System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving goals and challenges from a user; means for storing the received goals and challenges in a storage device; means for analyzing the stored goals and challenges; means for generating optimal feedback and advice based on the analysis; means for transmitting the generated feedback and advice to a user terminal; means for receiving and storing user actions and achievements in the storage device; means for analyzing the stored actions and achievements and tracking progress; and means for periodically generating and transmitting progress reports to the user terminal.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] Businesspeople face a lot of work and pressure in their daily lives, making it difficult to objectively evaluate and improve their careers and performance. Consulting with a human coach can be time-consuming and costly, and there are also problems with not knowing when and who to consult. The objective of this invention is to provide businesspeople with appropriate feedback and advice quickly and at low cost to help them take effective action toward achieving their goals and maximize their performance. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system including the following means: a means for receiving goals and tasks from a user, a means for storing the received goals and tasks in a storage device, a means for analyzing the stored goals and tasks, a means for generating optimal feedback and advice based on the analysis results, a means for transmitting the generated feedback and advice to a user terminal, a means for receiving the user's behavior and results and storing them in a storage device, a means for analyzing the stored behavior and results and tracking progress, and a means for periodically generating and transmitting progress reports to the user terminal. The system also includes a means for adjusting the content and format of the generated feedback and advice based on the user's personality and preferences, and a means for building a trusting relationship with the user, thereby providing individually tailored coaching and encouraging the user to take action. Furthermore, the system includes a means for generating an action plan for the user to achieve their goal, and a means for adjusting the action plan according to the user's progress, thereby providing continuous support for goal achievement.

[0006] "User" means an individual or organization that uses this system to receive support in achieving their goals.

[0007] A "goal" is a specific outcome or objective that the user wants to achieve.

[0008] A "challenge" is a problem or obstacle a user faces in achieving a goal.

[0009] "Means" is a general term for the methods, devices, and software used by this system to achieve a specific function.

[0010] The "receiving means" refers to a function or device for receiving information on goals and tasks input by a user.

[0011] "Storage device" refers to a physical or virtual recording medium for storing received data on goals, tasks, actions and results.

[0012] "Means of analysis" is a function that analyzes data related to goals, challenges, actions, and results to generate optimal feedback and advice.

[0013] "Feedback" is specific advice or guidance provided to users to help them achieve their goals based on the analysis results.

[0014] Advice is a specific suggestion or recommendation that helps users take action.

[0015] The "transmitting means" refers to a function or device for transmitting the generated feedback or advice to the user's terminal.

[0016] "Actions" are the specific steps or activities that users actually take toward achieving their goals.

[0017] "Outcomes" are achievements or accomplishments that result from actions taken by users toward achieving their goals.

[0018] "Tracking" means continuously monitoring a user's actions and achievements and tracking their progress.

[0019] A "progress report" is a report that summarizes the progress of a user toward achieving a goal based on their actions and results.

[0020] "Personality" refers to psychological characteristics that characterize a user's behavioral patterns and individuality.

[0021] "Preferences" refer to the user's particular preferences or tendencies.

[0022] A "trusting relationship" is a relationship based on mutual trust between the user and the system that promotes effective coaching.

[0023] An "action plan" is a specific step or action plan that a user must take to achieve their goal.

[0024] "Means for adjustment" is a function for changing and optimizing action plans and feedback according to the user's progress. [Brief explanation of the drawings]

[0025] [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

[0026] 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.

[0027] First, the terms used in the following description will be explained.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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."

[0033] [First embodiment]

[0034] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0035] 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.

[0036] 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).

[0037] 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.

[0038] 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.

[0039] 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.

[0040] 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.

[0041] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0042] 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.

[0043] 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.

[0044] 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.

[0045] 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."

[0046] This invention is an AI coaching system that helps businesspeople achieve their goals and maximize their performance. The system receives goals and challenges from users, analyzes them, and generates optimal feedback and advice. It also tracks the user's actions and results and generates regular progress reports. It also provides individualized feedback tailored to the user's personality and preferences, building a relationship of trust and helping the user take effective action toward achieving their goals.

[0047] User goal setting

[0048] Users input their goals and objectives into the terminal. For example, let's say you set a goal of "gaining 10 new clients in the next three months."

[0049] The terminal transmits the inputted goal and task to the server.

[0050] The server stores the received goals and tasks in a storage device.

[0051] Generate feedback and advice

[0052] The server retrieves the goals and challenges stored in the storage device and analyzes them using an AI analysis engine. For example, after analyzing "Strategy for acquiring new customers," it generates feedback such as: "As a next step, we recommend creating a potential customer list and launching an individual email campaign."

[0053] The server transmits the generated feedback and advice to the user terminal.

[0054] The device will display any feedback or advice it receives to the user.

[0055] Tracking actions and results

[0056] The user performs actions to achieve the goal and enters the results into the terminal. For example, they might enter, "I contacted three new customers today."

[0057] The terminal transmits information about the input actions and results to the server.

[0058] The server stores the received actions and results in a storage device and tracks the progress.

[0059] Generate progress reports

[0060] The server periodically analyzes the tracking data and generates progress reports, including the user's behavior history and unachieved goals. For example, a report might be generated that states, "Three new customers were contacted in the past week, and two of them responded positively."

[0061] The server transmits the generated progress report to the user terminal.

[0062] The terminal displays the received progress reports to the user.

[0063] Adjusting individual feedback

[0064] The server tailors the content and format of feedback and advice based on the user's personality and preferences: for example, if the user prefers detailed instructions, it provides feedback detailing specific steps.

[0065] The server communicates with the user to build a trusting relationship and provides coaching tailored to the user's needs and pace.

[0066] The above is a specific embodiment of the present invention. This system allows users to receive effective support for self-development and career advancement. This system provides objective and unbiased support from the user's perspective, greatly contributing to the achievement of businesspeople's goals.

[0067] The processing flow will be explained below.

[0068] Step 1:

[0069] The user inputs their goals and objectives into the terminal. For example, they might input "Acquire 10 new clients in the next three months."

[0070] Step 2:

[0071] The device sends the entered goals and tasks to the server, including the user ID.

[0072] Step 3:

[0073] The server stores the received goals and tasks in a memory device, including storing them in a database in association with the user ID.

[0074] Step 4:

[0075] The server retrieves the goals and tasks from the storage device and inputs them into the AI ​​analysis engine, which then generates optimal feedback and advice for achieving the goals.

[0076] Step 5:

[0077] The server sends the generated feedback and advice to the user device, including a message such as, "As a next step, we recommend that you create a potential customer list and launch a personalized email campaign."

[0078] Step 6:

[0079] The device will display any feedback or advice it receives to the user.

[0080] Step 7:

[0081] Users enter actions they have taken or results they have achieved into the device, for example, "I contacted three new customers today."

[0082] Step 8:

[0083] The device sends the input action and result information to the server. The transmitted data again includes the user ID.

[0084] Step 9:

[0085] The server tracks progress by storing the received actions and achievements in a storage device, which stores each action and achievement with a timestamp.

[0086] Step 10:

[0087] The server periodically retrieves the tracking data from the storage device and generates progress reports, such as "Three new customers were contacted in the past week, with two positive responses."

[0088] Step 11:

[0089] The server transmits the generated progress report to the user terminal.

[0090] Step 12:

[0091] The terminal displays the received progress reports to the user.

[0092] Step 13:

[0093] The server tailors the content and format of feedback and advice based on the user's personality and preferences, including a process of learning the feedback formats and styles that the user has preferred in the past.

[0094] Step 14:

[0095] The server communicates with the user to build trust with them, for example, by periodically sending a survey asking about user satisfaction and areas for improvement.

[0096] The above are the processing steps in a specific embodiment of the present invention. The specific operations for each step are clearly defined, making the overall flow easy to understand.

[0097] Example 1

[0098] 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."

[0099] There is a lack of effective support systems to help businesspeople achieve their goals and maximize their performance. In particular, there is a need for a system that can systematically provide feedback and advice tailored to the characteristics of each user, track actions and results, and generate progress reports. Conventional systems can only provide generic feedback, making it difficult to provide detailed instructions or adaptive support tailored to the characteristics of each individual user.

[0100] 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.

[0101] In this invention, the server includes means for receiving goals and tasks from a user, means for storing the received goals and tasks in a storage device, means for acquiring the stored goals and tasks and analyzing them using a generative AI model, means for generating optimal feedback and advice based on the analysis results, means for transmitting the generated feedback and advice to a user terminal, means for receiving the user's actions and results and storing them in a storage device, means for analyzing the stored actions and results and tracking progress, means for periodically generating progress reports and transmitting them to the user terminal, and means for adjusting the content and format of the generated feedback and advice based on the user's personality and preferences. This makes it possible to provide feedback and advice tailored to the characteristics of each user, and to systematically generate, adjust, track, and report on effective action plans.

[0102] "User" means an individual or organization that uses the system to assist them in achieving their goals.

[0103] "Goal" refers to the specific outcome or target value that the user aims to achieve.

[0104] A "challenge" is a problem or difficulty a user faces that prevents them from achieving their goal.

[0105] "Means for receiving" refers to the interface or function that takes in data provided by the user and inputs it into the system.

[0106] "Memory device" refers to a data storage device for storing received data, behavioral information, outcomes, and analysis results.

[0107] A "generative AI model" is an artificial intelligence model used to analyze a user's goals and challenges and generate feedback and advice.

[0108] The "means of analysis" is a system function that uses a generative AI model to execute the process of analyzing the goals and challenges provided by the user.

[0109] "Feedback" is evaluation information that shows specific action plans and areas for improvement for the goals and challenges provided by the user.

[0110] "Advice" is information that provides guidance on specific actions or strategies that users should take to achieve their goals.

[0111] "User Terminal" means the computer device used by a User to access the System and enter data and view feedback.

[0112] "Behaviors" refer to the specific activities or tasks that users perform to achieve their goals.

[0113] "Results" refers to the results or progress achieved as a result of a user's actions.

[0114] "Progress tracking means" means the system's ability to record user actions and achievements and track progress toward goal achievement in real time.

[0115] The "means for generating periodic progress reports" is a system function that creates progress reports at regular intervals based on the user's behavioral history and results.

[0116] "Personality and Preferences" refers to a user's behavioral patterns, preferences, and personal characteristics that serve as the basis for tailoring feedback and advice.

[0117] "Means for building trust" are system features that communicate with users and provide feedback and advice to build trust.

[0118] The "means for generating an action plan" is a system function that develops specific action steps to achieve the user's goal.

[0119] A "prompt sentence" is an input sentence used to prompt a generative AI model to perform appropriate analysis.

[0120] The present invention is an AI coaching system that helps users achieve their goals and maximize their performance. The system uses the following hardware and software components:

[0121] Hardware Configuration

[0122] 1. Server

[0123] 2. User device (PC, smartphone, etc.)

[0124] 3. Storage Devices (Database Systems)

[0125] Software Configuration

[0126] 1. AI analysis engine (e.g., generative AI model)

[0127] 2. Database management system (e.g., MySQL)

[0128] 3. Communication protocol (e.g. HTTP)

[0129] Setting user goals

[0130] Users input their goals and challenges through the device. For example, they can set a goal of "acquiring 10 new clients in the next three months." The input is done through a dedicated application or a web interface. The device then sends the input goals and challenges to the server.

[0131] Save goal data

[0132] The server stores the received goals and tasks in a database (e.g., MySQL). For example, it registers the goal data in the appropriate table using an INSERT statement.

[0133] Generate feedback and advice

[0134] The server sends the goals and tasks stored in the database to a generative AI model (e.g., GPT-4) using prompts for analysis. For example, the following prompts are used:

[0135] A user has set a goal of acquiring 10 new customers in three months. What next action would you recommend?

[0136] Based on this prompt, the AI ​​analytics engine generates specific strategic feedback, such as, "As a next step, we recommend that you create a prospect list and launch a personalized email campaign."

[0137] Send feedback and advice

[0138] The server sends the generated feedback and advice to the user's device. Specifically, the server returns the generated feedback as an HTTP response and displays it on the user's device.

[0139] Recording actions and achievements

[0140] The user performs actions to achieve the goal and enters the results into the device. For example, they might enter, "Today I contacted three new customers." The device then sends the entered information about the actions and results to the server.

[0141] Behavioral Data Storage

[0142] The server stores the received action and outcome information in a database, for example in a transaction table in the database using the MySQL INSERT statement.

[0143] Generate progress reports

[0144] The server periodically retrieves tracking data from the database and asks the generative AI model to analyze it to generate a progress report, such as "Three new customers were contacted in the past week, and two of them responded positively."

[0145] Sending a progress report

[0146] The server generates a progress report and sends it to the user's device via an HTTP response, where it can be displayed.

[0147] Adjusting individual feedback

[0148] The server tailors the content and format of the feedback and advice based on the user's personality and preferences. For example, it references the user's profile information stored in a database and provides feedback detailing specific steps to users who prefer detailed instructions.

[0149] The above is a specific embodiment of the present invention. This system allows users to receive feedback and advice tailored to their individual characteristics and implement effective action plans to achieve their goals. This makes it possible to systematically support users in improving their performance and achieving their goals.

[0150] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0151] Processing step details

[0152] Step 1:

[0153] The user inputs their goals and challenges into the device. An example input is "Acquire 10 new clients in the next three months." The input data is text data about the user's goals and challenges. The device acquires the input data and sends it to the server via an input form. The data format is JSON or XML.

[0154] Step 2:

[0155] The server analyzes the received goal and task data and stores it in a database. Specifically, it receives an HTTP request, extracts the data, and then stores it using the INSERT statement of a database management system (e.g., MySQL). The input is the goal and task data received from the user, and the output is the data stored in the database.

[0156] Step 3:

[0157] The server retrieves the stored goals and tasks and performs analysis using the generative AI model. Specifically, it retrieves the goals and tasks from the database using a SELECT statement, and then sends the retrieved data to the generative AI model (e.g., GPT-4) with a prompt statement attached. The input is the goal and task data retrieved from the database, and the output is the analysis results obtained from the generative AI model.

[0158] Step 4:

[0159] The server generates optimal feedback and advice based on the analysis results. The specific prompt used is, "The user has set a goal of acquiring 10 new customers in three months. What action do you recommend as the next step?" The generative AI model analyzes this prompt and generates specific feedback and advice. The input is the prompt and the analysis result data, and the output is specific feedback and advice.

[0160] Step 5:

[0161] The server sends the generated feedback and advice to the user terminal. Specifically, it returns the generated feedback and advice to the user terminal as an HTTP response. The input is the generated feedback and advice, and the output is the feedback and advice displayed on the user terminal.

[0162] Step 6:

[0163] The user performs actions to achieve a goal and enters the results into the device. For example, they might enter, "Today I contacted three new customers." The input data is text data about the user's actions and results. The device acquires the input data and sends it to the server. The data format is JSON or XML.

[0164] Step 7:

[0165] The server analyzes the received behavior and outcome data and stores it in a database. Specifically, it receives an HTTP request, extracts the data, and then stores it using the INSERT statement of a database management system (e.g., MySQL). The input is the behavior and outcome data received from the user, and the output is the data stored in the database.

[0166] Step 8:

[0167] The server periodically retrieves tracking data from the database and generates a progress report. Specifically, it retrieves actions and results from the database and generates a progress report based on them. For example, the generated report may include the following: "Three new customers were contacted in the past week, and two of them responded positively." The input is the tracking data retrieved from the database, and the output is the progress report.

[0168] Step 9:

[0169] The server sends the generated progress report to the user terminal. Specifically, it returns the progress report to the user terminal as an HTTP response. The input is the generated progress report, and the output is the progress report displayed on the user terminal.

[0170] Step 10:

[0171] The server adjusts the content and format of the feedback and advice based on the user's personality and preferences. For example, it refers to the user's profile information and provides feedback detailing specific steps to a user who prefers detailed instructions. The input is data about the user's personality and preferences, and the output is tailored feedback and advice.

[0172] The above is a detailed description of the processing steps and specific operations of the system of the present invention, which allows users to receive effective support and implement action plans to achieve their goals.

[0173] (Application example 1)

[0174] 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."

[0175] Conventional AI coaching systems lack specific action plans for achieving users' goals and dynamic adjustments to progress, making it difficult for businesspeople to effectively achieve their goals. In particular, they do not provide enough support to maximize the work efficiency of store staff, which prevents them from improving the overall productivity of stores.

[0176] 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.

[0177] In this invention, the server includes: means for receiving goals and tasks from a user; means for storing the received goals and tasks in a database; means for using an analysis engine to analyze the stored goals and tasks; means for using an artificial intelligence model to generate optimal feedback and advice based on the analysis results; communication means for sending the generated feedback and advice to a user terminal; means for receiving the user's actions and results and storing them in a database; means for analyzing the stored actions and results and tracking progress; means for periodically generating progress reports and sending them to the user terminal; and means for recording the user's actions and results and automatically generating a new action plan from the tracked data. This enables dynamic generation and adjustment of action plans according to the user's progress, maximizing the work efficiency of staff in the physical store and ultimately improving the productivity of the entire physical store.

[0178] "User" refers to any individual or organization that uses the System.

[0179] A "goal" is a specific objective or task that a user wants to achieve.

[0180] "Receiving means" refers to the function of acquiring input information from the user.

[0181] "Database" refers to a storage device that stores received goal and behavior data.

[0182] "Analysis engine" refers to a program or function for processing and analyzing data.

[0183] "Artificial intelligence model" refers to a machine learning algorithm that generates feedback and advice based on user data.

[0184] "Communication means" refers to the function of sending and receiving information between the server and the user terminal.

[0185] "Behavioral data" refers to the specific actions a user takes to achieve their goals and the results of those actions.

[0186] "Tracking tools" refers to features that record user actions and achievements and track progress.

[0187] "Progress Report" means a report summarizing a User's progress toward achieving their Goals.

[0188] An "action plan" refers to the specific procedures or steps a user takes to achieve a goal.

[0189] "Dynamic adjustment" refers to the ability to change plans and feedback in real time based on the user's progress and behavioral data.

[0190] "Brick and mortar store" refers to a retail establishment that sells goods and services at a physical location.

[0191] "Staff" refers to employees working at physical stores.

[0192] This invention is an AI coaching system that helps store staff achieve their goals and maximize work efficiency. The system includes the following components: users input their goals and challenges, analyzes them, generates optimal feedback and advice, tracks the user's actions and results, and generates regular progress reports. Furthermore, by providing individualized feedback tailored to the user's personality and preferences and building a relationship of trust, the system helps the user take effective action toward achieving their goals.

[0193] goal setting

[0194] Users input their goals and challenges into a smartphone app or tablet device. A specific example goal might be "Acquire 10 new clients in the next three months." The entered goals are sent to the server and stored in a database.

[0195] Generate feedback and advice

[0196] The server retrieves the goals and challenges stored in the database and analyzes them using an AI analysis engine (for example, OpenAI's GPT-4). For example, after analyzing "Strategy for Acquiring New Customers," the server generates feedback such as: "As a next step, we recommend creating a potential customer list and launching a personalized email campaign." The generated feedback is then sent to the user's device.

[0197] Tracking actions and results

[0198] Users take actions to achieve their goals and enter their results into the device. For example, "Today, I will enter how I contacted three new customers." The entered information about actions and results is sent to the server and stored in a database. The server analyzes this information and tracks the user's progress.

[0199] Generate progress reports

[0200] The server periodically analyzes the stored data and generates a progress report. The generated report includes the user's behavior history and unachieved goals. A specific example could be a report that states, "Three new customers were contacted in the past week, and two of them responded positively." The generated report is sent to the user's device.

[0201] Adjusting individual feedback

[0202] The server tailors the content and format of feedback and advice based on the user's personality and preferences. For example, if the user prefers detailed instructions, it provides feedback detailing specific steps. It also communicates with the user to build trust and provides coaching tailored to the user's needs and pace.

[0203] Technology used

[0204] Language: Python

[0205] Framework: Flask (server side)

[0206] Database: PostgreSQL

[0207] AI model: OpenAI's GPT-4

[0208] Device: iOS / Android compatible mobile app

[0209] Prompt Sentence Examples

[0210] Input the following prompts into the AI ​​model to generate specific feedback.

[0211] "User goal: Acquire 5 new customers in the next month

[0212] We recommend the following steps:

[0213] As described above, this invention is a system that provides specific and dynamic action plans to support users in achieving their goals, and is effective in maximizing the work efficiency of staff in physical stores.

[0214] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0215] Step 1:

[0216] Users input their goals and challenges into a smartphone app or tablet device. The input content is specific, such as "Acquire 10 new clients in the next three months." The input goals and challenges are sent to the server as structured data by the device. The server receives this data and stores it in a database.

[0217] Step 2:

[0218] The server retrieves the goals and challenges stored in the database. Next, it analyzes the goals and challenges using an AI analysis engine (for example, OpenAI's GPT-4). The analysis prompt uses the following: "User's goal: Acquire five new customers in the next month. Recommend next steps." The feedback generated as a result of the analysis includes specific steps, such as "We recommend creating a potential customer list and launching an individual email campaign."

[0219] Step 3:

[0220] The server sends the generated feedback and advice to the user terminal, which receives it and displays the feedback on the user's display, allowing the user to take specific action based on the feedback.

[0221] Step 4:

[0222] The user performs actions to achieve a goal and enters the results into the device. For example, they enter the results of their actions, such as "I contacted three new customers today." The entered action data is sent from the device to the server and stored in a database.

[0223] Step 5:

[0224] The server retrieves the received behavioral data from the database and analyzes the progress. As a result of the analysis, progress is tracked and a progress report is generated in the form of, for example, "Three new customers were contacted in the past week, and two of them responded positively." The tracking data is dynamically updated using an AI model.

[0225] Step 6:

[0226] The server then sends the generated progress report to the user's device, where it is displayed to the user, who can then check their own progress. This progress report includes a history of actions and unachieved goals.

[0227] Step 7:

[0228] The server adjusts the content and format of feedback and advice based on the user's personality and preferences. For example, it provides feedback detailing specific steps to users who prefer detailed instructions. This adjustment makes it possible to provide optimal coaching for each user. Based on user feedback, the server builds trust and continues to approach the user according to their individual needs and pace.

[0229] By following these steps, the system can effectively support users in achieving their goals and maximize the work efficiency of store staff.

[0230] 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.

[0231] This invention is an AI coaching system that helps businesspeople achieve their goals and maximize their performance. The system includes a means for receiving, storing, and analyzing a user's goals and challenges, and a means for providing generated feedback and advice. Furthermore, the system tracks the user's actions and achievements and periodically generates progress reports. It also provides personalized feedback based on the user's personality and preferences, and includes an emotion engine that recognizes the user's emotions, allowing it to adjust the feedback based on the user's emotions.

[0232] User goal setting and reception

[0233] Users input their goals and objectives into the terminal. For example, they can set a goal of "gaining 10 new clients in the next three months."

[0234] The terminal transmits the input goal and task data to the server.

[0235] The server stores the goals and tasks in a storage device.

[0236] Generate feedback and advice

[0237] The server retrieves the goals and challenges stored in the storage device and inputs them into the AI ​​analysis engine. The AI ​​analysis engine generates feedback and advice based on the strategy and specific action plan for achieving the goals. For example, "To acquire new customers, we recommend that you create a list of potential customers and begin individual approaches via email and phone."

[0238] The server transmits the generated feedback and advice to the user terminal.

[0239] The device will display any feedback or advice received to the user.

[0240] Tracking actions and results

[0241] The user performs an action to achieve the goal and enters it into the terminal. For example, "I contacted three new customers today."

[0242] The terminal transmits the input action and outcome data to the server.

[0243] The server stores user actions and achievements on a storage device to track progress and saves the data with a timestamp.

[0244] Generate and send status reports

[0245] The server periodically retrieves the tracking data from the storage device and generates progress reports, such as "Three new customers were contacted in the past week, with two positive responses."

[0246] The server sends the generated progress report to the user terminal.

[0247] The terminal displays received progress reports to the user.

[0248] Analysis by emotion engine

[0249] The server is also equipped with an emotion engine that recognizes the user's emotions.

[0250] The emotion engine analyzes information entered by the user into the device and real-time emotional data obtained from the device's camera and microphone. For example, it can determine whether the user is feeling stressed by analyzing facial expressions and voice tones.

[0251] The server records the emotion data recognized by the emotion engine and analyzes the user's emotional tendencies.

[0252] Adjusting Feedback Based on Emotions

[0253] The server integrates and analyzes the user's emotional and behavioral data, and generates feedback that takes into account the correlation between emotions and behavior. For example, if the user is tired, it can suggest relaxation methods to help them achieve their goals.

[0254] The server adjusts the generated feedback based on the emotional data as needed to provide optimal advice to the user.

[0255] The above is a specific embodiment of the present invention. The system can effectively support users in achieving their goals by providing personalized feedback based on the user's personality and preferences and adjusting advice based on emotions using an emotion engine.

[0256] The processing flow will be explained below.

[0257] Step 1:

[0258] The user inputs their goals and objectives into the terminal. For example, they can set "to acquire 10 new clients in the next three months."

[0259] Step 2:

[0260] The device sends the entered goal and task data to the server, including the user ID.

[0261] Step 3:

[0262] The server stores the received goals and tasks in a memory device, which stores them in a database containing the goals, tasks, and user IDs.

[0263] Step 4:

[0264] The server retrieves the goals and tasks from the storage device and inputs them into the AI ​​analysis engine, which then generates optimal feedback and advice to help the user achieve their goals.

[0265] Step 5:

[0266] The server sends the generated feedback and advice to the user's device, for example, a message saying, "We recommend that you create a potential customer list and launch a personalized email campaign on a specific date."

[0267] Step 6:

[0268] The device will display any feedback or advice received to the user.

[0269] Step 7:

[0270] Based on the feedback, the user takes specific actions and enters them into the device, for example, "I contacted three new customers today."

[0271] Step 8:

[0272] The device sends the input data of the actions and results to the server. The data includes the user ID, the action, and the results.

[0273] Step 9:

[0274] The server stores the received actions and results in a storage device and tracks the progress. It records the user's actions and results with timestamps.

[0275] Step 10:

[0276] The server periodically retrieves the tracking data from the storage device and generates progress reports, such as "Three new customers were contacted in the past week, and two responded positively."

[0277] Step 11:

[0278] The server sends the generated progress report to the user terminal.

[0279] Step 12:

[0280] The terminal displays received progress reports to the user.

[0281] Step 13:

[0282] The server tailors the content and format of the feedback and advice based on the user's personality and preferences, for example, if the user prefers detailed instructions, it provides feedback with specific steps.

[0283] Step 14:

[0284] The server sends data from the device (camera, microphone, text input, etc.) to the emotion engine to analyze the user's emotions in real time. The emotion engine analyzes the user's facial expressions and tone of voice to determine whether the user is feeling stressed.

[0285] Step 15:

[0286] The server stores the emotional data recognized by the emotion engine in a storage device and analyzes the user's emotional tendencies. The emotional data also records changes over time.

[0287] Step 16:

[0288] The server integrates and analyzes the user's emotional and behavioral data, and generates feedback that takes into account the correlation between emotions and behavior. For example, it may provide feedback such as, "Your recent behavior seems to be causing you stress. We recommend that you try relaxation techniques."

[0289] The above are the processing steps in a specific embodiment of the present invention. The specific operations performed in each step are clearly defined, making the overall flow easy to understand.

[0290] Example 2

[0291] 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."

[0292] Today's businesspeople are busy, and self-management, the formulation of action plans to achieve goals, and progress management require a great deal of time and effort. It is also difficult for them to receive appropriate feedback and advice in response to emotional changes and stress levels. Conventional systems do not adequately adjust feedback to reflect the user's individual emotional state, and are therefore unable to effectively support users in maintaining their motivation or improving their performance.

[0293] 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.

[0294] In this invention, the server includes means for receiving goals and tasks from a user, means for storing the received goals and tasks in a storage device, means for analyzing the stored goals and tasks, means for generating optimal feedback and advice based on the analysis results, means for transmitting the generated feedback and advice to a user terminal, means for receiving the user's actions and results and storing them in a storage device, means for analyzing the stored actions and results and tracking progress, means for periodically generating progress reports and transmitting them to the user terminal, means for receiving and analyzing the user's emotional data, and means for adjusting feedback based on the emotional data. This makes it possible to effectively support the user in achieving their goals and provide personalized feedback according to their emotional state.

[0295] "Goals and challenges" refers to the specific objectives the user wants to achieve and the problems they need to address.

[0296] "Means for receiving" refers to an interface for obtaining data input by a user.

[0297] "Storage device" refers to a database or storage system for saving received data.

[0298] "Means for analyzing" refers to algorithms or software that analyze the stored data and generate appropriate action plans or feedback.

[0299] "Feedback and Advice" refers to specific guidelines and advice provided to users based on the analysis results.

[0300] "Means for sending" refers to a communication system for sending the generated feedback or advice to a user terminal.

[0301] "User terminal" refers to a device used by a user, such as a computer, smartphone, or tablet.

[0302] "Actions and Results" refers to the actions actually taken by the user and the results obtained as a result thereof.

[0303] "Progress tracking means" refers to a system for recording user actions and achievements and monitoring progress.

[0304] "Progress Report" refers to a report that is generated periodically that summarizes a user's actions and achievements.

[0305] "Emotion data" is data that indicates the user's emotional state, and includes, for example, stress level and fatigue level.

[0306] An "emotion engine" refers to software or algorithms that analyze users' emotional data and reflect the results in feedback and advice.

[0307] This invention is an AI coaching system that helps businesspeople achieve their goals and maximize their performance. The system includes a means for receiving, storing, and analyzing a user's goals and challenges, and a means for providing generated feedback and advice. Furthermore, the system tracks the user's actions and achievements and periodically generates progress reports. It also includes an emotion engine that recognizes the user's emotions and can adjust feedback based on the emotion data.

[0308] Hardware and Software Use

[0309] The terminal provides an interface for users to input goals and tasks. Terminals can be smartphones, PCs, tablets, etc. These terminals are equipped with a network communication module and send data to the server.

[0310] The server integrates several key components. The database system uses a relational database management system such as PostgreSQL. The generative AI model uses OpenAI GPT-4 and other models to generate feedback and advice for achieving goals. The emotion engine uses Microsoft Azure Emotion API and other models to analyze user emotion data.

[0311] Examples of specific examples and prompts

[0312] For example, if a user sets a goal of "acquiring 10 new clients in the next three months," that information is sent to the server via the device and stored in a database. The server retrieves this goal data, inputs it into a generative AI model for analysis, and generates feedback such as the following:

[0313] "Next week, I recommend creating a prospect list and contacting 10 more companies."

[0314] If the user then reports that they "contacted three new customers today," that data is also sent to the server via the device and tracked.

[0315] Additionally, emotional data is collected. For example, the device's camera and microphone are used to capture the user's facial expressions and tone of voice, and the captured data is sent to a server. The server analyzes this emotional data and adjusts the feedback accordingly if the user is experiencing high levels of stress.

[0316] Here are some example prompts to input to the generative AI model:

[0317] Goal: Acquire 10 new clients

[0318] This week's action: Created a list of potential clients and contacted three companies.

[0319] Perceived stress level: High

[0320] Using the information below, suggest a specific action plan for the user for the next week and some advice on how to reduce stress.

[0321] User goal: Acquire 10 new customers

[0322] Action: This week I created a list of potential clients and contacted three of them.

[0323] Current Emotion: High stress levels

[0324] Suggestion Feedback:

[0325] 1. Specific action plan for next week

[0326] 2. Advice for reducing stress

[0327] This completes the description of the embodiment of the invention. This system supports users in achieving their goals and provides feedback according to their individual emotional state, thereby maintaining their motivation and improving their performance.

[0328] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0329] Step 1:

[0330] The user inputs their goals and objectives into the terminal. For example, they might input "Acquire 10 new clients in the next three months."

[0331] Input: Goals and challenges set by the user.

[0332] Data processing: Convert the goal and task data entered on the terminal into JSON format.

[0333] Output: Goal and assignment data in JSON format.

[0334] Step 2:

[0335] The terminal sends the entered goal and task data to the server, and the content entered by the user is sent via the network module.

[0336] Input: Goal and assignment data in JSON format.

[0337] Data operation: Send data to the server using a network protocol (e.g., HTTP POST request).

[0338] Output: The goal and task data sent to the server.

[0339] Step 3:

[0340] The server stores the received goals and tasks in a database, which is created using PostgreSQL.

[0341] Input: Goal and task data received by the server.

[0342] Data processing: Convert JSON format data into SQL insert statements and store them in the database.

[0343] Output: Goal and task data stored in a database.

[0344] Step 4:

[0345] The server retrieves the target data from the database and provides it to the generative AI model, which uses OpenAI GPT-4.

[0346] Input: Target data in the database.

[0347] Data Calculation: Converting goal data into prompts for the AI, such as "User-defined goal: Acquire 10 new customers."

[0348] Output: The prompt that is input to the generative AI model.

[0349] Step 5:

[0350] Generative AI models generate feedback and advice to help you achieve your goals.

[0351] Input: Prompt data.

[0352] Data computation: A generative AI model analyzes the prompts and generates appropriate feedback and advice, such as, "We recommend that you build a lead list next week and contact 10 more companies."

[0353] Output: Generated feedback and advice.

[0354] Step 6:

[0355] The server transmits the generated feedback and advice to the user terminal.

[0356] Input: Generated feedback and advice data.

[0357] Data operation: Sends data to the user terminal using a network protocol (e.g., HTTP POST request).

[0358] Output: Feedback and advice data sent to the user device.

[0359] Step 7:

[0360] The device will display the received feedback and advice to the user.

[0361] Input: Feedback and advice data sent by the server.

[0362] Data processing: Converting data into a format that can be displayed on the screen, for example, as a text message.

[0363] Output: Feedback and advice displayed to the user.

[0364] Step 8:

[0365] The user enters the actions or results they have achieved into the terminal. For example, they might enter, "I contacted three new customers today."

[0366] Input: User behavior and outcome data.

[0367] Data processing: Converts the action and result data entered on the device into JSON format.

[0368] Output: Behavior and outcome data in JSON format.

[0369] Step 9:

[0370] The terminal transmits the input action and outcome data to the server.

[0371] Input: Action and outcome data in JSON format.

[0372] Data operation: Send data to the server using a network protocol (e.g., HTTP POST request).

[0373] Output: Action and outcome data sent to the server.

[0374] Step 10:

[0375] The server records the received action and outcome data in a database to track progress.

[0376] Input: Action and outcome data received by the server.

[0377] Data processing: Converting JSON data into SQL insert statements and storing them in the database. The saved data is then fed into a progress tracking algorithm to update the progress.

[0378] Output: Behavioral and outcome data recorded in a database, updated progress.

[0379] Step 11:

[0380] The server periodically retrieves the progress data from the database and generates a progress report.

[0381] Input: Progress data in the database.

[0382] Data processing: Aggregate progress data and convert it into a report format, for example, "Contacted three new customers in the past week and received positive responses from two."

[0383] Output: The generated progress report.

[0384] Step 12:

[0385] The server transmits the generated progress report to the user terminal.

[0386] Input: Generated progress report data.

[0387] Data operation: Sends data to the user terminal using a network protocol (e.g., HTTP POST request).

[0388] Output: Progress report sent to user terminal.

[0389] Step 13:

[0390] The terminal displays the received progress report to the user.

[0391] Input: Progress report data sent by the server.

[0392] Data processing: Converting data into a format that can be displayed on the screen, for example, as a text message.

[0393] Output: A progress report displayed to the user.

[0394] Step 14:

[0395] The server analyzes the emotion data obtained from the user.

[0396] Input: User emotion data (e.g., facial capture, voice tone).

[0397] Data Calculation: Uses an emotion engine to analyze emotion data and identify the user's emotional state. For example, high stress level, high fatigue.

[0398] Output: Parsed emotional state data.

[0399] Step 15:

[0400] The server adjusts the feedback based on the emotion data.

[0401] Input: Parsed emotion data and progress data.

[0402] Data Computation: Using generative AI models to regenerate or adjust feedback while taking into account emotional data. Example: Suggesting relaxation techniques for a stressed user.

[0403] Output: Tailored feedback and advice.

[0404] Step 16:

[0405] The device displays tailored feedback to the user.

[0406] Input: Adjusted feedback data sent by the server.

[0407] Data processing: Converting data into a format that can be displayed on the screen, for example, as a text message.

[0408] Output: The adjusted feedback and advice displayed to the user.

[0409] (Application example 2)

[0410] 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."

[0411] Conventional factory robot systems have not adequately optimized production processes or managed the health of operators, leaving challenges in efficient robot operation and reducing operator stress. Furthermore, there is a lack of systems that go beyond simply analyzing production data and provide feedback based on the operator's emotional state. The present invention aims to solve these challenges by providing a system that maximizes the efficiency of factory robots and manages operator stress.

[0412] 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 receiving a user's goals and tasks, means for storing the received goals and tasks in a storage device, means for analyzing the stored goals and tasks, means for generating optimal feedback and advice based on the analysis results, means for transmitting the generated feedback and advice to a user terminal, means for receiving a user's actions and results and storing them in a storage device, means for analyzing the stored actions and results and tracking progress, means for periodically generating progress reports and transmitting them to the user terminal, means for collecting user emotion data, means for analyzing the user emotion data and adjusting feedback based on the emotions, and means for integrating and analyzing the user emotion data and behavioral data. This makes it possible to optimize the operation of a factory robot and provide feedback according to the operator's emotional state.

[0413] "Users" refer to factory managers and operators who use the system.

[0414] A "goal" is a specific production figure or result that the user wants to achieve.

[0415] A "challenge" is a problem or obstacle that a user must solve to achieve their goal.

[0416] A "means" is a method or device used to achieve a particular purpose.

[0417] "Storage device" refers to hardware or software for storing data.

[0418] A "server" is a centralized device for processing and storing data.

[0419] An "AI analysis engine" is software that uses artificial intelligence to analyze data and generate optimal feedback and advice.

[0420] "Feedback" is an evaluation or advice regarding the user's behavior or situation.

[0421] "Advice" is advice on actions or measures users should take to achieve their goals.

[0422] A "user terminal" is a device (e.g., a computer, a smartphone) that is directly operated by a user.

[0423] An "action" is a specific task that a user performs to achieve a goal.

[0424] "Results" refers to the results achieved by a user through their actions.

[0425] "Progress" is information that shows the progress of actions and results toward achieving a goal.

[0426] A "progress report" is a report summarizing progress.

[0427] "Emotional data" is information about a user's emotional state (e.g., stress, fatigue).

[0428] An "emotion engine" is software for analyzing user emotional data.

[0429] "Adjusting feedback based on emotion" means changing the content of feedback or advice based on the user's emotional state.

[0430] "Operation data" is information about the tasks and movements being performed by a factory robot.

[0431] "Tracking" means the continuous monitoring and recording of certain information.

[0432] This invention is an AI coaching system for optimizing manufacturing processes using factory robots and managing operator stress. The system includes means for receiving, storing, and analyzing user (factory manager or operator) goals and challenges, generating and sending feedback and advice, tracking behavior and results, generating progress reports, collecting and analyzing emotional data, and adjusting feedback.

[0433] Explaining program processing in natural language

[0434] The hardware used includes factory robots (e.g., general-purpose robotic devices), cameras (e.g., general-purpose webcams), and microphones (e.g., general-purpose USB microphones).The software used includes AI analysis engines (e.g., TensorFlow, PyTorch), emotion engines (e.g., Affectiva SDK), databases (e.g., PostgreSQL), and communication protocols (e.g., MQTT).

[0435] 1. Goal setting and receiving:

[0436] The server receives the goal entered by the factory manager into the edge device. For example, the factory manager sets a goal of "increasing daily production volume by 10%." The edge device sends this goal to the server and stores it in the server's storage device.

[0437] 2. Generate feedback and advice:

[0438] The server retrieves the goals and tasks from the storage device and inputs them into the AI ​​analysis engine. The AI ​​analysis engine analyzes the manufacturing process data and generates feedback and advice that suggests optimal operations and adjustments. For example, advice may be generated such as "shorten a specific manufacturing step" or "change the placement of operators." The generated feedback is sent to the factory robot's control system.

[0439] 3. Tracking actions and results:

[0440] The robot records its movement data in real time and transmits it to a server, which stores the tracking data in a storage device and monitors its progress.

[0441] 4. Generate progress reports:

[0442] The server periodically retrieves tracking data from the database and generates progress reports, such as "We've achieved a 5% improvement in continuous uptime over the past week and a new 10% increase in production," which are then sent to the factory manager for display.

[0443] 5. Analysis by Emotion Engine:

[0444] The camera and microphone collect the operator's facial expressions and voice and send them to a server. The emotion engine analyzes this data and determines the operator's emotional state (e.g., stress or fatigue).

[0445] 6. Adjusting feedback based on emotions:

[0446] The server integrates and analyzes emotion data and behavioral data to adjust feedback. For example, if an operator is fatigued, the system will provide feedback recommending a break, thereby supporting efficient production and operator health management.

[0447] Examples of specific examples and prompts

[0448] For example, a factory manager may set a goal of "increasing daily production volume by 10%," and the AI ​​analysis engine may suggest "shortening a specific manufacturing step." This suggestion is sent as feedback to the robot and implemented.

[0449] An example prompt is:

[0450] "Please tell me the progress towards today's goal. Please suggest optimal operations and areas that need adjustment based on the operation status of factory robots and operator sentiment data."

[0451] This system not only improves factory productivity but also supports the health management of operators.

[0452] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0453] Step 1:

[0454] The user (factory manager) inputs a goal into the edge device. For example, this goal might be "improve daily production by 10%." The edge device then sends this goal to the server.

[0455] Input: User-entered goal

[0456] Output: Target data sent to the server

[0457] Step 2:

[0458] The server stores the received goals in a storage device, specifically, in a database.

[0459] Input: Target data sent to the server

[0460] Output: Target data stored in memory device

[0461] Step 3:

[0462] The server retrieves the goals and tasks from the storage device and inputs them into the AI ​​analysis engine, which analyzes the data and generates optimal feedback and advice. During this process, machine learning algorithms find patterns in the data and suggest action plans.

[0463] Input: Goals and tasks retrieved from memory

[0464] Output: Feedback and advice generated by the AI ​​analytics engine

[0465] Step 4:

[0466] The server transmits the generated feedback and advice to the control systems of the factory robots, which adjust their operations based on the feedback and advice.

[0467] Input: Feedback and advice generated by the AI ​​analytics engine

[0468] Output: Adjustment of factory robot movements

[0469] Step 5:

[0470] The user (operator) monitors the actions performed by the robot during the manufacturing process, and the robot records the action data in real time and sends it to the server.

[0471] Input: Real-time operational data generated by factory robots

[0472] Output: Operational data sent to the server

[0473] Step 6:

[0474] The server stores the received operational data in a storage device and monitors progress, which is continuously stored in a database and used to generate progress reports.

[0475] Input: Operational data sent to the server

[0476] Output: Operational data stored in a memory device

[0477] Step 7:

[0478] The server periodically retrieves tracking data from the database and generates progress reports, which are then sent to the factory manager for display.

[0479] Input: Tracking data retrieved from the database

[0480] Output: Generated progress report and its display

[0481] Step 8:

[0482] The camera and microphone are used to collect the user's (operator's) emotional data, which includes facial expression recognition and voice analysis, and is sent to the server.

[0483] Input: Emotion data collected from the camera and microphone

[0484] Output: Emotion data sent to the server

[0485] Step 9:

[0486] The server uses an emotion engine to analyze the received emotion data and determine the user's emotional state (e.g., stress or fatigue) based on the analysis results.

[0487] Input: Emotion data sent to the server

[0488] Output: Parsed emotional state data

[0489] Step 10:

[0490] The server integrates and analyzes the emotional state data and behavioral data to adjust the feedback, such as when the user is fatigued, to recommend taking a break.

[0491] Input: Parsed emotional state data and behavioral data

[0492] Output: Regulated Feedback

[0493] This system's series of processes not only improves factory productivity but also effectively manages the health of operators.

[0494] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating 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.

[0495] 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.

[0496] 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.

[0497] [Second embodiment]

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

[0499] 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.

[0500] 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).

[0501] 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.

[0502] 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.

[0503] 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).

[0504] 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.

[0505] 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.

[0506] 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.

[0507] 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.

[0508] 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.

[0509] 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."

[0510] This invention is an AI coaching system that helps businesspeople achieve their goals and maximize their performance. The system receives goals and challenges from users, analyzes them, and generates optimal feedback and advice. It also tracks the user's actions and results and generates regular progress reports. It also provides individualized feedback tailored to the user's personality and preferences, building a relationship of trust and helping the user take effective action toward achieving their goals.

[0511] User goal setting

[0512] Users input their goals and objectives into the terminal. For example, let's say you set a goal of "gaining 10 new clients in the next three months."

[0513] The terminal transmits the inputted goal and task to the server.

[0514] The server stores the received goals and tasks in a storage device.

[0515] Generate feedback and advice

[0516] The server retrieves the goals and challenges stored in the storage device and analyzes them using an AI analysis engine. For example, after analyzing "Strategy for acquiring new customers," it generates feedback such as: "As a next step, we recommend creating a potential customer list and launching an individual email campaign."

[0517] The server transmits the generated feedback and advice to the user terminal.

[0518] The device will display any feedback or advice it receives to the user.

[0519] Tracking actions and results

[0520] The user performs actions to achieve the goal and enters the results into the terminal. For example, they might enter, "I contacted three new customers today."

[0521] The terminal transmits information about the input actions and results to the server.

[0522] The server stores the received actions and results in a storage device and tracks the progress.

[0523] Generate progress reports

[0524] The server periodically analyzes the tracking data and generates progress reports, including the user's behavior history and unachieved goals. For example, a report might be generated that states, "Three new customers were contacted in the past week, and two of them responded positively."

[0525] The server transmits the generated progress report to the user terminal.

[0526] The terminal displays the received progress reports to the user.

[0527] Adjusting individual feedback

[0528] The server tailors the content and format of feedback and advice based on the user's personality and preferences: for example, if the user prefers detailed instructions, it provides feedback detailing specific steps.

[0529] The server communicates with the user to build a trusting relationship and provides coaching tailored to the user's needs and pace.

[0530] The above is a specific embodiment of the present invention. This system allows users to receive effective support for self-development and career advancement. This system provides objective and unbiased support from the user's perspective, greatly contributing to the achievement of businesspeople's goals.

[0531] The processing flow will be explained below.

[0532] Step 1:

[0533] The user inputs their goals and objectives into the terminal. For example, they might input "Acquire 10 new clients in the next three months."

[0534] Step 2:

[0535] The device sends the entered goals and tasks to the server, including the user ID.

[0536] Step 3:

[0537] The server stores the received goals and tasks in a memory device, including storing them in a database in association with the user ID.

[0538] Step 4:

[0539] The server retrieves the goals and tasks from the storage device and inputs them into the AI ​​analysis engine, which then generates optimal feedback and advice for achieving the goals.

[0540] Step 5:

[0541] The server sends the generated feedback and advice to the user device, including a message such as, "As a next step, we recommend that you create a potential customer list and launch a personalized email campaign."

[0542] Step 6:

[0543] The device will display any feedback or advice it receives to the user.

[0544] Step 7:

[0545] Users enter actions they have taken or results they have achieved into the device, for example, "I contacted three new customers today."

[0546] Step 8:

[0547] The device sends the input action and result information to the server. The transmitted data again includes the user ID.

[0548] Step 9:

[0549] The server tracks progress by storing the received actions and achievements in a storage device, which stores each action and achievement with a timestamp.

[0550] Step 10:

[0551] The server periodically retrieves the tracking data from the storage device and generates progress reports, such as "Three new customers were contacted in the past week, with two positive responses."

[0552] Step 11:

[0553] The server transmits the generated progress report to the user terminal.

[0554] Step 12:

[0555] The terminal displays the received progress reports to the user.

[0556] Step 13:

[0557] The server tailors the content and format of feedback and advice based on the user's personality and preferences, including a process of learning the feedback formats and styles that the user has preferred in the past.

[0558] Step 14:

[0559] The server communicates with the user to build trust with them, for example, by periodically sending a survey asking about user satisfaction and areas for improvement.

[0560] The above are the processing steps in a specific embodiment of the present invention. The specific operations for each step are clearly defined, making the overall flow easy to understand.

[0561] Example 1

[0562] 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."

[0563] There is a lack of effective support systems to help businesspeople achieve their goals and maximize their performance. In particular, there is a need for a system that can systematically provide feedback and advice tailored to the characteristics of each user, track actions and results, and generate progress reports. Conventional systems can only provide generic feedback, making it difficult to provide detailed instructions or adaptive support tailored to the characteristics of each individual user.

[0564] 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.

[0565] In this invention, the server includes means for receiving goals and tasks from a user, means for storing the received goals and tasks in a storage device, means for acquiring the stored goals and tasks and analyzing them using a generative AI model, means for generating optimal feedback and advice based on the analysis results, means for transmitting the generated feedback and advice to a user terminal, means for receiving the user's actions and results and storing them in a storage device, means for analyzing the stored actions and results and tracking progress, means for periodically generating progress reports and transmitting them to the user terminal, and means for adjusting the content and format of the generated feedback and advice based on the user's personality and preferences. This makes it possible to provide feedback and advice tailored to the characteristics of each user, and to systematically generate, adjust, track, and report on effective action plans.

[0566] "User" means an individual or organization that uses the system to assist them in achieving their goals.

[0567] "Goal" refers to the specific outcome or target value that the user aims to achieve.

[0568] A "challenge" is a problem or difficulty a user faces that prevents them from achieving their goal.

[0569] "Means for receiving" refers to the interface or function that takes in data provided by the user and inputs it into the system.

[0570] "Memory device" refers to a data storage device for storing received data, behavioral information, outcomes, and analysis results.

[0571] A "generative AI model" is an artificial intelligence model used to analyze a user's goals and challenges and generate feedback and advice.

[0572] The "means of analysis" is a system function that uses a generative AI model to execute the process of analyzing the goals and challenges provided by the user.

[0573] "Feedback" is evaluation information that shows specific action plans and areas for improvement for the goals and challenges provided by the user.

[0574] "Advice" is information that provides guidance on specific actions or strategies that users should take to achieve their goals.

[0575] "User Terminal" means the computer device used by a User to access the System and enter data and view feedback.

[0576] "Behaviors" refer to the specific activities or tasks that users perform to achieve their goals.

[0577] "Results" refers to the results or progress achieved as a result of a user's actions.

[0578] "Progress tracking means" means the system's ability to record user actions and achievements and track progress toward goal achievement in real time.

[0579] The "means for generating periodic progress reports" is a system function that creates progress reports at regular intervals based on the user's behavioral history and results.

[0580] "Personality and Preferences" refers to a user's behavioral patterns, preferences, and personal characteristics that serve as the basis for tailoring feedback and advice.

[0581] "Means for building trust" are system features that communicate with users and provide feedback and advice to build trust.

[0582] The "means for generating an action plan" is a system function that develops specific action steps to achieve the user's goal.

[0583] A "prompt sentence" is an input sentence used to prompt a generative AI model to perform appropriate analysis.

[0584] The present invention is an AI coaching system that helps users achieve their goals and maximize their performance. The system uses the following hardware and software components:

[0585] Hardware Configuration

[0586] 1. Server

[0587] 2. User device (PC, smartphone, etc.)

[0588] 3. Storage Devices (Database Systems)

[0589] Software Configuration

[0590] 1. AI analysis engine (e.g., generative AI model)

[0591] 2. Database management system (e.g., MySQL)

[0592] 3. Communication protocol (e.g. HTTP)

[0593] Setting user goals

[0594] Users input their goals and challenges through the device. For example, they can set a goal of "acquiring 10 new clients in the next three months." The input is done through a dedicated application or a web interface. The device then sends the input goals and challenges to the server.

[0595] Save goal data

[0596] The server stores the received goals and tasks in a database (e.g., MySQL). For example, it registers the goal data in the appropriate table using an INSERT statement.

[0597] Generate feedback and advice

[0598] The server sends the goals and tasks stored in the database to a generative AI model (e.g., GPT-4) using prompts for analysis. For example, the following prompts are used:

[0599] A user has set a goal of acquiring 10 new customers in three months. What next action would you recommend?

[0600] Based on this prompt, the AI ​​analytics engine generates specific strategic feedback, such as, "As a next step, we recommend that you create a prospect list and launch a personalized email campaign."

[0601] Send feedback and advice

[0602] The server sends the generated feedback and advice to the user's device. Specifically, the server returns the generated feedback as an HTTP response and displays it on the user's device.

[0603] Recording actions and achievements

[0604] The user performs actions to achieve the goal and enters the results into the device. For example, they might enter, "Today I contacted three new customers." The device then sends the entered information about the actions and results to the server.

[0605] Behavioral Data Storage

[0606] The server stores the received action and outcome information in a database, for example in a transaction table in the database using the MySQL INSERT statement.

[0607] Generate progress reports

[0608] The server periodically retrieves tracking data from the database and asks the generative AI model to analyze it to generate a progress report, such as "Three new customers were contacted in the past week, and two of them responded positively."

[0609] Sending a progress report

[0610] The server generates a progress report and sends it to the user's device via an HTTP response, where it can be displayed.

[0611] Adjusting individual feedback

[0612] The server tailors the content and format of the feedback and advice based on the user's personality and preferences. For example, it references the user's profile information stored in a database and provides feedback detailing specific steps to users who prefer detailed instructions.

[0613] The above is a specific embodiment of the present invention. This system allows users to receive feedback and advice tailored to their individual characteristics and implement effective action plans to achieve their goals. This makes it possible to systematically support users in improving their performance and achieving their goals.

[0614] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0615] Processing step details

[0616] Step 1:

[0617] The user inputs their goals and challenges into the device. An example input is "Acquire 10 new clients in the next three months." The input data is text data about the user's goals and challenges. The device acquires the input data and sends it to the server via an input form. The data format is JSON or XML.

[0618] Step 2:

[0619] The server analyzes the received goal and task data and stores it in a database. Specifically, it receives an HTTP request, extracts the data, and then stores it using the INSERT statement of a database management system (e.g., MySQL). The input is the goal and task data received from the user, and the output is the data stored in the database.

[0620] Step 3:

[0621] The server retrieves the stored goals and tasks and performs analysis using the generative AI model. Specifically, it retrieves the goals and tasks from the database using a SELECT statement, and then sends the retrieved data to the generative AI model (e.g., GPT-4) with a prompt statement attached. The input is the goal and task data retrieved from the database, and the output is the analysis results obtained from the generative AI model.

[0622] Step 4:

[0623] The server generates optimal feedback and advice based on the analysis results. The specific prompt used is, "The user has set a goal of acquiring 10 new customers in three months. What action do you recommend as the next step?" The generative AI model analyzes this prompt and generates specific feedback and advice. The input is the prompt and the analysis result data, and the output is specific feedback and advice.

[0624] Step 5:

[0625] The server sends the generated feedback and advice to the user terminal. Specifically, it returns the generated feedback and advice to the user terminal as an HTTP response. The input is the generated feedback and advice, and the output is the feedback and advice displayed on the user terminal.

[0626] Step 6:

[0627] The user performs actions to achieve a goal and enters the results into the device. For example, they might enter, "Today I contacted three new customers." The input data is text data about the user's actions and results. The device acquires the input data and sends it to the server. The data format is JSON or XML.

[0628] Step 7:

[0629] The server analyzes the received behavior and outcome data and stores it in a database. Specifically, it receives an HTTP request, extracts the data, and then stores it using the INSERT statement of a database management system (e.g., MySQL). The input is the behavior and outcome data received from the user, and the output is the data stored in the database.

[0630] Step 8:

[0631] The server periodically retrieves tracking data from the database and generates a progress report. Specifically, it retrieves actions and results from the database and generates a progress report based on them. For example, the generated report may include the following: "Three new customers were contacted in the past week, and two of them responded positively." The input is the tracking data retrieved from the database, and the output is the progress report.

[0632] Step 9:

[0633] The server sends the generated progress report to the user terminal. Specifically, it returns the progress report to the user terminal as an HTTP response. The input is the generated progress report, and the output is the progress report displayed on the user terminal.

[0634] Step 10:

[0635] The server adjusts the content and format of the feedback and advice based on the user's personality and preferences. For example, it refers to the user's profile information and provides feedback detailing specific steps to a user who prefers detailed instructions. The input is data about the user's personality and preferences, and the output is tailored feedback and advice.

[0636] The above is a detailed description of the processing steps and specific operations of the system of the present invention, which allows users to receive effective support and implement action plans to achieve their goals.

[0637] (Application example 1)

[0638] 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."

[0639] Conventional AI coaching systems lack specific action plans for achieving users' goals and dynamic adjustments to progress, making it difficult for businesspeople to effectively achieve their goals. In particular, they do not provide enough support to maximize the work efficiency of store staff, which prevents them from improving the overall productivity of stores.

[0640] 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.

[0641] In this invention, the server includes: means for receiving goals and tasks from a user; means for storing the received goals and tasks in a database; means for using an analysis engine to analyze the stored goals and tasks; means for using an artificial intelligence model to generate optimal feedback and advice based on the analysis results; communication means for sending the generated feedback and advice to a user terminal; means for receiving the user's actions and results and storing them in a database; means for analyzing the stored actions and results and tracking progress; means for periodically generating progress reports and sending them to the user terminal; and means for recording the user's actions and results and automatically generating a new action plan from the tracked data. This enables dynamic generation and adjustment of action plans according to the user's progress, maximizing the work efficiency of staff in the physical store and ultimately improving the productivity of the entire physical store.

[0642] "User" refers to any individual or organization that uses the System.

[0643] A "goal" is a specific objective or task that a user wants to achieve.

[0644] "Receiving means" refers to the function of acquiring input information from the user.

[0645] "Database" refers to a storage device that stores received goal and behavior data.

[0646] "Analysis engine" refers to a program or function for processing and analyzing data.

[0647] "Artificial intelligence model" refers to a machine learning algorithm that generates feedback and advice based on user data.

[0648] "Communication means" refers to the function of sending and receiving information between the server and the user terminal.

[0649] "Behavioral data" refers to the specific actions a user takes to achieve their goals and the results of those actions.

[0650] "Tracking tools" refers to features that record user actions and achievements and track progress.

[0651] "Progress Report" means a report summarizing a User's progress toward achieving their Goals.

[0652] An "action plan" refers to the specific procedures or steps a user takes to achieve a goal.

[0653] "Dynamic adjustment" refers to the ability to change plans and feedback in real time based on the user's progress and behavioral data.

[0654] "Brick and mortar store" refers to a retail establishment that sells goods and services at a physical location.

[0655] "Staff" refers to employees working at physical stores.

[0656] This invention is an AI coaching system that helps store staff achieve their goals and maximize work efficiency. The system includes the following components: users input their goals and challenges, analyzes them, generates optimal feedback and advice, tracks the user's actions and results, and generates regular progress reports. Furthermore, by providing individualized feedback tailored to the user's personality and preferences and building a relationship of trust, the system helps the user take effective action toward achieving their goals.

[0657] goal setting

[0658] Users input their goals and challenges into a smartphone app or tablet device. A specific example goal might be "Acquire 10 new clients in the next three months." The entered goals are sent to the server and stored in a database.

[0659] Generate feedback and advice

[0660] The server retrieves the goals and challenges stored in the database and analyzes them using an AI analysis engine (for example, OpenAI's GPT-4). For example, after analyzing "Strategy for Acquiring New Customers," the server generates feedback such as: "As a next step, we recommend creating a potential customer list and launching a personalized email campaign." The generated feedback is then sent to the user's device.

[0661] Tracking actions and results

[0662] Users take actions to achieve their goals and enter their results into the device. For example, "Today, I will enter how I contacted three new customers." The entered information about actions and results is sent to the server and stored in a database. The server analyzes this information and tracks the user's progress.

[0663] Generate progress reports

[0664] The server periodically analyzes the stored data and generates a progress report. The generated report includes the user's behavior history and unachieved goals. A specific example could be a report that states, "Three new customers were contacted in the past week, and two of them responded positively." The generated report is sent to the user's device.

[0665] Adjusting individual feedback

[0666] The server tailors the content and format of feedback and advice based on the user's personality and preferences. For example, if the user prefers detailed instructions, it provides feedback detailing specific steps. It also communicates with the user to build trust and provides coaching tailored to the user's needs and pace.

[0667] Technology used

[0668] Language: Python

[0669] Framework: Flask (server side)

[0670] Database: PostgreSQL

[0671] AI model: OpenAI's GPT-4

[0672] Device: iOS / Android compatible mobile app

[0673] Prompt Sentence Examples

[0674] Input the following prompts into the AI ​​model to generate specific feedback.

[0675] "User goal: Acquire 5 new customers in the next month

[0676] We recommend the following steps:

[0677] As described above, this invention is a system that provides specific and dynamic action plans to support users in achieving their goals, and is effective in maximizing the work efficiency of staff in physical stores.

[0678] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0679] Step 1:

[0680] Users input their goals and challenges into a smartphone app or tablet device. The input content is specific, such as "Acquire 10 new clients in the next three months." The input goals and challenges are sent to the server as structured data by the device. The server receives this data and stores it in a database.

[0681] Step 2:

[0682] The server retrieves the goals and challenges stored in the database. Next, it analyzes the goals and challenges using an AI analysis engine (for example, OpenAI's GPT-4). The analysis prompt uses the following: "User's goal: Acquire five new customers in the next month. Recommend next steps." The feedback generated as a result of the analysis includes specific steps, such as "We recommend creating a potential customer list and launching an individual email campaign."

[0683] Step 3:

[0684] The server sends the generated feedback and advice to the user terminal, which receives it and displays the feedback on the user's display, allowing the user to take specific action based on the feedback.

[0685] Step 4:

[0686] The user performs actions to achieve a goal and enters the results into the device. For example, they enter the results of their actions, such as "I contacted three new customers today." The entered action data is sent from the device to the server and stored in a database.

[0687] Step 5:

[0688] The server retrieves the received behavioral data from the database and analyzes the progress. As a result of the analysis, progress is tracked and a progress report is generated in the form of, for example, "Three new customers were contacted in the past week, and two of them responded positively." The tracking data is dynamically updated using an AI model.

[0689] Step 6:

[0690] The server then sends the generated progress report to the user's device, where it is displayed to the user, who can then check their own progress. This progress report includes a history of actions and unachieved goals.

[0691] Step 7:

[0692] The server adjusts the content and format of feedback and advice based on the user's personality and preferences. For example, it provides feedback detailing specific steps to users who prefer detailed instructions. This adjustment makes it possible to provide optimal coaching for each user. Based on user feedback, the server builds trust and continues to approach the user according to their individual needs and pace.

[0693] By following these steps, the system can effectively support users in achieving their goals and maximize the work efficiency of store staff.

[0694] 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.

[0695] This invention is an AI coaching system that helps businesspeople achieve their goals and maximize their performance. The system includes a means for receiving, storing, and analyzing a user's goals and challenges, and a means for providing generated feedback and advice. Furthermore, the system tracks the user's actions and achievements and periodically generates progress reports. It also provides personalized feedback based on the user's personality and preferences, and includes an emotion engine that recognizes the user's emotions, allowing it to adjust the feedback based on the user's emotions.

[0696] User goal setting and reception

[0697] Users input their goals and objectives into the terminal. For example, they can set a goal of "gaining 10 new clients in the next three months."

[0698] The terminal transmits the input goal and task data to the server.

[0699] The server stores the goals and tasks in a storage device.

[0700] Generate feedback and advice

[0701] The server retrieves the goals and challenges stored in the storage device and inputs them into the AI ​​analysis engine. The AI ​​analysis engine generates feedback and advice based on the strategy and specific action plan for achieving the goals. For example, "To acquire new customers, we recommend that you create a list of potential customers and begin individual approaches via email and phone."

[0702] The server transmits the generated feedback and advice to the user terminal.

[0703] The device will display any feedback or advice received to the user.

[0704] Tracking actions and results

[0705] The user performs an action to achieve the goal and enters it into the terminal. For example, "I contacted three new customers today."

[0706] The terminal transmits the input action and outcome data to the server.

[0707] The server stores user actions and achievements on a storage device to track progress and saves the data with a timestamp.

[0708] Generate and send status reports

[0709] The server periodically retrieves the tracking data from the storage device and generates progress reports, such as "Three new customers were contacted in the past week, with two positive responses."

[0710] The server sends the generated progress report to the user terminal.

[0711] The terminal displays received progress reports to the user.

[0712] Analysis by emotion engine

[0713] The server is also equipped with an emotion engine that recognizes the user's emotions.

[0714] The emotion engine analyzes information entered by the user into the device and real-time emotional data obtained from the device's camera and microphone. For example, it can determine whether the user is feeling stressed by analyzing facial expressions and voice tones.

[0715] The server records the emotion data recognized by the emotion engine and analyzes the user's emotional tendencies.

[0716] Adjusting Feedback Based on Emotions

[0717] The server integrates and analyzes the user's emotional and behavioral data, and generates feedback that takes into account the correlation between emotions and behavior. For example, if the user is tired, it can suggest relaxation methods to help them achieve their goals.

[0718] The server adjusts the generated feedback based on the emotional data as needed to provide optimal advice to the user.

[0719] The above is a specific embodiment of the present invention. The system can effectively support users in achieving their goals by providing personalized feedback based on the user's personality and preferences and adjusting advice based on emotions using an emotion engine.

[0720] The processing flow will be explained below.

[0721] Step 1:

[0722] The user inputs their goals and objectives into the terminal. For example, they can set "to acquire 10 new clients in the next three months."

[0723] Step 2:

[0724] The device sends the entered goal and task data to the server, including the user ID.

[0725] Step 3:

[0726] The server stores the received goals and tasks in a memory device, which stores them in a database containing the goals, tasks, and user IDs.

[0727] Step 4:

[0728] The server retrieves the goals and tasks from the storage device and inputs them into the AI ​​analysis engine, which then generates optimal feedback and advice to help the user achieve their goals.

[0729] Step 5:

[0730] The server sends the generated feedback and advice to the user's device, for example, a message saying, "We recommend that you create a potential customer list and launch a personalized email campaign on a specific date."

[0731] Step 6:

[0732] The device will display any feedback or advice received to the user.

[0733] Step 7:

[0734] Based on the feedback, the user takes specific actions and enters them into the device, for example, "I contacted three new customers today."

[0735] Step 8:

[0736] The device sends the input data of the actions and results to the server. The data includes the user ID, the action, and the results.

[0737] Step 9:

[0738] The server stores the received actions and results in a storage device and tracks the progress. It records the user's actions and results with timestamps.

[0739] Step 10:

[0740] The server periodically retrieves the tracking data from the storage device and generates progress reports, such as "Three new customers were contacted in the past week, and two responded positively."

[0741] Step 11:

[0742] The server sends the generated progress report to the user terminal.

[0743] Step 12:

[0744] The terminal displays received progress reports to the user.

[0745] Step 13:

[0746] The server tailors the content and format of the feedback and advice based on the user's personality and preferences, for example, if the user prefers detailed instructions, it provides feedback with specific steps.

[0747] Step 14:

[0748] The server sends data from the device (camera, microphone, text input, etc.) to the emotion engine to analyze the user's emotions in real time. The emotion engine analyzes the user's facial expressions and tone of voice to determine whether the user is feeling stressed.

[0749] Step 15:

[0750] The server stores the emotional data recognized by the emotion engine in a storage device and analyzes the user's emotional tendencies. The emotional data also records changes over time.

[0751] Step 16:

[0752] The server integrates and analyzes the user's emotional and behavioral data, and generates feedback that takes into account the correlation between emotions and behavior. For example, it may provide feedback such as, "Your recent behavior seems to be causing you stress. We recommend that you try relaxation techniques."

[0753] The above are the processing steps in a specific embodiment of the present invention. The specific operations performed in each step are clearly defined, making the overall flow easy to understand.

[0754] Example 2

[0755] 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."

[0756] Today's businesspeople are busy, and self-management, the formulation of action plans to achieve goals, and progress management require a great deal of time and effort. It is also difficult for them to receive appropriate feedback and advice in response to emotional changes and stress levels. Conventional systems do not adequately adjust feedback to reflect the user's individual emotional state, and are therefore unable to effectively support users in maintaining their motivation or improving their performance.

[0757] 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.

[0758] In this invention, the server includes means for receiving goals and tasks from a user, means for storing the received goals and tasks in a storage device, means for analyzing the stored goals and tasks, means for generating optimal feedback and advice based on the analysis results, means for transmitting the generated feedback and advice to a user terminal, means for receiving the user's actions and results and storing them in a storage device, means for analyzing the stored actions and results and tracking progress, means for periodically generating progress reports and transmitting them to the user terminal, means for receiving and analyzing the user's emotional data, and means for adjusting feedback based on the emotional data. This makes it possible to effectively support the user in achieving their goals and provide personalized feedback according to their emotional state.

[0759] "Goals and challenges" refers to the specific objectives the user wants to achieve and the problems they need to address.

[0760] "Means for receiving" refers to an interface for obtaining data input by a user.

[0761] "Storage device" refers to a database or storage system for saving received data.

[0762] "Means for analyzing" refers to algorithms or software that analyze the stored data and generate appropriate action plans or feedback.

[0763] "Feedback and Advice" refers to specific guidelines and advice provided to users based on the analysis results.

[0764] "Means for sending" refers to a communication system for sending the generated feedback or advice to a user terminal.

[0765] "User terminal" refers to a device used by a user, such as a computer, smartphone, or tablet.

[0766] "Actions and Results" refers to the actions actually taken by the user and the results obtained as a result thereof.

[0767] "Progress tracking means" refers to a system for recording user actions and achievements and monitoring progress.

[0768] "Progress Report" refers to a report that is generated periodically that summarizes a user's actions and achievements.

[0769] "Emotion data" is data that indicates the user's emotional state, and includes, for example, stress level and fatigue level.

[0770] An "emotion engine" refers to software or algorithms that analyze users' emotional data and reflect the results in feedback and advice.

[0771] This invention is an AI coaching system that helps businesspeople achieve their goals and maximize their performance. The system includes a means for receiving, storing, and analyzing a user's goals and challenges, and a means for providing generated feedback and advice. Furthermore, the system tracks the user's actions and achievements and periodically generates progress reports. It also includes an emotion engine that recognizes the user's emotions and can adjust feedback based on the emotion data.

[0772] Hardware and Software Use

[0773] The terminal provides an interface for users to input goals and tasks. Terminals can be smartphones, PCs, tablets, etc. These terminals are equipped with a network communication module and send data to the server.

[0774] The server integrates several key components. The database system uses a relational database management system such as PostgreSQL. The generative AI model uses OpenAI GPT-4 and other models to generate feedback and advice for achieving goals. The emotion engine uses Microsoft Azure Emotion API and other models to analyze user emotion data.

[0775] Examples of specific examples and prompts

[0776] For example, if a user sets a goal of "acquiring 10 new clients in the next three months," that information is sent to the server via the device and stored in a database. The server retrieves this goal data, inputs it into a generative AI model for analysis, and generates feedback such as the following:

[0777] "Next week, I recommend creating a prospect list and contacting 10 more companies."

[0778] If the user then reports that they "contacted three new customers today," that data is also sent to the server via the device and tracked.

[0779] Additionally, emotional data is collected. For example, the device's camera and microphone are used to capture the user's facial expressions and tone of voice, and the captured data is sent to a server. The server analyzes this emotional data and adjusts the feedback accordingly if the user is experiencing high levels of stress.

[0780] Here are some example prompts to input to the generative AI model:

[0781] Goal: Acquire 10 new clients

[0782] This week's action: Created a list of potential clients and contacted three companies.

[0783] Perceived stress level: High

[0784] Using the information below, suggest a specific action plan for the user for the next week and some advice on how to reduce stress.

[0785] User goal: Acquire 10 new customers

[0786] Action: This week I created a list of potential clients and contacted three of them.

[0787] Current Emotion: High stress levels

[0788] Suggestion Feedback:

[0789] 1. Specific action plan for next week

[0790] 2. Advice for reducing stress

[0791] This completes the description of the embodiment of the invention. This system supports users in achieving their goals and provides feedback according to their individual emotional state, thereby maintaining their motivation and improving their performance.

[0792] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0793] Step 1:

[0794] The user inputs their goals and objectives into the terminal. For example, they might input "Acquire 10 new clients in the next three months."

[0795] Input: Goals and challenges set by the user.

[0796] Data processing: Convert the goal and task data entered on the terminal into JSON format.

[0797] Output: Goal and assignment data in JSON format.

[0798] Step 2:

[0799] The terminal sends the entered goal and task data to the server, and the content entered by the user is sent via the network module.

[0800] Input: Goal and assignment data in JSON format.

[0801] Data operation: Send data to the server using a network protocol (e.g., HTTP POST request).

[0802] Output: The goal and task data sent to the server.

[0803] Step 3:

[0804] The server stores the received goals and tasks in a database, which is created using PostgreSQL.

[0805] Input: Goal and task data received by the server.

[0806] Data processing: Convert JSON format data into SQL insert statements and store them in the database.

[0807] Output: Goal and task data stored in a database.

[0808] Step 4:

[0809] The server retrieves the target data from the database and provides it to the generative AI model, which uses OpenAI GPT-4.

[0810] Input: Target data in the database.

[0811] Data Calculation: Converting goal data into prompts for the AI, such as "User-defined goal: Acquire 10 new customers."

[0812] Output: The prompt that is input to the generative AI model.

[0813] Step 5:

[0814] Generative AI models generate feedback and advice to help you achieve your goals.

[0815] Input: Prompt data.

[0816] Data computation: A generative AI model analyzes the prompts and generates appropriate feedback and advice, such as, "We recommend that you build a lead list next week and contact 10 more companies."

[0817] Output: Generated feedback and advice.

[0818] Step 6:

[0819] The server transmits the generated feedback and advice to the user terminal.

[0820] Input: Generated feedback and advice data.

[0821] Data operation: Sends data to the user terminal using a network protocol (e.g., HTTP POST request).

[0822] Output: Feedback and advice data sent to the user device.

[0823] Step 7:

[0824] The device will display the received feedback and advice to the user.

[0825] Input: Feedback and advice data sent by the server.

[0826] Data processing: Converting data into a format that can be displayed on the screen, for example, as a text message.

[0827] Output: Feedback and advice displayed to the user.

[0828] Step 8:

[0829] The user enters the actions or results they have achieved into the terminal. For example, they might enter, "I contacted three new customers today."

[0830] Input: User behavior and outcome data.

[0831] Data processing: Converts the action and result data entered on the device into JSON format.

[0832] Output: Behavior and outcome data in JSON format.

[0833] Step 9:

[0834] The terminal transmits the input action and outcome data to the server.

[0835] Input: Action and outcome data in JSON format.

[0836] Data operation: Send data to the server using a network protocol (e.g., HTTP POST request).

[0837] Output: Action and outcome data sent to the server.

[0838] Step 10:

[0839] The server records the received action and outcome data in a database to track progress.

[0840] Input: Action and outcome data received by the server.

[0841] Data processing: Converting JSON data into SQL insert statements and storing them in the database. The saved data is then fed into a progress tracking algorithm to update the progress.

[0842] Output: Behavioral and outcome data recorded in a database, updated progress.

[0843] Step 11:

[0844] The server periodically retrieves the progress data from the database and generates a progress report.

[0845] Input: Progress data in the database.

[0846] Data processing: Aggregate progress data and convert it into a report format, for example, "Contacted three new customers in the past week and received positive responses from two."

[0847] Output: The generated progress report.

[0848] Step 12:

[0849] The server transmits the generated progress report to the user terminal.

[0850] Input: Generated progress report data.

[0851] Data operation: Sends data to the user terminal using a network protocol (e.g., HTTP POST request).

[0852] Output: Progress report sent to user terminal.

[0853] Step 13:

[0854] The terminal displays the received progress report to the user.

[0855] Input: Progress report data sent by the server.

[0856] Data processing: Converting data into a format that can be displayed on the screen, for example, as a text message.

[0857] Output: A progress report displayed to the user.

[0858] Step 14:

[0859] The server analyzes the emotion data obtained from the user.

[0860] Input: User emotion data (e.g., facial capture, voice tone).

[0861] Data Calculation: Uses an emotion engine to analyze emotion data and identify the user's emotional state. For example, high stress level, high fatigue.

[0862] Output: Parsed emotional state data.

[0863] Step 15:

[0864] The server adjusts the feedback based on the emotion data.

[0865] Input: Parsed emotion data and progress data.

[0866] Data Computation: Using generative AI models to regenerate or adjust feedback while taking into account emotional data. Example: Suggesting relaxation techniques for a stressed user.

[0867] Output: Tailored feedback and advice.

[0868] Step 16:

[0869] The device displays tailored feedback to the user.

[0870] Input: Adjusted feedback data sent by the server.

[0871] Data processing: Converting data into a format that can be displayed on the screen, for example, as a text message.

[0872] Output: The adjusted feedback and advice displayed to the user.

[0873] (Application example 2)

[0874] 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."

[0875] Conventional factory robot systems have not adequately optimized production processes or managed the health of operators, leaving challenges in efficient robot operation and reducing operator stress. Furthermore, there is a lack of systems that go beyond simply analyzing production data and provide feedback based on the operator's emotional state. The present invention aims to solve these challenges by providing a system that maximizes the efficiency of factory robots and manages operator stress.

[0876] 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 receiving a user's goals and tasks, means for storing the received goals and tasks in a storage device, means for analyzing the stored goals and tasks, means for generating optimal feedback and advice based on the analysis results, means for transmitting the generated feedback and advice to a user terminal, means for receiving a user's actions and results and storing them in a storage device, means for analyzing the stored actions and results and tracking progress, means for periodically generating progress reports and transmitting them to the user terminal, means for collecting user emotion data, means for analyzing the user emotion data and adjusting feedback based on the emotions, and means for integrating and analyzing the user emotion data and behavioral data. This makes it possible to optimize the operation of a factory robot and provide feedback according to the operator's emotional state.

[0877] "Users" refer to factory managers and operators who use the system.

[0878] A "goal" is a specific production figure or result that the user wants to achieve.

[0879] A "challenge" is a problem or obstacle that a user must solve to achieve their goal.

[0880] A "means" is a method or device used to achieve a particular purpose.

[0881] "Storage device" refers to hardware or software for storing data.

[0882] A "server" is a centralized device for processing and storing data.

[0883] An "AI analysis engine" is software that uses artificial intelligence to analyze data and generate optimal feedback and advice.

[0884] "Feedback" is an evaluation or advice regarding the user's behavior or situation.

[0885] "Advice" is advice on actions or measures users should take to achieve their goals.

[0886] A "user terminal" is a device (e.g., a computer, a smartphone) that is directly operated by a user.

[0887] An "action" is a specific task that a user performs to achieve a goal.

[0888] "Results" refers to the results achieved by a user through their actions.

[0889] "Progress" is information that shows the progress of actions and results toward achieving a goal.

[0890] A "progress report" is a report summarizing progress.

[0891] "Emotional data" is information about a user's emotional state (e.g., stress, fatigue).

[0892] An "emotion engine" is software for analyzing user emotional data.

[0893] "Adjusting feedback based on emotion" means changing the content of feedback or advice based on the user's emotional state.

[0894] "Operation data" is information about the tasks and movements being performed by a factory robot.

[0895] "Tracking" means the continuous monitoring and recording of certain information.

[0896] This invention is an AI coaching system for optimizing manufacturing processes using factory robots and managing operator stress. The system includes means for receiving, storing, and analyzing user (factory manager or operator) goals and challenges, generating and sending feedback and advice, tracking behavior and results, generating progress reports, collecting and analyzing emotional data, and adjusting feedback.

[0897] Explaining program processing in natural language

[0898] The hardware used includes factory robots (e.g., general-purpose robotic devices), cameras (e.g., general-purpose webcams), and microphones (e.g., general-purpose USB microphones).The software used includes AI analysis engines (e.g., TensorFlow, PyTorch), emotion engines (e.g., Affectiva SDK), databases (e.g., PostgreSQL), and communication protocols (e.g., MQTT).

[0899] 1. Goal setting and receiving:

[0900] The server receives the goal entered by the factory manager into the edge device. For example, the factory manager sets a goal of "increasing daily production volume by 10%." The edge device sends this goal to the server and stores it in the server's storage device.

[0901] 2. Generate feedback and advice:

[0902] The server retrieves the goals and tasks from the storage device and inputs them into the AI ​​analysis engine. The AI ​​analysis engine analyzes the manufacturing process data and generates feedback and advice that suggests optimal operations and adjustments. For example, advice may be generated such as "shorten a specific manufacturing step" or "change the placement of operators." The generated feedback is sent to the factory robot's control system.

[0903] 3. Tracking actions and results:

[0904] The robot records its movement data in real time and transmits it to a server, which stores the tracking data in a storage device and monitors its progress.

[0905] 4. Generate progress reports:

[0906] The server periodically retrieves tracking data from the database and generates progress reports, such as "We've achieved a 5% improvement in continuous uptime over the past week and a new 10% increase in production," which are then sent to the factory manager for display.

[0907] 5. Analysis by Emotion Engine:

[0908] The camera and microphone collect the operator's facial expressions and voice and send them to a server. The emotion engine analyzes this data and determines the operator's emotional state (e.g., stress or fatigue).

[0909] 6. Adjusting feedback based on emotions:

[0910] The server integrates and analyzes emotion data and behavioral data to adjust feedback. For example, if an operator is fatigued, the system will provide feedback recommending a break, thereby supporting efficient production and operator health management.

[0911] Examples of specific examples and prompts

[0912] For example, a factory manager may set a goal of "increasing daily production volume by 10%," and the AI ​​analysis engine may suggest "shortening a specific manufacturing step." This suggestion is sent as feedback to the robot and implemented.

[0913] An example prompt is:

[0914] "Please tell me the progress towards today's goal. Please suggest optimal operations and areas that need adjustment based on the operation status of factory robots and operator sentiment data."

[0915] This system not only improves factory productivity but also supports the health management of operators.

[0916] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0917] Step 1:

[0918] The user (factory manager) inputs a goal into the edge device. For example, this goal might be "improve daily production by 10%." The edge device then sends this goal to the server.

[0919] Input: User-entered goal

[0920] Output: Target data sent to the server

[0921] Step 2:

[0922] The server stores the received goals in a storage device, specifically, in a database.

[0923] Input: Target data sent to the server

[0924] Output: Target data stored in memory device

[0925] Step 3:

[0926] The server retrieves the goals and tasks from the storage device and inputs them into the AI ​​analysis engine, which analyzes the data and generates optimal feedback and advice. During this process, machine learning algorithms find patterns in the data and suggest action plans.

[0927] Input: Goals and tasks retrieved from memory

[0928] Output: Feedback and advice generated by the AI ​​analytics engine

[0929] Step 4:

[0930] The server transmits the generated feedback and advice to the control systems of the factory robots, which adjust their operations based on the feedback and advice.

[0931] Input: Feedback and advice generated by the AI ​​analytics engine

[0932] Output: Adjustment of factory robot movements

[0933] Step 5:

[0934] The user (operator) monitors the actions performed by the robot during the manufacturing process, and the robot records the action data in real time and sends it to the server.

[0935] Input: Real-time operational data generated by factory robots

[0936] Output: Operational data sent to the server

[0937] Step 6:

[0938] The server stores the received operational data in a storage device and monitors progress, which is continuously stored in a database and used to generate progress reports.

[0939] Input: Operational data sent to the server

[0940] Output: Operational data stored in a memory device

[0941] Step 7:

[0942] The server periodically retrieves tracking data from the database and generates progress reports, which are then sent to the factory manager for display.

[0943] Input: Tracking data retrieved from the database

[0944] Output: Generated progress report and its display

[0945] Step 8:

[0946] The camera and microphone are used to collect the user's (operator's) emotional data, which includes facial expression recognition and voice analysis, and is sent to the server.

[0947] Input: Emotion data collected from the camera and microphone

[0948] Output: Emotion data sent to the server

[0949] Step 9:

[0950] The server uses an emotion engine to analyze the received emotion data and determine the user's emotional state (e.g., stress or fatigue) based on the analysis results.

[0951] Input: Emotion data sent to the server

[0952] Output: Parsed emotional state data

[0953] Step 10:

[0954] The server integrates and analyzes the emotional state data and behavioral data to adjust the feedback, such as when the user is fatigued, to recommend taking a break.

[0955] Input: Parsed emotional state data and behavioral data

[0956] Output: Regulated Feedback

[0957] This system's series of processes not only improves factory productivity but also effectively manages the health of operators.

[0958] 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.

[0959] 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.

[0960] 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.

[0961] [Third embodiment]

[0962] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0963] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0964] 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).

[0965] 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.

[0966] 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.

[0967] 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).

[0968] 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.

[0969] 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.

[0970] 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.

[0971] 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.

[0972] 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.

[0973] 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."

[0974] This invention is an AI coaching system that helps businesspeople achieve their goals and maximize their performance. The system receives goals and challenges from users, analyzes them, and generates optimal feedback and advice. It also tracks the user's actions and results and generates regular progress reports. It also provides individualized feedback tailored to the user's personality and preferences, building a relationship of trust and helping the user take effective action toward achieving their goals.

[0975] User goal setting

[0976] Users input their goals and objectives into the terminal. For example, let's say you set a goal of "gaining 10 new clients in the next three months."

[0977] The terminal transmits the inputted goal and task to the server.

[0978] The server stores the received goals and tasks in a storage device.

[0979] Generate feedback and advice

[0980] The server retrieves the goals and challenges stored in the storage device and analyzes them using an AI analysis engine. For example, after analyzing "Strategy for acquiring new customers," it generates feedback such as: "As a next step, we recommend creating a potential customer list and launching an individual email campaign."

[0981] The server transmits the generated feedback and advice to the user terminal.

[0982] The device will display any feedback or advice it receives to the user.

[0983] Tracking actions and results

[0984] The user performs actions to achieve the goal and enters the results into the terminal. For example, they might enter, "I contacted three new customers today."

[0985] The terminal transmits information about the input actions and results to the server.

[0986] The server stores the received actions and results in a storage device and tracks the progress.

[0987] Generate progress reports

[0988] The server periodically analyzes the tracking data and generates progress reports, including the user's behavior history and unachieved goals. For example, a report might be generated that states, "Three new customers were contacted in the past week, and two of them responded positively."

[0989] The server transmits the generated progress report to the user terminal.

[0990] The terminal displays the received progress reports to the user.

[0991] Adjusting individual feedback

[0992] The server tailors the content and format of feedback and advice based on the user's personality and preferences: for example, if the user prefers detailed instructions, it provides feedback detailing specific steps.

[0993] The server communicates with the user to build a trusting relationship and provides coaching tailored to the user's needs and pace.

[0994] The above is a specific embodiment of the present invention. This system allows users to receive effective support for self-development and career advancement. This system provides objective and unbiased support from the user's perspective, greatly contributing to the achievement of businesspeople's goals.

[0995] The processing flow will be explained below.

[0996] Step 1:

[0997] The user inputs their goals and objectives into the terminal. For example, they might input "Acquire 10 new clients in the next three months."

[0998] Step 2:

[0999] The device sends the entered goals and tasks to the server, including the user ID.

[1000] Step 3:

[1001] The server stores the received goals and tasks in a memory device, including storing them in a database in association with the user ID.

[1002] Step 4:

[1003] The server retrieves the goals and tasks from the storage device and inputs them into the AI ​​analysis engine, which then generates optimal feedback and advice for achieving the goals.

[1004] Step 5:

[1005] The server sends the generated feedback and advice to the user device, including a message such as, "As a next step, we recommend that you create a potential customer list and launch a personalized email campaign."

[1006] Step 6:

[1007] The device will display any feedback or advice it receives to the user.

[1008] Step 7:

[1009] Users enter actions they have taken or results they have achieved into the device, for example, "I contacted three new customers today."

[1010] Step 8:

[1011] The device sends the input action and result information to the server. The transmitted data again includes the user ID.

[1012] Step 9:

[1013] The server tracks progress by storing the received actions and achievements in a storage device, which stores each action and achievement with a timestamp.

[1014] Step 10:

[1015] The server periodically retrieves the tracking data from the storage device and generates progress reports, such as "Three new customers were contacted in the past week, with two positive responses."

[1016] Step 11:

[1017] The server transmits the generated progress report to the user terminal.

[1018] Step 12:

[1019] The terminal displays the received progress reports to the user.

[1020] Step 13:

[1021] The server tailors the content and format of feedback and advice based on the user's personality and preferences, including a process of learning the feedback formats and styles that the user has preferred in the past.

[1022] Step 14:

[1023] The server communicates with the user to build trust with them, for example, by periodically sending a survey asking about user satisfaction and areas for improvement.

[1024] The above are the processing steps in a specific embodiment of the present invention. The specific operations for each step are clearly defined, making the overall flow easy to understand.

[1025] Example 1

[1026] 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."

[1027] There is a lack of effective support systems to help businesspeople achieve their goals and maximize their performance. In particular, there is a need for a system that can systematically provide feedback and advice tailored to the characteristics of each user, track actions and results, and generate progress reports. Conventional systems can only provide generic feedback, making it difficult to provide detailed instructions or adaptive support tailored to the characteristics of each individual user.

[1028] 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.

[1029] In this invention, the server includes means for receiving goals and tasks from a user, means for storing the received goals and tasks in a storage device, means for acquiring the stored goals and tasks and analyzing them using a generative AI model, means for generating optimal feedback and advice based on the analysis results, means for transmitting the generated feedback and advice to a user terminal, means for receiving the user's actions and results and storing them in a storage device, means for analyzing the stored actions and results and tracking progress, means for periodically generating progress reports and transmitting them to the user terminal, and means for adjusting the content and format of the generated feedback and advice based on the user's personality and preferences. This makes it possible to provide feedback and advice tailored to the characteristics of each user, and to systematically generate, adjust, track, and report on effective action plans.

[1030] "User" means an individual or organization that uses the system to assist them in achieving their goals.

[1031] "Goal" refers to the specific outcome or target value that the user aims to achieve.

[1032] A "challenge" is a problem or difficulty a user faces that prevents them from achieving their goal.

[1033] "Means for receiving" refers to the interface or function that takes in data provided by the user and inputs it into the system.

[1034] "Memory device" refers to a data storage device for storing received data, behavioral information, outcomes, and analysis results.

[1035] A "generative AI model" is an artificial intelligence model used to analyze a user's goals and challenges and generate feedback and advice.

[1036] The "means of analysis" is a system function that uses a generative AI model to execute the process of analyzing the goals and challenges provided by the user.

[1037] "Feedback" is evaluation information that shows specific action plans and areas for improvement for the goals and challenges provided by the user.

[1038] "Advice" is information that provides guidance on specific actions or strategies that users should take to achieve their goals.

[1039] "User Terminal" means the computer device used by a User to access the System and enter data and view feedback.

[1040] "Behaviors" refer to the specific activities or tasks that users perform to achieve their goals.

[1041] "Results" refers to the results or progress achieved as a result of a user's actions.

[1042] "Progress tracking means" means the system's ability to record user actions and achievements and track progress toward goal achievement in real time.

[1043] The "means for generating periodic progress reports" is a system function that creates progress reports at regular intervals based on the user's behavioral history and results.

[1044] "Personality and Preferences" refers to a user's behavioral patterns, preferences, and personal characteristics that serve as the basis for tailoring feedback and advice.

[1045] "Means for building trust" are system features that communicate with users and provide feedback and advice to build trust.

[1046] The "means for generating an action plan" is a system function that develops specific action steps to achieve the user's goal.

[1047] A "prompt sentence" is an input sentence used to prompt a generative AI model to perform appropriate analysis.

[1048] The present invention is an AI coaching system that helps users achieve their goals and maximize their performance. The system uses the following hardware and software components:

[1049] Hardware Configuration

[1050] 1. Server

[1051] 2. User device (PC, smartphone, etc.)

[1052] 3. Storage Devices (Database Systems)

[1053] Software Configuration

[1054] 1. AI analysis engine (e.g., generative AI model)

[1055] 2. Database management system (e.g., MySQL)

[1056] 3. Communication protocol (e.g. HTTP)

[1057] Setting user goals

[1058] Users input their goals and challenges through the device. For example, they can set a goal of "acquiring 10 new clients in the next three months." The input is done through a dedicated application or a web interface. The device then sends the input goals and challenges to the server.

[1059] Save goal data

[1060] The server stores the received goals and tasks in a database (e.g., MySQL). For example, it registers the goal data in the appropriate table using an INSERT statement.

[1061] Generate feedback and advice

[1062] The server sends the goals and tasks stored in the database to a generative AI model (e.g., GPT-4) using prompts for analysis. For example, the following prompts are used:

[1063] A user has set a goal of acquiring 10 new customers in three months. What next action would you recommend?

[1064] Based on this prompt, the AI ​​analytics engine generates specific strategic feedback, such as, "As a next step, we recommend that you create a prospect list and launch a personalized email campaign."

[1065] Send feedback and advice

[1066] The server sends the generated feedback and advice to the user's device. Specifically, the server returns the generated feedback as an HTTP response and displays it on the user's device.

[1067] Recording actions and achievements

[1068] The user performs actions to achieve the goal and enters the results into the device. For example, they might enter, "Today I contacted three new customers." The device then sends the entered information about the actions and results to the server.

[1069] Behavioral Data Storage

[1070] The server stores the received action and outcome information in a database, for example in a transaction table in the database using the MySQL INSERT statement.

[1071] Generate progress reports

[1072] The server periodically retrieves tracking data from the database and asks the generative AI model to analyze it to generate a progress report, such as "Three new customers were contacted in the past week, and two of them responded positively."

[1073] Sending a progress report

[1074] The server generates a progress report and sends it to the user's device via an HTTP response, where it can be displayed.

[1075] Adjusting individual feedback

[1076] The server tailors the content and format of the feedback and advice based on the user's personality and preferences. For example, it references the user's profile information stored in a database and provides feedback detailing specific steps to users who prefer detailed instructions.

[1077] The above is a specific embodiment of the present invention. This system allows users to receive feedback and advice tailored to their individual characteristics and implement effective action plans to achieve their goals. This makes it possible to systematically support users in improving their performance and achieving their goals.

[1078] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1079] Processing step details

[1080] Step 1:

[1081] The user inputs their goals and challenges into the device. An example input is "Acquire 10 new clients in the next three months." The input data is text data about the user's goals and challenges. The device acquires the input data and sends it to the server via an input form. The data format is JSON or XML.

[1082] Step 2:

[1083] The server analyzes the received goal and task data and stores it in a database. Specifically, it receives an HTTP request, extracts the data, and then stores it using the INSERT statement of a database management system (e.g., MySQL). The input is the goal and task data received from the user, and the output is the data stored in the database.

[1084] Step 3:

[1085] The server retrieves the stored goals and tasks and performs analysis using the generative AI model. Specifically, it retrieves the goals and tasks from the database using a SELECT statement, and then sends the retrieved data to the generative AI model (e.g., GPT-4) with a prompt statement attached. The input is the goal and task data retrieved from the database, and the output is the analysis results obtained from the generative AI model.

[1086] Step 4:

[1087] The server generates optimal feedback and advice based on the analysis results. The specific prompt used is, "The user has set a goal of acquiring 10 new customers in three months. What action do you recommend as the next step?" The generative AI model analyzes this prompt and generates specific feedback and advice. The input is the prompt and the analysis result data, and the output is specific feedback and advice.

[1088] Step 5:

[1089] The server sends the generated feedback and advice to the user terminal. Specifically, it returns the generated feedback and advice to the user terminal as an HTTP response. The input is the generated feedback and advice, and the output is the feedback and advice displayed on the user terminal.

[1090] Step 6:

[1091] The user performs actions to achieve a goal and enters the results into the device. For example, they might enter, "Today I contacted three new customers." The input data is text data about the user's actions and results. The device acquires the input data and sends it to the server. The data format is JSON or XML.

[1092] Step 7:

[1093] The server analyzes the received behavior and outcome data and stores it in a database. Specifically, it receives an HTTP request, extracts the data, and then stores it using the INSERT statement of a database management system (e.g., MySQL). The input is the behavior and outcome data received from the user, and the output is the data stored in the database.

[1094] Step 8:

[1095] The server periodically retrieves tracking data from the database and generates a progress report. Specifically, it retrieves actions and results from the database and generates a progress report based on them. For example, the generated report may include the following: "Three new customers were contacted in the past week, and two of them responded positively." The input is the tracking data retrieved from the database, and the output is the progress report.

[1096] Step 9:

[1097] The server sends the generated progress report to the user terminal. Specifically, it returns the progress report to the user terminal as an HTTP response. The input is the generated progress report, and the output is the progress report displayed on the user terminal.

[1098] Step 10:

[1099] The server adjusts the content and format of the feedback and advice based on the user's personality and preferences. For example, it refers to the user's profile information and provides feedback detailing specific steps to a user who prefers detailed instructions. The input is data about the user's personality and preferences, and the output is tailored feedback and advice.

[1100] The above is a detailed description of the processing steps and specific operations of the system of the present invention, which allows users to receive effective support and implement action plans to achieve their goals.

[1101] (Application example 1)

[1102] 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."

[1103] Conventional AI coaching systems lack specific action plans for achieving users' goals and dynamic adjustments to progress, making it difficult for businesspeople to effectively achieve their goals. In particular, they do not provide enough support to maximize the work efficiency of store staff, which prevents them from improving the overall productivity of stores.

[1104] 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.

[1105] In this invention, the server includes: means for receiving goals and tasks from a user; means for storing the received goals and tasks in a database; means for using an analysis engine to analyze the stored goals and tasks; means for using an artificial intelligence model to generate optimal feedback and advice based on the analysis results; communication means for sending the generated feedback and advice to a user terminal; means for receiving the user's actions and results and storing them in a database; means for analyzing the stored actions and results and tracking progress; means for periodically generating progress reports and sending them to the user terminal; and means for recording the user's actions and results and automatically generating a new action plan from the tracked data. This enables dynamic generation and adjustment of action plans according to the user's progress, maximizing the work efficiency of staff in the physical store and ultimately improving the productivity of the entire physical store.

[1106] "User" refers to any individual or organization that uses the System.

[1107] A "goal" is a specific objective or task that a user wants to achieve.

[1108] "Receiving means" refers to the function of acquiring input information from the user.

[1109] "Database" refers to a storage device that stores received goal and behavior data.

[1110] "Analysis engine" refers to a program or function for processing and analyzing data.

[1111] "Artificial intelligence model" refers to a machine learning algorithm that generates feedback and advice based on user data.

[1112] "Communication means" refers to the function of sending and receiving information between the server and the user terminal.

[1113] "Behavioral data" refers to the specific actions a user takes to achieve their goals and the results of those actions.

[1114] "Tracking tools" refers to features that record user actions and achievements and track progress.

[1115] "Progress Report" means a report summarizing a User's progress toward achieving their Goals.

[1116] An "action plan" refers to the specific procedures or steps a user takes to achieve a goal.

[1117] "Dynamic adjustment" refers to the ability to change plans and feedback in real time based on the user's progress and behavioral data.

[1118] "Brick and mortar store" refers to a retail establishment that sells goods and services at a physical location.

[1119] "Staff" refers to employees working at physical stores.

[1120] This invention is an AI coaching system that helps store staff achieve their goals and maximize work efficiency. The system includes the following components: users input their goals and challenges, analyzes them, generates optimal feedback and advice, tracks the user's actions and results, and generates regular progress reports. Furthermore, by providing individualized feedback tailored to the user's personality and preferences and building a relationship of trust, the system helps the user take effective action toward achieving their goals.

[1121] goal setting

[1122] Users input their goals and challenges into a smartphone app or tablet device. A specific example goal might be "Acquire 10 new clients in the next three months." The entered goals are sent to the server and stored in a database.

[1123] Generate feedback and advice

[1124] The server retrieves the goals and challenges stored in the database and analyzes them using an AI analysis engine (for example, OpenAI's GPT-4). For example, after analyzing "Strategy for Acquiring New Customers," the server generates feedback such as: "As a next step, we recommend creating a potential customer list and launching a personalized email campaign." The generated feedback is then sent to the user's device.

[1125] Tracking actions and results

[1126] Users take actions to achieve their goals and enter their results into the device. For example, "Today, I will enter how I contacted three new customers." The entered information about actions and results is sent to the server and stored in a database. The server analyzes this information and tracks the user's progress.

[1127] Generate progress reports

[1128] The server periodically analyzes the stored data and generates a progress report. The generated report includes the user's behavior history and unachieved goals. A specific example could be a report that states, "Three new customers were contacted in the past week, and two of them responded positively." The generated report is sent to the user's device.

[1129] Adjusting individual feedback

[1130] The server tailors the content and format of feedback and advice based on the user's personality and preferences. For example, if the user prefers detailed instructions, it provides feedback detailing specific steps. It also communicates with the user to build trust and provides coaching tailored to the user's needs and pace.

[1131] Technology used

[1132] Language: Python

[1133] Framework: Flask (server side)

[1134] Database: PostgreSQL

[1135] AI model: OpenAI's GPT-4

[1136] Device: iOS / Android compatible mobile app

[1137] Prompt Sentence Examples

[1138] Input the following prompts into the AI ​​model to generate specific feedback.

[1139] "User goal: Acquire 5 new customers in the next month

[1140] We recommend the following steps:

[1141] As described above, this invention is a system that provides specific and dynamic action plans to support users in achieving their goals, and is effective in maximizing the work efficiency of staff in physical stores.

[1142] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1143] Step 1:

[1144] Users input their goals and challenges into a smartphone app or tablet device. The input content is specific, such as "Acquire 10 new clients in the next three months." The input goals and challenges are sent to the server as structured data by the device. The server receives this data and stores it in a database.

[1145] Step 2:

[1146] The server retrieves the goals and challenges stored in the database. Next, it analyzes the goals and challenges using an AI analysis engine (for example, OpenAI's GPT-4). The analysis prompt uses the following: "User's goal: Acquire five new customers in the next month. Recommend next steps." The feedback generated as a result of the analysis includes specific steps, such as "We recommend creating a potential customer list and launching an individual email campaign."

[1147] Step 3:

[1148] The server sends the generated feedback and advice to the user terminal, which receives it and displays the feedback on the user's display, allowing the user to take specific action based on the feedback.

[1149] Step 4:

[1150] The user performs actions to achieve a goal and enters the results into the device. For example, they enter the results of their actions, such as "I contacted three new customers today." The entered action data is sent from the device to the server and stored in a database.

[1151] Step 5:

[1152] The server retrieves the received behavioral data from the database and analyzes the progress. As a result of the analysis, progress is tracked and a progress report is generated in the form of, for example, "Three new customers were contacted in the past week, and two of them responded positively." The tracking data is dynamically updated using an AI model.

[1153] Step 6:

[1154] The server then sends the generated progress report to the user's device, where it is displayed to the user, who can then check their own progress. This progress report includes a history of actions and unachieved goals.

[1155] Step 7:

[1156] The server adjusts the content and format of feedback and advice based on the user's personality and preferences. For example, it provides feedback detailing specific steps to users who prefer detailed instructions. This adjustment makes it possible to provide optimal coaching for each user. Based on user feedback, the server builds trust and continues to approach the user according to their individual needs and pace.

[1157] By following these steps, the system can effectively support users in achieving their goals and maximize the work efficiency of store staff.

[1158] 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.

[1159] This invention is an AI coaching system that helps businesspeople achieve their goals and maximize their performance. The system includes a means for receiving, storing, and analyzing a user's goals and challenges, and a means for providing generated feedback and advice. Furthermore, the system tracks the user's actions and achievements and periodically generates progress reports. It also provides personalized feedback based on the user's personality and preferences, and includes an emotion engine that recognizes the user's emotions, allowing it to adjust the feedback based on the user's emotions.

[1160] User goal setting and reception

[1161] Users input their goals and objectives into the terminal. For example, they can set a goal of "gaining 10 new clients in the next three months."

[1162] The terminal transmits the input goal and task data to the server.

[1163] The server stores the goals and tasks in a storage device.

[1164] Generate feedback and advice

[1165] The server retrieves the goals and challenges stored in the storage device and inputs them into the AI ​​analysis engine. The AI ​​analysis engine generates feedback and advice based on the strategy and specific action plan for achieving the goals. For example, "To acquire new customers, we recommend that you create a list of potential customers and begin individual approaches via email and phone."

[1166] The server transmits the generated feedback and advice to the user terminal.

[1167] The device will display any feedback or advice received to the user.

[1168] Tracking actions and results

[1169] The user performs an action to achieve the goal and enters it into the terminal. For example, "I contacted three new customers today."

[1170] The terminal transmits the input action and outcome data to the server.

[1171] The server stores user actions and achievements on a storage device to track progress and saves the data with a timestamp.

[1172] Generate and send status reports

[1173] The server periodically retrieves the tracking data from the storage device and generates progress reports, such as "Three new customers were contacted in the past week, with two positive responses."

[1174] The server sends the generated progress report to the user terminal.

[1175] The terminal displays received progress reports to the user.

[1176] Analysis by emotion engine

[1177] The server is also equipped with an emotion engine that recognizes the user's emotions.

[1178] The emotion engine analyzes information entered by the user into the device and real-time emotional data obtained from the device's camera and microphone. For example, it can determine whether the user is feeling stressed by analyzing facial expressions and voice tones.

[1179] The server records the emotion data recognized by the emotion engine and analyzes the user's emotional tendencies.

[1180] Adjusting Feedback Based on Emotions

[1181] The server integrates and analyzes the user's emotional and behavioral data, and generates feedback that takes into account the correlation between emotions and behavior. For example, if the user is tired, it can suggest relaxation methods to help them achieve their goals.

[1182] The server adjusts the generated feedback based on the emotional data as needed to provide optimal advice to the user.

[1183] The above is a specific embodiment of the present invention. The system can effectively support users in achieving their goals by providing personalized feedback based on the user's personality and preferences and adjusting advice based on emotions using an emotion engine.

[1184] The processing flow will be explained below.

[1185] Step 1:

[1186] The user inputs their goals and objectives into the terminal. For example, they can set "to acquire 10 new clients in the next three months."

[1187] Step 2:

[1188] The device sends the entered goal and task data to the server, including the user ID.

[1189] Step 3:

[1190] The server stores the received goals and tasks in a memory device, which stores them in a database containing the goals, tasks, and user IDs.

[1191] Step 4:

[1192] The server retrieves the goals and tasks from the storage device and inputs them into the AI ​​analysis engine, which then generates optimal feedback and advice to help the user achieve their goals.

[1193] Step 5:

[1194] The server sends the generated feedback and advice to the user's device, for example, a message saying, "We recommend that you create a potential customer list and launch a personalized email campaign on a specific date."

[1195] Step 6:

[1196] The device will display any feedback or advice received to the user.

[1197] Step 7:

[1198] Based on the feedback, the user takes specific actions and enters them into the device, for example, "I contacted three new customers today."

[1199] Step 8:

[1200] The device sends the input data of the actions and results to the server. The data includes the user ID, the action, and the results.

[1201] Step 9:

[1202] The server stores the received actions and results in a storage device and tracks the progress. It records the user's actions and results with timestamps.

[1203] Step 10:

[1204] The server periodically retrieves the tracking data from the storage device and generates progress reports, such as "Three new customers were contacted in the past week, and two responded positively."

[1205] Step 11:

[1206] The server sends the generated progress report to the user terminal.

[1207] Step 12:

[1208] The terminal displays received progress reports to the user.

[1209] Step 13:

[1210] The server tailors the content and format of the feedback and advice based on the user's personality and preferences, for example, if the user prefers detailed instructions, it provides feedback with specific steps.

[1211] Step 14:

[1212] The server sends data from the device (camera, microphone, text input, etc.) to the emotion engine to analyze the user's emotions in real time. The emotion engine analyzes the user's facial expressions and tone of voice to determine whether the user is feeling stressed.

[1213] Step 15:

[1214] The server stores the emotional data recognized by the emotion engine in a storage device and analyzes the user's emotional tendencies. The emotional data also records changes over time.

[1215] Step 16:

[1216] The server integrates and analyzes the user's emotional and behavioral data, and generates feedback that takes into account the correlation between emotions and behavior. For example, it may provide feedback such as, "Your recent behavior seems to be causing you stress. We recommend that you try relaxation techniques."

[1217] The above are the processing steps in a specific embodiment of the present invention. The specific operations performed in each step are clearly defined, making the overall flow easy to understand.

[1218] Example 2

[1219] 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."

[1220] Today's businesspeople are busy, and self-management, the formulation of action plans to achieve goals, and progress management require a great deal of time and effort. It is also difficult for them to receive appropriate feedback and advice in response to emotional changes and stress levels. Conventional systems do not adequately adjust feedback to reflect the user's individual emotional state, and are therefore unable to effectively support users in maintaining their motivation or improving their performance.

[1221] 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.

[1222] In this invention, the server includes means for receiving goals and tasks from a user, means for storing the received goals and tasks in a storage device, means for analyzing the stored goals and tasks, means for generating optimal feedback and advice based on the analysis results, means for transmitting the generated feedback and advice to a user terminal, means for receiving the user's actions and results and storing them in a storage device, means for analyzing the stored actions and results and tracking progress, means for periodically generating progress reports and transmitting them to the user terminal, means for receiving and analyzing the user's emotional data, and means for adjusting feedback based on the emotional data. This makes it possible to effectively support the user in achieving their goals and provide personalized feedback according to their emotional state.

[1223] "Goals and challenges" refers to the specific objectives the user wants to achieve and the problems they need to address.

[1224] "Means for receiving" refers to an interface for obtaining data input by a user.

[1225] "Storage device" refers to a database or storage system for saving received data.

[1226] "Means for analyzing" refers to algorithms or software that analyze the stored data and generate appropriate action plans or feedback.

[1227] "Feedback and Advice" refers to specific guidelines and advice provided to users based on the analysis results.

[1228] "Means for sending" refers to a communication system for sending the generated feedback or advice to a user terminal.

[1229] "User terminal" refers to a device used by a user, such as a computer, smartphone, or tablet.

[1230] "Actions and Results" refers to the actions actually taken by the user and the results obtained as a result thereof.

[1231] "Progress tracking means" refers to a system for recording user actions and achievements and monitoring progress.

[1232] "Progress Report" refers to a report that is generated periodically that summarizes a user's actions and achievements.

[1233] "Emotion data" is data that indicates the user's emotional state, and includes, for example, stress level and fatigue level.

[1234] An "emotion engine" refers to software or algorithms that analyze users' emotional data and reflect the results in feedback and advice.

[1235] This invention is an AI coaching system that helps businesspeople achieve their goals and maximize their performance. The system includes a means for receiving, storing, and analyzing a user's goals and challenges, and a means for providing generated feedback and advice. Furthermore, the system tracks the user's actions and achievements and periodically generates progress reports. It also includes an emotion engine that recognizes the user's emotions and can adjust feedback based on the emotion data.

[1236] Hardware and Software Use

[1237] The terminal provides an interface for users to input goals and tasks. Terminals can be smartphones, PCs, tablets, etc. These terminals are equipped with a network communication module and send data to the server.

[1238] The server integrates several key components. The database system uses a relational database management system such as PostgreSQL. The generative AI model uses OpenAI GPT-4 and other models to generate feedback and advice for achieving goals. The emotion engine uses Microsoft Azure Emotion API and other models to analyze user emotion data.

[1239] Examples of specific examples and prompts

[1240] For example, if a user sets a goal of "acquiring 10 new clients in the next three months," that information is sent to the server via the device and stored in a database. The server retrieves this goal data, inputs it into a generative AI model for analysis, and generates feedback such as the following:

[1241] "Next week, I recommend creating a prospect list and contacting 10 more companies."

[1242] If the user then reports that they "contacted three new customers today," that data is also sent to the server via the device and tracked.

[1243] Additionally, emotional data is collected. For example, the device's camera and microphone are used to capture the user's facial expressions and tone of voice, and the captured data is sent to a server. The server analyzes this emotional data and adjusts the feedback accordingly if the user is experiencing high levels of stress.

[1244] Here are some example prompts to input to the generative AI model:

[1245] Goal: Acquire 10 new clients

[1246] This week's action: Created a list of potential clients and contacted three companies.

[1247] Perceived stress level: High

[1248] Using the information below, suggest a specific action plan for the user for the next week and some advice on how to reduce stress.

[1249] User goal: Acquire 10 new customers

[1250] Action: This week I created a list of potential clients and contacted three of them.

[1251] Current Emotion: High stress levels

[1252] Suggestion Feedback:

[1253] 1. Specific action plan for next week

[1254] 2. Advice for reducing stress

[1255] This completes the description of the embodiment of the invention. This system supports users in achieving their goals and provides feedback according to their individual emotional state, thereby maintaining their motivation and improving their performance.

[1256] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1257] Step 1:

[1258] The user inputs their goals and objectives into the terminal. For example, they might input "Acquire 10 new clients in the next three months."

[1259] Input: Goals and challenges set by the user.

[1260] Data processing: Convert the goal and task data entered on the terminal into JSON format.

[1261] Output: Goal and assignment data in JSON format.

[1262] Step 2:

[1263] The terminal sends the entered goal and task data to the server, and the content entered by the user is sent via the network module.

[1264] Input: Goal and assignment data in JSON format.

[1265] Data operation: Send data to the server using a network protocol (e.g., HTTP POST request).

[1266] Output: The goal and task data sent to the server.

[1267] Step 3:

[1268] The server stores the received goals and tasks in a database, which is created using PostgreSQL.

[1269] Input: Goal and task data received by the server.

[1270] Data processing: Convert JSON format data into SQL insert statements and store them in the database.

[1271] Output: Goal and task data stored in a database.

[1272] Step 4:

[1273] The server retrieves the target data from the database and provides it to the generative AI model, which uses OpenAI GPT-4.

[1274] Input: Target data in the database.

[1275] Data Calculation: Converting goal data into prompts for the AI, such as "User-defined goal: Acquire 10 new customers."

[1276] Output: The prompt that is input to the generative AI model.

[1277] Step 5:

[1278] Generative AI models generate feedback and advice to help you achieve your goals.

[1279] Input: Prompt data.

[1280] Data computation: A generative AI model analyzes the prompts and generates appropriate feedback and advice, such as, "We recommend that you build a lead list next week and contact 10 more companies."

[1281] Output: Generated feedback and advice.

[1282] Step 6:

[1283] The server transmits the generated feedback and advice to the user terminal.

[1284] Input: Generated feedback and advice data.

[1285] Data operation: Sends data to the user terminal using a network protocol (e.g., HTTP POST request).

[1286] Output: Feedback and advice data sent to the user device.

[1287] Step 7:

[1288] The device will display the received feedback and advice to the user.

[1289] Input: Feedback and advice data sent by the server.

[1290] Data processing: Converting data into a format that can be displayed on the screen, for example, as a text message.

[1291] Output: Feedback and advice displayed to the user.

[1292] Step 8:

[1293] The user enters the actions or results they have achieved into the terminal. For example, they might enter, "I contacted three new customers today."

[1294] Input: User behavior and outcome data.

[1295] Data processing: Converts the action and result data entered on the device into JSON format.

[1296] Output: Behavior and outcome data in JSON format.

[1297] Step 9:

[1298] The terminal transmits the input action and outcome data to the server.

[1299] Input: Action and outcome data in JSON format.

[1300] Data operation: Send data to the server using a network protocol (e.g., HTTP POST request).

[1301] Output: Action and outcome data sent to the server.

[1302] Step 10:

[1303] The server records the received action and outcome data in a database to track progress.

[1304] Input: Action and outcome data received by the server.

[1305] Data processing: Converting JSON data into SQL insert statements and storing them in the database. The saved data is then fed into a progress tracking algorithm to update the progress.

[1306] Output: Behavioral and outcome data recorded in a database, updated progress.

[1307] Step 11:

[1308] The server periodically retrieves the progress data from the database and generates a progress report.

[1309] Input: Progress data in the database.

[1310] Data processing: Aggregate progress data and convert it into a report format, for example, "Contacted three new customers in the past week and received positive responses from two."

[1311] Output: The generated progress report.

[1312] Step 12:

[1313] The server transmits the generated progress report to the user terminal.

[1314] Input: Generated progress report data.

[1315] Data operation: Sends data to the user terminal using a network protocol (e.g., HTTP POST request).

[1316] Output: Progress report sent to user terminal.

[1317] Step 13:

[1318] The terminal displays the received progress report to the user.

[1319] Input: Progress report data sent by the server.

[1320] Data processing: Converting data into a format that can be displayed on the screen, for example, as a text message.

[1321] Output: A progress report displayed to the user.

[1322] Step 14:

[1323] The server analyzes the emotion data obtained from the user.

[1324] Input: User emotion data (e.g., facial capture, voice tone).

[1325] Data Calculation: Uses an emotion engine to analyze emotion data and identify the user's emotional state. For example, high stress level, high fatigue.

[1326] Output: Parsed emotional state data.

[1327] Step 15:

[1328] The server adjusts the feedback based on the emotion data.

[1329] Input: Parsed emotion data and progress data.

[1330] Data Computation: Using generative AI models to regenerate or adjust feedback while taking into account emotional data. Example: Suggesting relaxation techniques for a stressed user.

[1331] Output: Tailored feedback and advice.

[1332] Step 16:

[1333] The device displays tailored feedback to the user.

[1334] Input: Adjusted feedback data sent by the server.

[1335] Data processing: Converting data into a format that can be displayed on the screen, for example, as a text message.

[1336] Output: The adjusted feedback and advice displayed to the user.

[1337] (Application example 2)

[1338] 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."

[1339] Conventional factory robot systems have not adequately optimized production processes or managed the health of operators, leaving challenges in efficient robot operation and reducing operator stress. Furthermore, there is a lack of systems that go beyond simply analyzing production data and provide feedback based on the operator's emotional state. The present invention aims to solve these challenges by providing a system that maximizes the efficiency of factory robots and manages operator stress.

[1340] 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 receiving a user's goals and tasks, means for storing the received goals and tasks in a storage device, means for analyzing the stored goals and tasks, means for generating optimal feedback and advice based on the analysis results, means for transmitting the generated feedback and advice to a user terminal, means for receiving a user's actions and results and storing them in a storage device, means for analyzing the stored actions and results and tracking progress, means for periodically generating progress reports and transmitting them to the user terminal, means for collecting user emotion data, means for analyzing the user emotion data and adjusting feedback based on the emotions, and means for integrating and analyzing the user emotion data and behavioral data. This makes it possible to optimize the operation of a factory robot and provide feedback according to the operator's emotional state.

[1341] "Users" refer to factory managers and operators who use the system.

[1342] A "goal" is a specific production figure or result that the user wants to achieve.

[1343] A "challenge" is a problem or obstacle that a user must solve to achieve their goal.

[1344] A "means" is a method or device used to achieve a particular purpose.

[1345] "Storage device" refers to hardware or software for storing data.

[1346] A "server" is a centralized device for processing and storing data.

[1347] An "AI analysis engine" is software that uses artificial intelligence to analyze data and generate optimal feedback and advice.

[1348] "Feedback" is an evaluation or advice regarding the user's behavior or situation.

[1349] "Advice" is advice on actions or measures users should take to achieve their goals.

[1350] A "user terminal" is a device (e.g., a computer, a smartphone) that is directly operated by a user.

[1351] An "action" is a specific task that a user performs to achieve a goal.

[1352] "Results" refers to the results achieved by a user through their actions.

[1353] "Progress" is information that shows the progress of actions and results toward achieving a goal.

[1354] A "progress report" is a report summarizing progress.

[1355] "Emotional data" is information about a user's emotional state (e.g., stress, fatigue).

[1356] An "emotion engine" is software for analyzing user emotional data.

[1357] "Adjusting feedback based on emotion" means changing the content of feedback or advice based on the user's emotional state.

[1358] "Operation data" is information about the tasks and movements being performed by a factory robot.

[1359] "Tracking" means the continuous monitoring and recording of certain information.

[1360] This invention is an AI coaching system for optimizing manufacturing processes using factory robots and managing operator stress. The system includes means for receiving, storing, and analyzing user (factory manager or operator) goals and challenges, generating and sending feedback and advice, tracking behavior and results, generating progress reports, collecting and analyzing emotional data, and adjusting feedback.

[1361] Explaining program processing in natural language

[1362] The hardware used includes factory robots (e.g., general-purpose robotic devices), cameras (e.g., general-purpose webcams), and microphones (e.g., general-purpose USB microphones).The software used includes AI analysis engines (e.g., TensorFlow, PyTorch), emotion engines (e.g., Affectiva SDK), databases (e.g., PostgreSQL), and communication protocols (e.g., MQTT).

[1363] 1. Goal setting and receiving:

[1364] The server receives the goal entered by the factory manager into the edge device. For example, the factory manager sets a goal of "increasing daily production volume by 10%." The edge device sends this goal to the server and stores it in the server's storage device.

[1365] 2. Generate feedback and advice:

[1366] The server retrieves the goals and tasks from the storage device and inputs them into the AI ​​analysis engine. The AI ​​analysis engine analyzes the manufacturing process data and generates feedback and advice that suggests optimal operations and adjustments. For example, advice may be generated such as "shorten a specific manufacturing step" or "change the placement of operators." The generated feedback is sent to the factory robot's control system.

[1367] 3. Tracking actions and results:

[1368] The robot records its movement data in real time and transmits it to a server, which stores the tracking data in a storage device and monitors its progress.

[1369] 4. Generate progress reports:

[1370] The server periodically retrieves tracking data from the database and generates progress reports, such as "We've achieved a 5% improvement in continuous uptime over the past week and a new 10% increase in production," which are then sent to the factory manager for display.

[1371] 5. Analysis by Emotion Engine:

[1372] The camera and microphone collect the operator's facial expressions and voice and send them to a server. The emotion engine analyzes this data and determines the operator's emotional state (e.g., stress or fatigue).

[1373] 6. Adjusting feedback based on emotions:

[1374] The server integrates and analyzes emotion data and behavioral data to adjust feedback. For example, if an operator is fatigued, the system will provide feedback recommending a break, thereby supporting efficient production and operator health management.

[1375] Examples of specific examples and prompts

[1376] For example, a factory manager may set a goal of "increasing daily production volume by 10%," and the AI ​​analysis engine may suggest "shortening a specific manufacturing step." This suggestion is sent as feedback to the robot and implemented.

[1377] An example prompt is:

[1378] "Please tell me the progress towards today's goal. Please suggest optimal operations and areas that need adjustment based on the operation status of factory robots and operator sentiment data."

[1379] This system not only improves factory productivity but also supports the health management of operators.

[1380] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1381] Step 1:

[1382] The user (factory manager) inputs a goal into the edge device. For example, this goal might be "improve daily production by 10%." The edge device then sends this goal to the server.

[1383] Input: User-entered goal

[1384] Output: Target data sent to the server

[1385] Step 2:

[1386] The server stores the received goals in a storage device, specifically, in a database.

[1387] Input: Target data sent to the server

[1388] Output: Target data stored in memory device

[1389] Step 3:

[1390] The server retrieves the goals and tasks from the storage device and inputs them into the AI ​​analysis engine, which analyzes the data and generates optimal feedback and advice. During this process, machine learning algorithms find patterns in the data and suggest action plans.

[1391] Input: Goals and tasks retrieved from memory

[1392] Output: Feedback and advice generated by the AI ​​analytics engine

[1393] Step 4:

[1394] The server transmits the generated feedback and advice to the control systems of the factory robots, which adjust their operations based on the feedback and advice.

[1395] Input: Feedback and advice generated by the AI ​​analytics engine

[1396] Output: Adjustment of factory robot movements

[1397] Step 5:

[1398] The user (operator) monitors the actions performed by the robot during the manufacturing process, and the robot records the action data in real time and sends it to the server.

[1399] Input: Real-time operational data generated by factory robots

[1400] Output: Operational data sent to the server

[1401] Step 6:

[1402] The server stores the received operational data in a storage device and monitors progress, which is continuously stored in a database and used to generate progress reports.

[1403] Input: Operational data sent to the server

[1404] Output: Operational data stored in a memory device

[1405] Step 7:

[1406] The server periodically retrieves tracking data from the database and generates progress reports, which are then sent to the factory manager for display.

[1407] Input: Tracking data retrieved from the database

[1408] Output: Generated progress report and its display

[1409] Step 8:

[1410] The camera and microphone are used to collect the user's (operator's) emotional data, which includes facial expression recognition and voice analysis, and is sent to the server.

[1411] Input: Emotion data collected from the camera and microphone

[1412] Output: Emotion data sent to the server

[1413] Step 9:

[1414] The server uses an emotion engine to analyze the received emotion data and determine the user's emotional state (e.g., stress or fatigue) based on the analysis results.

[1415] Input: Emotion data sent to the server

[1416] Output: Parsed emotional state data

[1417] Step 10:

[1418] The server integrates and analyzes the emotional state data and behavioral data to adjust the feedback, such as when the user is fatigued, to recommend taking a break.

[1419] Input: Parsed emotional state data and behavioral data

[1420] Output: Regulated Feedback

[1421] This system's series of processes not only improves factory productivity but also effectively manages the health of operators.

[1422] 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.

[1423] 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.

[1424] 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.

[1425] [Fourth embodiment]

[1426] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1427] 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.

[1428] 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).

[1429] 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.

[1430] 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.

[1431] 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).

[1432] 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.

[1433] 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.

[1434] 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.

[1435] 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.

[1436] 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.

[1437] 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.

[1438] 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."

[1439] This invention is an AI coaching system that helps businesspeople achieve their goals and maximize their performance. The system receives goals and challenges from users, analyzes them, and generates optimal feedback and advice. It also tracks the user's actions and results and generates regular progress reports. It also provides individualized feedback tailored to the user's personality and preferences, building a relationship of trust and helping the user take effective action toward achieving their goals.

[1440] User goal setting

[1441] Users input their goals and objectives into the terminal. For example, let's say you set a goal of "gaining 10 new clients in the next three months."

[1442] The terminal transmits the inputted goal and task to the server.

[1443] The server stores the received goals and tasks in a storage device.

[1444] Generate feedback and advice

[1445] The server retrieves the goals and challenges stored in the storage device and analyzes them using an AI analysis engine. For example, after analyzing "Strategy for acquiring new customers," it generates feedback such as: "As a next step, we recommend creating a potential customer list and launching an individual email campaign."

[1446] The server transmits the generated feedback and advice to the user terminal.

[1447] The device will display any feedback or advice it receives to the user.

[1448] Tracking actions and results

[1449] The user performs actions to achieve the goal and enters the results into the terminal. For example, they might enter, "I contacted three new customers today."

[1450] The terminal transmits information about the input actions and results to the server.

[1451] The server stores the received actions and results in a storage device and tracks the progress.

[1452] Generate progress reports

[1453] The server periodically analyzes the tracking data and generates progress reports, including the user's behavior history and unachieved goals. For example, a report might be generated that states, "Three new customers were contacted in the past week, and two of them responded positively."

[1454] The server transmits the generated progress report to the user terminal.

[1455] The terminal displays the received progress reports to the user.

[1456] Adjusting individual feedback

[1457] The server tailors the content and format of feedback and advice based on the user's personality and preferences: for example, if the user prefers detailed instructions, it provides feedback detailing specific steps.

[1458] The server communicates with the user to build a trusting relationship and provides coaching tailored to the user's needs and pace.

[1459] The above is a specific embodiment of the present invention. This system allows users to receive effective support for self-development and career advancement. This system provides objective and unbiased support from the user's perspective, greatly contributing to the achievement of businesspeople's goals.

[1460] The processing flow will be explained below.

[1461] Step 1:

[1462] The user inputs their goals and objectives into the terminal. For example, they might input "Acquire 10 new clients in the next three months."

[1463] Step 2:

[1464] The device sends the entered goals and tasks to the server, including the user ID.

[1465] Step 3:

[1466] The server stores the received goals and tasks in a memory device, including storing them in a database in association with the user ID.

[1467] Step 4:

[1468] The server retrieves the goals and tasks from the storage device and inputs them into the AI ​​analysis engine, which then generates optimal feedback and advice for achieving the goals.

[1469] Step 5:

[1470] The server sends the generated feedback and advice to the user device, including a message such as, "As a next step, we recommend that you create a potential customer list and launch a personalized email campaign."

[1471] Step 6:

[1472] The device will display any feedback or advice it receives to the user.

[1473] Step 7:

[1474] Users enter actions they have taken or results they have achieved into the device, for example, "I contacted three new customers today."

[1475] Step 8:

[1476] The device sends the input action and result information to the server. The transmitted data again includes the user ID.

[1477] Step 9:

[1478] The server tracks progress by storing the received actions and achievements in a storage device, which stores each action and achievement with a timestamp.

[1479] Step 10:

[1480] The server periodically retrieves the tracking data from the storage device and generates progress reports, such as "Three new customers were contacted in the past week, with two positive responses."

[1481] Step 11:

[1482] The server transmits the generated progress report to the user terminal.

[1483] Step 12:

[1484] The terminal displays the received progress reports to the user.

[1485] Step 13:

[1486] The server tailors the content and format of feedback and advice based on the user's personality and preferences, including a process of learning the feedback formats and styles that the user has preferred in the past.

[1487] Step 14:

[1488] The server communicates with the user to build trust with them, for example, by periodically sending a survey asking about user satisfaction and areas for improvement.

[1489] The above are the processing steps in a specific embodiment of the present invention. The specific operations for each step are clearly defined, making the overall flow easy to understand.

[1490] Example 1

[1491] 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."

[1492] There is a lack of effective support systems to help businesspeople achieve their goals and maximize their performance. In particular, there is a need for a system that can systematically provide feedback and advice tailored to the characteristics of each user, track actions and results, and generate progress reports. Conventional systems can only provide generic feedback, making it difficult to provide detailed instructions or adaptive support tailored to the characteristics of each individual user.

[1493] 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.

[1494] In this invention, the server includes means for receiving goals and tasks from a user, means for storing the received goals and tasks in a storage device, means for acquiring the stored goals and tasks and analyzing them using a generative AI model, means for generating optimal feedback and advice based on the analysis results, means for transmitting the generated feedback and advice to a user terminal, means for receiving the user's actions and results and storing them in a storage device, means for analyzing the stored actions and results and tracking progress, means for periodically generating progress reports and transmitting them to the user terminal, and means for adjusting the content and format of the generated feedback and advice based on the user's personality and preferences. This makes it possible to provide feedback and advice tailored to the characteristics of each user, and to systematically generate, adjust, track, and report on effective action plans.

[1495] "User" means an individual or organization that uses the system to assist them in achieving their goals.

[1496] "Goal" refers to the specific outcome or target value that the user aims to achieve.

[1497] A "challenge" is a problem or difficulty a user faces that prevents them from achieving their goal.

[1498] "Means for receiving" refers to the interface or function that takes in data provided by the user and inputs it into the system.

[1499] "Memory device" refers to a data storage device for storing received data, behavioral information, outcomes, and analysis results.

[1500] A "generative AI model" is an artificial intelligence model used to analyze a user's goals and challenges and generate feedback and advice.

[1501] The "means of analysis" is a system function that uses a generative AI model to execute the process of analyzing the goals and challenges provided by the user.

[1502] "Feedback" is evaluation information that shows specific action plans and areas for improvement for the goals and challenges provided by the user.

[1503] "Advice" is information that provides guidance on specific actions or strategies that users should take to achieve their goals.

[1504] "User Terminal" means the computer device used by a User to access the System and enter data and view feedback.

[1505] "Behaviors" refer to the specific activities or tasks that users perform to achieve their goals.

[1506] "Results" refers to the results or progress achieved as a result of a user's actions.

[1507] "Progress tracking means" means the system's ability to record user actions and achievements and track progress toward goal achievement in real time.

[1508] The "means for generating periodic progress reports" is a system function that creates progress reports at regular intervals based on the user's behavioral history and results.

[1509] "Personality and Preferences" refers to a user's behavioral patterns, preferences, and personal characteristics that serve as the basis for tailoring feedback and advice.

[1510] "Means for building trust" are system features that communicate with users and provide feedback and advice to build trust.

[1511] The "means for generating an action plan" is a system function that develops specific action steps to achieve the user's goal.

[1512] A "prompt sentence" is an input sentence used to prompt a generative AI model to perform appropriate analysis.

[1513] The present invention is an AI coaching system that helps users achieve their goals and maximize their performance. The system uses the following hardware and software components:

[1514] Hardware Configuration

[1515] 1. Server

[1516] 2. User device (PC, smartphone, etc.)

[1517] 3. Storage Devices (Database Systems)

[1518] Software Configuration

[1519] 1. AI analysis engine (e.g., generative AI model)

[1520] 2. Database management system (e.g., MySQL)

[1521] 3. Communication protocol (e.g. HTTP)

[1522] Setting user goals

[1523] Users input their goals and challenges through the device. For example, they can set a goal of "acquiring 10 new clients in the next three months." The input is done through a dedicated application or a web interface. The device then sends the input goals and challenges to the server.

[1524] Save goal data

[1525] The server stores the received goals and tasks in a database (e.g., MySQL). For example, it registers the goal data in the appropriate table using an INSERT statement.

[1526] Generate feedback and advice

[1527] The server sends the goals and tasks stored in the database to a generative AI model (e.g., GPT-4) using prompts for analysis. For example, the following prompts are used:

[1528] A user has set a goal of acquiring 10 new customers in three months. What next action would you recommend?

[1529] Based on this prompt, the AI ​​analytics engine generates specific strategic feedback, such as, "As a next step, we recommend that you create a prospect list and launch a personalized email campaign."

[1530] Send feedback and advice

[1531] The server sends the generated feedback and advice to the user's device. Specifically, the server returns the generated feedback as an HTTP response and displays it on the user's device.

[1532] Recording actions and achievements

[1533] The user performs actions to achieve the goal and enters the results into the device. For example, they might enter, "Today I contacted three new customers." The device then sends the entered information about the actions and results to the server.

[1534] Behavioral Data Storage

[1535] The server stores the received action and outcome information in a database, for example in a transaction table in the database using the MySQL INSERT statement.

[1536] Generate progress reports

[1537] The server periodically retrieves tracking data from the database and asks the generative AI model to analyze it to generate a progress report, such as "Three new customers were contacted in the past week, and two of them responded positively."

[1538] Sending a progress report

[1539] The server generates a progress report and sends it to the user's device via an HTTP response, where it can be displayed.

[1540] Adjusting individual feedback

[1541] The server tailors the content and format of the feedback and advice based on the user's personality and preferences. For example, it references the user's profile information stored in a database and provides feedback detailing specific steps to users who prefer detailed instructions.

[1542] The above is a specific embodiment of the present invention. This system allows users to receive feedback and advice tailored to their individual characteristics and implement effective action plans to achieve their goals. This makes it possible to systematically support users in improving their performance and achieving their goals.

[1543] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1544] Processing step details

[1545] Step 1:

[1546] The user inputs their goals and challenges into the device. An example input is "Acquire 10 new clients in the next three months." The input data is text data about the user's goals and challenges. The device acquires the input data and sends it to the server via an input form. The data format is JSON or XML.

[1547] Step 2:

[1548] The server analyzes the received goal and task data and stores it in a database. Specifically, it receives an HTTP request, extracts the data, and then stores it using the INSERT statement of a database management system (e.g., MySQL). The input is the goal and task data received from the user, and the output is the data stored in the database.

[1549] Step 3:

[1550] The server retrieves the stored goals and tasks and performs analysis using the generative AI model. Specifically, it retrieves the goals and tasks from the database using a SELECT statement, and then sends the retrieved data to the generative AI model (e.g., GPT-4) with a prompt statement attached. The input is the goal and task data retrieved from the database, and the output is the analysis results obtained from the generative AI model.

[1551] Step 4:

[1552] The server generates optimal feedback and advice based on the analysis results. The specific prompt used is, "The user has set a goal of acquiring 10 new customers in three months. What action do you recommend as the next step?" The generative AI model analyzes this prompt and generates specific feedback and advice. The input is the prompt and the analysis result data, and the output is specific feedback and advice.

[1553] Step 5:

[1554] The server sends the generated feedback and advice to the user terminal. Specifically, it returns the generated feedback and advice to the user terminal as an HTTP response. The input is the generated feedback and advice, and the output is the feedback and advice displayed on the user terminal.

[1555] Step 6:

[1556] The user performs actions to achieve a goal and enters the results into the device. For example, they might enter, "Today I contacted three new customers." The input data is text data about the user's actions and results. The device acquires the input data and sends it to the server. The data format is JSON or XML.

[1557] Step 7:

[1558] The server analyzes the received behavior and outcome data and stores it in a database. Specifically, it receives an HTTP request, extracts the data, and then stores it using the INSERT statement of a database management system (e.g., MySQL). The input is the behavior and outcome data received from the user, and the output is the data stored in the database.

[1559] Step 8:

[1560] The server periodically retrieves tracking data from the database and generates a progress report. Specifically, it retrieves actions and results from the database and generates a progress report based on them. For example, the generated report may include the following: "Three new customers were contacted in the past week, and two of them responded positively." The input is the tracking data retrieved from the database, and the output is the progress report.

[1561] Step 9:

[1562] The server sends the generated progress report to the user terminal. Specifically, it returns the progress report to the user terminal as an HTTP response. The input is the generated progress report, and the output is the progress report displayed on the user terminal.

[1563] Step 10:

[1564] The server adjusts the content and format of the feedback and advice based on the user's personality and preferences. For example, it refers to the user's profile information and provides feedback detailing specific steps to a user who prefers detailed instructions. The input is data about the user's personality and preferences, and the output is tailored feedback and advice.

[1565] The above is a detailed description of the processing steps and specific operations of the system of the present invention, which allows users to receive effective support and implement action plans to achieve their goals.

[1566] (Application example 1)

[1567] 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."

[1568] Conventional AI coaching systems lack specific action plans for achieving users' goals and dynamic adjustments to progress, making it difficult for businesspeople to effectively achieve their goals. In particular, they do not provide enough support to maximize the work efficiency of store staff, which prevents them from improving the overall productivity of stores.

[1569] 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.

[1570] In this invention, the server includes: means for receiving goals and tasks from a user; means for storing the received goals and tasks in a database; means for using an analysis engine to analyze the stored goals and tasks; means for using an artificial intelligence model to generate optimal feedback and advice based on the analysis results; communication means for sending the generated feedback and advice to a user terminal; means for receiving the user's actions and results and storing them in a database; means for analyzing the stored actions and results and tracking progress; means for periodically generating progress reports and sending them to the user terminal; and means for recording the user's actions and results and automatically generating a new action plan from the tracked data. This enables dynamic generation and adjustment of action plans according to the user's progress, maximizing the work efficiency of staff in the physical store and ultimately improving the productivity of the entire physical store.

[1571] "User" refers to any individual or organization that uses the System.

[1572] A "goal" is a specific objective or task that a user wants to achieve.

[1573] "Receiving means" refers to the function of acquiring input information from the user.

[1574] "Database" refers to a storage device that stores received goal and behavior data.

[1575] "Analysis engine" refers to a program or function for processing and analyzing data.

[1576] "Artificial intelligence model" refers to a machine learning algorithm that generates feedback and advice based on user data.

[1577] "Communication means" refers to the function of sending and receiving information between the server and the user terminal.

[1578] "Behavioral data" refers to the specific actions a user takes to achieve their goals and the results of those actions.

[1579] "Tracking tools" refers to features that record user actions and achievements and track progress.

[1580] "Progress Report" means a report summarizing a User's progress toward achieving their Goals.

[1581] An "action plan" refers to the specific procedures or steps a user takes to achieve a goal.

[1582] "Dynamic adjustment" refers to the ability to change plans and feedback in real time based on the user's progress and behavioral data.

[1583] "Brick and mortar store" refers to a retail establishment that sells goods and services at a physical location.

[1584] "Staff" refers to employees working at physical stores.

[1585] This invention is an AI coaching system that helps store staff achieve their goals and maximize work efficiency. The system includes the following components: users input their goals and challenges, analyzes them, generates optimal feedback and advice, tracks the user's actions and results, and generates regular progress reports. Furthermore, by providing individualized feedback tailored to the user's personality and preferences and building a relationship of trust, the system helps the user take effective action toward achieving their goals.

[1586] goal setting

[1587] Users input their goals and challenges into a smartphone app or tablet device. A specific example goal might be "Acquire 10 new clients in the next three months." The entered goals are sent to the server and stored in a database.

[1588] Generate feedback and advice

[1589] The server retrieves the goals and challenges stored in the database and analyzes them using an AI analysis engine (for example, OpenAI's GPT-4). For example, after analyzing "Strategy for Acquiring New Customers," the server generates feedback such as: "As a next step, we recommend creating a potential customer list and launching a personalized email campaign." The generated feedback is then sent to the user's device.

[1590] Tracking actions and results

[1591] Users take actions to achieve their goals and enter their results into the device. For example, "Today, I will enter how I contacted three new customers." The entered information about actions and results is sent to the server and stored in a database. The server analyzes this information and tracks the user's progress.

[1592] Generate progress reports

[1593] The server periodically analyzes the stored data and generates a progress report. The generated report includes the user's behavior history and unachieved goals. A specific example could be a report that states, "Three new customers were contacted in the past week, and two of them responded positively." The generated report is sent to the user's device.

[1594] Adjusting individual feedback

[1595] The server tailors the content and format of feedback and advice based on the user's personality and preferences. For example, if the user prefers detailed instructions, it provides feedback detailing specific steps. It also communicates with the user to build trust and provides coaching tailored to the user's needs and pace.

[1596] Technology used

[1597] Language: Python

[1598] Framework: Flask (server side)

[1599] Database: PostgreSQL

[1600] AI model: OpenAI's GPT-4

[1601] Device: iOS / Android compatible mobile app

[1602] Prompt Sentence Examples

[1603] Input the following prompts into the AI ​​model to generate specific feedback.

[1604] "User goal: Acquire 5 new customers in the next month

[1605] We recommend the following steps:

[1606] As described above, this invention is a system that provides specific and dynamic action plans to support users in achieving their goals, and is effective in maximizing the work efficiency of staff in physical stores.

[1607] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1608] Step 1:

[1609] Users input their goals and challenges into a smartphone app or tablet device. The input content is specific, such as "Acquire 10 new clients in the next three months." The input goals and challenges are sent to the server as structured data by the device. The server receives this data and stores it in a database.

[1610] Step 2:

[1611] The server retrieves the goals and challenges stored in the database. Next, it analyzes the goals and challenges using an AI analysis engine (for example, OpenAI's GPT-4). The analysis prompt uses the following: "User's goal: Acquire five new customers in the next month. Recommend next steps." The feedback generated as a result of the analysis includes specific steps, such as "We recommend creating a potential customer list and launching an individual email campaign."

[1612] Step 3:

[1613] The server sends the generated feedback and advice to the user terminal, which receives it and displays the feedback on the user's display, allowing the user to take specific action based on the feedback.

[1614] Step 4:

[1615] The user performs actions to achieve a goal and enters the results into the device. For example, they enter the results of their actions, such as "I contacted three new customers today." The entered action data is sent from the device to the server and stored in a database.

[1616] Step 5:

[1617] The server retrieves the received behavioral data from the database and analyzes the progress. As a result of the analysis, progress is tracked and a progress report is generated in the form of, for example, "Three new customers were contacted in the past week, and two of them responded positively." The tracking data is dynamically updated using an AI model.

[1618] Step 6:

[1619] The server then sends the generated progress report to the user's device, where it is displayed to the user, who can then check their own progress. This progress report includes a history of actions and unachieved goals.

[1620] Step 7:

[1621] The server adjusts the content and format of feedback and advice based on the user's personality and preferences. For example, it provides feedback detailing specific steps to users who prefer detailed instructions. This adjustment makes it possible to provide optimal coaching for each user. Based on user feedback, the server builds trust and continues to approach the user according to their individual needs and pace.

[1622] By following these steps, the system can effectively support users in achieving their goals and maximize the work efficiency of store staff.

[1623] 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.

[1624] This invention is an AI coaching system that helps businesspeople achieve their goals and maximize their performance. The system includes a means for receiving, storing, and analyzing a user's goals and challenges, and a means for providing generated feedback and advice. Furthermore, the system tracks the user's actions and achievements and periodically generates progress reports. It also provides personalized feedback based on the user's personality and preferences, and includes an emotion engine that recognizes the user's emotions, allowing it to adjust the feedback based on the user's emotions.

[1625] User goal setting and reception

[1626] Users input their goals and objectives into the terminal. For example, they can set a goal of "gaining 10 new clients in the next three months."

[1627] The terminal transmits the input goal and task data to the server.

[1628] The server stores the goals and tasks in a storage device.

[1629] Generate feedback and advice

[1630] The server retrieves the goals and challenges stored in the storage device and inputs them into the AI ​​analysis engine. The AI ​​analysis engine generates feedback and advice based on the strategy and specific action plan for achieving the goals. For example, "To acquire new customers, we recommend that you create a list of potential customers and begin individual approaches via email and phone."

[1631] The server transmits the generated feedback and advice to the user terminal.

[1632] The device will display any feedback or advice received to the user.

[1633] Tracking actions and results

[1634] The user performs an action to achieve the goal and enters it into the terminal. For example, "I contacted three new customers today."

[1635] The terminal transmits the input action and outcome data to the server.

[1636] The server stores user actions and achievements on a storage device to track progress and saves the data with a timestamp.

[1637] Generate and send status reports

[1638] The server periodically retrieves the tracking data from the storage device and generates progress reports, such as "Three new customers were contacted in the past week, with two positive responses."

[1639] The server sends the generated progress report to the user terminal.

[1640] The terminal displays received progress reports to the user.

[1641] Analysis by emotion engine

[1642] The server is also equipped with an emotion engine that recognizes the user's emotions.

[1643] The emotion engine analyzes information entered by the user into the device and real-time emotional data obtained from the device's camera and microphone. For example, it can determine whether the user is feeling stressed by analyzing facial expressions and voice tones.

[1644] The server records the emotion data recognized by the emotion engine and analyzes the user's emotional tendencies.

[1645] Adjusting Feedback Based on Emotions

[1646] The server integrates and analyzes the user's emotional and behavioral data, and generates feedback that takes into account the correlation between emotions and behavior. For example, if the user is tired, it can suggest relaxation methods to help them achieve their goals.

[1647] The server adjusts the generated feedback based on the emotional data as needed to provide optimal advice to the user.

[1648] The above is a specific embodiment of the present invention. The system can effectively support users in achieving their goals by providing personalized feedback based on the user's personality and preferences and adjusting advice based on emotions using an emotion engine.

[1649] The processing flow will be explained below.

[1650] Step 1:

[1651] The user inputs their goals and objectives into the terminal. For example, they can set "to acquire 10 new clients in the next three months."

[1652] Step 2:

[1653] The device sends the entered goal and task data to the server, including the user ID.

[1654] Step 3:

[1655] The server stores the received goals and tasks in a memory device, which stores them in a database containing the goals, tasks, and user IDs.

[1656] Step 4:

[1657] The server retrieves the goals and tasks from the storage device and inputs them into the AI ​​analysis engine, which then generates optimal feedback and advice to help the user achieve their goals.

[1658] Step 5:

[1659] The server sends the generated feedback and advice to the user's device, for example, a message saying, "We recommend that you create a potential customer list and launch a personalized email campaign on a specific date."

[1660] Step 6:

[1661] The device will display any feedback or advice received to the user.

[1662] Step 7:

[1663] Based on the feedback, the user takes specific actions and enters them into the device, for example, "I contacted three new customers today."

[1664] Step 8:

[1665] The device sends the input data of the actions and results to the server. The data includes the user ID, the action, and the results.

[1666] Step 9:

[1667] The server stores the received actions and results in a storage device and tracks the progress. It records the user's actions and results with timestamps.

[1668] Step 10:

[1669] The server periodically retrieves the tracking data from the storage device and generates progress reports, such as "Three new customers were contacted in the past week, and two responded positively."

[1670] Step 11:

[1671] The server sends the generated progress report to the user terminal.

[1672] Step 12:

[1673] The terminal displays received progress reports to the user.

[1674] Step 13:

[1675] The server tailors the content and format of the feedback and advice based on the user's personality and preferences, for example, if the user prefers detailed instructions, it provides feedback with specific steps.

[1676] Step 14:

[1677] The server sends data from the device (camera, microphone, text input, etc.) to the emotion engine to analyze the user's emotions in real time. The emotion engine analyzes the user's facial expressions and tone of voice to determine whether the user is feeling stressed.

[1678] Step 15:

[1679] The server stores the emotional data recognized by the emotion engine in a storage device and analyzes the user's emotional tendencies. The emotional data also records changes over time.

[1680] Step 16:

[1681] The server integrates and analyzes the user's emotional and behavioral data, and generates feedback that takes into account the correlation between emotions and behavior. For example, it may provide feedback such as, "Your recent behavior seems to be causing you stress. We recommend that you try relaxation techniques."

[1682] The above are the processing steps in a specific embodiment of the present invention. The specific operations performed in each step are clearly defined, making the overall flow easy to understand.

[1683] Example 2

[1684] 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."

[1685] Today's businesspeople are busy, and self-management, the formulation of action plans to achieve goals, and progress management require a great deal of time and effort. It is also difficult for them to receive appropriate feedback and advice in response to emotional changes and stress levels. Conventional systems do not adequately adjust feedback to reflect the user's individual emotional state, and are therefore unable to effectively support users in maintaining their motivation or improving their performance.

[1686] 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.

[1687] In this invention, the server includes means for receiving goals and tasks from a user, means for storing the received goals and tasks in a storage device, means for analyzing the stored goals and tasks, means for generating optimal feedback and advice based on the analysis results, means for transmitting the generated feedback and advice to a user terminal, means for receiving the user's actions and results and storing them in a storage device, means for analyzing the stored actions and results and tracking progress, means for periodically generating progress reports and transmitting them to the user terminal, means for receiving and analyzing the user's emotional data, and means for adjusting feedback based on the emotional data. This makes it possible to effectively support the user in achieving their goals and provide personalized feedback according to their emotional state.

[1688] "Goals and challenges" refers to the specific objectives the user wants to achieve and the problems they need to address.

[1689] "Means for receiving" refers to an interface for obtaining data input by a user.

[1690] "Storage device" refers to a database or storage system for saving received data.

[1691] "Means for analyzing" refers to algorithms or software that analyze the stored data and generate appropriate action plans or feedback.

[1692] "Feedback and Advice" refers to specific guidelines and advice provided to users based on the analysis results.

[1693] "Means for sending" refers to a communication system for sending the generated feedback or advice to a user terminal.

[1694] "User terminal" refers to a device used by a user, such as a computer, smartphone, or tablet.

[1695] "Actions and Results" refers to the actions actually taken by the user and the results obtained as a result thereof.

[1696] "Progress tracking means" refers to a system for recording user actions and achievements and monitoring progress.

[1697] "Progress Report" refers to a report that is generated periodically that summarizes a user's actions and achievements.

[1698] "Emotion data" is data that indicates the user's emotional state, and includes, for example, stress level and fatigue level.

[1699] An "emotion engine" refers to software or algorithms that analyze users' emotional data and reflect the results in feedback and advice.

[1700] This invention is an AI coaching system that helps businesspeople achieve their goals and maximize their performance. The system includes a means for receiving, storing, and analyzing a user's goals and challenges, and a means for providing generated feedback and advice. Furthermore, the system tracks the user's actions and achievements and periodically generates progress reports. It also includes an emotion engine that recognizes the user's emotions and can adjust feedback based on the emotion data.

[1701] Hardware and Software Use

[1702] The terminal provides an interface for users to input goals and tasks. Terminals can be smartphones, PCs, tablets, etc. These terminals are equipped with a network communication module and send data to the server.

[1703] The server integrates several key components. The database system uses a relational database management system such as PostgreSQL. The generative AI model uses OpenAI GPT-4 and other models to generate feedback and advice for achieving goals. The emotion engine uses Microsoft Azure Emotion API and other models to analyze user emotion data.

[1704] Examples of specific examples and prompts

[1705] For example, if a user sets a goal of "acquiring 10 new clients in the next three months," that information is sent to the server via the device and stored in a database. The server retrieves this goal data, inputs it into a generative AI model for analysis, and generates feedback such as the following:

[1706] "Next week, I recommend creating a prospect list and contacting 10 more companies."

[1707] If the user then reports that they "contacted three new customers today," that data is also sent to the server via the device and tracked.

[1708] Additionally, emotional data is collected. For example, the device's camera and microphone are used to capture the user's facial expressions and tone of voice, and the captured data is sent to a server. The server analyzes this emotional data and adjusts the feedback accordingly if the user is experiencing high levels of stress.

[1709] Here are some example prompts to input to the generative AI model:

[1710] Goal: Acquire 10 new clients

[1711] This week's action: Created a list of potential clients and contacted three companies.

[1712] Perceived stress level: High

[1713] Using the information below, suggest a specific action plan for the user for the next week and some advice on how to reduce stress.

[1714] User goal: Acquire 10 new customers

[1715] Action: This week I created a list of potential clients and contacted three of them.

[1716] Current Emotion: High stress levels

[1717] Suggestion Feedback:

[1718] 1. Specific action plan for next week

[1719] 2. Advice for reducing stress

[1720] This completes the description of the embodiment of the invention. This system supports users in achieving their goals and provides feedback according to their individual emotional state, thereby maintaining their motivation and improving their performance.

[1721] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1722] Step 1:

[1723] The user inputs their goals and objectives into the terminal. For example, they might input "Acquire 10 new clients in the next three months."

[1724] Input: Goals and challenges set by the user.

[1725] Data processing: Convert the goal and task data entered on the terminal into JSON format.

[1726] Output: Goal and assignment data in JSON format.

[1727] Step 2:

[1728] The terminal sends the entered goal and task data to the server, and the content entered by the user is sent via the network module.

[1729] Input: Goal and assignment data in JSON format.

[1730] Data operation: Send data to the server using a network protocol (e.g., HTTP POST request).

[1731] Output: The goal and task data sent to the server.

[1732] Step 3:

[1733] The server stores the received goals and tasks in a database, which is created using PostgreSQL.

[1734] Input: Goal and task data received by the server.

[1735] Data processing: Convert JSON format data into SQL insert statements and store them in the database.

[1736] Output: Goal and task data stored in a database.

[1737] Step 4:

[1738] The server retrieves the target data from the database and provides it to the generative AI model, which uses OpenAI GPT-4.

[1739] Input: Target data in the database.

[1740] Data Calculation: Converting goal data into prompts for the AI, such as "User-defined goal: Acquire 10 new customers."

[1741] Output: The prompt that is input to the generative AI model.

[1742] Step 5:

[1743] Generative AI models generate feedback and advice to help you achieve your goals.

[1744] Input: Prompt data.

[1745] Data computation: A generative AI model analyzes the prompts and generates appropriate feedback and advice, such as, "We recommend that you build a lead list next week and contact 10 more companies."

[1746] Output: Generated feedback and advice.

[1747] Step 6:

[1748] The server transmits the generated feedback and advice to the user terminal.

[1749] Input: Generated feedback and advice data.

[1750] Data operation: Sends data to the user terminal using a network protocol (e.g., HTTP POST request).

[1751] Output: Feedback and advice data sent to the user device.

[1752] Step 7:

[1753] The device will display the received feedback and advice to the user.

[1754] Input: Feedback and advice data sent by the server.

[1755] Data processing: Converting data into a format that can be displayed on the screen, for example, as a text message.

[1756] Output: Feedback and advice displayed to the user.

[1757] Step 8:

[1758] The user enters the actions or results they have achieved into the terminal. For example, they might enter, "I contacted three new customers today."

[1759] Input: User behavior and outcome data.

[1760] Data processing: Converts the action and result data entered on the device into JSON format.

[1761] Output: Behavior and outcome data in JSON format.

[1762] Step 9:

[1763] The terminal transmits the input action and outcome data to the server.

[1764] Input: Action and outcome data in JSON format.

[1765] Data operation: Send data to the server using a network protocol (e.g., HTTP POST request).

[1766] Output: Action and outcome data sent to the server.

[1767] Step 10:

[1768] The server records the received action and outcome data in a database to track progress.

[1769] Input: Action and outcome data received by the server.

[1770] Data processing: Converting JSON data into SQL insert statements and storing them in the database. The saved data is then fed into a progress tracking algorithm to update the progress.

[1771] Output: Behavioral and outcome data recorded in a database, updated progress.

[1772] Step 11:

[1773] The server periodically retrieves the progress data from the database and generates a progress report.

[1774] Input: Progress data in the database.

[1775] Data processing: Aggregate progress data and convert it into a report format, for example, "Contacted three new customers in the past week and received positive responses from two."

[1776] Output: The generated progress report.

[1777] Step 12:

[1778] The server transmits the generated progress report to the user terminal.

[1779] Input: Generated progress report data.

[1780] Data operation: Sends data to the user terminal using a network protocol (e.g., HTTP POST request).

[1781] Output: Progress report sent to user terminal.

[1782] Step 13:

[1783] The terminal displays the received progress report to the user.

[1784] Input: Progress report data sent by the server.

[1785] Data processing: Converting data into a format that can be displayed on the screen, for example, as a text message.

[1786] Output: A progress report displayed to the user.

[1787] Step 14:

[1788] The server analyzes the emotion data obtained from the user.

[1789] Input: User emotion data (e.g., facial capture, voice tone).

[1790] Data Calculation: Uses an emotion engine to analyze emotion data and identify the user's emotional state. For example, high stress level, high fatigue.

[1791] Output: Parsed emotional state data.

[1792] Step 15:

[1793] The server adjusts the feedback based on the emotion data.

[1794] Input: Parsed emotion data and progress data.

[1795] Data Computation: Using generative AI models to regenerate or adjust feedback while taking into account emotional data. Example: Suggesting relaxation techniques for a stressed user.

[1796] Output: Tailored feedback and advice.

[1797] Step 16:

[1798] The device displays tailored feedback to the user.

[1799] Input: Adjusted feedback data sent by the server.

[1800] Data processing: Converting data into a format that can be displayed on the screen, for example, as a text message.

[1801] Output: The adjusted feedback and advice displayed to the user.

[1802] (Application example 2)

[1803] 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."

[1804] Conventional factory robot systems have not adequately optimized production processes or managed the health of operators, leaving challenges in efficient robot operation and reducing operator stress. Furthermore, there is a lack of systems that go beyond simply analyzing production data and provide feedback based on the operator's emotional state. The present invention aims to solve these challenges by providing a system that maximizes the efficiency of factory robots and manages operator stress.

[1805] 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 receiving a user's goals and tasks, means for storing the received goals and tasks in a storage device, means for analyzing the stored goals and tasks, means for generating optimal feedback and advice based on the analysis results, means for transmitting the generated feedback and advice to a user terminal, means for receiving a user's actions and results and storing them in a storage device, means for analyzing the stored actions and results and tracking progress, means for periodically generating progress reports and transmitting them to the user terminal, means for collecting user emotion data, means for analyzing the user emotion data and adjusting feedback based on the emotions, and means for integrating and analyzing the user emotion data and behavioral data. This makes it possible to optimize the operation of a factory robot and provide feedback according to the operator's emotional state.

[1806] "Users" refer to factory managers and operators who use the system.

[1807] A "goal" is a specific production figure or result that the user wants to achieve.

[1808] A "challenge" is a problem or obstacle that a user must solve to achieve their goal.

[1809] A "means" is a method or device used to achieve a particular purpose.

[1810] "Storage device" refers to hardware or software for storing data.

[1811] A "server" is a centralized device for processing and storing data.

[1812] An "AI analysis engine" is software that uses artificial intelligence to analyze data and generate optimal feedback and advice.

[1813] "Feedback" is an evaluation or advice regarding the user's behavior or situation.

[1814] "Advice" is advice on actions or measures users should take to achieve their goals.

[1815] A "user terminal" is a device (e.g., a computer, a smartphone) that is directly operated by a user.

[1816] An "action" is a specific task that a user performs to achieve a goal.

[1817] "Results" refers to the results achieved by a user through their actions.

[1818] "Progress" is information that shows the progress of actions and results toward achieving a goal.

[1819] A "progress report" is a report summarizing progress.

[1820] "Emotional data" is information about a user's emotional state (e.g., stress, fatigue).

[1821] An "emotion engine" is software for analyzing user emotional data.

[1822] "Adjusting feedback based on emotion" means changing the content of feedback or advice based on the user's emotional state.

[1823] "Operation data" is information about the tasks and movements being performed by a factory robot.

[1824] "Tracking" means the continuous monitoring and recording of certain information.

[1825] This invention is an AI coaching system for optimizing manufacturing processes using factory robots and managing operator stress. The system includes means for receiving, storing, and analyzing user (factory manager or operator) goals and challenges, generating and sending feedback and advice, tracking behavior and results, generating progress reports, collecting and analyzing emotional data, and adjusting feedback.

[1826] Explaining program processing in natural language

[1827] The hardware used includes factory robots (e.g., general-purpose robotic devices), cameras (e.g., general-purpose webcams), and microphones (e.g., general-purpose USB microphones).The software used includes AI analysis engines (e.g., TensorFlow, PyTorch), emotion engines (e.g., Affectiva SDK), databases (e.g., PostgreSQL), and communication protocols (e.g., MQTT).

[1828] 1. Goal setting and receiving:

[1829] The server receives the goal entered by the factory manager into the edge device. For example, the factory manager sets a goal of "increasing daily production volume by 10%." The edge device sends this goal to the server and stores it in the server's storage device.

[1830] 2. Generate feedback and advice:

[1831] The server retrieves the goals and tasks from the storage device and inputs them into the AI ​​analysis engine. The AI ​​analysis engine analyzes the manufacturing process data and generates feedback and advice that suggests optimal operations and adjustments. For example, advice may be generated such as "shorten a specific manufacturing step" or "change the placement of operators." The generated feedback is sent to the factory robot's control system.

[1832] 3. Tracking actions and results:

[1833] The robot records its movement data in real time and transmits it to a server, which stores the tracking data in a storage device and monitors its progress.

[1834] 4. Generate progress reports:

[1835] The server periodically retrieves tracking data from the database and generates progress reports, such as "We've achieved a 5% improvement in continuous uptime over the past week and a new 10% increase in production," which are then sent to the factory manager for display.

[1836] 5. Analysis by Emotion Engine:

[1837] The camera and microphone collect the operator's facial expressions and voice and send them to a server. The emotion engine analyzes this data and determines the operator's emotional state (e.g., stress or fatigue).

[1838] 6. Adjusting feedback based on emotions:

[1839] The server integrates and analyzes emotion data and behavioral data to adjust feedback. For example, if an operator is fatigued, the system will provide feedback recommending a break, thereby supporting efficient production and operator health management.

[1840] Examples of specific examples and prompts

[1841] For example, a factory manager may set a goal of "increasing daily production volume by 10%," and the AI ​​analysis engine may suggest "shortening a specific manufacturing step." This suggestion is sent as feedback to the robot and implemented.

[1842] An example prompt is:

[1843] "Please tell me the progress towards today's goal. Please suggest optimal operations and areas that need adjustment based on the operation status of factory robots and operator sentiment data."

[1844] This system not only improves factory productivity but also supports the health management of operators.

[1845] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1846] Step 1:

[1847] The user (factory manager) inputs a goal into the edge device. For example, this goal might be "improve daily production by 10%." The edge device then sends this goal to the server.

[1848] Input: User-entered goal

[1849] Output: Target data sent to the server

[1850] Step 2:

[1851] The server stores the received goals in a storage device, specifically, in a database.

[1852] Input: Target data sent to the server

[1853] Output: Target data stored in memory device

[1854] Step 3:

[1855] The server retrieves the goals and tasks from the storage device and inputs them into the AI ​​analysis engine, which analyzes the data and generates optimal feedback and advice. During this process, machine learning algorithms find patterns in the data and suggest action plans.

[1856] Input: Goals and tasks retrieved from memory

[1857] Output: Feedback and advice generated by the AI ​​analytics engine

[1858] Step 4:

[1859] The server transmits the generated feedback and advice to the control systems of the factory robots, which adjust their operations based on the feedback and advice.

[1860] Input: Feedback and advice generated by the AI ​​analytics engine

[1861] Output: Adjustment of factory robot movements

[1862] Step 5:

[1863] The user (operator) monitors the actions performed by the robot during the manufacturing process, and the robot records the action data in real time and sends it to the server.

[1864] Input: Real-time operational data generated by factory robots

[1865] Output: Operational data sent to the server

[1866] Step 6:

[1867] The server stores the received operational data in a storage device and monitors progress, which is continuously stored in a database and used to generate progress reports.

[1868] Input: Operational data sent to the server

[1869] Output: Operational data stored in a memory device

[1870] Step 7:

[1871] The server periodically retrieves tracking data from the database and generates progress reports, which are then sent to the factory manager for display.

[1872] Input: Tracking data retrieved from the database

[1873] Output: Generated progress report and its display

[1874] Step 8:

[1875] The camera and microphone are used to collect the user's (operator's) emotional data, which includes facial expression recognition and voice analysis, and is sent to the server.

[1876] Input: Emotion data collected from the camera and microphone

[1877] Output: Emotion data sent to the server

[1878] Step 9:

[1879] The server uses an emotion engine to analyze the received emotion data and determine the user's emotional state (e.g., stress or fatigue) based on the analysis results.

[1880] Input: Emotion data sent to the server

[1881] Output: Parsed emotional state data

[1882] Step 10:

[1883] The server integrates and analyzes the emotional state data and behavioral data to adjust the feedback, such as when the user is fatigued, to recommend taking a break.

[1884] Input: Parsed emotional state data and behavioral data

[1885] Output: Regulated Feedback

[1886] This system's series of processes not only improves factory productivity but also effectively manages the health of operators.

[1887] 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.

[1888] 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.

[1889] 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.

[1890] 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.

[1891] 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.

[1892] 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.

[1893] 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).

[1894] 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.

[1895] 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."

[1896] 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.

[1897] 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).

[1898] 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.

[1899] 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.

[1900] 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.

[1901] 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.

[1902] 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.

[1903] 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.

[1904] 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.

[1905] 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.

[1906] 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.

[1907] 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.

[1908] The following is further disclosed regarding the above embodiment.

[1909] (Claim 1)

[1910] means for receiving goals and challenges from a user;

[1911] means for storing the received goals and tasks in a storage device;

[1912] means for analyzing the stored goals and tasks;

[1913] A means for generating optimal feedback and advice based on the analysis results;

[1914] means for transmitting the generated feedback and advice to a user terminal;

[1915] means for receiving and storing the user's actions and results in a storage device;

[1916] means for analyzing the stored actions and achievements and tracking progress;

[1917] means for periodically generating and transmitting progress reports to a user terminal;

[1918] A system including:

[1919] (Claim 2)

[1920] means for tailoring the content and format of the generated feedback and advice based on the user's characteristics and preferences;

[1921] A means of building trust with users,

[1922] The system of claim 1 further comprising:

[1923] (Claim 3)

[1924] a means for generating an action plan for achieving the user's goals;

[1925] a means of adjusting the action plan according to the user's progress;

[1926] The system of claim 1 further comprising:

[1927] "Example 1"

[1928] (Claim 1)

[1929] means for receiving goals and challenges from a user;

[1930] means for storing the received goals and tasks in a storage device;

[1931] means for retrieving and analyzing the stored goals and challenges using a generative AI model;

[1932] A means for generating optimal feedback and advice based on the analysis results;

[1933] means for transmitting the generated feedback and advice to a user terminal;

[1934] means for receiving and storing the user's actions and results in a storage device;

[1935] means for analyzing the stored actions and achievements and tracking progress;

[1936] means for periodically generating and transmitting progress reports to a user terminal;

[1937] means for tailoring the content and format of the generated feedback and advice based on the user's characteristics and preferences;

[1938] A system including:

[1939] (Claim 2)

[1940] means for generating a user action plan;

[1941] a means of adjusting the action plan according to the user's progress;

[1942] The system of claim 1 further comprising:

[1943] (Claim 3)

[1944] A means of building trust with users,

[1945] 10. The system of claim 1, further comprising means for generating a prompt sentence to input to the generative AI model.

[1946] "Application Example 1"

[1947] (Claim 1)

[1948] means for receiving goals and challenges from a user;

[1949] means for storing the received goals and challenges in a database;

[1950] means for utilizing an analysis engine to analyze the stored goals and challenges;

[1951] a means for utilizing an artificial intelligence model to generate optimal feedback and advice based on the analysis results;

[1952] a communication means for transmitting the generated feedback and advice to a user terminal;

[1953] A means for receiving and storing the user's actions and results in a database;

[1954] means for analyzing the stored actions and achievements and tracking progress;

[1955] means for periodically generating and transmitting progress reports to a user terminal;

[1956] a means for recording user actions and outcomes and automatically generating new action plans from the tracked data;

[1957] A system including:

[1958] (Claim 2)

[1959] means for tailoring the content and format of the generated feedback and advice based on the user's characteristics and preferences;

[1960] 10. The system of claim 1, further comprising means for establishing a trust relationship with the user.

[1961] (Claim 3)

[1962] A means for automatically adjusting the action plan according to the user's progress;

[1963] 10. The system of claim 1, further comprising means for dynamically updating the generated feedback and advice based on user performance.

[1964] "Example 2: Combining Emotion Engines"

[1965] (Claim 1)

[1966] means for receiving goals and challenges from a user;

[1967] means for storing the received goals and tasks in a storage device;

[1968] means for analyzing the stored goals and tasks;

[1969] A means for generating optimal feedback and advice based on the analysis results;

[1970] means for transmitting the generated feedback and advice to a user terminal;

[1971] means for receiving and storing the user's actions and results in a storage device;

[1972] means for analyzing the stored actions and achievements and tracking progress;

[1973] means for periodically generating and transmitting progress reports to a user terminal;

[1974] means for receiving and analyzing user emotion data;

[1975] a means for adjusting feedback based on the emotional data;

[1976] A system including:

[1977] (Claim 2)

[1978] means for tailoring the content and format of the generated feedback and advice based on the user's characteristics and preferences;

[1979] means for generating the generated feedback and advice based on a generative AI model;

[1980] A means of building trust with users,

[1981] means for providing a sensor for collecting user emotion data in real time;

[1982] The system of claim 1 further comprising:

[1983] (Claim 3)

[1984] a means for generating an action plan for achieving the user's goals;

[1985] a means of adjusting the action plan according to the user's progress;

[1986] A means for providing advice for achieving goals based on the user's emotional data;

[1987] The system of claim 1 further comprising:

[1988] "Application example 2 when combining emotion engines"

[1989] (Claim 1)

[1990] means for receiving goals and challenges from a user;

[1991] means for storing the received goals and tasks in a storage device;

[1992] means for analyzing the stored goals and tasks;

[1993] A means for generating optimal feedback and advice based on the analysis results;

[1994] means for transmitting the generated feedback and advice to a user terminal;

[1995] means for receiving and storing the user's actions and results in a storage device;

[1996] means for analyzing the stored actions and achievements and tracking progress;

[1997] means for periodically generating and transmitting progress reports to a user terminal;

[1998] a means for collecting user emotional data;

[1999] a means for analyzing the user's emotional data and adjusting the feedback based on the emotional data;

[2000] A means of integrating and analyzing user emotional and behavioral data,

[2001] A system including:

[2002] (Claim 2)

[2003] means for tailoring the content and format of the generated feedback and advice based on the user's characteristics and preferences;

[2004] A means of building trust with users,

[2005] A method to suggest relaxation methods and break times based on the user's emotional data,

[2006] The system of claim 1 further comprising:

[2007] (Claim 3)

[2008] a means for generating an action plan for achieving the user's goals;

[2009] a means of adjusting the action plan according to the user's progress;

[2010] A means for recording and tracking the operation data of factory robots in real time;

[2011] The system of claim 1 further comprising: [Explanation of symbols]

[2012] 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. means for receiving goals and challenges from a user; means for storing the received goals and tasks in a storage device; means for analyzing the stored goals and tasks; A means for generating optimal feedback and advice based on the analysis results; means for transmitting the generated feedback and advice to a user terminal; means for receiving and storing the user's actions and results in a storage device; means for analyzing the stored actions and achievements and tracking progress; means for periodically generating and transmitting progress reports to a user terminal; A system including:

2. means for tailoring the content and format of the generated feedback and advice based on the user's characteristics and preferences; A means of building trust with users, The system of claim 1 further comprising:

3. a means for generating an action plan for achieving the user's goals; a means of adjusting the action plan according to the user's progress; The system of claim 1 further comprising:

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