0172] The server collects company information, HR data, and goal setting data provided by the company. This data is obtained via APIs and database connections. The input is data from each department and HR department of the company, and the output is in the form of the original data stored on the server.

[0173] Step 2:

[0174] The server analyzes the collected data using an AI algorithm. Specifically, it inputs each employee's past production performance and skill set into an analytical model, from which individual goals are generated. The input is each employee's past data, and the output is customized goal data.

[0175] Step 3:

[0176] The server sets evaluation criteria based on the created goals. For example, it sets specific evaluation indicators and ranking methods to show the degree of goal achievement. The input is customized goal data, and the output is evaluation criteria data for that goal.

[0177] Step 4:

[0178] The server stores the generated goals and evaluation criteria in a database. The input is the customized goal and evaluation criteria data, and the output is the data recorded in the database.

[0179] Step 5:

[0180] The terminal (smart glasses) displays the goals to the employee through a user interface. The employee can visually confirm the goals through the smart glasses while working. The input is the goal data received from the server, and the output is the goal information displayed on the display of the smart glasses.

[0181] Step 6:

[0182] The user (employee) inputs progress data into the terminal via smart glasses while working. This progress data can be entered via a keyboard or voice recognition function. The input is the employee's progress data, and the output is the progress data recorded on the terminal.

[0183] Step 7:

[0184] The terminal transmits the collected progress data to the server in real time. The input is the progress data recorded on the terminal, and the output is the progress data transmitted to the server.

[0185] Step 8:

[0186] The server analyzes the received progress data and generates feedback using a generative AI model. The input is the progress data sent from the terminal, and the output is the feedback data provided to the employee.

[0187] Step 9:

[0188] The terminal displays the feedback from the server on the smart glasses, allowing employees to quickly take corrective measures. The input is the feedback data received from the server, and the output is the feedback information displayed on the smart glasses display.

[0189] Step 10:

[0190] After receiving the feedback, the employee re-enters the progress data as needed and continues to communicate with the server. The input is the newly entered progress data, and the output is the updated progress data in the server.

[0191] These steps will ensure that the goal management system is operating effectively, improving the company's production efficiency and employee motivation.

[0192] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0193] This invention relates to a system that incorporates an emotion engine into a company's goal management system, providing feedback and evaluation that takes into account the employee's emotional state, thereby improving employee satisfaction and motivation. This system consists of three main components: a server, a terminal, and a user.

[0194] Server Operation

[0195] The server receives company information, personnel data, and goal setting data provided by the company. This data is collected and pre-processed via APIs and database connections. It then analyzes this data using AI algorithms to generate customized goals for each employee. Evaluation criteria are also calculated based on the generated goals and stored in the database.

[0196] Furthermore, the server is equipped with an emotion engine that receives the user's emotion data. The emotion engine analyzes the text, voice, and facial recognition data entered by the user to recognize the user's emotional state. For example, it can determine positive or negative emotions from the text entered by the user.

[0197] Device behavior

[0198] The terminal provides an interface for goal setting and progress input through a user interface. The user (employee) checks his / her goals through the terminal and periodically inputs his / her progress. In addition, the user also inputs information that represents his / her emotional state.

[0199] As a concrete example, a sales manager logs in to a terminal and checks the target provided by the server (e.g., a 15% increase in sales). Then, at the end of each month, he or she enters the sales progress along with his or her emotional state (e.g., "highly motivated" or "stressed"). This data is sent to the server in real time.

[0200] User Actions

[0201] Users (employees and evaluators) use the interface provided by the server and terminal to understand their goals and periodically enter their progress. The user self-evaluates and confirms and accepts the emotional feedback provided by the server. The emotion engine analyzes the user's emotional state and provides feedback based on the results in real time.

[0202] For example, after entering monthly sales figures, a sales manager receives feedback based on their emotional state analyzed by the emotion engine. For example, they may receive specific advice such as, "Achievement rate is 60%. Improvement plan for the next quarter: Strengthen approach to specific customer segments. Current emotional state: Feeling stressed. We recommend taking a vacation to refresh yourself."

[0203] Overall system operation

[0204] This system can provide individual feedback to both the evaluator and the person being evaluated that takes into account their emotional state, significantly improving the sense of satisfaction and fairness of the evaluation. In addition, by incorporating the emotional data analyzed by the emotion engine as part of the evaluation process, the overall evaluation process proceeds more effectively and efficiently.

[0205] The present invention provides an intuitive and easy-to-use interface for both employees and evaluators, and significantly improves the quality and efficiency of evaluations through real-time feedback and advice. Furthermore, the incorporation of an emotion engine enables flexible responses based on the employee's emotional state, improving overall performance and employee satisfaction.

[0206] The processing flow will be explained below.

[0207] Step 1:

[0208] The server collects company information, personnel data, and goal setting data provided by the company, and obtains this data via API and database connection.

[0209] Step 2:

[0210] The server pre-processes the acquired data, which includes checking, normalizing, and converting the data into a format suitable for analysis.

[0211] Step 3:

[0212] The server then uses AI algorithms to analyze the pre-processed data and generate customized goals for each employee.

[0213] Step 4:

[0214] The server sets evaluation criteria based on the generated goals and calculates evaluation criteria that include quantitative and qualitative elements.

[0215] Step 5:

[0216] The server stores the goals and evaluation criteria in a database, which allows for consistent management of the data.

[0217] Step 6:

[0218] The terminal provides the user with a login interface, prompting them to enter their username and password, and then sends the authentication information to the server.

[0219] Step 7:

[0220] The terminal displays the goal settings and evaluation criteria obtained from the server to the user, allowing the user to check their own goals.

[0221] Step 8:

[0222] The terminal provides the user with options for inputting emotional information through a user interface, which can be input in the form of text, voice, facial recognition data, etc.

[0223] Step 9:

[0224] Users periodically input their progress and emotional information, which is then sent to the server in real time.

[0225] Step 10:

[0226] The server analyzes the progress data and emotional data, and the emotional engine recognizes the user's emotional state and generates personalized feedback based on the emotional data.

[0227] Step 11:

[0228] The server generates the analyzed progress data and emotional feedback, and transmits the feedback to the device in real time.

[0229] Step 12:

[0230] The device displays feedback to the user, including specific advice based on progress and emotional state.

[0231] Step 13:

[0232] The user checks the feedback and performs a self-evaluation, and the self-evaluation data is sent to the server via the terminal.

[0233] Step 14:

[0234] The server generates the final assessment, which is provided to both the user and the assessor.

[0235] Step 15:

[0236] The terminal displays the final evaluation results to the user, and next goals and areas for improvement are presented based on the evaluation results.

[0237] The above steps realize a system that integrates goal setting, progress management, and collection and evaluation of emotional information.

[0238] Example 2

[0239] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0240] Conventional goal management systems have difficulty reflecting employees' emotional state in the feedback and evaluation process, which has led to issues such as insufficient improvement of employee satisfaction and motivation. In addition, there was a need for an integrated approach that not only handles quantitative evaluations but also emotional state and progress data.

[0241] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for collecting company information, personnel data, and goal setting data, a means for preprocessing the collected data, and a means for analyzing the preprocessed data and generating goals customized for each employee. This makes it possible to set and evaluate customized goals that take emotional states into consideration.

[0242] "Company information" refers to information about an organization's basic data, business operations, and management strategies.

[0243] "Personnel data" refers to data including employee personal information, work history, evaluation records, salary information, etc.

[0244] "Goal setting data" refers to data that indicates the specific goals to be achieved by each employee or department and the associated evaluation criteria.

[0245] "Data preprocessing" is the process of converting collected raw data into an analyzable form by filling in missing values, removing outliers, normalizing, etc.

[0246] "Customized goals" are specific goals that are set specifically for each employee based on their job duties and abilities.

[0247] "Evaluation criteria" are data that show specific indicators and standards for evaluating an employee's level of goal achievement.

[0248] A "database" is an information system that efficiently stores and manages collected information and allows it to be quickly searched and retrieved as needed.

[0249] A "user interface" is a system that includes screens and input forms that allow users to interact with a system.

[0250] "Progress data" is data that indicates the current progress toward achieving a goal.

[0251] "Real-time processing" is a processing method in which processing is executed immediately when data is entered or updated, and the results are provided.

[0252] "Feedback" is information that provides employees with information about their progress toward their goals, an evaluation of their work, and specific advice on areas for improvement.

[0253] The "emotion engine" is a system that analyzes and determines the emotional state of employees from their input data (text, voice, facial recognition, etc.).

[0254] "Quantitative evaluation" is an evaluation method based on numerical and quantitative data.

[0255] "Qualitative evaluation" is an evaluation method that does not rely on numerical values, but is based on subjective information such as observation and feedback.

[0256] This system incorporates an emotion engine into a company's goal management system, providing feedback and evaluations that take into account the employee's emotional state, thereby improving employee satisfaction and motivation. The system consists of three main components: a server, a terminal, and a user.

[0257] Server Operation

[0258] The server collects company information, personnel data, and goal setting data through APIs and database connections. The collected data is preprocessed using Python and SQL. The preprocessed data is then analyzed using AI algorithms such as Scikit-learn and TensorFlow to generate customized goals for each employee. The generated goals and evaluation criteria are stored in a MySQL database.

[0259] In addition, the server is equipped with an emotion engine that integrates Google's Sentiment Analysis API. The emotion engine analyzes the text, voice, and facial recognition data entered by the user to recognize the user's emotional state. For example, it analyzes the user's input text, "I'm very tired today," and identifies negative emotions.

[0260] Device behavior

[0261] The terminal runs as a web application using React.js and provides users with an interface for entering goals and progress. Users (employees) can check their goals and enter their progress through the terminal. In addition, users can also enter their emotional state.

[0262] For example, when a sales employee logs in to their terminal, a target provided by the server (e.g., "Increase sales by 15%) is displayed. At the end of each month, they enter their emotional state (e.g., "Highly motivated" or "Feeling stressed") along with their sales progress. This data is sent to the server in real time.

[0263] User Actions

[0264] The user (employee or evaluator) uses the interface provided by the server and terminal to understand their goals and periodically enter their progress. The user self-evaluates, checks and accepts the emotional feedback provided by the server. Feedback based on the emotional state analyzed by the emotion engine is provided in real time.

[0265] For example, after a sales employee enters their monthly sales figures, they receive feedback based on their emotional state analyzed by the emotion engine. For example, they may receive specific advice such as, "Achievement rate is 66.7%. Improvement plan for the next quarter: Strengthen your approach to specific customer segments. Current emotional state: Highly motivated. We recommend taking a vacation to refresh yourself."

[0266] Prompt Sentence Examples

[0267] An example prompt for a generative AI model might look like this:

[0268] "Given the given goal, evaluate the employee's progress and generate feedback that takes into account their emotional state. Include improvement measures and recommended actions if the goal is 66.7% achieved."

[0269] This system can provide individual feedback to both the evaluator and the person being evaluated that takes into account their emotional state, significantly improving the sense of satisfaction and fairness of the evaluation. In addition, by incorporating the emotional data analyzed by the emotion engine as part of the evaluation process, the overall evaluation process proceeds more effectively and efficiently.

[0270] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0271] Step 1:

[0272] The server collects company data, specifically company information, HR data, and goal setting data through APIs and database connections. For example, it retrieves employee information from a HR database using an SQL query. The input to this operation is the API request or SQL query, and the output is the collected raw data.

[0273] Step 2:

[0274] The server preprocesses the collected data. Specifically, it performs tasks such as filling in missing values, removing outliers, and normalizing the collected data. The input is the collected raw data, and the output is the preprocessed data. For example, data cleaning is performed using the Python Pandas library.

[0275] Step 3:

[0276] The server analyzes the preprocessed data and generates customized goals. Specifically, it analyzes the data using machine learning algorithms such as Scikit-learn and TensorFlow to set goals for each employee. The input is the preprocessed data, and the output is individual goal setting data. For example, a random forest model is used to predict goals.

[0277] Step 4:

[0278] The server sets evaluation criteria based on the generated goals. Specifically, it calculates the evaluation criteria based on the generated goals and the company's evaluation policy. The input is individual goal setting data and the company's evaluation policy, and the output is evaluation criteria data. For example, it calculates evaluation criteria using goal achievement rates and key performance indicators (KPIs).

[0279] Step 5:

[0280] The server saves the goals and evaluation criteria in a database. Specifically, it saves the goal setting data and evaluation criteria data in a MySQL database. The input is the goal setting data and evaluation criteria data, and the output is the status of saving to the database. For example, data is inserted into the database using an SQL query.

[0281] Step 6:

[0282] The terminal provides employees with a user interface for entering goals and progress. Specifically, the goal setting screen and progress input screen are displayed through a web application using React.js. The input is the user's login information, and the output is the goal setting screen that is displayed. For example, after logging in, an employee can check their goals on the web screen.

[0283] Step 7:

[0284] The user inputs their progress and emotional state. Specifically, they periodically input their goal achievement status and their emotional state using the terminal interface. The input is the user's progress data and emotional state data, and the output is that this data is sent to the server. For example, they input "10% increase in sales" and "highly motivated."

[0285] Step 8:

[0286] The server receives and analyzes the input data and generates feedback. Specifically, it uses an AI algorithm to analyze progress data and emotional state data and generate individualized feedback. The input is the progress data and emotional state data sent by the user, and the output is feedback data. For example, it generates "achievement level 66.7%, improvement plan for the next quarter: strengthen approach to specific customer segments."

[0287] Step 9:

[0288] The user confirms and accepts the feedback. Specifically, the user confirms the feedback provided by the server through the terminal interface and reflects it in the next action plan. The input is the feedback data provided by the server, and the output is the user's next action plan. For example, a sales employee accepts the advice to "strengthen their approach to a specific customer base in the next quarter" and reflects it in their actual business plan.

[0289] (Application example 2)

[0290] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0291] Conventional goal management systems fail to take into account the emotional state of employees, resulting in problems such as a lack of employee satisfaction and motivation. Furthermore, uniform evaluations and feedback that ignore emotions are factors that reduce the fairness and effectiveness of evaluations. In particular, on-site work such as robot operators in factories involves significant physical and mental strain, and fluctuations in emotional state are directly linked to work efficiency and safety, so appropriate responses are required.

[0292] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting company information, personnel data, and goal setting data, means for analyzing the collected data and generating goals customized for each employee, means for setting evaluation criteria based on the generated goals, means for saving the goals and evaluation criteria in a database, means for employees to input their goals and progress through a user interface, means for processing progress data in real time and providing feedback, means for inputting or detecting the employee's emotional state, means for analyzing the emotional data and customizing the feedback based on the emotional state, and means for providing feedback to the employee and saving the emotional data in a database. This enables individual feedback that takes the employee's emotional state into consideration, improving employee satisfaction and motivation, and improving work efficiency and safety, particularly in factory floor work.

[0293] "Company information" refers to information about a company's basic data and organizational structure.

[0294] "Human resources data" refers to data including employee personal information, job titles, evaluation history, salary information, etc.

[0295] "Goal setting data" refers to data related to work goals and deliverables that a company sets for its employees.

[0296] A "collection means" is a method or device for acquiring and recording data.

[0297] An "analytical means" is a method or device for analyzing collected data and deriving a specific result.

[0298] "Customized goals" are specific work goals tailored to each employee.

[0299] "Evaluation criteria" are quantitative and qualitative indicators used to evaluate employee performance.

[0300] A "database storage means" is a method or device for storing data long-term and making it accessible at a later time.

[0301] A "user interface" is a screen display and input device that allows a user to interact with a system.

[0302] "Means for inputting progress" refers to a method or device that allows an employee to input the progress of their work into the system.

[0303] "Means for processing and providing feedback in real time" refers to a method or device for analyzing progress data in real time and providing the results as feedback.

[0304] "Means for inputting or detecting emotional state" refers to methods or devices for conveying an employee's emotions to the system, including voice input, text input, facial recognition, etc.

[0305] A "means for analyzing emotional data" is a method or apparatus for analyzing input or sensed emotional data to identify an employee's current emotional state.

[0306] A "means for customizing feedback" is a method or apparatus for generating personalized feedback based on evaluation criteria and emotional data.

[0307] A "means for providing feedback to employees" is a method or device for communicating system-generated feedback to employees.

[0308] The present invention aims to improve productivity and motivation by providing feedback and evaluation that takes into account employees' emotional states. The system consists of three main components: a server, a terminal, and a user.

[0309] Server Operation

[0310] The server has the following functions:

[0311] 1. Data collection: The server collects company information, personnel data, and goal setting data via APIs and database connections.

[0312] 2. Data analysis: The collected data is analyzed by AI algorithms to generate customized goals and evaluation criteria for each employee, which are then stored in a database.

[0313] 3. Emotion analysis: Using an emotion engine, the system analyzes the emotion data received from users (text, voice, facial recognition data, etc.) to recognize the emotional state of employees.

[0314] The server uses the following hardware and software: a high-performance server, an Emotion Engine, a Feedback Generator, and a database system.

[0315] Device behavior

[0316] The terminal has the following features:

[0317] 1. Interface provision: Provide an interface for employees to input goals and progress through a user interface.

[0318] 2. Progress input: Employees can periodically input their goal progress.

[0319] 3. Emotion input: Ability to input or detect employees' emotional state (voice, facial recognition, etc.).

[0320] Hardware and software used on your device: PC, smartphone, camera (for facial recognition), microphone (for voice analysis).

[0321] User Actions

[0322] Users, i.e. factory or office employees and managers, go through the following process:

[0323] 1. Data entry: Employees enter their progress and emotional state into a terminal.

[0324] 2. Feedback reception: Receive individually customized feedback based on the emotional data analyzed by the server.

[0325] 3. Evaluate and Improve: Use the feedback provided to improve your work.

[0326] Specific examples

[0327] For example, a factory robot operator might use the system to perform their daily tasks:

[0328] 1. Prompt to enter progress:

[0329] Please tell us your progress today:

[0330] Progress: Production line adjustment work is 80% complete.

[0331] 2. Emotional state prompt:

[0332] Please describe your emotional state today:

[0333] Emotional state: Feeling tired. Having difficulty concentrating.

[0334] 3. Feedback provided by the system:

[0335] feedback:

[0336] Progress is on schedule, but you are experiencing a decline in concentration. Please take a short break to refresh yourself and get back to work.

[0337] The system analyzes employees' work progress and emotional state in real time and provides individually customized feedback, thereby improving productivity and employee motivation across the company.

[0338] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0339] Step 1:

[0340] The server uses APIs and database connections to collect company information, personnel data, and goal setting data. The collected data is temporarily stored and organized in the database. Specifically, the collected data includes basic company data, personnel structure, employee history, and goal achievement status.

[0341] Input: Company information, personnel data, goal setting data

[0342] Output: Organized database entries

[0343] Step 2:

[0344] The server analyzes the collected data using an AI algorithm to generate customized goals for each employee. The generated goals are optimized based on the employee's current situation and output in the form of goals and evaluation criteria.

[0345] Input: Organized database entries

[0346] Output: Customized goals and metrics

[0347] Step 3:

[0348] The server stores the generated goals and evaluation criteria in a database, which can be later reviewed by employees.

[0349] Input: Customized goals and metrics

[0350] Output: Goals and metrics stored in a database

[0351] Step 4:

[0352] The terminal provides an interface for employees to input goals and progress through a user interface, and the data entered by the employees is transmitted to the server in real time.

[0353] Input: Goals and progress information entered by employees

[0354] Output: Progress data sent to the server

[0355] Step 5:

[0356] The server processes the progress data in real time and generates the analysis results as feedback, automatically generating optimal feedback based on the employee's progress and achievement level.

[0357] Input: Progress data

[0358] Output: Generated feedback

[0359] Step 6:

[0360] The server receives employee emotional state data (text, voice, facial recognition data, etc.) sent from the device and analyzes it using an emotion engine. The analysis results are output as data indicating the employee's emotional state.

[0361] Input: Emotional state data

[0362] Output: Parsed emotional state data

[0363] Step 7:

[0364] The server then personalizes the feedback based on the analyzed emotional state data, generating specific advice tailored to the employee's current emotional state.

[0365] Input: Parsed emotional state data

[0366] Output: Customized feedback

[0367] Step 8:

[0368] The server provides the generated feedback to the employee and stores the feedback along with the emotion data in a database.

[0369] Input:Customized Feedback

[0370] Output: Feedback provided to employees, feedback and sentiment data stored in a database

[0371] The above processing steps realize a system that provides real-time feedback that takes into account the emotions of employees, which improves employee satisfaction and motivation, and also increases work efficiency and safety in factory work.

[0372] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0373] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0374] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0375] [Second embodiment]

[0376] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0377] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0378] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0379] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0380] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0381] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0382] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0383] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0384] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0385] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0386] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0387] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0388] This invention relates to a system and method for improving the efficiency of the target management system implemented by a company and for improving the sense of satisfaction and fairness among employees. This invention is realized through the cooperation of three components: a server, a terminal, and a user.

[0389] Server Operation

[0390] The server receives and analyzes company information, personnel data, and goal setting data provided by the company. First, the server acquires various data via APIs and database connections. The acquired data is analyzed and processed by AI algorithms to generate customized goal settings for each employee.

[0391] As a specific example, the server uses information from the sales department to analyze the past sales performance and achievement level of sales department employees, and sets the next period's sales target to increase by 15%. At the same time, the server also calculates evaluation criteria for the set target and stores them in the database. For example, it can rank employees according to their achievement level of the sales target, setting criteria such as high evaluation for achievement of 80% or more and low evaluation for achievement of less than 50%.

[0392] Device behavior

[0393] The terminal provides an interface for setting goals and inputting progress through a user interface. Users (employees) can check their own goals and periodically input their progress through the terminal.

[0394] For example, a sales manager logs in to a terminal and checks the target provided by the server (e.g., a 15% increase in sales). Next, at the end of each month, the manager enters the sales progress and sends it to the server. At this time, the terminal sends the entered data to the server in real time, allowing the manager to receive feedback.

[0395] User Actions

[0396] Users (employees and evaluators) use the interface provided by the server and terminal to understand their goals and periodically enter their progress. Users also perform self-evaluations and confirm and accept the feedback provided by the server.

[0397] For example, after a sales manager inputs monthly sales figures, he or she can receive feedback from the server, such as "Current achievement rate is 60%. Improvement plan for the next quarter: Strengthen approach to specific customer segments." This feedback is provided in real time, making it possible to take prompt improvement measures.

[0398] Overall system operation

[0399] This system streamlines company-wide goal management, improves employee motivation, and reduces the burden on evaluators. In addition, by integrating qualitative and quantitative evaluations, the evaluation process becomes more transparent and fair, leading to overall performance improvements.

[0400] The present invention provides an intuitive and easy-to-use interface for both employees and raters, and significantly improves the quality and efficiency of appraisals through real-time feedback and advice.

[0401] The processing flow will be explained below.

[0402] Step 1:

[0403] The server collects company information, personnel data, and goal setting data provided by the company. This data is obtained via API and database connection.

[0404] Step 2:

[0405] The server preprocesses the collected data, maintaining its integrity and converting it into a format suitable for analysis.

[0406] Step 3:

[0407] The server uses AI algorithms to analyze the data and generate customized goals for each employee.

[0408] Step 4:

[0409] The server sets evaluation criteria based on the generated goals, and the specific evaluation criteria include quantitative and qualitative elements.

[0410] Step 5:

[0411] The server stores the goals and evaluation criteria in a database, which allows for consistent management of the data.

[0412] Step 6:

[0413] The terminal provides the user with a login interface, prompting them to enter their username and password, and then sends the authentication information to the server.

[0414] Step 7:

[0415] The terminal displays the goal settings and evaluation criteria obtained from the server to the user, allowing the user to confirm their own goals.

[0416] Step 8:

[0417] The user periodically inputs progress information via the terminal, and the input data is sent to the server in real time.

[0418] Step 9:

[0419] The server analyzes the received progress data and generates real-time feedback, which is then sent to the device.

[0420] Step 10:

[0421] The device displays feedback to the user, allowing them to receive advice based on their progress.

[0422] Step 11:

[0423] The user inputs their self-evaluation and sends it to the server via their terminal, where the input data is saved.

[0424] Step 12:

[0425] The server generates the final assessment, which is provided to both the user and the assessor.

[0426] Step 13:

[0427] The device displays the final evaluation results to the user, and suggests areas for improvement and future goals based on the evaluation.

[0428] Step 14:

[0429] The user checks the final evaluation results and considers improvement measures for the next period, completing the entire evaluation process.

[0430] The above steps realize a system that integrates goal setting, progress management, and evaluation.

[0431] Example 1

[0432] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0433] With conventional goal management systems, employees often lack a sense of satisfaction or fairness regarding the goals set within the company, making efficient goal management difficult. Furthermore, because evaluation criteria are not clear, evaluations can lack transparency and fairness. Furthermore, progress cannot be entered and feedback cannot be provided in real time, which can delay rapid responses and the implementation of improvement measures.

[0434] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0435] In this invention, the server includes means for collecting company information, personnel information, and goal data, means for analyzing the collected data using an AI algorithm and generating goals customized for each employee, means for setting evaluation criteria based on the generated goals, means for saving the goals and evaluation criteria in a data storage device, means for employees to input their goals and progress through a user interface, and means for processing progress data in real time and providing feedback. This enables efficient and transparent goal management within a company, increases employees' sense of satisfaction and fairness, and enables prompt feedback and the implementation of improvement measures.

[0436] "Company information" refers to data about a company's basic information and organizational structure.

[0437] "Human resources information" refers to data about employees' individual attributes, job duties, and past performance.

[0438] "Goal Data" refers to data relating to goals to be achieved set for a company or individual employees.

[0439] "AI algorithm" refers to a computational method that uses artificial intelligence technology to analyze data and generate specific patterns or predictions.

[0440] "Customized goals" refer to individual goals set based on each employee's characteristics and past performance.

[0441] "Evaluation criteria" refers to the indicators and standards used to evaluate an employee's level of goal achievement.

[0442] "Data storage device" refers to a system or database for storing data.

[0443] "User interface" refers to the screen or interface through which a user interacts with a system.

[0444] "Progress Data" refers to data relating to the current achievement or progress towards a goal.

[0445] "Real-time processing" refers to the immediate collection and analysis of progress data.

[0446] "Feedback" refers to notification and advice regarding evaluation results and improvement measures based on progress.

[0447] This invention relates to a system and method for improving the efficiency of the target management system adopted by companies and enhancing employees' sense of satisfaction and fairness. This system is realized through the cooperation of three components: a server, a terminal, and a user.

[0448] Server Operation

[0449] The server receives company information, personnel information, and goal data provided by the company and analyzes this data. First, the server obtains various data via APIs and database connections. Specifically, the server uses the following hardware and software:

[0450] Database: MySQL, PostgreSQL

[0451] AI algorithms: Python, TensorFlow, Scikit-learn

[0452] API frameworks: Flask, Django

[0453] The acquired data is analyzed and processed by an AI algorithm to generate customized goals for each employee. For example, the server uses information from the sales department to analyze the sales department's past sales performance and achievement level, and sets the next period's sales target to increase by 15%. At the same time, the server also calculates evaluation criteria for the set target and stores them in the database. For example, it can rank employees according to their level of achievement of the sales target, setting criteria such as a high evaluation for achievement of 80% or more and a low evaluation for achievement of less than 50%.

[0454] Device behavior

[0455] The terminal provides an interface for goal setting and progress input through a user interface. Users (employees) check their goals and periodically input their progress through the terminal. Specifically, the terminal uses the following hardware and software:

[0456] Frontend: React, Vue.js

[0457] Backend: Node.js (Express)

[0458] For example, a sales manager logs in to a terminal and checks the target provided by the server (e.g., a 15% increase in sales). Then, at the end of each month, the manager enters the sales progress and sends it to the server. At this time, the terminal sends the entered data to the server in real time, allowing the manager to receive feedback.

[0459] User Actions

[0460] Users (employees and evaluators) use the interface provided by the server and terminal to understand their own goals and periodically enter their progress. Users also perform self-evaluations and confirm and accept the feedback provided by the server. For example, after a sales manager enters monthly sales figures, the server can provide feedback with specific advice, such as "Current achievement rate is 60%. Improvement plan for the next quarter: Strengthen approach to specific customer segments." This feedback is provided in real time, enabling prompt improvement measures to be implemented.

[0461] Examples of specific examples and prompts

[0462] After logging in to their device, the sales manager checks the next quarter's sales target (e.g., a 15% increase) provided by the server. At the end of each month, the manager enters the monthly sales and presses the "Send" button on the device to send the data to the server. The server receives this data, analyzes it in real time, and calculates the achievement rate. The calculation results are displayed as, for example, "Current achievement rate is 60%." Furthermore, the server uses an AI model to generate feedback such as "Improvement measures for the next quarter: Strengthen approach to specific customer segments," and immediately sends this to the device. The manager can receive this feedback and make an action plan for the next quarter.

[0463] Prompt Sentence Examples

[0464] By inputting the following prompt sentence into the generative AI model, the processing of the above program can be explained in natural language.

[0465] Please explain how a corporate goal management system works. The system consists of three components: a server, a terminal, and a user. The server analyzes data and sets customized goals, while the terminal displays goal settings and provides progress input. The user checks goals and inputs progress. Please explain how the entire system works using specific examples.

[0466] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0467] Step 1:

[0468] Data collection

[0469] The server obtains company information, personnel information, and goal data provided by the company. Specifically, the server collects this data using APIs and database connections. The input is data obtained from the company's personnel system and goal management system. For example, the server periodically sends an HTTP request to an API endpoint and receives JSON-formatted data as a response. The received data is then stored in a database.

[0470] Step 2:

[0471] Data analysis and goal setting

[0472] The server analyzes the collected data using an AI algorithm. The input here is the data collected in step 1. Specifically, it uses Python's TensorFlow library to analyze past performance data and set customized goals for each employee. For example, for employees in the sales department, it sets a sales goal for the next fiscal year to increase by 15% based on past sales data. The analysis results are stored in a database.

[0473] Step 3:

[0474] Setting evaluation criteria

[0475] The server sets evaluation criteria based on the generated goals. The input for this step is the customized goals generated in step 2. Specifically, it ranks the sales goals according to their achievement level. For example, it sets criteria such as high evaluation for achievement of 80% or more and low evaluation for achievement of less than 50%, and saves this in the database.

[0476] Step 4:

[0477] Providing a goal presentation and progress input interface

[0478] The terminal presents goals to employees through a user interface and provides an interface for them to input their progress. The input is goal setting information sent from the server. For example, a dashboard built using React displays each employee's goal (e.g., 15% increase in sales). The user inputs their progress here, and the data is sent to the server in real time.

[0479] Step 5:

[0480] Progress data collection and analysis

[0481] The server receives the progress data sent from the terminal and analyzes it in real time. The input is the progress data entered by the user in step 4. Specifically, the server receives the progress data (e.g., monthly sales) via the Node.js backend API and analyzes it using a Python script. The output is the calculated achievement level for each employee (e.g., current achievement level is 60%).

[0482] Step 6:

[0483] Generating and Providing Feedback

[0484] The server generates feedback based on the results of analyzing the progress data and sends it to the device. The input is the calculation result of the achievement level obtained in step 5. Specifically, an AI model is used to generate optimal feedback based on the evaluation results of each employee. This feedback might be something like, "Improvement plan for the next quarter: Strengthen approach to specific customer segments." The generated feedback is sent to the device in real time and can be viewed by the user.

[0485] This series of processes will improve the efficiency of goal management across the entire company, improve employee motivation, and reduce the burden on evaluators.

[0486] (Application example 1)

[0487] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0488] Conventional goal management systems make it difficult to set employee goals and monitor progress, and they tend to be out of sync with actual work, especially in factories and other workplaces. Real-time feedback is also difficult, making it difficult to implement rapid improvement measures to achieve goals. This leads to a lack of transparency and fairness in evaluations, which can lead to lower motivation and increased burdens on evaluators.

[0489] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0490] In this invention, the server includes a means for collecting company information, personnel data, and goal setting data, a means for analyzing the collected data and generating customized goals for each employee, and a means for setting evaluation criteria based on the generated goals. This allows employees to view their goals and feedback through smart glasses, collect progress data during actual work, and receive feedback in real time. This improves the efficiency of goal management and improves employees' sense of satisfaction and fairness.

[0491] "Company Information" means information including organizational structure, performance, department information, and other company-related data.

[0492] "Human Resources Data" means data related to employee names, job titles, evaluation history, skill sets, and working hours.

[0493] "Goal setting data" refers to data regarding the specific performance and production goals that each employee or department must achieve.

[0494] "Collection means" refers to the software or hardware components that collect the required data through a database or API.

[0495] "Means of analysis" refers to AI algorithms and machine learning models that analyze the collected data and extract relevant information.

[0496] "Customized goals" are individual goals set for each employee based on their skills, past performance, and current situation.

[0497] "Evaluation criteria" are standards for evaluating the degree of achievement of set goals, and include specific evaluation indicators and ranking methods.

[0498] "Means for storing data in a database" means a database management system for securely storing collected data and generated goals and evaluation criteria.

[0499] "User interface" refers to the software screens or applications that allow employees to enter and review goals and progress.

[0500] "Progress data" is specific data that shows how an employee is progressing toward their goals.

[0501] "Real-time processing means" means a high-speed computing mechanism that instantly analyzes received data and provides feedback.

[0502] "Means for providing feedback" is a function for providing advice and suggestions for improvement to employees based on progress data.

[0503] "Smart glasses" are devices that provide visual information to the wearer and assist them in real-world tasks.

[0504] "Means for displaying goals and feedback" means software functionality for displaying set goals and real-time feedback through the display of the smart glasses.

[0505] "Means for collecting progress data" refers to an input function for collecting specific work progress from employees through the smart glasses.

[0506] This invention aims to improve the efficiency of goal management in factories, and describes a system in which employees use smart glasses to set goals, manage progress, and receive real-time feedback.

[0507] Server Operation

[0508] The server first collects company information, personnel data, and goal setting data provided by the company. This data, obtained through existing database management systems or APIs, is then analyzed using AI algorithms. For example, it takes into account an employee's past production performance and skill set to customize goals appropriate for each employee. The generated goals are then stored in a database along with evaluation criteria.

[0509] Smart glasses terminal operation

[0510] A dedicated application is installed on the smart glasses used as terminals. This application allows employees to visually check their goals and progress through a user interface. Employees can check their goals in real time and enter their progress directly through the smart glasses while working. This allows progress data to be sent to a server in real time, and feedback is provided immediately as an analysis result.

[0511] User Actions

[0512] By wearing the smart glasses, employees can check their set goals and progress in real time while they work. They can also input progress data and receive prompt feedback from the server, enabling employees to take prompt action to improve their work.

[0513] System operation example

[0514] For example, when a factory worker puts on the smart glasses, the production target for the current month is displayed. The worker inputs their progress as they work, and the server analyzes this in real time and provides feedback. This feedback suggests specific improvement measures, such as "Please reevaluate next week's production plan."

[0515] Prompt Sentence Examples

[0516] Examples of specific prompts that smart glasses applications might provide to users include:

[0517] "How close are you to achieving your goal this month? Please give me some specific numbers."

[0518] "What should we improve next?"

[0519] "Please enter your progress data."

[0520] This will improve the efficiency and transparency of goal management. In particular, by allowing employees to receive feedback in real time, it is possible to take prompt corrective measures, which is expected to improve overall production efficiency and fairness in evaluations.

[0521] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0522] Step 1:

[0523] The server collects company information, HR data, and goal setting data provided by the company. This data is obtained via APIs and database connections. The input is data from each department and HR department of the company, and the output is in the form of the original data stored on the server.

[0524] Step 2:

[0525] The server analyzes the collected data using an AI algorithm. Specifically, it inputs each employee's past production performance and skill set into an analytical model, from which individual goals are generated. The input is each employee's past data, and the output is customized goal data.

[0526] Step 3:

[0527] The server sets evaluation criteria based on the created goals. For example, it sets specific evaluation indicators and ranking methods to show the degree of goal achievement. The input is customized goal data, and the output is evaluation criteria data for that goal.

[0528] Step 4:

[0529] The server stores the generated goals and evaluation criteria in a database. The input is the customized goal and evaluation criteria data, and the output is the data recorded in the database.

[0530] Step 5:

[0531] The terminal (smart glasses) displays the goals to the employee through a user interface. The employee can visually confirm the goals through the smart glasses while working. The input is the goal data received from the server, and the output is the goal information displayed on the display of the smart glasses.

[0532] Step 6:

[0533] The user (employee) inputs progress data into the terminal via smart glasses while working. This progress data can be entered via a keyboard or voice recognition function. The input is the employee's progress data, and the output is the progress data recorded on the terminal.

[0534] Step 7:

[0535] The terminal transmits the collected progress data to the server in real time. The input is the progress data recorded on the terminal, and the output is the progress data transmitted to the server.

[0536] Step 8:

[0537] The server analyzes the received progress data and generates feedback using a generative AI model. The input is the progress data sent from the terminal, and the output is the feedback data provided to the employee.

[0538] Step 9:

[0539] The terminal displays the feedback from the server on the smart glasses, allowing employees to quickly take corrective measures. The input is the feedback data received from the server, and the output is the feedback information displayed on the smart glasses display.

[0540] Step 10:

[0541] After receiving the feedback, the employee re-enters the progress data as needed and continues to communicate with the server. The input is the newly entered progress data, and the output is the updated progress data in the server.

[0542] These steps will ensure that the goal management system is operating effectively, improving the company's production efficiency and employee motivation.

[0543] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0544] This invention relates to a system that incorporates an emotion engine into a company's goal management system, providing feedback and evaluation that takes into account the employee's emotional state, thereby improving employee satisfaction and motivation. This system consists of three main components: a server, a terminal, and a user.

[0545] Server Operation

[0546] The server receives company information, personnel data, and goal setting data provided by the company. This data is collected and pre-processed via APIs and database connections. It then analyzes this data using AI algorithms to generate customized goals for each employee. Evaluation criteria are also calculated based on the generated goals and stored in the database.

[0547] Furthermore, the server is equipped with an emotion engine that receives the user's emotion data. The emotion engine analyzes the text, voice, and facial recognition data entered by the user to recognize the user's emotional state. For example, it can determine positive or negative emotions from the text entered by the user.

[0548] Device behavior

[0549] The terminal provides an interface for goal setting and progress input through a user interface. The user (employee) checks his / her goals through the terminal and periodically inputs his / her progress. In addition, the user also inputs information that represents his / her emotional state.

[0550] As a concrete example, a sales manager logs in to a terminal and checks the target provided by the server (e.g., a 15% increase in sales). Then, at the end of each month, he or she enters the sales progress along with his or her emotional state (e.g., "highly motivated" or "stressed"). This data is sent to the server in real time.

[0551] User Actions

[0552] Users (employees and evaluators) use the interface provided by the server and terminal to understand their goals and periodically enter their progress. The user self-evaluates and confirms and accepts the emotional feedback provided by the server. The emotion engine analyzes the user's emotional state and provides feedback based on the results in real time.

[0553] For example, after entering monthly sales figures, a sales manager receives feedback based on their emotional state analyzed by the emotion engine. For example, they may receive specific advice such as, "Achievement rate is 60%. Improvement plan for the next quarter: Strengthen approach to specific customer segments. Current emotional state: Feeling stressed. We recommend taking a vacation to refresh yourself."

[0554] Overall system operation

[0555] This system can provide individual feedback to both the evaluator and the person being evaluated that takes into account their emotional state, significantly improving the sense of satisfaction and fairness of the evaluation. In addition, by incorporating the emotional data analyzed by the emotion engine as part of the evaluation process, the overall evaluation process proceeds more effectively and efficiently.

[0556] The present invention provides an intuitive and easy-to-use interface for both employees and evaluators, and significantly improves the quality and efficiency of evaluations through real-time feedback and advice. Furthermore, the incorporation of an emotion engine enables flexible responses based on the employee's emotional state, improving overall performance and employee satisfaction.

[0557] The processing flow will be explained below.

[0558] Step 1:

[0559] The server collects company information, personnel data, and goal setting data provided by the company, and obtains this data via API and database connection.

[0560] Step 2:

[0561] The server pre-processes the acquired data, which includes checking, normalizing, and converting the data into a format suitable for analysis.

[0562] Step 3:

[0563] The server then uses AI algorithms to analyze the pre-processed data and generate customized goals for each employee.

[0564] Step 4:

[0565] The server sets evaluation criteria based on the generated goals and calculates evaluation criteria that include quantitative and qualitative elements.

[0566] Step 5:

[0567] The server stores the goals and evaluation criteria in a database, which allows for consistent management of the data.

[0568] Step 6:

[0569] The terminal provides the user with a login interface, prompting them to enter their username and password, and then sends the authentication information to the server.

[0570] Step 7:

[0571] The terminal displays the goal settings and evaluation criteria obtained from the server to the user, allowing the user to check their own goals.

[0572] Step 8:

[0573] The terminal provides the user with options for inputting emotional information through a user interface, which can be input in the form of text, voice, facial recognition data, etc.

[0574] Step 9:

[0575] Users periodically input their progress and emotional information, which is then sent to the server in real time.

[0576] Step 10:

[0577] The server analyzes the progress data and emotional data, and the emotional engine recognizes the user's emotional state and generates personalized feedback based on the emotional data.

[0578] Step 11:

[0579] The server generates the analyzed progress data and emotional feedback, and transmits the feedback to the device in real time.

[0580] Step 12:

[0581] The device displays feedback to the user, including specific advice based on progress and emotional state.

[0582] Step 13:

[0583] The user checks the feedback and performs a self-evaluation, and the self-evaluation data is sent to the server via the terminal.

[0584] Step 14:

[0585] The server generates the final assessment, which is provided to both the user and the assessor.

[0586] Step 15:

[0587] The terminal displays the final evaluation results to the user, and next goals and areas for improvement are presented based on the evaluation results.

[0588] The above steps realize a system that integrates goal setting, progress management, and collection and evaluation of emotional information.

[0589] Example 2

[0590] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0591] Conventional goal management systems have difficulty reflecting employees' emotional state in the feedback and evaluation process, which has led to issues such as insufficient improvement of employee satisfaction and motivation. In addition, there was a need for an integrated approach that not only handles quantitative evaluations but also emotional state and progress data.

[0592] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for collecting company information, personnel data, and goal setting data, a means for preprocessing the collected data, and a means for analyzing the preprocessed data and generating goals customized for each employee. This makes it possible to set and evaluate customized goals that take emotional states into consideration.

[0593] "Company information" refers to information about an organization's basic data, business operations, and management strategies.

[0594] "Personnel data" refers to data including employee personal information, work history, evaluation records, salary information, etc.

[0595] "Goal setting data" refers to data that indicates the specific goals to be achieved by each employee or department and the associated evaluation criteria.

[0596] "Data preprocessing" is the process of converting collected raw data into an analyzable form by filling in missing values, removing outliers, normalizing, etc.

[0597] "Customized goals" are specific goals that are set specifically for each employee based on their job duties and abilities.

[0598] "Evaluation criteria" are data that show specific indicators and standards for evaluating an employee's level of goal achievement.

[0599] A "database" is an information system that efficiently stores and manages collected information and allows it to be quickly searched and retrieved as needed.

[0600] A "user interface" is a system that includes screens and input forms that allow users to interact with a system.

[0601] "Progress data" is data that indicates the current progress toward achieving a goal.

[0602] "Real-time processing" is a processing method in which processing is executed immediately when data is entered or updated, and the results are provided.

[0603] "Feedback" is information that provides employees with information about their progress toward their goals, an evaluation of their work, and specific advice on areas for improvement.

[0604] The "emotion engine" is a system that analyzes and determines the emotional state of employees from their input data (text, voice, facial recognition, etc.).

[0605] "Quantitative evaluation" is an evaluation method based on numerical and quantitative data.

[0606] "Qualitative evaluation" is an evaluation method that does not rely on numerical values, but is based on subjective information such as observation and feedback.

[0607] This system incorporates an emotion engine into a company's goal management system, providing feedback and evaluations that take into account the employee's emotional state, thereby improving employee satisfaction and motivation. The system consists of three main components: a server, a terminal, and a user.

[0608] Server Operation

[0609] The server collects company information, personnel data, and goal setting data through APIs and database connections. The collected data is preprocessed using Python and SQL. The preprocessed data is then analyzed using AI algorithms such as Scikit-learn and TensorFlow to generate customized goals for each employee. The generated goals and evaluation criteria are stored in a MySQL database.

[0610] In addition, the server is equipped with an emotion engine that integrates Google's Sentiment Analysis API. The emotion engine analyzes the text, voice, and facial recognition data entered by the user to recognize the user's emotional state. For example, it analyzes the user's input text, "I'm very tired today," and identifies negative emotions.

[0611] Device behavior

[0612] The terminal runs as a web application using React.js and provides users with an interface for entering goals and progress. Users (employees) can check their goals and enter their progress through the terminal. In addition, users can also enter their emotional state.

[0613] For example, when a sales employee logs in to their terminal, a target provided by the server (e.g., "Increase sales by 15%) is displayed. At the end of each month, they enter their emotional state (e.g., "Highly motivated" or "Feeling stressed") along with their sales progress. This data is sent to the server in real time.

[0614] User Actions

[0615] The user (employee or evaluator) uses the interface provided by the server and terminal to understand their goals and periodically enter their progress. The user self-evaluates, checks and accepts the emotional feedback provided by the server. Feedback based on the emotional state analyzed by the emotion engine is provided in real time.

[0616] For example, after a sales employee enters their monthly sales figures, they receive feedback based on their emotional state analyzed by the emotion engine. For example, they may receive specific advice such as, "Achievement rate is 66.7%. Improvement plan for the next quarter: Strengthen your approach to specific customer segments. Current emotional state: Highly motivated. We recommend taking a vacation to refresh yourself."

[0617] Prompt Sentence Examples

[0618] An example prompt for a generative AI model might look like this:

[0619] "Given the given goal, evaluate the employee's progress and generate feedback that takes into account their emotional state. Include improvement measures and recommended actions if the goal is 66.7% achieved."

[0620] This system can provide individual feedback to both the evaluator and the person being evaluated that takes into account their emotional state, significantly improving the sense of satisfaction and fairness of the evaluation. In addition, by incorporating the emotional data analyzed by the emotion engine as part of the evaluation process, the overall evaluation process proceeds more effectively and efficiently.

[0621] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0622] Step 1:

[0623] The server collects company data, specifically company information, HR data, and goal setting data through APIs and database connections. For example, it retrieves employee information from a HR database using an SQL query. The input to this operation is the API request or SQL query, and the output is the collected raw data.

[0624] Step 2:

[0625] The server preprocesses the collected data. Specifically, it performs tasks such as filling in missing values, removing outliers, and normalizing the collected data. The input is the collected raw data, and the output is the preprocessed data. For example, data cleaning is performed using the Python Pandas library.

[0626] Step 3:

[0627] The server analyzes the preprocessed data and generates customized goals. Specifically, it analyzes the data using machine learning algorithms such as Scikit-learn and TensorFlow to set goals for each employee. The input is the preprocessed data, and the output is individual goal setting data. For example, a random forest model is used to predict goals.

[0628] Step 4:

[0629] The server sets evaluation criteria based on the generated goals. Specifically, it calculates the evaluation criteria based on the generated goals and the company's evaluation policy. The input is individual goal setting data and the company's evaluation policy, and the output is evaluation criteria data. For example, it calculates evaluation criteria using goal achievement rates and key performance indicators (KPIs).

[0630] Step 5:

[0631] The server saves the goals and evaluation criteria in a database. Specifically, it saves the goal setting data and evaluation criteria data in a MySQL database. The input is the goal setting data and evaluation criteria data, and the output is the status of saving to the database. For example, data is inserted into the database using an SQL query.

[0632] Step 6:

[0633] The terminal provides employees with a user interface for entering goals and progress. Specifically, the goal setting screen and progress input screen are displayed through a web application using React.js. The input is the user's login information, and the output is the goal setting screen that is displayed. For example, after logging in, an employee can check their goals on the web screen.

[0634] Step 7:

[0635] The user inputs their progress and emotional state. Specifically, they periodically input their goal achievement status and their emotional state using the terminal interface. The input is the user's progress data and emotional state data, and the output is that this data is sent to the server. For example, they input "10% increase in sales" and "highly motivated."

[0636] Step 8:

[0637] The server receives and analyzes the input data and generates feedback. Specifically, it uses an AI algorithm to analyze progress data and emotional state data and generate individualized feedback. The input is the progress data and emotional state data sent by the user, and the output is feedback data. For example, it generates "achievement level 66.7%, improvement plan for the next quarter: strengthen approach to specific customer segments."

[0638] Step 9:

[0639] The user confirms and accepts the feedback. Specifically, the user confirms the feedback provided by the server through the terminal interface and reflects it in the next action plan. The input is the feedback data provided by the server, and the output is the user's next action plan. For example, a sales employee accepts the advice to "strengthen their approach to a specific customer base in the next quarter" and reflects it in their actual business plan.

[0640] (Application example 2)

[0641] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0642] Conventional goal management systems fail to take into account the emotional state of employees, resulting in problems such as a lack of employee satisfaction and motivation. Furthermore, uniform evaluations and feedback that ignore emotions are factors that reduce the fairness and effectiveness of evaluations. In particular, on-site work such as robot operators in factories involves significant physical and mental strain, and fluctuations in emotional state are directly linked to work efficiency and safety, so appropriate responses are required.

[0643] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting company information, personnel data, and goal setting data, means for analyzing the collected data and generating goals customized for each employee, means for setting evaluation criteria based on the generated goals, means for saving the goals and evaluation criteria in a database, means for employees to input their goals and progress through a user interface, means for processing progress data in real time and providing feedback, means for inputting or detecting the employee's emotional state, means for analyzing the emotional data and customizing the feedback based on the emotional state, and means for providing feedback to the employee and saving the emotional data in a database. This enables individual feedback that takes the employee's emotional state into consideration, improving employee satisfaction and motivation, and improving work efficiency and safety, particularly in factory floor work.

[0644] "Company information" refers to information about a company's basic data and organizational structure.

[0645] "Human resources data" refers to data including employee personal information, job titles, evaluation history, salary information, etc.

[0646] "Goal setting data" refers to data related to work goals and deliverables that a company sets for its employees.

[0647] A "collection means" is a method or device for acquiring and recording data.

[0648] An "analytical means" is a method or device for analyzing collected data and deriving a specific result.

[0649] "Customized goals" are specific work goals tailored to each employee.

[0650] "Evaluation criteria" are quantitative and qualitative indicators used to evaluate employee performance.

[0651] A "database storage means" is a method or device for storing data long-term and making it accessible at a later time.

[0652] A "user interface" is a screen display and input device that allows a user to interact with a system.

[0653] "Means for inputting progress" refers to a method or device that allows an employee to input the progress of their work into the system.

[0654] "Means for processing and providing feedback in real time" refers to a method or device for analyzing progress data in real time and providing the results as feedback.

[0655] "Means for inputting or detecting emotional state" refers to methods or devices for conveying an employee's emotions to the system, including voice input, text input, facial recognition, etc.

[0656] A "means for analyzing emotional data" is a method or apparatus for analyzing input or sensed emotional data to identify an employee's current emotional state.

[0657] A "means for customizing feedback" is a method or apparatus for generating personalized feedback based on evaluation criteria and emotional data.

[0658] A "means for providing feedback to employees" is a method or device for communicating system-generated feedback to employees.

[0659] The present invention aims to improve productivity and motivation by providing feedback and evaluation that takes into account employees' emotional states. The system consists of three main components: a server, a terminal, and a user.

[0660] Server Operation

[0661] The server has the following functions:

[0662] 1. Data collection: The server collects company information, personnel data, and goal setting data via APIs and database connections.

[0663] 2. Data analysis: The collected data is analyzed by AI algorithms to generate customized goals and evaluation criteria for each employee, which are then stored in a database.

[0664] 3. Emotion analysis: Using an emotion engine, the system analyzes the emotion data received from users (text, voice, facial recognition data, etc.) to recognize the emotional state of employees.

[0665] The server uses the following hardware and software: a high-performance server, an Emotion Engine, a Feedback Generator, and a database system.

[0666] Device behavior

[0667] The terminal has the following features:

[0668] 1. Interface provision: Provide an interface for employees to input goals and progress through a user interface.

[0669] 2. Progress input: Employees can periodically input their goal progress.

[0670] 3. Emotion input: Ability to input or detect employees' emotional state (voice, facial recognition, etc.).

[0671] Hardware and software used on your device: PC, smartphone, camera (for facial recognition), microphone (for voice analysis).

[0672] User Actions

[0673] Users, i.e. factory or office employees and managers, go through the following process:

[0674] 1. Data entry: Employees enter their progress and emotional state into a terminal.

[0675] 2. Feedback reception: Receive individually customized feedback based on the emotional data analyzed by the server.

[0676] 3. Evaluate and Improve: Use the feedback provided to improve your work.

[0677] Specific examples

[0678] For example, a factory robot operator might use the system to perform their daily tasks:

[0679] 1. Prompt to enter progress:

[0680] Please tell us your progress today:

[0681] Progress: Production line adjustment work is 80% complete.

[0682] 2. Emotional state prompt:

[0683] Please describe your emotional state today:

[0684] Emotional state: Feeling tired. Having difficulty concentrating.

[0685] 3. Feedback provided by the system:

[0686] feedback:

[0687] Progress is on schedule, but you are experiencing a decline in concentration. Please take a short break to refresh yourself and get back to work.

[0688] The system analyzes employees' work progress and emotional state in real time and provides individually customized feedback, thereby improving productivity and employee motivation across the company.

[0689] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0690] Step 1:

[0691] The server uses APIs and database connections to collect company information, personnel data, and goal setting data. The collected data is temporarily stored and organized in the database. Specifically, the collected data includes basic company data, personnel structure, employee history, and goal achievement status.

[0692] Input: Company information, personnel data, goal setting data

[0693] Output: Organized database entries

[0694] Step 2:

[0695] The server analyzes the collected data using an AI algorithm to generate customized goals for each employee. The generated goals are optimized based on the employee's current situation and output in the form of goals and evaluation criteria.

[0696] Input: Organized database entries

[0697] Output: Customized goals and metrics

[0698] Step 3:

[0699] The server stores the generated goals and evaluation criteria in a database, which can be later reviewed by employees.

[0700] Input: Customized goals and metrics

[0701] Output: Goals and metrics stored in a database

[0702] Step 4:

[0703] The terminal provides an interface for employees to input goals and progress through a user interface, and the data entered by the employees is transmitted to the server in real time.

[0704] Input: Goals and progress information entered by employees

[0705] Output: Progress data sent to the server

[0706] Step 5:

[0707] The server processes the progress data in real time and generates the analysis results as feedback, automatically generating optimal feedback based on the employee's progress and achievement level.

[0708] Input: Progress data

[0709] Output: Generated feedback

[0710] Step 6:

[0711] The server receives employee emotional state data (text, voice, facial recognition data, etc.) sent from the device and analyzes it using an emotion engine. The analysis results are output as data indicating the employee's emotional state.

[0712] Input: Emotional state data

[0713] Output: Parsed emotional state data

[0714] Step 7:

[0715] The server then personalizes the feedback based on the analyzed emotional state data, generating specific advice tailored to the employee's current emotional state.

[0716] Input: Parsed emotional state data

[0717] Output: Customized feedback

[0718] Step 8:

[0719] The server provides the generated feedback to the employee and stores the feedback along with the emotion data in a database.

[0720] Input:Customized Feedback

[0721] Output: Feedback provided to employees, feedback and sentiment data stored in a database

[0722] The above processing steps realize a system that provides real-time feedback that takes into account the emotions of employees, which improves employee satisfaction and motivation, and also increases work efficiency and safety in factory work.

[0723] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0724] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0725] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0726] [Third embodiment]

[0727] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0728] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0729] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0730] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0731] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0732] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0733] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0734] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0735] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0736] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0737] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0738] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0739] This invention relates to a system and method for improving the efficiency of the target management system implemented by a company and for improving the sense of satisfaction and fairness among employees. This invention is realized through the cooperation of three components: a server, a terminal, and a user.

[0740] Server Operation

[0741] The server receives and analyzes company information, personnel data, and goal setting data provided by the company. First, the server acquires various data via APIs and database connections. The acquired data is analyzed and processed by AI algorithms to generate customized goal settings for each employee.

[0742] As a specific example, the server uses information from the sales department to analyze the past sales performance and achievement level of sales department employees, and sets the next period's sales target to increase by 15%. At the same time, the server also calculates evaluation criteria for the set target and stores them in the database. For example, it can rank employees according to their achievement level of the sales target, setting criteria such as high evaluation for achievement of 80% or more and low evaluation for achievement of less than 50%.

[0743] Device behavior

[0744] The terminal provides an interface for setting goals and inputting progress through a user interface. Users (employees) can check their own goals and periodically input their progress through the terminal.

[0745] For example, a sales manager logs in to a terminal and checks the target provided by the server (e.g., a 15% increase in sales). Next, at the end of each month, the manager enters the sales progress and sends it to the server. At this time, the terminal sends the entered data to the server in real time, allowing the manager to receive feedback.

[0746] User Actions

[0747] Users (employees and evaluators) use the interface provided by the server and terminal to understand their goals and periodically enter their progress. Users also perform self-evaluations and confirm and accept the feedback provided by the server.

[0748] For example, after a sales manager inputs monthly sales figures, he or she can receive feedback from the server, such as "Current achievement rate is 60%. Improvement plan for the next quarter: Strengthen approach to specific customer segments." This feedback is provided in real time, making it possible to take prompt improvement measures.

[0749] Overall system operation

[0750] This system streamlines company-wide goal management, improves employee motivation, and reduces the burden on evaluators. In addition, by integrating qualitative and quantitative evaluations, the evaluation process becomes more transparent and fair, leading to overall performance improvements.

[0751] The present invention provides an intuitive and easy-to-use interface for both employees and raters, and significantly improves the quality and efficiency of appraisals through real-time feedback and advice.

[0752] The processing flow will be explained below.

[0753] Step 1:

[0754] The server collects company information, personnel data, and goal setting data provided by the company. This data is obtained via API and database connection.

[0755] Step 2:

[0756] The server preprocesses the collected data, maintaining its integrity and converting it into a format suitable for analysis.

[0757] Step 3:

[0758] The server uses AI algorithms to analyze the data and generate customized goals for each employee.

[0759] Step 4:

[0760] The server sets evaluation criteria based on the generated goals, and the specific evaluation criteria include quantitative and qualitative elements.

[0761] Step 5:

[0762] The server stores the goals and evaluation criteria in a database, which allows for consistent management of the data.

[0763] Step 6:

[0764] The terminal provides the user with a login interface, prompting them to enter their username and password, and then sends the authentication information to the server.

[0765] Step 7:

[0766] The terminal displays the goal settings and evaluation criteria obtained from the server to the user, allowing the user to confirm their own goals.

[0767] Step 8:

[0768] The user periodically inputs progress information via the terminal, and the input data is sent to the server in real time.

[0769] Step 9:

[0770] The server analyzes the received progress data and generates real-time feedback, which is then sent to the device.

[0771] Step 10:

[0772] The device displays feedback to the user, allowing them to receive advice based on their progress.

[0773] Step 11:

[0774] The user inputs their self-evaluation and sends it to the server via their terminal, where the input data is saved.

[0775] Step 12:

[0776] The server generates the final assessment, which is provided to both the user and the assessor.

[0777] Step 13:

[0778] The device displays the final evaluation results to the user, and suggests areas for improvement and future goals based on the evaluation.

[0779] Step 14:

[0780] The user checks the final evaluation results and considers improvement measures for the next period, completing the entire evaluation process.

[0781] The above steps realize a system that integrates goal setting, progress management, and evaluation.

[0782] Example 1

[0783] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0784] With conventional goal management systems, employees often lack a sense of satisfaction or fairness regarding the goals set within the company, making efficient goal management difficult. Furthermore, because evaluation criteria are not clear, evaluations can lack transparency and fairness. Furthermore, progress cannot be entered and feedback cannot be provided in real time, which can delay rapid responses and the implementation of improvement measures.

[0785] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0786] In this invention, the server includes means for collecting company information, personnel information, and goal data, means for analyzing the collected data using an AI algorithm and generating goals customized for each employee, means for setting evaluation criteria based on the generated goals, means for saving the goals and evaluation criteria in a data storage device, means for employees to input their goals and progress through a user interface, and means for processing progress data in real time and providing feedback. This enables efficient and transparent goal management within a company, increases employees' sense of satisfaction and fairness, and enables prompt feedback and the implementation of improvement measures.

[0787] "Company information" refers to data about a company's basic information and organizational structure.

[0788] "Human resources information" refers to data about employees' individual attributes, job duties, and past performance.

[0789] "Goal Data" refers to data relating to goals to be achieved set for a company or individual employees.

[0790] "AI algorithm" refers to a computational method that uses artificial intelligence technology to analyze data and generate specific patterns or predictions.

[0791] "Customized goals" refer to individual goals set based on each employee's characteristics and past performance.

[0792] "Evaluation criteria" refers to the indicators and standards used to evaluate an employee's level of goal achievement.

[0793] "Data storage device" refers to a system or database for storing data.

[0794] "User interface" refers to the screen or interface through which a user interacts with a system.

[0795] "Progress Data" refers to data relating to the current achievement or progress towards a goal.

[0796] "Real-time processing" refers to the immediate collection and analysis of progress data.

[0797] "Feedback" refers to notification and advice regarding evaluation results and improvement measures based on progress.

[0798] This invention relates to a system and method for improving the efficiency of the target management system adopted by companies and enhancing employees' sense of satisfaction and fairness. This system is realized through the cooperation of three components: a server, a terminal, and a user.

[0799] Server Operation

[0800] The server receives company information, personnel information, and goal data provided by the company and analyzes this data. First, the server obtains various data via APIs and database connections. Specifically, the server uses the following hardware and software:

[0801] Database: MySQL, PostgreSQL

[0802] AI algorithms: Python, TensorFlow, Scikit-learn

[0803] API frameworks: Flask, Django

[0804] The acquired data is analyzed and processed by an AI algorithm to generate customized goals for each employee. For example, the server uses information from the sales department to analyze the sales department's past sales performance and achievement level, and sets the next period's sales target to increase by 15%. At the same time, the server also calculates evaluation criteria for the set target and stores them in the database. For example, it can rank employees according to their level of achievement of the sales target, setting criteria such as a high evaluation for achievement of 80% or more and a low evaluation for achievement of less than 50%.

[0805] Device behavior

[0806] The terminal provides an interface for goal setting and progress input through a user interface. Users (employees) check their goals and periodically input their progress through the terminal. Specifically, the terminal uses the following hardware and software:

[0807] Frontend: React, Vue.js

[0808] Backend: Node.js (Express)

[0809] For example, a sales manager logs in to a terminal and checks the target provided by the server (e.g., a 15% increase in sales). Then, at the end of each month, the manager enters the sales progress and sends it to the server. At this time, the terminal sends the entered data to the server in real time, allowing the manager to receive feedback.

[0810] User Actions

[0811] Users (employees and evaluators) use the interface provided by the server and terminal to understand their own goals and periodically enter their progress. Users also perform self-evaluations and confirm and accept the feedback provided by the server. For example, after a sales manager enters monthly sales figures, the server can provide feedback with specific advice, such as "Current achievement rate is 60%. Improvement plan for the next quarter: Strengthen approach to specific customer segments." This feedback is provided in real time, enabling prompt improvement measures to be implemented.

[0812] Examples of specific examples and prompts

[0813] After logging in to their device, the sales manager checks the next quarter's sales target (e.g., a 15% increase) provided by the server. At the end of each month, the manager enters the monthly sales and presses the "Send" button on the device to send the data to the server. The server receives this data, analyzes it in real time, and calculates the achievement rate. The calculation results are displayed as, for example, "Current achievement rate is 60%." Furthermore, the server uses an AI model to generate feedback such as "Improvement measures for the next quarter: Strengthen approach to specific customer segments," and immediately sends this to the device. The manager can receive this feedback and make an action plan for the next quarter.

[0814] Prompt Sentence Examples

[0815] By inputting the following prompt sentence into the generative AI model, the processing of the above program can be explained in natural language.

[0816] Please explain how a corporate goal management system works. The system consists of three components: a server, a terminal, and a user. The server analyzes data and sets customized goals, while the terminal displays goal settings and provides progress input. The user checks goals and inputs progress. Please explain how the entire system works using specific examples.

[0817] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0818] Step 1:

[0819] Data collection

[0820] The server obtains company information, personnel information, and goal data provided by the company. Specifically, the server collects this data using APIs and database connections. The input is data obtained from the company's personnel system and goal management system. For example, the server periodically sends an HTTP request to an API endpoint and receives JSON-formatted data as a response. The received data is then stored in a database.

[0821] Step 2:

[0822] Data analysis and goal setting

[0823] The server analyzes the collected data using an AI algorithm. The input here is the data collected in step 1. Specifically, it uses Python's TensorFlow library to analyze past performance data and set customized goals for each employee. For example, for employees in the sales department, it sets a sales goal for the next fiscal year to increase by 15% based on past sales data. The analysis results are stored in a database.

[0824] Step 3:

[0825] Setting evaluation criteria

[0826] The server sets evaluation criteria based on the generated goals. The input for this step is the customized goals generated in step 2. Specifically, it ranks the sales goals according to their achievement level. For example, it sets criteria such as high evaluation for achievement of 80% or more and low evaluation for achievement of less than 50%, and saves this in the database.

[0827] Step 4:

[0828] Providing a goal presentation and progress input interface

[0829] The terminal presents goals to employees through a user interface and provides an interface for them to input their progress. The input is goal setting information sent from the server. For example, a dashboard built using React displays each employee's goal (e.g., 15% increase in sales). The user inputs their progress here, and the data is sent to the server in real time.

[0830] Step 5:

[0831] Progress data collection and analysis

[0832] The server receives the progress data sent from the terminal and analyzes it in real time. The input is the progress data entered by the user in step 4. Specifically, the server receives the progress data (e.g., monthly sales) via the Node.js backend API and analyzes it using a Python script. The output is the calculated achievement level for each employee (e.g., current achievement level is 60%).

[0833] Step 6:

[0834] Generating and Providing Feedback

[0835] The server generates feedback based on the results of analyzing the progress data and sends it to the device. The input is the calculation result of the achievement level obtained in step 5. Specifically, an AI model is used to generate optimal feedback based on the evaluation results of each employee. This feedback might be something like, "Improvement plan for the next quarter: Strengthen approach to specific customer segments." The generated feedback is sent to the device in real time and can be viewed by the user.

[0836] This series of processes will improve the efficiency of goal management across the entire company, improve employee motivation, and reduce the burden on evaluators.

[0837] (Application example 1)

[0838] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0839] Conventional goal management systems make it difficult to set employee goals and monitor progress, and they tend to be out of sync with actual work, especially in factories and other workplaces. Real-time feedback is also difficult, making it difficult to implement rapid improvement measures to achieve goals. This leads to a lack of transparency and fairness in evaluations, which can lead to lower motivation and increased burdens on evaluators.

[0840] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0841] In this invention, the server includes a means for collecting company information, personnel data, and goal setting data, a means for analyzing the collected data and generating customized goals for each employee, and a means for setting evaluation criteria based on the generated goals. This allows employees to view their goals and feedback through smart glasses, collect progress data during actual work, and receive feedback in real time. This improves the efficiency of goal management and improves employees' sense of satisfaction and fairness.

[0842] "Company Information" means information including organizational structure, performance, department information, and other company-related data.

[0843] "Human Resources Data" means data related to employee names, job titles, evaluation history, skill sets, and working hours.

[0844] "Goal setting data" refers to data regarding the specific performance and production goals that each employee or department must achieve.

[0845] "Collection means" refers to the software or hardware components that collect the required data through a database or API.

[0846] "Means of analysis" refers to AI algorithms and machine learning models that analyze the collected data and extract relevant information.

[0847] "Customized goals" are individual goals set for each employee based on their skills, past performance, and current situation.

[0848] "Evaluation criteria" are standards for evaluating the degree of achievement of set goals, and include specific evaluation indicators and ranking methods.

[0849] "Means for storing data in a database" means a database management system for securely storing collected data and generated goals and evaluation criteria.

[0850] "User interface" refers to the software screens or applications that allow employees to enter and review goals and progress.

[0851] "Progress data" is specific data that shows how an employee is progressing toward their goals.

[0852] "Real-time processing means" means a high-speed computing mechanism that instantly analyzes received data and provides feedback.

[0853] "Means for providing feedback" is a function for providing advice and suggestions for improvement to employees based on progress data.

[0854] "Smart glasses" are devices that provide visual information to the wearer and assist them in real-world tasks.

[0855] "Means for displaying goals and feedback" means software functionality for displaying set goals and real-time feedback through the display of the smart glasses.

[0856] "Means for collecting progress data" refers to an input function for collecting specific work progress from employees through the smart glasses.

[0857] This invention aims to improve the efficiency of goal management in factories, and describes a system in which employees use smart glasses to set goals, manage progress, and receive real-time feedback.

[0858] Server Operation

[0859] The server first collects company information, personnel data, and goal setting data provided by the company. This data, obtained through existing database management systems or APIs, is then analyzed using AI algorithms. For example, it takes into account an employee's past production performance and skill set to customize goals appropriate for each employee. The generated goals are then stored in a database along with evaluation criteria.

[0860] Smart glasses terminal operation

[0861] A dedicated application is installed on the smart glasses used as terminals. This application allows employees to visually check their goals and progress through a user interface. Employees can check their goals in real time and enter their progress directly through the smart glasses while working. This allows progress data to be sent to a server in real time, and feedback is provided immediately as an analysis result.

[0862] User Actions

[0863] By wearing the smart glasses, employees can check their set goals and progress in real time while they work. They can also input progress data and receive prompt feedback from the server, enabling employees to take prompt action to improve their work.

[0864] System operation example

[0865] For example, when a factory worker puts on the smart glasses, the production target for the current month is displayed. The worker inputs their progress as they work, and the server analyzes this in real time and provides feedback. This feedback suggests specific improvement measures, such as "Please reevaluate next week's production plan."

[0866] Prompt Sentence Examples

[0867] Examples of specific prompts that smart glasses applications might provide to users include:

[0868] "How close are you to achieving your goal this month? Please give me some specific numbers."

[0869] "What should we improve next?"

[0870] "Please enter your progress data."

[0871] This will improve the efficiency and transparency of goal management. In particular, by allowing employees to receive feedback in real time, it is possible to take prompt corrective measures, which is expected to improve overall production efficiency and fairness in evaluations.

[0872] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0873] Step 1:

[0874] The server collects company information, HR data, and goal setting data provided by the company. This data is obtained via APIs and database connections. The input is data from each department and HR department of the company, and the output is in the form of the original data stored on the server.

[0875] Step 2:

[0876] The server analyzes the collected data using an AI algorithm. Specifically, it inputs each employee's past production performance and skill set into an analytical model, from which individual goals are generated. The input is each employee's past data, and the output is customized goal data.

[0877] Step 3:

[0878] The server sets evaluation criteria based on the created goals. For example, it sets specific evaluation indicators and ranking methods to show the degree of goal achievement. The input is customized goal data, and the output is evaluation criteria data for that goal.

[0879] Step 4:

[0880] The server stores the generated goals and evaluation criteria in a database. The input is the customized goal and evaluation criteria data, and the output is the data recorded in the database.

[0881] Step 5:

[0882] The terminal (smart glasses) displays the goals to the employee through a user interface. The employee can visually confirm the goals through the smart glasses while working. The input is the goal data received from the server, and the output is the goal information displayed on the display of the smart glasses.

[0883] Step 6:

[0884] The user (employee) inputs progress data into the terminal via smart glasses while working. This progress data can be entered via a keyboard or voice recognition function. The input is the employee's progress data, and the output is the progress data recorded on the terminal.

[0885] Step 7:

[0886] The terminal transmits the collected progress data to the server in real time. The input is the progress data recorded on the terminal, and the output is the progress data transmitted to the server.

[0887] Step 8:

[0888] The server analyzes the received progress data and generates feedback using a generative AI model. The input is the progress data sent from the terminal, and the output is the feedback data provided to the employee.

[0889] Step 9:

[0890] The terminal displays the feedback from the server on the smart glasses, allowing employees to quickly take corrective measures. The input is the feedback data received from the server, and the output is the feedback information displayed on the smart glasses display.

[0891] Step 10:

[0892] After receiving the feedback, the employee re-enters the progress data as needed and continues to communicate with the server. The input is the newly entered progress data, and the output is the updated progress data in the server.

[0893] These steps will ensure that the goal management system is operating effectively, improving the company's production efficiency and employee motivation.

[0894] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0895] This invention relates to a system that incorporates an emotion engine into a company's goal management system, providing feedback and evaluation that takes into account the employee's emotional state, thereby improving employee satisfaction and motivation. This system consists of three main components: a server, a terminal, and a user.

[0896] Server Operation

[0897] The server receives company information, personnel data, and goal setting data provided by the company. This data is collected and pre-processed via APIs and database connections. It then analyzes this data using AI algorithms to generate customized goals for each employee. Evaluation criteria are also calculated based on the generated goals and stored in the database.

[0898] Furthermore, the server is equipped with an emotion engine that receives the user's emotion data. The emotion engine analyzes the text, voice, and facial recognition data entered by the user to recognize the user's emotional state. For example, it can determine positive or negative emotions from the text entered by the user.

[0899] Device behavior

[0900] The terminal provides an interface for goal setting and progress input through a user interface. The user (employee) checks his / her goals through the terminal and periodically inputs his / her progress. In addition, the user also inputs information that represents his / her emotional state.

[0901] As a concrete example, a sales manager logs in to a terminal and checks the target provided by the server (e.g., a 15% increase in sales). Then, at the end of each month, he or she enters the sales progress along with his or her emotional state (e.g., "highly motivated" or "stressed"). This data is sent to the server in real time.

[0902] User Actions

[0903] Users (employees and evaluators) use the interface provided by the server and terminal to understand their goals and periodically enter their progress. The user self-evaluates and confirms and accepts the emotional feedback provided by the server. The emotion engine analyzes the user's emotional state and provides feedback based on the results in real time.

[0904] For example, after entering monthly sales figures, a sales manager receives feedback based on their emotional state analyzed by the emotion engine. For example, they may receive specific advice such as, "Achievement rate is 60%. Improvement plan for the next quarter: Strengthen approach to specific customer segments. Current emotional state: Feeling stressed. We recommend taking a vacation to refresh yourself."

[0905] Overall system operation

[0906] This system can provide individual feedback to both the evaluator and the person being evaluated that takes into account their emotional state, significantly improving the sense of satisfaction and fairness of the evaluation. In addition, by incorporating the emotional data analyzed by the emotion engine as part of the evaluation process, the overall evaluation process proceeds more effectively and efficiently.

[0907] The present invention provides an intuitive and easy-to-use interface for both employees and evaluators, and significantly improves the quality and efficiency of evaluations through real-time feedback and advice. Furthermore, the incorporation of an emotion engine enables flexible responses based on the employee's emotional state, improving overall performance and employee satisfaction.

[0908] The processing flow will be explained below.

[0909] Step 1:

[0910] The server collects company information, personnel data, and goal setting data provided by the company, and obtains this data via API and database connection.

[0911] Step 2:

[0912] The server pre-processes the acquired data, which includes checking, normalizing, and converting the data into a format suitable for analysis.

[0913] Step 3:

[0914] The server then uses AI algorithms to analyze the pre-processed data and generate customized goals for each employee.

[0915] Step 4:

[0916] The server sets evaluation criteria based on the generated goals and calculates evaluation criteria that include quantitative and qualitative elements.

[0917] Step 5:

[0918] The server stores the goals and evaluation criteria in a database, which allows for consistent management of the data.

[0919] Step 6:

[0920] The terminal provides the user with a login interface, prompting them to enter their username and password, and then sends the authentication information to the server.

[0921] Step 7:

[0922] The terminal displays the goal settings and evaluation criteria obtained from the server to the user, allowing the user to check their own goals.

[0923] Step 8:

[0924] The terminal provides the user with options for inputting emotional information through a user interface, which can be input in the form of text, voice, facial recognition data, etc.

[0925] Step 9:

[0926] Users periodically input their progress and emotional information, which is then sent to the server in real time.

[0927] Step 10:

[0928] The server analyzes the progress data and emotional data, and the emotional engine recognizes the user's emotional state and generates personalized feedback based on the emotional data.

[0929] Step 11:

[0930] The server generates the analyzed progress data and emotional feedback, and transmits the feedback to the device in real time.

[0931] Step 12:

[0932] The device displays feedback to the user, including specific advice based on progress and emotional state.

[0933] Step 13:

[0934] The user checks the feedback and performs a self-evaluation, and the self-evaluation data is sent to the server via the terminal.

[0935] Step 14:

[0936] The server generates the final assessment, which is provided to both the user and the assessor.

[0937] Step 15:

[0938] The terminal displays the final evaluation results to the user, and next goals and areas for improvement are presented based on the evaluation results.

[0939] The above steps realize a system that integrates goal setting, progress management, and collection and evaluation of emotional information.

[0940] Example 2

[0941] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0942] Conventional goal management systems have difficulty reflecting employees' emotional state in the feedback and evaluation process, which has led to issues such as insufficient improvement of employee satisfaction and motivation. In addition, there was a need for an integrated approach that not only handles quantitative evaluations but also emotional state and progress data.

[0943] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for collecting company information, personnel data, and goal setting data, a means for preprocessing the collected data, and a means for analyzing the preprocessed data and generating goals customized for each employee. This makes it possible to set and evaluate customized goals that take emotional states into consideration.

[0944] "Company information" refers to information about an organization's basic data, business operations, and management strategies.

[0945] "Personnel data" refers to data including employee personal information, work history, evaluation records, salary information, etc.

[0946] "Goal setting data" refers to data that indicates the specific goals to be achieved by each employee or department and the associated evaluation criteria.

[0947] "Data preprocessing" is the process of converting collected raw data into an analyzable form by filling in missing values, removing outliers, normalizing, etc.

[0948] "Customized goals" are specific goals that are set specifically for each employee based on their job duties and abilities.

[0949] "Evaluation criteria" are data that show specific indicators and standards for evaluating an employee's level of goal achievement.

[0950] A "database" is an information system that efficiently stores and manages collected information and allows it to be quickly searched and retrieved as needed.

[0951] A "user interface" is a system that includes screens and input forms that allow users to interact with a system.

[0952] "Progress data" is data that indicates the current progress toward achieving a goal.

[0953] "Real-time processing" is a processing method in which processing is executed immediately when data is entered or updated, and the results are provided.

[0954] "Feedback" is information that provides employees with information about their progress toward their goals, an evaluation of their work, and specific advice on areas for improvement.

[0955] The "emotion engine" is a system that analyzes and determines the emotional state of employees from their input data (text, voice, facial recognition, etc.).

[0956] "Quantitative evaluation" is an evaluation method based on numerical and quantitative data.

[0957] "Qualitative evaluation" is an evaluation method that does not rely on numerical values, but is based on subjective information such as observation and feedback.

[0958] This system incorporates an emotion engine into a company's goal management system, providing feedback and evaluations that take into account the employee's emotional state, thereby improving employee satisfaction and motivation. The system consists of three main components: a server, a terminal, and a user.

[0959] Server Operation

[0960] The server collects company information, personnel data, and goal setting data through APIs and database connections. The collected data is preprocessed using Python and SQL. The preprocessed data is then analyzed using AI algorithms such as Scikit-learn and TensorFlow to generate customized goals for each employee. The generated goals and evaluation criteria are stored in a MySQL database.

[0961] In addition, the server is equipped with an emotion engine that integrates Google's Sentiment Analysis API. The emotion engine analyzes the text, voice, and facial recognition data entered by the user to recognize the user's emotional state. For example, it analyzes the user's input text, "I'm very tired today," and identifies negative emotions.

[0962] Device behavior

[0963] The terminal runs as a web application using React.js and provides users with an interface for entering goals and progress. Users (employees) can check their goals and enter their progress through the terminal. In addition, users can also enter their emotional state.

[0964] For example, when a sales employee logs in to their terminal, a target provided by the server (e.g., "Increase sales by 15%) is displayed. At the end of each month, they enter their emotional state (e.g., "Highly motivated" or "Feeling stressed") along with their sales progress. This data is sent to the server in real time.

[0965] User Actions

[0966] The user (employee or evaluator) uses the interface provided by the server and terminal to understand their goals and periodically enter their progress. The user self-evaluates, checks and accepts the emotional feedback provided by the server. Feedback based on the emotional state analyzed by the emotion engine is provided in real time.

[0967] For example, after a sales employee enters their monthly sales figures, they receive feedback based on their emotional state analyzed by the emotion engine. For example, they may receive specific advice such as, "Achievement rate is 66.7%. Improvement plan for the next quarter: Strengthen your approach to specific customer segments. Current emotional state: Highly motivated. We recommend taking a vacation to refresh yourself."

[0968] Prompt Sentence Examples

[0969] An example prompt for a generative AI model might look like this:

[0970] "Given the given goal, evaluate the employee's progress and generate feedback that takes into account their emotional state. Include improvement measures and recommended actions if the goal is 66.7% achieved."

[0971] This system can provide individual feedback to both the evaluator and the person being evaluated that takes into account their emotional state, significantly improving the sense of satisfaction and fairness of the evaluation. In addition, by incorporating the emotional data analyzed by the emotion engine as part of the evaluation process, the overall evaluation process proceeds more effectively and efficiently.

[0972] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0973] Step 1:

[0974] The server collects company data, specifically company information, HR data, and goal setting data through APIs and database connections. For example, it retrieves employee information from a HR database using an SQL query. The input to this operation is the API request or SQL query, and the output is the collected raw data.

[0975] Step 2:

[0976] The server preprocesses the collected data. Specifically, it performs tasks such as filling in missing values, removing outliers, and normalizing the collected data. The input is the collected raw data, and the output is the preprocessed data. For example, data cleaning is performed using the Python Pandas library.

[0977] Step 3:

[0978] The server analyzes the preprocessed data and generates customized goals. Specifically, it analyzes the data using machine learning algorithms such as Scikit-learn and TensorFlow to set goals for each employee. The input is the preprocessed data, and the output is individual goal setting data. For example, a random forest model is used to predict goals.

[0979] Step 4:

[0980] The server sets evaluation criteria based on the generated goals. Specifically, it calculates the evaluation criteria based on the generated goals and the company's evaluation policy. The input is individual goal setting data and the company's evaluation policy, and the output is evaluation criteria data. For example, it calculates evaluation criteria using goal achievement rates and key performance indicators (KPIs).

[0981] Step 5:

[0982] The server saves the goals and evaluation criteria in a database. Specifically, it saves the goal setting data and evaluation criteria data in a MySQL database. The input is the goal setting data and evaluation criteria data, and the output is the status of saving to the database. For example, data is inserted into the database using an SQL query.

[0983] Step 6:

[0984] The terminal provides employees with a user interface for entering goals and progress. Specifically, the goal setting screen and progress input screen are displayed through a web application using React.js. The input is the user's login information, and the output is the goal setting screen that is displayed. For example, after logging in, an employee can check their goals on the web screen.

[0985] Step 7:

[0986] The user inputs their progress and emotional state. Specifically, they periodically input their goal achievement status and their emotional state using the terminal interface. The input is the user's progress data and emotional state data, and the output is that this data is sent to the server. For example, they input "10% increase in sales" and "highly motivated."

[0987] Step 8:

[0988] The server receives and analyzes the input data and generates feedback. Specifically, it uses an AI algorithm to analyze progress data and emotional state data and generate individualized feedback. The input is the progress data and emotional state data sent by the user, and the output is feedback data. For example, it generates "achievement level 66.7%, improvement plan for the next quarter: strengthen approach to specific customer segments."

[0989] Step 9:

[0990] The user confirms and accepts the feedback. Specifically, the user confirms the feedback provided by the server through the terminal interface and reflects it in the next action plan. The input is the feedback data provided by the server, and the output is the user's next action plan. For example, a sales employee accepts the advice to "strengthen their approach to a specific customer base in the next quarter" and reflects it in their actual business plan.

[0991] (Application example 2)

[0992] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0993] Conventional goal management systems fail to take into account the emotional state of employees, resulting in problems such as a lack of employee satisfaction and motivation. Furthermore, uniform evaluations and feedback that ignore emotions are factors that reduce the fairness and effectiveness of evaluations. In particular, on-site work such as robot operators in factories involves significant physical and mental strain, and fluctuations in emotional state are directly linked to work efficiency and safety, so appropriate responses are required.

[0994] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting company information, personnel data, and goal setting data, means for analyzing the collected data and generating goals customized for each employee, means for setting evaluation criteria based on the generated goals, means for saving the goals and evaluation criteria in a database, means for employees to input their goals and progress through a user interface, means for processing progress data in real time and providing feedback, means for inputting or detecting the employee's emotional state, means for analyzing the emotional data and customizing the feedback based on the emotional state, and means for providing feedback to the employee and saving the emotional data in a database. This enables individual feedback that takes the employee's emotional state into consideration, improving employee satisfaction and motivation, and improving work efficiency and safety, particularly in factory floor work.

[0995] "Company information" refers to information about a company's basic data and organizational structure.

[0996] "Human resources data" refers to data including employee personal information, job titles, evaluation history, salary information, etc.

[0997] "Goal setting data" refers to data related to work goals and deliverables that a company sets for its employees.

[0998] A "collection means" is a method or device for acquiring and recording data.

[0999] An "analytical means" is a method or device for analyzing collected data and deriving a specific result.

[1000] "Customized goals" are specific work goals tailored to each employee.

[1001] "Evaluation criteria" are quantitative and qualitative indicators used to evaluate employee performance.

[1002] A "database storage means" is a method or device for storing data long-term and making it accessible at a later time.

[1003] A "user interface" is a screen display and input device that allows a user to interact with a system.

[1004] "Means for inputting progress" refers to a method or device that allows an employee to input the progress of their work into the system.

[1005] "Means for processing and providing feedback in real time" refers to a method or device for analyzing progress data in real time and providing the results as feedback.

[1006] "Means for inputting or detecting emotional state" refers to methods or devices for conveying an employee's emotions to the system, including voice input, text input, facial recognition, etc.

[1007] A "means for analyzing emotional data" is a method or apparatus for analyzing input or sensed emotional data to identify an employee's current emotional state.

[1008] A "means for customizing feedback" is a method or apparatus for generating personalized feedback based on evaluation criteria and emotional data.

[1009] A "means for providing feedback to employees" is a method or device for communicating system-generated feedback to employees.

[1010] The present invention aims to improve productivity and motivation by providing feedback and evaluation that takes into account employees' emotional states. The system consists of three main components: a server, a terminal, and a user.

[1011] Server Operation

[1012] The server has the following functions:

[1013] 1. Data collection: The server collects company information, personnel data, and goal setting data via APIs and database connections.

[1014] 2. Data analysis: The collected data is analyzed by AI algorithms to generate customized goals and evaluation criteria for each employee, which are then stored in a database.

[1015] 3. Emotion analysis: Using an emotion engine, the system analyzes the emotion data received from users (text, voice, facial recognition data, etc.) to recognize the emotional state of employees.

[1016] The server uses the following hardware and software: a high-performance server, an Emotion Engine, a Feedback Generator, and a database system.

[1017] Device behavior

[1018] The terminal has the following features:

[1019] 1. Interface provision: Provide an interface for employees to input goals and progress through a user interface.

[1020] 2. Progress input: Employees can periodically input their goal progress.

[1021] 3. Emotion input: Ability to input or detect employees' emotional state (voice, facial recognition, etc.).

[1022] Hardware and software used on your device: PC, smartphone, camera (for facial recognition), microphone (for voice analysis).

[1023] User Actions

[1024] Users, i.e. factory or office employees and managers, go through the following process:

[1025] 1. Data entry: Employees enter their progress and emotional state into a terminal.

[1026] 2. Feedback reception: Receive individually customized feedback based on the emotional data analyzed by the server.

[1027] 3. Evaluate and Improve: Use the feedback provided to improve your work.

[1028] Specific examples

[1029] For example, a factory robot operator might use the system to perform their daily tasks:

[1030] 1. Prompt to enter progress:

[1031] Please tell us your progress today:

[1032] Progress: Production line adjustment work is 80% complete.

[1033] 2. Emotional state prompt:

[1034] Please describe your emotional state today:

[1035] Emotional state: Feeling tired. Having difficulty concentrating.

[1036] 3. Feedback provided by the system:

[1037] feedback:

[1038] Progress is on schedule, but you are experiencing a decline in concentration. Please take a short break to refresh yourself and get back to work.

[1039] The system analyzes employees' work progress and emotional state in real time and provides individually customized feedback, thereby improving productivity and employee motivation across the company.

[1040] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1041] Step 1:

[1042] The server uses APIs and database connections to collect company information, personnel data, and goal setting data. The collected data is temporarily stored and organized in the database. Specifically, the collected data includes basic company data, personnel structure, employee history, and goal achievement status.

[1043] Input: Company information, personnel data, goal setting data

[1044] Output: Organized database entries

[1045] Step 2:

[1046] The server analyzes the collected data using an AI algorithm to generate customized goals for each employee. The generated goals are optimized based on the employee's current situation and output in the form of goals and evaluation criteria.

[1047] Input: Organized database entries

[1048] Output: Customized goals and metrics

[1049] Step 3:

[1050] The server stores the generated goals and evaluation criteria in a database, which can be later reviewed by employees.

[1051] Input: Customized goals and metrics

[1052] Output: Goals and metrics stored in a database

[1053] Step 4:

[1054] The terminal provides an interface for employees to input goals and progress through a user interface, and the data entered by the employees is transmitted to the server in real time.

[1055] Input: Goals and progress information entered by employees

[1056] Output: Progress data sent to the server

[1057] Step 5:

[1058] The server processes the progress data in real time and generates the analysis results as feedback, automatically generating optimal feedback based on the employee's progress and achievement level.

[1059] Input: Progress data

[1060] Output: Generated feedback

[1061] Step 6:

[1062] The server receives employee emotional state data (text, voice, facial recognition data, etc.) sent from the device and analyzes it using an emotion engine. The analysis results are output as data indicating the employee's emotional state.

[1063] Input: Emotional state data

[1064] Output: Parsed emotional state data

[1065] Step 7:

[1066] The server then personalizes the feedback based on the analyzed emotional state data, generating specific advice tailored to the employee's current emotional state.

[1067] Input: Parsed emotional state data

[1068] Output: Customized feedback

[1069] Step 8:

[1070] The server provides the generated feedback to the employee and stores the feedback along with the emotion data in a database.

[1071] Input:Customized Feedback

[1072] Output: Feedback provided to employees, feedback and sentiment data stored in a database

[1073] The above processing steps realize a system that provides real-time feedback that takes into account the emotions of employees, which improves employee satisfaction and motivation, and also increases work efficiency and safety in factory work.

[1074] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1075] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1076] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1077] [Fourth embodiment]

[1078] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1079] 7, a 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.

[1080] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1081] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1082] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1083] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1084] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1085] The control object 443 includes a display device, LEDs in the eyes, and motors for driving 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1086] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1087] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1088] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1089] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1090] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1091] This invention relates to a system and method for improving the efficiency of the target management system implemented by a company and for improving the sense of satisfaction and fairness among employees. This invention is realized through the cooperation of three components: a server, a terminal, and a user.

[1092] Server Operation

[1093] The server receives and analyzes company information, personnel data, and goal setting data provided by the company. First, the server acquires various data via APIs and database connections. The acquired data is analyzed and processed by AI algorithms to generate customized goal settings for each employee.

[1094] As a specific example, the server uses information from the sales department to analyze the past sales performance and achievement level of sales department employees, and sets the next period's sales target to increase by 15%. At the same time, the server also calculates evaluation criteria for the set target and stores them in the database. For example, it can rank employees according to their achievement level of the sales target, setting criteria such as high evaluation for achievement of 80% or more and low evaluation for achievement of less than 50%.

[1095] Device behavior

[1096] The terminal provides an interface for setting goals and inputting progress through a user interface. Users (employees) can check their own goals and periodically input their progress through the terminal.

[1097] For example, a sales manager logs in to a terminal and checks the target provided by the server (e.g., a 15% increase in sales). Next, at the end of each month, the manager enters the sales progress and sends it to the server. At this time, the terminal sends the entered data to the server in real time, allowing the manager to receive feedback.

[1098] User Actions

[1099] Users (employees and evaluators) use the interface provided by the server and terminal to understand their goals and periodically enter their progress. Users also perform self-evaluations and confirm and accept the feedback provided by the server.

[1100] For example, after a sales manager inputs monthly sales figures, he or she can receive feedback from the server, such as "Current achievement rate is 60%. Improvement plan for the next quarter: Strengthen approach to specific customer segments." This feedback is provided in real time, making it possible to take prompt improvement measures.

[1101] Overall system operation

[1102] This system streamlines company-wide goal management, improves employee motivation, and reduces the burden on evaluators. In addition, by integrating qualitative and quantitative evaluations, the evaluation process becomes more transparent and fair, leading to overall performance improvements.

[1103] The present invention provides an intuitive and easy-to-use interface for both employees and raters, and significantly improves the quality and efficiency of appraisals through real-time feedback and advice.

[1104] The processing flow will be explained below.

[1105] Step 1:

[1106] The server collects company information, personnel data, and goal setting data provided by the company. This data is obtained via API and database connection.

[1107] Step 2:

[1108] The server preprocesses the collected data, maintaining its integrity and converting it into a format suitable for analysis.

[1109] Step 3:

[1110] The server uses AI algorithms to analyze the data and generate customized goals for each employee.

[1111] Step 4:

[1112] The server sets evaluation criteria based on the generated goals, and the specific evaluation criteria include quantitative and qualitative elements.

[1113] Step 5:

[1114] The server stores the goals and evaluation criteria in a database, which allows for consistent management of the data.

[1115] Step 6:

[1116] The terminal provides the user with a login interface, prompting them to enter their username and password, and then sends the authentication information to the server.

[1117] Step 7:

[1118] The terminal displays the goal settings and evaluation criteria obtained from the server to the user, allowing the user to confirm their own goals.

[1119] Step 8:

[1120] The user periodically inputs progress information via the terminal, and the input data is sent to the server in real time.

[1121] Step 9:

[1122] The server analyzes the received progress data and generates real-time feedback, which is then sent to the device.

[1123] Step 10:

[1124] The device displays feedback to the user, allowing them to receive advice based on their progress.

[1125] Step 11:

[1126] The user inputs their self-evaluation and sends it to the server via their terminal, where the input data is saved.

[1127] Step 12:

[1128] The server generates the final assessment, which is provided to both the user and the assessor.

[1129] Step 13:

[1130] The device displays the final evaluation results to the user, and suggests areas for improvement and future goals based on the evaluation.

[1131] Step 14:

[1132] The user checks the final evaluation results and considers improvement measures for the next period, completing the entire evaluation process.

[1133] The above steps realize a system that integrates goal setting, progress management, and evaluation.

[1134] Example 1

[1135] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1136] With conventional goal management systems, employees often lack a sense of satisfaction or fairness regarding the goals set within the company, making efficient goal management difficult. Furthermore, because evaluation criteria are not clear, evaluations can lack transparency and fairness. Furthermore, progress cannot be entered and feedback cannot be provided in real time, which can delay rapid responses and the implementation of improvement measures.

[1137] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1138] In this invention, the server includes means for collecting company information, personnel information, and goal data, means for analyzing the collected data using an AI algorithm and generating goals customized for each employee, means for setting evaluation criteria based on the generated goals, means for saving the goals and evaluation criteria in a data storage device, means for employees to input their goals and progress through a user interface, and means for processing progress data in real time and providing feedback. This enables efficient and transparent goal management within a company, increases employees' sense of satisfaction and fairness, and enables prompt feedback and the implementation of improvement measures.

[1139] "Company information" refers to data about a company's basic information and organizational structure.

[1140] "Human resources information" refers to data about employees' individual attributes, job duties, and past performance.

[1141] "Goal Data" refers to data relating to goals to be achieved set for a company or individual employees.

[1142] "AI algorithm" refers to a computational method that uses artificial intelligence technology to analyze data and generate specific patterns or predictions.

[1143] "Customized goals" refer to individual goals set based on each employee's characteristics and past performance.

[1144] "Evaluation criteria" refers to the indicators and standards used to evaluate an employee's level of goal achievement.

[1145] "Data storage device" refers to a system or database for storing data.

[1146] "User interface" refers to the screen or interface through which a user interacts with a system.

[1147] "Progress Data" refers to data relating to the current achievement or progress towards a goal.

[1148] "Real-time processing" refers to the immediate collection and analysis of progress data.

[1149] "Feedback" refers to notification and advice regarding evaluation results and improvement measures based on progress.

[1150] This invention relates to a system and method for improving the efficiency of the target management system adopted by companies and enhancing employees' sense of satisfaction and fairness. This system is realized through the cooperation of three components: a server, a terminal, and a user.

[1151] Server Operation

[1152] The server receives company information, personnel information, and goal data provided by the company and analyzes this data. First, the server obtains various data via APIs and database connections. Specifically, the server uses the following hardware and software:

[1153] Database: MySQL, PostgreSQL

[1154] AI algorithms: Python, TensorFlow, Scikit-learn

[1155] API frameworks: Flask, Django

[1156] The acquired data is analyzed and processed by an AI algorithm to generate customized goals for each employee. For example, the server uses information from the sales department to analyze the sales department's past sales performance and achievement level, and sets the next period's sales target to increase by 15%. At the same time, the server also calculates evaluation criteria for the set target and stores them in the database. For example, it can rank employees according to their level of achievement of the sales target, setting criteria such as a high evaluation for achievement of 80% or more and a low evaluation for achievement of less than 50%.

[1157] Device behavior

[1158] The terminal provides an interface for goal setting and progress input through a user interface. Users (employees) check their goals and periodically input their progress through the terminal. Specifically, the terminal uses the following hardware and software:

[1159] Frontend: React, Vue.js

[1160] Backend: Node.js (Express)

[1161] For example, a sales manager logs in to a terminal and checks the target provided by the server (e.g., a 15% increase in sales). Then, at the end of each month, the manager enters the sales progress and sends it to the server. At this time, the terminal sends the entered data to the server in real time, allowing the manager to receive feedback.

[1162] User Actions

[1163] Users (employees and evaluators) use the interface provided by the server and terminal to understand their own goals and periodically enter their progress. Users also perform self-evaluations and confirm and accept the feedback provided by the server. For example, after a sales manager enters monthly sales figures, the server can provide feedback with specific advice, such as "Current achievement rate is 60%. Improvement plan for the next quarter: Strengthen approach to specific customer segments." This feedback is provided in real time, enabling prompt improvement measures to be implemented.

[1164] Examples of specific examples and prompts

[1165] After logging in to their device, the sales manager checks the next quarter's sales target (e.g., a 15% increase) provided by the server. At the end of each month, the manager enters the monthly sales and presses the "Send" button on the device to send the data to the server. The server receives this data, analyzes it in real time, and calculates the achievement rate. The calculation results are displayed as, for example, "Current achievement rate is 60%." Furthermore, the server uses an AI model to generate feedback such as "Improvement measures for the next quarter: Strengthen approach to specific customer segments," and immediately sends this to the device. The manager can receive this feedback and make an action plan for the next quarter.

[1166] Prompt Sentence Examples

[1167] By inputting the following prompt sentence into the generative AI model, the processing of the above program can be explained in natural language.

[1168] Please explain how a corporate goal management system works. The system consists of three components: a server, a terminal, and a user. The server analyzes data and sets customized goals, while the terminal displays goal settings and provides progress input. The user checks goals and inputs progress. Please explain how the entire system works using specific examples.

[1169] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1170] Step 1:

[1171] Data collection

[1172] The server obtains company information, personnel information, and goal data provided by the company. Specifically, the server collects this data using APIs and database connections. The input is data obtained from the company's personnel system and goal management system. For example, the server periodically sends an HTTP request to an API endpoint and receives JSON-formatted data as a response. The received data is then stored in a database.

[1173] Step 2:

[1174] Data analysis and goal setting

[1175] The server analyzes the collected data using an AI algorithm. The input here is the data collected in step 1. Specifically, it uses Python's TensorFlow library to analyze past performance data and set customized goals for each employee. For example, for employees in the sales department, it sets a sales goal for the next fiscal year to increase by 15% based on past sales data. The analysis results are stored in a database.

[1176] Step 3:

[1177] Setting evaluation criteria

[1178] The server sets evaluation criteria based on the generated goals. The input for this step is the customized goals generated in step 2. Specifically, it ranks the sales goals according to their achievement level. For example, it sets criteria such as high evaluation for achievement of 80% or more and low evaluation for achievement of less than 50%, and saves this in the database.

[1179] Step 4:

[1180] Providing a goal presentation and progress input interface

[1181] The terminal presents goals to employees through a user interface and provides an interface for them to input their progress. The input is goal setting information sent from the server. For example, a dashboard built using React displays each employee's goal (e.g., 15% increase in sales). The user inputs their progress here, and the data is sent to the server in real time.

[1182] Step 5:

[1183] Progress data collection and analysis

[1184] The server receives the progress data sent from the terminal and analyzes it in real time. The input is the progress data entered by the user in step 4. Specifically, the server receives the progress data (e.g., monthly sales) via the Node.js backend API and analyzes it using a Python script. The output is the calculated achievement level for each employee (e.g., current achievement level is 60%).

[1185] Step 6:

[1186] Generating and Providing Feedback

[1187] The server generates feedback based on the results of analyzing the progress data and sends it to the device. The input is the calculation result of the achievement level obtained in step 5. Specifically, an AI model is used to generate optimal feedback based on the evaluation results of each employee. This feedback might be something like, "Improvement plan for the next quarter: Strengthen approach to specific customer segments." The generated feedback is sent to the device in real time and can be viewed by the user.

[1188] This series of processes will improve the efficiency of goal management across the entire company, improve employee motivation, and reduce the burden on evaluators.

[1189] (Application example 1)

[1190] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1191] Conventional goal management systems make it difficult to set employee goals and monitor progress, and they tend to be out of sync with actual work, especially in factories and other workplaces. Real-time feedback is also difficult, making it difficult to implement rapid improvement measures to achieve goals. This leads to a lack of transparency and fairness in evaluations, which can lead to lower motivation and increased burdens on evaluators.

[1192] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1193] In this invention, the server includes a means for collecting company information, personnel data, and goal setting data, a means for analyzing the collected data and generating customized goals for each employee, and a means for setting evaluation criteria based on the generated goals. This allows employees to view their goals and feedback through smart glasses, collect progress data during actual work, and receive feedback in real time. This improves the efficiency of goal management and improves employees' sense of satisfaction and fairness.

[1194] "Company Information" means information including organizational structure, performance, department information, and other company-related data.

[1195] "Human Resources Data" means data related to employee names, job titles, evaluation history, skill sets, and working hours.

[1196] "Goal setting data" refers to data regarding the specific performance and production goals that each employee or department must achieve.

[1197] "Collection means" refers to the software or hardware components that collect the required data through a database or API.

[1198] "Means of analysis" refers to AI algorithms and machine learning models that analyze the collected data and extract relevant information.

[1199] "Customized goals" are individual goals set for each employee based on their skills, past performance, and current situation.

[1200] "Evaluation criteria" are standards for evaluating the degree of achievement of set goals, and include specific evaluation indicators and ranking methods.

[1201] "Means for storing data in a database" means a database management system for securely storing collected data and generated goals and evaluation criteria.

[1202] "User interface" refers to the software screens or applications that allow employees to enter and review goals and progress.

[1203] "Progress data" is specific data that shows how an employee is progressing toward their goals.

[1204] "Real-time processing means" means a high-speed computing mechanism that instantly analyzes received data and provides feedback.

[1205] "Means for providing feedback" is a function for providing advice and suggestions for improvement to employees based on progress data.

[1206] "Smart glasses" are devices that provide visual information to the wearer and assist them in real-world tasks.

[1207] "Means for displaying goals and feedback" means software functionality for displaying set goals and real-time feedback through the display of the smart glasses.

[1208] "Means for collecting progress data" refers to an input function for collecting specific work progress from employees through the smart glasses.

[1209] This invention aims to improve the efficiency of goal management in factories, and describes a system in which employees use smart glasses to set goals, manage progress, and receive real-time feedback.

[1210] Server Operation

[1211] The server first collects company information, personnel data, and goal setting data provided by the company. This data, obtained through existing database management systems or APIs, is then analyzed using AI algorithms. For example, it takes into account an employee's past production performance and skill set to customize goals appropriate for each employee. The generated goals are then stored in a database along with evaluation criteria.

[1212] Smart glasses terminal operation

[1213] A dedicated application is installed on the smart glasses used as terminals. This application allows employees to visually check their goals and progress through a user interface. Employees can check their goals in real time and enter their progress directly through the smart glasses while working. This allows progress data to be sent to a server in real time, and feedback is provided immediately as an analysis result.

[1214] User Actions

[1215] By wearing the smart glasses, employees can check their set goals and progress in real time while they work. They can also input progress data and receive prompt feedback from the server, enabling employees to take prompt action to improve their work.

[1216] System operation example

[1217] For example, when a factory worker puts on the smart glasses, the production target for the current month is displayed. The worker inputs their progress as they work, and the server analyzes this in real time and provides feedback. This feedback suggests specific improvement measures, such as "Please reevaluate next week's production plan."

[1218] Prompt Sentence Examples

[1219] Examples of specific prompts that smart glasses applications might provide to users include:

[1220] "How close are you to achieving your goal this month? Please give me some specific numbers."

[1221] "What should we improve next?"

[1222] "Please enter your progress data."

[1223] This will improve the efficiency and transparency of goal management. In particular, by allowing employees to receive feedback in real time, it is possible to take prompt corrective measures, which is expected to improve overall production efficiency and fairness in evaluations.

[1224] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1225] Step 1:

[1226] The server collects company information, HR data, and goal setting data provided by the company. This data is obtained via APIs and database connections. The input is data from each department and HR department of the company, and the output is in the form of the original data stored on the server.

[1227] Step 2:

[1228] The server analyzes the collected data using an AI algorithm. Specifically, it inputs each employee's past production performance and skill set into an analytical model, from which individual goals are generated. The input is each employee's past data, and the output is customized goal data.

[1229] Step 3:

[1230] The server sets evaluation criteria based on the created goals. For example, it sets specific evaluation indicators and ranking methods to show the degree of goal achievement. The input is customized goal data, and the output is evaluation criteria data for that goal.

[1231] Step 4:

[1232] The server stores the generated goals and evaluation criteria in a database. The input is the customized goal and evaluation criteria data, and the output is the data recorded in the database.

[1233] Step 5:

[1234] The terminal (smart glasses) displays the goals to the employee through a user interface. The employee can visually confirm the goals through the smart glasses while working. The input is the goal data received from the server, and the output is the goal information displayed on the display of the smart glasses.

[1235] Step 6:

[1236] The user (employee) inputs progress data into the terminal via smart glasses while working. This progress data can be entered via a keyboard or voice recognition function. The input is the employee's progress data, and the output is the progress data recorded on the terminal.

[1237] Step 7:

[1238] The terminal transmits the collected progress data to the server in real time. The input is the progress data recorded on the terminal, and the output is the progress data transmitted to the server.

[1239] Step 8:

[1240] The server analyzes the received progress data and generates feedback using a generative AI model. The input is the progress data sent from the terminal, and the output is the feedback data provided to the employee.

[1241] Step 9:

[1242] The terminal displays the feedback from the server on the smart glasses, allowing employees to quickly take corrective measures. The input is the feedback data received from the server, and the output is the feedback information displayed on the smart glasses display.

[1243] Step 10:

[1244] After receiving the feedback, the employee re-enters the progress data as needed and continues to communicate with the server. The input is the newly entered progress data, and the output is the updated progress data in the server.

[1245] These steps will ensure that the goal management system is operating effectively, improving the company's production efficiency and employee motivation.

[1246] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1247] This invention relates to a system that incorporates an emotion engine into a company's goal management system, providing feedback and evaluation that takes into account the employee's emotional state, thereby improving employee satisfaction and motivation. This system consists of three main components: a server, a terminal, and a user.

[1248] Server Operation

[1249] The server receives company information, personnel data, and goal setting data provided by the company. This data is collected and pre-processed via APIs and database connections. It then analyzes this data using AI algorithms to generate customized goals for each employee. Evaluation criteria are also calculated based on the generated goals and stored in the database.

[1250] Furthermore, the server is equipped with an emotion engine that receives the user's emotion data. The emotion engine analyzes the text, voice, and facial recognition data entered by the user to recognize the user's emotional state. For example, it can determine positive or negative emotions from the text entered by the user.

[1251] Device behavior

[1252] The terminal provides an interface for goal setting and progress input through a user interface. The user (employee) checks his / her goals through the terminal and periodically inputs his / her progress. In addition, the user also inputs information that represents his / her emotional state.

[1253] As a concrete example, a sales manager logs in to a terminal and checks the target provided by the server (e.g., a 15% increase in sales). Then, at the end of each month, he or she enters the sales progress along with his or her emotional state (e.g., "highly motivated" or "stressed"). This data is sent to the server in real time.

[1254] User Actions

[1255] Users (employees and evaluators) use the interface provided by the server and terminal to understand their goals and periodically enter their progress. The user self-evaluates and confirms and accepts the emotional feedback provided by the server. The emotion engine analyzes the user's emotional state and provides feedback based on the results in real time.

[1256] For example, after entering monthly sales figures, a sales manager receives feedback based on their emotional state analyzed by the emotion engine. For example, they may receive specific advice such as, "Achievement rate is 60%. Improvement plan for the next quarter: Strengthen approach to specific customer segments. Current emotional state: Feeling stressed. We recommend taking a vacation to refresh yourself."

[1257] Overall system operation

[1258] This system can provide individual feedback to both the evaluator and the person being evaluated that takes into account their emotional state, significantly improving the sense of satisfaction and fairness of the evaluation. In addition, by incorporating the emotional data analyzed by the emotion engine as part of the evaluation process, the overall evaluation process proceeds more effectively and efficiently.

[1259] The present invention provides an intuitive and easy-to-use interface for both employees and evaluators, and significantly improves the quality and efficiency of evaluations through real-time feedback and advice. Furthermore, the incorporation of an emotion engine enables flexible responses based on the employee's emotional state, improving overall performance and employee satisfaction.

[1260] The processing flow will be explained below.

[1261] Step 1:

[1262] The server collects company information, personnel data, and goal setting data provided by the company, and obtains this data via API and database connection.

[1263] Step 2:

[1264] The server pre-processes the acquired data, which includes checking, normalizing, and converting the data into a format suitable for analysis.

[1265] Step 3:

[1266] The server then uses AI algorithms to analyze the pre-processed data and generate customized goals for each employee.

[1267] Step 4:

[1268] The server sets evaluation criteria based on the generated goals and calculates evaluation criteria that include quantitative and qualitative elements.

[1269] Step 5:

[1270] The server stores the goals and evaluation criteria in a database, which allows for consistent management of the data.

[1271] Step 6:

[1272] The terminal provides the user with a login interface, prompting them to enter their username and password, and then sends the authentication information to the server.

[1273] Step 7:

[1274] The terminal displays the goal settings and evaluation criteria obtained from the server to the user, allowing the user to check their own goals.

[1275] Step 8:

[1276] The terminal provides the user with options for inputting emotional information through a user interface, which can be input in the form of text, voice, facial recognition data, etc.

[1277] Step 9:

[1278] Users periodically input their progress and emotional information, which is then sent to the server in real time.

[1279] Step 10:

[1280] The server analyzes the progress data and emotional data, and the emotional engine recognizes the user's emotional state and generates personalized feedback based on the emotional data.

[1281] Step 11:

[1282] The server generates the analyzed progress data and emotional feedback, and transmits the feedback to the device in real time.

[1283] Step 12:

[1284] The device displays feedback to the user, including specific advice based on progress and emotional state.

[1285] Step 13:

[1286] The user checks the feedback and performs a self-evaluation, and the self-evaluation data is sent to the server via the terminal.

[1287] Step 14:

[1288] The server generates the final assessment, which is provided to both the user and the assessor.

[1289] Step 15:

[1290] The terminal displays the final evaluation results to the user, and next goals and areas for improvement are presented based on the evaluation results.

[1291] The above steps realize a system that integrates goal setting, progress management, and collection and evaluation of emotional information.

[1292] Example 2

[1293] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1294] Conventional goal management systems have difficulty reflecting employees' emotional state in the feedback and evaluation process, which has led to issues such as insufficient improvement of employee satisfaction and motivation. In addition, there was a need for an integrated approach that not only handles quantitative evaluations but also emotional state and progress data.

[1295] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for collecting company information, personnel data, and goal setting data, a means for preprocessing the collected data, and a means for analyzing the preprocessed data and generating goals customized for each employee. This makes it possible to set and evaluate customized goals that take emotional states into consideration.

[1296] "Company information" refers to information about an organization's basic data, business operations, and management strategies.

[1297] "Personnel data" refers to data including employee personal information, work history, evaluation records, salary information, etc.

[1298] "Goal setting data" refers to data that indicates the specific goals to be achieved by each employee or department and the associated evaluation criteria.

[1299] "Data preprocessing" is the process of converting collected raw data into an analyzable form by filling in missing values, removing outliers, normalizing, etc.

[1300] "Customized goals" are specific goals that are set specifically for each employee based on their job duties and abilities.

[1301] "Evaluation criteria" are data that show specific indicators and standards for evaluating an employee's level of goal achievement.

[1302] A "database" is an information system that efficiently stores and manages collected information and allows it to be quickly searched and retrieved as needed.

[1303] A "user interface" is a system that includes screens and input forms that allow users to interact with a system.

[1304] "Progress data" is data that indicates the current progress toward achieving a goal.

[1305] "Real-time processing" is a processing method in which processing is executed immediately when data is entered or updated, and the results are provided.

[1306] "Feedback" is information that provides employees with information about their progress toward their goals, an evaluation of their work, and specific advice on areas for improvement.

[1307] The "emotion engine" is a system that analyzes and determines the emotional state of employees from their input data (text, voice, facial recognition, etc.).

[1308] "Quantitative evaluation" is an evaluation method based on numerical and quantitative data.

[1309] "Qualitative evaluation" is an evaluation method that does not rely on numerical values, but is based on subjective information such as observation and feedback.

[1310] This system incorporates an emotion engine into a company's goal management system, providing feedback and evaluations that take into account the employee's emotional state, thereby improving employee satisfaction and motivation. The system consists of three main components: a server, a terminal, and a user.

[1311] Server Operation

[1312] The server collects company information, personnel data, and goal setting data through APIs and database connections. The collected data is preprocessed using Python and SQL. The preprocessed data is then analyzed using AI algorithms such as Scikit-learn and TensorFlow to generate customized goals for each employee. The generated goals and evaluation criteria are stored in a MySQL database.

[1313] In addition, the server is equipped with an emotion engine that integrates Google's Sentiment Analysis API. The emotion engine analyzes the text, voice, and facial recognition data entered by the user to recognize the user's emotional state. For example, it analyzes the user's input text, "I'm very tired today," and identifies negative emotions.

[1314] Device behavior

[1315] The terminal runs as a web application using React.js and provides users with an interface for entering goals and progress. Users (employees) can check their goals and enter their progress through the terminal. In addition, users can also enter their emotional state.

[1316] For example, when a sales employee logs in to their terminal, a target provided by the server (e.g., "Increase sales by 15%) is displayed. At the end of each month, they enter their emotional state (e.g., "Highly motivated" or "Feeling stressed") along with their sales progress. This data is sent to the server in real time.

[1317] User Actions

[1318] The user (employee or evaluator) uses the interface provided by the server and terminal to understand their goals and periodically enter their progress. The user self-evaluates, checks and accepts the emotional feedback provided by the server. Feedback based on the emotional state analyzed by the emotion engine is provided in real time.

[1319] For example, after a sales employee enters their monthly sales figures, they receive feedback based on their emotional state analyzed by the emotion engine. For example, they may receive specific advice such as, "Achievement rate is 66.7%. Improvement plan for the next quarter: Strengthen your approach to specific customer segments. Current emotional state: Highly motivated. We recommend taking a vacation to refresh yourself."

[1320] Prompt Sentence Examples

[1321] An example prompt for a generative AI model might look like this:

[1322] "Given the given goal, evaluate the employee's progress and generate feedback that takes into account their emotional state. Include improvement measures and recommended actions if the goal is 66.7% achieved."

[1323] This system can provide individual feedback to both the evaluator and the person being evaluated that takes into account their emotional state, significantly improving the sense of satisfaction and fairness of the evaluation. In addition, by incorporating the emotional data analyzed by the emotion engine as part of the evaluation process, the overall evaluation process proceeds more effectively and efficiently.

[1324] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1325] Step 1:

[1326] The server collects company data, specifically company information, HR data, and goal setting data through APIs and database connections. For example, it retrieves employee information from a HR database using an SQL query. The input to this operation is the API request or SQL query, and the output is the collected raw data.

[1327] Step 2:

[1328] The server preprocesses the collected data. Specifically, it performs tasks such as filling in missing values, removing outliers, and normalizing the collected data. The input is the collected raw data, and the output is the preprocessed data. For example, data cleaning is performed using the Python Pandas library.

[1329] Step 3:

[1330] The server analyzes the preprocessed data and generates customized goals. Specifically, it analyzes the data using machine learning algorithms such as Scikit-learn and TensorFlow to set goals for each employee. The input is the preprocessed data, and the output is individual goal setting data. For example, a random forest model is used to predict goals.

[1331] Step 4:

[1332] The server sets evaluation criteria based on the generated goals. Specifically, it calculates the evaluation criteria based on the generated goals and the company's evaluation policy. The input is individual goal setting data and the company's evaluation policy, and the output is evaluation criteria data. For example, it calculates evaluation criteria using goal achievement rates and key performance indicators (KPIs).

[1333] Step 5:

[1334] The server saves the goals and evaluation criteria in a database. Specifically, it saves the goal setting data and evaluation criteria data in a MySQL database. The input is the goal setting data and evaluation criteria data, and the output is the status of saving to the database. For example, data is inserted into the database using an SQL query.

[1335] Step 6:

[1336] The terminal provides employees with a user interface for entering goals and progress. Specifically, the goal setting screen and progress input screen are displayed through a web application using React.js. The input is the user's login information, and the output is the goal setting screen that is displayed. For example, after logging in, an employee can check their goals on the web screen.

[1337] Step 7:

[1338] The user inputs their progress and emotional state. Specifically, they periodically input their goal achievement status and their emotional state using the terminal interface. The input is the user's progress data and emotional state data, and the output is that this data is sent to the server. For example, they input "10% increase in sales" and "highly motivated."

[1339] Step 8:

[1340] The server receives and analyzes the input data and generates feedback. Specifically, it uses an AI algorithm to analyze progress data and emotional state data and generate individualized feedback. The input is the progress data and emotional state data sent by the user, and the output is feedback data. For example, it generates "achievement level 66.7%, improvement plan for the next quarter: strengthen approach to specific customer segments."

[1341] Step 9:

[1342] The user confirms and accepts the feedback. Specifically, the user confirms the feedback provided by the server through the terminal interface and reflects it in the next action plan. The input is the feedback data provided by the server, and the output is the user's next action plan. For example, a sales employee accepts the advice to "strengthen their approach to a specific customer base in the next quarter" and reflects it in their actual business plan.

[1343] (Application example 2)

[1344] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1345] Conventional goal management systems fail to take into account the emotional state of employees, resulting in problems such as a lack of employee satisfaction and motivation. Furthermore, uniform evaluations and feedback that ignore emotions are factors that reduce the fairness and effectiveness of evaluations. In particular, on-site work such as robot operators in factories involves significant physical and mental strain, and fluctuations in emotional state are directly linked to work efficiency and safety, so appropriate responses are required.

[1346] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting company information, personnel data, and goal setting data, means for analyzing the collected data and generating goals customized for each employee, means for setting evaluation criteria based on the generated goals, means for saving the goals and evaluation criteria in a database, means for employees to input their goals and progress through a user interface, means for processing progress data in real time and providing feedback, means for inputting or detecting the employee's emotional state, means for analyzing the emotional data and customizing the feedback based on the emotional state, and means for providing feedback to the employee and saving the emotional data in a database. This enables individual feedback that takes the employee's emotional state into consideration, improving employee satisfaction and motivation, and improving work efficiency and safety, particularly in factory floor work.

[1347] "Company information" refers to information about a company's basic data and organizational structure.

[1348] "Human resources data" refers to data including employee personal information, job titles, evaluation history, salary information, etc.

[1349] "Goal setting data" refers to data related to work goals and deliverables that a company sets for its employees.

[1350] A "collection means" is a method or device for acquiring and recording data.

[1351] An "analytical means" is a method or device for analyzing collected data and deriving a specific result.

[1352] "Customized goals" are specific work goals tailored to each employee.

[1353] "Evaluation criteria" are quantitative and qualitative indicators used to evaluate employee performance.

[1354] A "database storage means" is a method or device for storing data long-term and making it accessible at a later time.

[1355] A "user interface" is a screen display and input device that allows a user to interact with a system.

[1356] "Means for inputting progress" refers to a method or device that allows an employee to input the progress of their work into the system.

[1357] "Means for processing and providing feedback in real time" refers to a method or device for analyzing progress data in real time and providing the results as feedback.

[1358] "Means for inputting or detecting emotional state" refers to methods or devices for conveying an employee's emotions to the system, including voice input, text input, facial recognition, etc.

[1359] A "means for analyzing emotional data" is a method or apparatus for analyzing input or sensed emotional data to identify an employee's current emotional state.

[1360] A "means for customizing feedback" is a method or apparatus for generating personalized feedback based on evaluation criteria and emotional data.

[1361] A "means for providing feedback to employees" is a method or device for communicating system-generated feedback to employees.

[1362] The present invention aims to improve productivity and motivation by providing feedback and evaluation that takes into account employees' emotional states. The system consists of three main components: a server, a terminal, and a user.

[1363] Server Operation

[1364] The server has the following functions:

[1365] 1. Data collection: The server collects company information, personnel data, and goal setting data via APIs and database connections.

[1366] 2. Data analysis: The collected data is analyzed by AI algorithms to generate customized goals and evaluation criteria for each employee, which are then stored in a database.

[1367] 3. Emotion analysis: Using an emotion engine, the system analyzes the emotion data received from users (text, voice, facial recognition data, etc.) to recognize the emotional state of employees.

[1368] The server uses the following hardware and software: a high-performance server, an Emotion Engine, a Feedback Generator, and a database system.

[1369] Device behavior

[1370] The terminal has the following features:

[1371] 1. Interface provision: Provide an interface for employees to input goals and progress through a user interface.

[1372] 2. Progress input: Employees can periodically input their goal progress.

[1373] 3. Emotion input: Ability to input or detect employees' emotional state (voice, facial recognition, etc.).

[1374] Hardware and software used on your device: PC, smartphone, camera (for facial recognition), microphone (for voice analysis).

[1375] User Actions

[1376] Users, i.e. factory or office employees and managers, go through the following process:

[1377] 1. Data entry: Employees enter their progress and emotional state into a terminal.

[1378] 2. Feedback reception: Receive individually customized feedback based on the emotional data analyzed by the server.

[1379] 3. Evaluate and Improve: Use the feedback provided to improve your work.

[1380] Specific examples

[1381] For example, a factory robot operator might use the system to perform their daily tasks:

[1382] 1. Prompt to enter progress:

[1383] Please tell us your progress today:

[1384] Progress: Production line adjustment work is 80% complete.

[1385] 2. Emotional state prompt:

[1386] Please describe your emotional state today:

[1387] Emotional state: Feeling tired. Having difficulty concentrating.

[1388] 3. Feedback provided by the system:

[1389] feedback:

[1390] Progress is on schedule, but you are experiencing a decline in concentration. Please take a short break to refresh yourself and get back to work.

[1391] The system analyzes employees' work progress and emotional state in real time and provides individually customized feedback, thereby improving productivity and employee motivation across the company.

[1392] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1393] Step 1:

[1394] The server uses APIs and database connections to collect company information, personnel data, and goal setting data. The collected data is temporarily stored and organized in the database. Specifically, the collected data includes basic company data, personnel structure, employee history, and goal achievement status.

[1395] Input: Company information, personnel data, goal setting data

[1396] Output: Organized database entries

[1397] Step 2:

[1398] The server analyzes the collected data using an AI algorithm to generate customized goals for each employee. The generated goals are optimized based on the employee's current situation and output in the form of goals and evaluation criteria.

[1399] Input: Organized database entries

[1400] Output: Customized goals and metrics

[1401] Step 3:

[1402] The server stores the generated goals and evaluation criteria in a database, which can be later reviewed by employees.

[1403] Input: Customized goals and metrics

[1404] Output: Goals and metrics stored in a database

[1405] Step 4:

[1406] The terminal provides an interface for employees to input goals and progress through a user interface, and the data entered by the employees is transmitted to the server in real time.

[1407] Input: Goals and progress information entered by employees

[1408] Output: Progress data sent to the server

[1409] Step 5:

[1410] The server processes the progress data in real time and generates the analysis results as feedback, automatically generating optimal feedback based on the employee's progress and achievement level.

[1411] Input: Progress data

[1412] Output: Generated feedback

[1413] Step 6:

[1414] The server receives employee emotional state data (text, voice, facial recognition data, etc.) sent from the device and analyzes it using an emotion engine. The analysis results are output as data indicating the employee's emotional state.

[1415] Input: Emotional state data

[1416] Output: Parsed emotional state data

[1417] Step 7:

[1418] The server then personalizes the feedback based on the analyzed emotional state data, generating specific advice tailored to the employee's current emotional state.

[1419] Input: Parsed emotional state data

[1420] Output: Customized feedback

[1421] Step 8:

[1422] The server provides the generated feedback to the employee and stores the feedback along with the emotion data in a database.

[1423] Input:Customized Feedback

[1424] Output: Feedback provided to employees, feedback and sentiment data stored in a database

[1425] The above processing steps realize a system that provides real-time feedback that takes into account the emotions of employees, which improves employee satisfaction and motivation, and also increases work efficiency and safety in factory work.

[1426] 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 control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1427] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1428] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1429] The emotion identification model 59 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 an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1430] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1431] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1432] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1433] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1434] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs 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 a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1435] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1436] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1437] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1438] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1439] 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.

[1440] It is not necessary to store all 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 all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1441] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1442] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with 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). Also, the hardware resource that executes the specific processing may be a single processor.

[1443] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1444] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1445] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1446] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1447] The following is further disclosed regarding the above embodiment.

[1448] (Claim 1)

[1449] A means of collecting company information, personnel data, and goal setting data;

[1450] A means of analyzing the collected data and generating customized goals for each employee;

[1451] A means for setting evaluation criteria based on the generated goals;

[1452] a means for storing the goals and evaluation criteria in a database;

[1453] a means for employees to input goals and progress through a user interface;

[1454] a means of processing progress data in real time and providing feedback;

[1455] A system including:

[1456] (Claim 2)

[1457] 10. The system of claim 1, further comprising means for integrating quantitative and qualitative evaluations to set evaluation criteria.

[1458] (Claim 3)

[1459] 10. The system of claim 1, further comprising means for periodically collecting and providing progress and feedback data to both the rater and the ratee.

[1460] "Example 1"

[1461] (Claim 1)

[1462] A means of collecting company information, personnel information, and goal data;

[1463] A means of analyzing collected data using AI algorithms to generate customized goals for each employee;

[1464] A means for setting evaluation criteria based on the generated goals;

[1465] means for storing the goals and evaluation criteria in a data store;

[1466] a means for employees to input goals and progress through a user interface;

[1467] a means of processing progress data in real time and providing feedback;

[1468] A system including:

[1469] (Claim 2)

[1470] 10. The system of claim 1, further comprising means for integrating quantitative and qualitative evaluations to set evaluation criteria.

[1471] (Claim 3)

[1472] 10. The system of claim 1, further comprising means for periodically collecting and providing progress and feedback data to both the rater and the ratee.

[1473] "Application Example 1"

[1474] (Claim 1)

[1475] A means of collecting company information, personnel data, and goal setting data;

[1476] A means of analyzing the collected data and generating customized goals for each employee;

[1477] A means for setting evaluation criteria based on the generated goals;

[1478] a means for storing the goals and evaluation criteria in a database;

[1479] a means for employees to input goals and progress through a user interface;

[1480] a means of processing progress data in real time and providing feedback;

[1481] means for displaying goals and feedback via the smart glasses;

[1482] means for collecting progress data from the smart glasses;

[1483] A system including:

[1484] (Claim 2)

[1485] 10. The system of claim 1, further comprising means for integrating quantitative and qualitative evaluations to set evaluation criteria.

[1486] (Claim 3)

[1487] 10. The system of claim 1, further comprising means for periodically collecting and providing progress and feedback data to both the rater and the ratee.

[1488] "Example 2: Combining Emotion Engines"

[1489] (Claim 1)

[1490] A means of collecting company information, personnel data, and goal setting data;

[1491] means for pre-processing the collected data;

[1492] a means for analyzing the pre-processed data and generating customized goals for each employee;

[1493] A means for setting evaluation criteria based on the generated goals;

[1494] a means for storing the goals and evaluation criteria in a database;

[1495] means for providing a user interface for employees to input goals and progress;

[1496] means for processing progress data and emotional state data in real time and providing customized feedback;

[1497] means including an emotion engine for analyzing the emotional state data input from the employee;

[1498] A system including:

[1499] (Claim 2)

[1500] 10. The system of claim 1, further comprising means for integrating quantitative and qualitative evaluations to set evaluation criteria.

[1501] (Claim 3)

[1502] 10. The system of claim 1, further comprising means for periodically collecting and providing progress and feedback data to both the rater and the ratee.

[1503] "Application example 2 when combining emotion engines"

[1504] (Claim 1)

[1505] A means of collecting company information, personnel data, and goal setting data;

[1506] A means of analyzing the collected data and generating customized goals for each employee;

[1507] A means for setting evaluation criteria based on the generated goals;

[1508] a means for storing the goals and evaluation criteria in a database;

[1509] a means for employees to input goals and progress through a user interface;

[1510] a means of processing progress data in real time and providing feedback;

[1511] a means for inputting or detecting the employee's emotional state;

[1512] means for analyzing the emotional data and customizing feedback based on the emotional state;

[1513] A means of providing feedback to employees and storing sentiment data in a database;

[1514] A system including:

[1515] (Claim 2)

[1516] 10. The system of claim 1, further comprising means for integrating quantitative and qualitative evaluations to set evaluation criteria.

[1517] (Claim 3)

[1518] 10. The system of claim 1, further comprising means for periodically collecting and providing progress data, sentiment data, and feedback data to both the rater and ratee. [Explanation of symbols]

[1519] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of collecting company information, personnel data, and goal setting data; A means of analyzing the collected data and generating customized goals for each employee; A means for setting evaluation criteria based on the generated goals; a means for storing the goals and evaluation criteria in a database; a means for employees to input goals and progress through a user interface; a means of processing progress data in real time and providing feedback; A system including:

2. The system of claim 1 , further comprising means for integrating quantitative and qualitative evaluations to set evaluation criteria.

3. 10. The system of claim 1, further comprising means for periodically collecting and providing progress and feedback data to both the rater and the ratee.

Images