system

Abstract

Provide a system. 【Solution means】 Means for receiving and storing target data from a user, Means for generating relevant questions based on the target data, Means for presenting the questions to the user and collecting answer data, Means for analyzing the answer data and identifying the essential elements of the user, Means for comparing the target data with the analysis result and identifying the gap, Means for generating an action plan to fill the gap, Means for presenting the action plan to the user A system including.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Many individuals are in a situation where it is difficult to receive appropriate guidance and support to realize their ideal selves. In particular, when aiming at career path formation and life improvement, it is difficult to clearly understand what specific steps should be taken. There is a need to improve such a situation and provide personalized mentoring for individual users.

Means for Solving the Problems

[0005] The present invention provides a system that presents an optimal growth path to each individual user and supports its realization by comprising means for receiving and storing target data from the user, means for generating relevant questions based on the target data, means for presenting questions to the user and collecting response data, means for analyzing the response data and identifying the user's essential elements, means for comparing the target data with the analysis results and identifying gaps, means for generating an action plan to bridge the gaps, and means for presenting the action plan to the user.

[0006] A "user" is an individual who uses a system to achieve their own goals and realize their ideals.

[0007] "Target data" refers to information in which users specifically describe their ideal self or the goals they wish to achieve.

[0008] "Questions" are generated based on the user's goal data and are necessary to understand the user's essential characteristics and current situation.

[0009] "Response data" refers to the response information that users provide in response to the questions presented to them.

[0010] "Analysis" is an information processing method used to identify essential user elements based on collected response data.

[0011] A "gap" is the difference between a user's target data and their current data, and it represents an issue that needs to be addressed to achieve that goal.

[0012] An "action plan" is a collection of specific guidelines and proposals generated by a system to bridge identified gaps. [Brief explanation of the drawing]

[0013] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

MODE FOR CARRYING OUT THE INVENTION

[0014] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0017] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0019] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor and 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), or Bluetooth (registered trademark), and the like.

[0020] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0024] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0025] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0026] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0027] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0028] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0031] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0032] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0033] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0034] This invention is an AI-based system that supports users in achieving their goals, providing the necessary steps for users to realize their ideal selves. This system is implemented in the following form.

[0035] First, the device provides the user with an interface, allowing them to input their goals and ideal self. The information entered here is sent to the server as "goal data" and stored. Next, the server analyzes this goal data and automatically generates questions based on the direction the user is aiming for.

[0036] The generated questions are presented to the user through the device, and the user enters their answers. These answers are sent to the server as "answer data" and stored there. The server analyzes the collected answer data to identify essential elements such as the user's skills, knowledge, and experience.

[0037] Next, the server compares the target data with the analyzed user's current situation and identifies the "gap" between them. Based on this gap, the server generates an action plan that the user can implement. This action plan includes skills to learn and activities to participate in.

[0038] Finally, the device displays the generated action plan to the user, providing specific action plans and suggestions. Based on this information, the user can take their own steps toward their ideal state.

[0039] As a concrete example, consider a user who sets a goal such as "I want to become a marketing director in the future." The server asks the user questions about their current experience and skills via the terminal and analyzes the provided answers. As a result, it identifies that the user needs to improve their strategic thinking and project management skills. Based on this, the server suggests taking online marketing-related courses or attending industry events. The terminal displays these suggestions to the user and helps them take concrete action.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] The device displays a login screen to the user, prompting them to log in to the system with their account. Once the user logs in, their dashboard is displayed.

[0043] Step 2:

[0044] The device displays a screen where the user can input their ideal self or goals. The user then describes their goals in detail and sends the entered information to the server as "goal data."

[0045] Step 3:

[0046] The server stores the received goal data and analyzes its content using a text analysis module. Next, it generates questions to obtain the information the user needs to achieve their goals. These questions are created using a knowledge base related to the user's goals.

[0047] Step 4:

[0048] The terminal displays the generated questions to the user sequentially. The user answers each question in detail and sends these answers to the server as "answer data".

[0049] Step 5:

[0050] The server analyzes the response data collected from users using natural language processing technology. From the analysis results, it identifies the user's skills, knowledge, and experience level, and gains a detailed understanding of the user's current situation.

[0051] Step 6:

[0052] The server compares the user's current data with their target data and identifies the gap between them. Next, it generates a specific action plan to bridge this gap.

[0053] Step 7:

[0054] The device visually displays the generated action plan to the user. The user can then plan and execute the next steps based on this plan.

[0055] Step 8:

[0056] The server regularly collects user feedback and progress updates, and updates the action plan as needed. The device notifies the user of new information, supporting continuous growth.

[0057] (Example 1)

[0058] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0059] Traditionally, it has been difficult for users to effectively formulate concrete steps to achieve their goals. In particular, it has been difficult to construct appropriate action plans tailored to each user's individual skill and knowledge level, often resulting in delays in goal achievement. The present invention aims to solve these problems and provide a system that supports users' efficient self-realization.

[0060] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0061] In this invention, the server includes means for receiving and storing information about goals from the user, means for automatically generating relevant information requests based on the information, and means for presenting the information requests to the user and collecting the user's response. This enables the user to quickly obtain a specific and actionable action plan tailored to their individual needs regarding their goals.

[0062] "Information related to goals" refers to information that includes specific data and facts about the state the user aims for or the objectives they wish to achieve.

[0063] An "information request" is a question or request for data generated to uncover details related to the user's goals.

[0064] "User response" refers to the answers and feedback that users provide in response to information requests.

[0065] "Capability elements" refer to fundamental elements that are identified as individual characteristics, such as a user's skills, knowledge, and experience.

[0066] "Difference" refers to the discrepancies or deficiencies that exist between the user's current situation and the information regarding their goals.

[0067] An "action plan" is a plan that includes specific steps and strategies that a user should take to achieve their goals.

[0068] "Natural language processing technology" refers to the technology used to enable computers to understand and generate human language.

[0069] An "educational program" is a learning process organized for users to acquire specific knowledge or skills.

[0070] "Skills enhancement activities" refer to training and practice activities aimed at improving users' skills and expertise.

[0071] A "networking event" is a gathering designed as a place for users to build networks with other individuals and share knowledge and experiences.

[0072] This invention is an AI-based support system that provides users with specific steps to achieve their goals. The invention is implemented utilizing terminals, servers, and generative AI models.

[0073] The terminal provides a user interface and displays a form for the user to input information about their goals. This form allows the user to enter their goals via text boxes and selection menus. The entered goal information is converted into the appropriate data format and sent to the server.

[0074] The server stores the goal information received from the user in a database. Based on the stored data, the server generates information requests. In this process, a generative AI model is used, and relevant questions are automatically generated using natural language processing techniques. For example, by inputting "Generate questions related to the user's goals" as a prompt into the model, an appropriate information request is generated.

[0075] The generated information request is presented to the user via the terminal. The user inputs a response to this information request, and the terminal sends that response to the server. The server analyzes the user's response data and uses machine learning algorithms to identify the user's capability elements. Based on this analysis, the server compares it with target information and identifies any discrepancies.

[0076] Based on the identified differences, the server generates an action plan. This plan includes specific actionable steps, such as educational programs, skills development activities, and social events. Finally, the generated action plan is presented to the user via the terminal.

[0077] For example, if a user sets the goal of "becoming a marketing director," the server generates questions about their past experience and skills and analyzes the user's responses. If the results identify that the user needs to improve their strategic thinking and project management skills, the server can include suitable online courses or industry events in their action plan. This information is displayed to the user on their device, providing concrete steps toward self-actualization.

[0078] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0079] Step 1:

[0080] The terminal provides the user with an interface and presents an input form for goal information. The user enters their goal into a text box and submits the data by pressing the submit button. The input in this process is the user's goal information, and the output is that information converted into a digital data format.

[0081] Step 2:

[0082] The terminal transmits the entered target information as digital data to the server. The server stores this data in a database. The input is digitized target information, and the output is structured data stored in the database.

[0083] Step 3:

[0084] The server analyzes the stored goal data and automatically generates relevant information requests using a generative AI model. The prompt "Generate questions related to the user's goals" is input to the model, and the AI ​​uses natural language processing techniques to generate appropriate questions. The input is the goal data, and the output is the automatically generated questions.

[0085] Step 4:

[0086] The terminal presents the user with a generated information request. The user inputs their response via the interface. The input is the question received from the server, and the output is the user's response data.

[0087] Step 5:

[0088] The device sends the user's responses as "response data" to the server. The server receives this data and stores it again in its database. Simultaneously, it analyzes the response data using a machine learning algorithm to identify the user's ability elements. The input is the user's response data, and the output is the analyzed user ability elements.

[0089] Step 6:

[0090] The server compares the identified user's capability elements with target data and identifies discrepancies. This analysis clarifies the shortcomings and gaps that need to be filled in order to achieve the goals. The input is the analyzed capability elements and target data, and the output is gap information.

[0091] Step 7:

[0092] The server generates an action plan based on the identified gaps. This action plan includes educational programs, skills development activities, and social events, and is structured as concrete steps that the user can take. The input is gap information, and the output is the user-oriented action plan.

[0093] Step 8:

[0094] The terminal displays the generated action plan to the user, indicating the specific actions to take next. Upon completion of this process, the user gains a clear set of steps toward achieving their goals. The input is the action plan received from the server, and the output is the specific action plan displayed in the user interface.

[0095] (Application Example 1)

[0096] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0097] In modern industry, there is a demand for increased efficiency in machine operation and manufacturing processes. However, it is not easy for workers to identify specific steps and skill gaps necessary to achieve their goals and to take action accordingly. In particular, a lack of real-time support and rapid feedback hinders improvements in work efficiency.

[0098] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0099] In this invention, the server includes means for receiving and storing target data from the user, means for presenting information in real time through the user's device, and means for displaying the action plan in a format suitable for the user's environment. This enables workers to identify specific steps and necessary skills to achieve their goals and to immediately put them into practice.

[0100] "Means for receiving and storing goal data from users" refers to technologies for collecting information about the objectives and goals set by users and storing it in a storage device.

[0101] "Means for generating relevant questions based on the aforementioned target data" refers to a technology that automatically creates questions that are in line with the goals set by the user.

[0102] "Means for presenting the aforementioned questions to users and collecting response data" refers to the process of displaying the generated questions to users and collecting their responses.

[0103] "Means for analyzing the aforementioned response data and identifying the essential elements of the user" refers to a technology that analyzes user responses and clarifies the characteristics of the user's skills and knowledge.

[0104] "Means of presenting information in real time through the user's device" refers to methods of providing information instantly through the user's device.

[0105] "Means for comparing the aforementioned target data with the analysis results and identifying the gap" refers to techniques for finding the difference between the user's goals and the current situation.

[0106] "Means for generating an action plan to bridge the gap" refers to a technique for creating a specific action plan to resolve the identified gap.

[0107] "Means for displaying the aforementioned action plan in a format suitable for the user's environment" refers to technology for presenting an action plan in a format appropriate to the user's environment.

[0108] The system that implements this application works by facilitating data communication between a user terminal and a server. The terminal provides a user interface for the user to input target data. This target data is sent from the terminal to the server and stored there.

[0109] The server analyzes the received target data and generates relevant questions based on the user's situation. Natural language processing technology is used for this question generation. The generated questions are presented to the user via the terminal, and the user enters their answers. The answer data is also sent to the server and stored.

[0110] Next, the server analyzes the response data to identify essential elements such as the user's skills, knowledge, and experience. The server compares the user's goals with the analyzed elements to identify skill gaps in achieving those goals. Based on the identified gaps, the server generates an action plan. The action plan includes specific skills to be learned and activities to participate in.

[0111] The generated action plan is displayed on the device in a format tailored to the user's environment. Users can review these suggestions on the device and take concrete action. Hardware options include smart glasses or similar wearable devices. The software will utilize Python programs and TENSORFLOW®.

[0112] For example, if a factory worker sets a goal to improve the efficiency of the production line, the server can suggest the skills and procedures necessary to improve efficiency.

[0113] An example of a prompt message would be: "Create an AI assistant that suggests the skills needed to improve efficiency and how to improve current work procedures, based on the goals set by the user."

[0114] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0115] Step 1:

[0116] The user inputs goal data through their device. This goal data includes specific objectives they wish to achieve. The device converts this information into a digital format and sends it to the server.

[0117] Step 2:

[0118] The server stores the received target data. This stored data is used to generate relevant questions based on the targets. Utilizing natural language processing techniques, the server automatically creates customized questions based on the target data.

[0119] Step 3:

[0120] The server generates a question and sends it to the terminal, which then displays the question to the user. The user enters and inputs their answer to the displayed question. This answer data then proceeds to the next process.

[0121] Step 4:

[0122] The user's response data is sent from the terminal to the server. The server analyzes this data to identify essential elements such as the user's skills, knowledge, and experience. This process uses a generative AI model and applies regression analysis and classification algorithms.

[0123] Step 5:

[0124] The server compares identified essential elements with target data. This comparison reveals the gap between the user's current state and the conditions necessary to achieve the goals. Data mining techniques are used to identify this gap.

[0125] Step 6:

[0126] The server generates an action plan for the user based on the gaps. The action plan includes specific training and work processes that need improvement. The generated plan is sent to the terminal in JSON format.

[0127] Step 7:

[0128] The device displays the received action plan in a format suitable for the user's environment. The user can then follow the displayed action plan to take steps toward achieving their goals. Through this feedback loop, the user can continuously improve.

[0129] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0130] This invention combines a system that supports users in achieving their goals with an emotion engine that recognizes the user's emotional state. This system provides personalized mentoring tailored to the user's emotions, helping them more effectively realize their ideal self.

[0131] First, the device provides the user with a login screen, and the user logs in. After logging in, the user is taken to a screen where they can enter their goals and ideal self. The goals entered by the user are sent to the server as "goal data" and stored within the system.

[0132] Next, the server uses natural language processing technology to analyze the goal data and generate questions related to the user's goals. Furthermore, the server uses an emotion engine to infer the user's emotional state and adjusts the content and timing of the questions based on the results. The generated questions are then presented to the user via the terminal.

[0133] When a user answers a question, the server receives and stores the response data. The sentiment engine analyzes the text data contained in these responses to identify the user's emotional elements. This clarifies the user's current emotional state.

[0134] Next, the server compares the target data with the user's current situation (skills and experience) and identifies the gap. Taking into account the results of the emotion engine's analysis, it generates an action plan tailored to the user's psychological motivations and drive. This may include recommendations for educational programs, skill-building activities, or industry events.

[0135] Finally, when the device presents an action plan to the user, it utilizes an emotion engine to select a presentation style that matches the user's emotional state. For example, if the user is highly motivated, it will present more challenging content; conversely, if they are feeling anxious, it will provide reassuring information. This allows users to receive optimal support tailored to their emotions and move forward towards achieving their ideals.

[0136] As a concrete example, suppose a user sets the goal of "leading a team to success as a project manager." In this case, the server analyzes the user's experience and skill level and generates questions related to "team leadership" and "project management." Furthermore, if the emotion engine determines that the user is "highly motivated," the terminal will present an action plan that encourages setting challenging goals. On the other hand, if the user is experiencing "anxiety or fear," the plan will focus on reinforcing basic skills. In this way, the system provides flexible support based on emotions.

[0137] The following describes the processing flow.

[0138] Step 1:

[0139] The device displays a login screen to the user, who then logs in using their account information. After logging in, the user's dashboard screen is displayed.

[0140] Step 2:

[0141] The device displays a form for the user to input their goals and ideal self. The user enters their goal data into this form and presses the submit button upon completion. The submitted goal data is sent to the server.

[0142] Step 3:

[0143] The server stores the received goal data and analyzes its content using natural language processing technology. This analysis prepares the server to generate questions related to the user's goal achievement.

[0144] Step 4:

[0145] The server activates the emotion engine and receives data from the sensors and cameras being used to infer the user's emotional state while accessing the system. The analyzed emotion information is used to adjust the content and timing of questions.

[0146] Step 5:

[0147] The server generates questions related to the user's goals. The generated questions are adjusted to the user's emotional state. For example, if the user is highly focused, deep questions are asked; if they are easily distracted, concise questions are prepared.

[0148] Step 6:

[0149] The device displays generated questions to the user sequentially, and the user answers them. The answer data is sent from the device to the server and stored there.

[0150] Step 7:

[0151] The server analyzes user response data using natural language processing technology. This analysis identifies essential elements such as the user's skills, experience, and knowledge, as well as the emotional characteristics expressed in the responses.

[0152] Step 8:

[0153] The server compares the target data with the analysis results and identifies any gaps between them. In addition, it takes into account the user's psychological motivations and motives based on emotional information.

[0154] Step 9:

[0155] The server generates an action plan based on the user's gaps and emotional information. The plan includes skill enhancements, networking events to attend, and learning resources. The plan is designed to be flexible based on the user's emotional state.

[0156] Step 10:

[0157] The device presents the user with a generated action plan, and the emotion engine suggests a way of expressing it that is tailored to each individual user. This ensures that appropriate support is provided according to the user's emotional state.

[0158] Step 11:

[0159] The server continuously collects user feedback and new emotional state data to improve and update action plans. This allows for continuous personalized support and helps users grow.

[0160] (Example 2)

[0161] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0162] Conventional goal-achievement support systems have struggled to provide individualized support that takes into account the user's emotional state. Furthermore, the lack of flexibility in question generation and action plan presentation to adapt to the user's different emotional state has hindered users from effectively progressing towards their goals.

[0163] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0164] In this invention, the server includes means for receiving and storing goal data from the user, means for generating related questions, and means for analyzing the response data to identify the user's emotional state. This makes it possible to improve the quality of support for the user in achieving their goals and to provide individualized and effective support tailored to their emotional state.

[0165] "Target data" refers to information that expresses the goals or ideal state that the user wishes to achieve.

[0166] "Question generation" refers to the process of creating appropriate questions for users based on information about their goal data.

[0167] "Response data" refers to the information and answers that users provide in response to the questions presented to them.

[0168] "Emotional state" refers to the user's psychological state and feelings at any given time.

[0169] An "action plan" refers to a plan that outlines the specific means and steps necessary for a user to achieve their goals.

[0170] A "generative model" refers to an artificial intelligence model that learns from large amounts of data and enables tasks such as natural language generation.

[0171] A "prompt statement" refers to a sentence or phrase that is input to a generative model in order to obtain a specific response.

[0172] This invention is a system that supports users in achieving their goals and provides personalized plans that take into account the user's emotional state. The user first logs in via a terminal and enters their goals. This goal data is then sent to and stored on the server. The server utilizes a generative AI model and analyzes this goal data through natural language processing. Using the results, the server generates questions related to the user's goals. Prompt statements are used in the generation process; for example, appropriate questions are generated for the goal data "I want to lead my team to success as a project manager." An example of a prompt statement is, "Generate emotion-based questions and action plans to support the user in achieving their goals."

[0173] Furthermore, the server uses an emotion engine to infer the user's emotional state and adjusts the content and timing of the questions based on this. This process enables targeting that aligns with the user's emotional needs. The generated questions are presented to the user via the device, and the user's responses are sent back to the server. The server analyzes the response data to reveal the user's emotional state.

[0174] Based on this, the server compares the target data with the user's current skills and experience and generates an action plan necessary for achievement. This plan includes educational programs, skill-building activities, and industry networking events. Finally, the terminal presents this action plan to the user, using a presentation style that matches the user's emotional state to maximize the effectiveness of the support. The entire system aims to adapt to the user's emotional state and provide optimal support.

[0175] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0176] Step 1:

[0177] The user logs in using their device. They enter their user ID and password on the login screen and send this information to the authentication server. The server verifies the entered authentication information against its database. If authentication is successful, it starts a session and displays the user's goal input screen. A notification of successful authentication is sent to the device.

[0178] Step 2:

[0179] The user enters their goals and ideal self into the device. The entered goal data is sent to the server and stored directly in the database. The server receives this goal data and sends a response message to the device confirming that it has been saved.

[0180] Step 3:

[0181] The server retrieves the stored target data and performs analysis using a generative AI model. The server uses natural language processing techniques to extract keywords and analyze intent from the target data, generating relevant questions based on the results. In this process, prompts are used to instruct the generative AI model to generate responses, resulting in highly relevant questions. The generated questions are formatted into a data format and sent to the terminal.

[0182] Step 4:

[0183] The terminal displays questions received from the server to the user. The user enters answers to each question via the terminal. This answer data is sent to the server in real time and stored in the database. The terminal displays a message to the user confirming that the questions have been successfully submitted.

[0184] Step 5:

[0185] The server analyzes user response data. It uses an emotion engine to analyze the response text and infer the user's emotional state. Text mining techniques are employed to identify emotions, and an emotion score is calculated and recorded in a database. This score is used to generate action plans.

[0186] Step 6:

[0187] The server compares target data with the user's current skill information to identify gaps. Taking into account analysis results regarding emotional state, it generates an action plan tailored to the user's motivation. Using a generative AI model, it creates specific educational activities, skill development suggestions, and participation proposals for social events using prompt messages. This action plan is then sent to the user's device.

[0188] Step 7:

[0189] The device presents the user with an action plan sent from the server. Based on the output of the emotion engine, the plan is displayed in a user-friendly interface that is tailored to the user's emotional state. The content of the feedback is adjusted according to the user's emotional state.

[0190] (Application Example 2)

[0191] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0192] In modern factory environments, improving productivity and optimizing operator work efficiency are key challenges. However, traditional methods struggle to create efficient work plans that take into account the emotions and stress levels of individual operators. Therefore, there is a need for new approaches that provide personalized support tailored to the emotional state of workers, promote efficient production activities, and reduce work-related stress.

[0193] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0194] In this invention, the server includes means for receiving and storing goal information from a user; means for generating relevant questions based on the goal information; means for presenting the questions to the user and collecting answer information; means for analyzing the answer information and identifying the user's emotional elements; means for comparing the goal information with the analysis results and identifying the differences; means for generating an action plan to bridge the differences; means for presenting the action plan to the user and selecting a method of expression based on the emotional state; and means for adjusting work suggestions to the user based on the emotional state. This enables flexible and effective work support tailored to the emotional state of each operator.

[0195] A "user" is an individual or group that uses this system to set goals and strive to achieve them.

[0196] "Goal information" refers to data and information about the goals that users wish to achieve.

[0197] "Relevant questions" are questions generated based on goal information to support the user in achieving their goals.

[0198] "Answer information" refers to data and information about the answers to questions that users have provided to the system.

[0199] "Emotional elements" are elements analyzed to identify the user's emotional and psychological state.

[0200] "Difference" refers to the gap between the user's current situation and their goals, identified by comparing target information with analysis results.

[0201] An "action plan" is a set of specific steps or proposals for action created to bridge identified gaps.

[0202] "Method of presentation" refers to the way and style in which information or plans are presented, which is adjusted according to the user's emotional state.

[0203] A "task proposal" is a specific task suggestion presented to the user while taking their emotional state into consideration.

[0204] This invention is a system designed to support operators in factories and can improve work efficiency based on the user's emotional state. The system is intended for use by operators via smart glasses, allowing them to obtain information in real time even while working.

[0205] The server is responsible for receiving and storing goal information from the user. Based on this goal information, it generates relevant questions and displays them on the smart glasses. The server receives the question answers and analyzes them using natural language processing technology. In doing so, it utilizes an emotion engine to identify the user's emotional elements. This analysis reveals the discrepancies between the user's current situation and their goal information.

[0206] The server then creates an action plan to bridge the gap. This action plan includes specific details such as educational programs, skills development activities, or the introduction of automation tools. The action plan is presented in a way that is tailored to the user's emotional state and is offered as a work suggestion to the user.

[0207] For example, if an operator sets a goal of eliminating bottlenecks in the manufacturing process, the server will generate related questions, such as "What are some areas for improvement in the current process?" Based on these results, line balancing and suggestions for new automation tools will be made.

[0208] Examples of prompt messages are as follows:

[0209] "What actions should be taken to improve the efficiency of the manufacturing line? Please suggest ways to improve current performance based on emotional states."

[0210] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0211] Step 1:

[0212] The user logs into the system via smart glasses. The logged-in information is sent from the device to the server for user authentication. This allows the system to associate the user's environment with their goal information.

[0213] Step 2:

[0214] The user inputs their desired goals through smart glasses. The device retrieves this goal information and sends it to the server. The server stores the goal information in a database and prepares it for data analysis in the next step.

[0215] Step 3:

[0216] The server generates relevant questions based on the stored goal information. Using natural language processing techniques, it generates prompt sentences related to the goal, preparing to extract the information necessary for the user to achieve that goal. The input for this step is the goal information, and the output is the generated prompt sentences.

[0217] Step 4:

[0218] The server presents generated questions to the user via smart glasses. The user answers the presented questions, and the answers are sent from the device to the server. The device controls the display of the questions and provides an interface that makes it easy for the user to answer.

[0219] Step 5:

[0220] The server analyzes the response information received from the user. Here, it utilizes an emotion engine to extract emotional elements from the user's responses. The input is the response information, and the output is the analyzed emotional element data. Through data analysis, it becomes possible to identify the user's emotional state.

[0221] Step 6:

[0222] The server compares the target information with the analyzed emotional elements and identifies the differences between them. By clarifying the gap between the user's current situation and their goals, the server forms the basis for the next necessary action plan.

[0223] Step 7:

[0224] The server generates an action plan to bridge the identified discrepancies. This plan includes specific steps such as implementing training programs or automation tools. The input is the discrepancy information, and the output is the action plan.

[0225] Step 8:

[0226] The server presents the generated action plan to the user. The display style of the action plan is adjusted according to the user's emotional state. In this process, the terminal presents the action plan in a visually clear and easy-to-understand manner, allowing the user to understand it intuitively.

[0227] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0228] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0229] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0230] [Second Embodiment]

[0231] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0232] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0233] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0234] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0235] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0236] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0237] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0238] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0239] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0240] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0241] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0242] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0243] This invention is an AI-based system that supports users in achieving their goals, providing the necessary steps for users to realize their ideal selves. This system is implemented in the following form.

[0244] First, the device provides the user with an interface, allowing them to input their goals and ideal self. The information entered here is sent to the server as "goal data" and stored. Next, the server analyzes this goal data and automatically generates questions based on the direction the user is aiming for.

[0245] The generated questions are presented to the user through the device, and the user enters their answers. These answers are sent to the server as "answer data" and stored there. The server analyzes the collected answer data to identify essential elements such as the user's skills, knowledge, and experience.

[0246] Next, the server compares the target data with the analyzed user's current situation and identifies the "gap" between them. Based on this gap, the server generates an action plan that the user can implement. This action plan includes skills to learn and activities to participate in.

[0247] Finally, the device displays the generated action plan to the user, providing specific action plans and suggestions. Based on this information, the user can take their own steps toward their ideal state.

[0248] As a concrete example, consider a user who sets a goal such as "I want to become a marketing director in the future." The server asks the user questions about their current experience and skills via the terminal and analyzes the provided answers. As a result, it identifies that the user needs to improve their strategic thinking and project management skills. Based on this, the server suggests taking online marketing-related courses or attending industry events. The terminal displays these suggestions to the user and helps them take concrete action.

[0249] The following describes the processing flow.

[0250] Step 1:

[0251] The device displays a login screen to the user, prompting them to log in to the system with their account. Once the user logs in, their dashboard is displayed.

[0252] Step 2:

[0253] The device displays a screen where the user can input their ideal self or goals. The user then describes their goals in detail and sends the entered information to the server as "goal data."

[0254] Step 3:

[0255] The server stores the received goal data and analyzes its content using a text analysis module. Next, it generates questions to obtain the information the user needs to achieve their goals. These questions are created using a knowledge base related to the user's goals.

[0256] Step 4:

[0257] The terminal displays the generated questions to the user sequentially. The user answers each question in detail and sends these answers to the server as "answer data".

[0258] Step 5:

[0259] The server analyzes the response data collected from users using natural language processing technology. From the analysis results, it identifies the user's skills, knowledge, and experience level, and gains a detailed understanding of the user's current situation.

[0260] Step 6:

[0261] The server compares the user's current data with their target data and identifies the gap between them. Next, it generates a specific action plan to bridge this gap.

[0262] Step 7:

[0263] The device visually displays the generated action plan to the user. The user can then plan and execute the next steps based on this plan.

[0264] Step 8:

[0265] The server regularly collects user feedback and progress updates, and updates the action plan as needed. The device notifies the user of new information, supporting continuous growth.

[0266] (Example 1)

[0267] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0268] Traditionally, it has been difficult for users to effectively formulate concrete steps to achieve their goals. In particular, it has been difficult to construct appropriate action plans tailored to each user's individual skill and knowledge level, often resulting in delays in goal achievement. The present invention aims to solve these problems and provide a system that supports users' efficient self-realization.

[0269] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0270] In this invention, the server includes means for receiving and storing information about goals from the user, means for automatically generating relevant information requests based on the information, and means for presenting the information requests to the user and collecting the user's response. This enables the user to quickly obtain a specific and actionable action plan tailored to their individual needs regarding their goals.

[0271] "Information related to goals" refers to information that includes specific data and facts about the state the user aims for or the objectives they wish to achieve.

[0272] An "information request" is a question or request for data generated to uncover details related to the user's goals.

[0273] "User response" refers to the answers and feedback that users provide in response to information requests.

[0274] "Capability elements" refer to fundamental elements that are identified as individual characteristics, such as a user's skills, knowledge, and experience.

[0275] "Difference" refers to the discrepancies or deficiencies that exist between the user's current situation and the information regarding their goals.

[0276] An "action plan" is a plan that includes specific steps and strategies that a user should take to achieve their goals.

[0277] "Natural language processing technology" refers to the technology used to enable computers to understand and generate human language.

[0278] An "educational program" is a learning process organized for users to acquire specific knowledge or skills.

[0279] "Skills enhancement activities" refer to training and practice activities aimed at improving users' skills and expertise.

[0280] A "networking event" is a gathering designed as a place for users to build networks with other individuals and share knowledge and experiences.

[0281] This invention is an AI-based support system that provides users with specific steps to achieve their goals. The invention is implemented utilizing terminals, servers, and generative AI models.

[0282] The terminal provides a user interface and displays a form for the user to input information about their goals. This form allows the user to enter their goals via text boxes and selection menus. The entered goal information is converted into the appropriate data format and sent to the server.

[0283] The server stores the target information received from the user in the database. Based on the stored data, the server generates an information request. In this process, a generation AI model is utilized, and natural language processing technology is used to automatically generate relevant questions. For example, by inputting "Please generate questions related to the user's goal" as a prompt sentence into the model, an appropriate information request is generated.

[0284] The generated information request is presented to the user through the terminal. The user inputs a response to this information request, and the terminal sends the response to the server. The server analyzes the user's response data and uses a machine learning algorithm to identify the user's ability elements. Based on this analysis result, the server compares it with the target information and identifies the existing differences.

[0285] Based on the identified differences, the server generates an action plan. This plan includes specific executable steps such as an educational program, ability improvement activities, and communication events. Finally, the generated action plan is presented to the user through the terminal.

[0286] As a specific example, when the user sets a goal of "becoming a marketing director", the server generates questions about past experiences and skills and analyzes the user's response. As a result, if it is identified that the user needs to improve strategic thinking and project management as necessary skills, the server can include suitable online courses and industry events in the action plan. This information is displayed to the user on the terminal, providing specific steps towards self-fulfillment.

[0287] The specific processing flow in Example 1 will be described using FIG. 11.

[0288] Step 1:

[0289] The terminal provides the user with an interface and presents an input form for goal information. The user enters their goal into a text box and submits the data by pressing the submit button. The input in this process is the user's goal information, and the output is that information converted into a digital data format.

[0290] Step 2:

[0291] The terminal transmits the entered target information as digital data to the server. The server stores this data in a database. The input is digitized target information, and the output is structured data stored in the database.

[0292] Step 3:

[0293] The server analyzes the stored goal data and automatically generates relevant information requests using a generative AI model. The prompt "Generate questions related to the user's goals" is input to the model, and the AI ​​uses natural language processing techniques to generate appropriate questions. The input is the goal data, and the output is the automatically generated questions.

[0294] Step 4:

[0295] The terminal presents the user with a generated information request. The user inputs their response via the interface. The input is the question received from the server, and the output is the user's response data.

[0296] Step 5:

[0297] The device sends the user's responses as "response data" to the server. The server receives this data and stores it again in its database. Simultaneously, it analyzes the response data using a machine learning algorithm to identify the user's ability elements. The input is the user's response data, and the output is the analyzed user ability elements.

[0298] Step 6:

[0299] The server compares the identified user's capability elements with target data and identifies discrepancies. This analysis clarifies the shortcomings and gaps that need to be filled in order to achieve the goals. The input is the analyzed capability elements and target data, and the output is gap information.

[0300] Step 7:

[0301] The server generates an action plan based on the identified gaps. This action plan includes educational programs, skills development activities, and social events, and is structured as concrete steps that the user can take. The input is gap information, and the output is the user-oriented action plan.

[0302] Step 8:

[0303] The terminal displays the generated action plan to the user, indicating the specific actions to take next. Upon completion of this process, the user gains a clear set of steps toward achieving their goals. The input is the action plan received from the server, and the output is the specific action plan displayed in the user interface.

[0304] (Application Example 1)

[0305] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0306] In modern industry, there is a demand for increased efficiency in machine operation and manufacturing processes. However, it is not easy for workers to identify specific steps and skill gaps necessary to achieve their goals and to take action accordingly. In particular, a lack of real-time support and rapid feedback hinders improvements in work efficiency.

[0307] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0308] In this invention, the server includes means for receiving and storing target data from a user, means for presenting information in real time through a device used by the user, and means for displaying the action plan in a form suitable for the user's usage environment. Thereby, an operator can identify specific steps and necessary skills for achieving their own goals and utilize them immediately.

[0309] The means for receiving and storing target data from a user is a technology for collecting information regarding the purposes and goals set by a user and storing it in a storage device.

[0310] The means for generating relevant questions based on the target data is a technology for automatically creating questions that conform to the goals set by the user.

[0311] The means for presenting the questions to the user and collecting answer data is a process for displaying the generated questions to the user and collecting their answers.

[0312] The means for analyzing the answer data and identifying the essential elements of the user is a technology for analyzing the user's answers and clarifying the characteristics of the user's skills and knowledge. [[ID=2C]]

[0313] The means for presenting information in real time through a device used by the user is a method for immediately providing information via the device used by the user.

[0314] [[ID=?]] The means for comparing the target data with the analysis result and identifying the gap is a technology for finding out the difference between the user's goal and the current situation.

[0315] The means for generating an action plan for filling the gap is a technology for creating a specific action plan for eliminating the identified gap.

[0316] It should be noted that there seems to be an error in the original text where "2C" is used instead of "20" in the ID field. This has been maintained in the translation as per the instruction to preserve all tags exactly as-is."Means for displaying the aforementioned action plan in a format suitable for the user's environment" refers to technology for presenting an action plan in a format appropriate to the user's environment.

[0317] The system that implements this application works by facilitating data communication between a user terminal and a server. The terminal provides a user interface for the user to input target data. This target data is sent from the terminal to the server and stored there.

[0318] The server analyzes the received target data and generates relevant questions based on the user's situation. Natural language processing technology is used for this question generation. The generated questions are presented to the user via the terminal, and the user enters their answers. The answer data is also sent to the server and stored.

[0319] Next, the server analyzes the response data to identify essential elements such as the user's skills, knowledge, and experience. The server compares the user's goals with the analyzed elements to identify skill gaps in achieving those goals. Based on the identified gaps, the server generates an action plan. The action plan includes specific skills to be learned and activities to participate in.

[0320] The generated action plan will be displayed on the device in a format tailored to the user's environment. Users can review these suggestions on the device and take concrete action. Hardware options include smart glasses or similar wearable devices. The software will utilize Python programs and TensorFlow.

[0321] For example, if a factory worker sets a goal to improve the efficiency of the production line, the server can suggest the skills and procedures necessary to improve efficiency.

[0322] An example of a prompt message would be: "Create an AI assistant that suggests the skills needed to improve efficiency and how to improve current work procedures, based on the goals set by the user."

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

[0324] Step 1:

[0325] The user inputs goal data through their device. This goal data includes specific objectives they wish to achieve. The device converts this information into a digital format and sends it to the server.

[0326] Step 2:

[0327] The server stores the received target data. This stored data is used to generate relevant questions based on the targets. Utilizing natural language processing techniques, the server automatically creates customized questions based on the target data.

[0328] Step 3:

[0329] The server generates a question and sends it to the terminal, which then displays the question to the user. The user enters and inputs their answer to the displayed question. This answer data then proceeds to the next process.

[0330] Step 4:

[0331] The user's response data is sent from the terminal to the server. The server analyzes this data to identify essential elements such as the user's skills, knowledge, and experience. This process uses a generative AI model and applies regression analysis and classification algorithms.

[0332] Step 5:

[0333] The server compares identified essential elements with target data. This comparison reveals the gap between the user's current state and the conditions necessary to achieve the goals. Data mining techniques are used to identify this gap.

[0334] Step 6:

[0335] The server generates an action plan for the user based on the gaps. The action plan includes specific training and work processes that need improvement. The generated plan is sent to the terminal in JSON format.

[0336] Step 7:

[0337] The device displays the received action plan in a format suitable for the user's environment. The user can then follow the displayed action plan to take steps toward achieving their goals. Through this feedback loop, the user can continuously improve.

[0338] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0339] This invention combines a system that supports users in achieving their goals with an emotion engine that recognizes the user's emotional state. This system provides personalized mentoring tailored to the user's emotions, helping them more effectively realize their ideal self.

[0340] First, the device provides the user with a login screen, and the user logs in. After logging in, the user is taken to a screen where they can enter their goals and ideal self. The goals entered by the user are sent to the server as "goal data" and stored within the system.

[0341] Next, the server uses natural language processing technology to analyze the goal data and generate questions related to the user's goals. Furthermore, the server uses an emotion engine to infer the user's emotional state and adjusts the content and timing of the questions based on the results. The generated questions are then presented to the user via the terminal.

[0342] When a user answers a question, the server receives and stores the response data. The sentiment engine analyzes the text data contained in these responses to identify the user's emotional elements. This clarifies the user's current emotional state.

[0343] Next, the server compares the target data with the user's current situation (skills and experience) and identifies the gap. Taking into account the results of the emotion engine's analysis, it generates an action plan tailored to the user's psychological motivations and drive. This may include recommendations for educational programs, skill-building activities, or industry events.

[0344] Finally, when the device presents an action plan to the user, it utilizes an emotion engine to select a presentation style that matches the user's emotional state. For example, if the user is highly motivated, it will present more challenging content; conversely, if they are feeling anxious, it will provide reassuring information. This allows users to receive optimal support tailored to their emotions and move forward towards achieving their ideals.

[0345] As a concrete example, suppose a user sets the goal of "leading a team to success as a project manager." In this case, the server analyzes the user's experience and skill level and generates questions related to "team leadership" and "project management." Furthermore, if the emotion engine determines that the user is "highly motivated," the terminal will present an action plan that encourages setting challenging goals. On the other hand, if the user is experiencing "anxiety or fear," the plan will focus on reinforcing basic skills. In this way, the system provides flexible support based on emotions.

[0346] The following describes the processing flow.

[0347] Step 1:

[0348] The device displays a login screen to the user, who then logs in using their account information. After logging in, the user's dashboard screen is displayed.

[0349] Step 2:

[0350] The device displays a form for the user to input their goals and ideal self. The user enters their goal data into this form and presses the submit button upon completion. The submitted goal data is sent to the server.

[0351] Step 3:

[0352] The server stores the received goal data and analyzes its content using natural language processing technology. This analysis prepares the server to generate questions related to the user's goal achievement.

[0353] Step 4:

[0354] The server activates the emotion engine and receives data from the sensors and cameras being used to infer the user's emotional state while accessing the system. The analyzed emotion information is used to adjust the content and timing of questions.

[0355] Step 5:

[0356] The server generates questions related to the user's goals. The generated questions are adjusted to the user's emotional state. For example, if the user is highly focused, deep questions are asked; if they are easily distracted, concise questions are prepared.

[0357] Step 6:

[0358] The device displays generated questions to the user sequentially, and the user answers them. The answer data is sent from the device to the server and stored there.

[0359] Step 7:

[0360] The server analyzes user response data using natural language processing technology. This analysis identifies essential elements such as the user's skills, experience, and knowledge, as well as the emotional characteristics expressed in the responses.

[0361] Step 8:

[0362] The server compares the target data with the analysis results and identifies any gaps between them. In addition, it takes into account the user's psychological motivations and motives based on emotional information.

[0363] Step 9:

[0364] The server generates an action plan based on the user's gaps and emotional information. The plan includes skill enhancements, networking events to attend, and learning resources. The plan is designed to be flexible based on the user's emotional state.

[0365] Step 10:

[0366] The device presents the user with a generated action plan, and the emotion engine suggests a way of expressing it that is tailored to each individual user. This ensures that appropriate support is provided according to the user's emotional state.

[0367] Step 11:

[0368] The server continuously collects user feedback and new emotional state data to improve and update action plans. This allows for continuous personalized support and helps users grow.

[0369] (Example 2)

[0370] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0371] Conventional goal-achievement support systems have struggled to provide individualized support that takes into account the user's emotional state. Furthermore, the lack of flexibility in question generation and action plan presentation to adapt to the user's different emotional state has hindered users from effectively progressing towards their goals.

[0372] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0373] In this invention, the server includes means for receiving and storing goal data from the user, means for generating related questions, and means for analyzing the response data to identify the user's emotional state. This makes it possible to improve the quality of support for the user in achieving their goals and to provide individualized and effective support tailored to their emotional state.

[0374] "Target data" refers to information that expresses the goals or ideal state that the user wishes to achieve.

[0375] "Question generation" refers to the process of creating appropriate questions for users based on information about their goal data.

[0376] "Response data" refers to the information and answers that users provide in response to the questions presented to them.

[0377] "Emotional state" refers to the user's psychological state and feelings at any given time.

[0378] An "action plan" refers to a plan that outlines the specific means and steps necessary for a user to achieve their goals.

[0379] A "generative model" refers to an artificial intelligence model that learns from large amounts of data and enables tasks such as natural language generation.

[0380] A "prompt statement" refers to a sentence or phrase that is input to a generative model in order to obtain a specific response.

[0381] This invention is a system that supports users in achieving their goals and provides personalized plans that take into account the user's emotional state. The user first logs in via a terminal and enters their goals. This goal data is then sent to and stored on the server. The server utilizes a generative AI model and analyzes this goal data through natural language processing. Using the results, the server generates questions related to the user's goals. Prompt statements are used in the generation process; for example, appropriate questions are generated for the goal data "I want to lead my team to success as a project manager." An example of a prompt statement is, "Generate emotion-based questions and action plans to support the user in achieving their goals."

[0382] Furthermore, the server uses an emotion engine to infer the user's emotional state and adjusts the content and timing of the questions based on this. This process enables targeting that aligns with the user's emotional needs. The generated questions are presented to the user via the device, and the user's responses are sent back to the server. The server analyzes the response data to reveal the user's emotional state.

[0383] Based on this, the server compares the target data with the user's current skills and experience and generates an action plan necessary for achievement. This plan includes educational programs, skill-building activities, and industry networking events. Finally, the terminal presents this action plan to the user, using a presentation style that matches the user's emotional state to maximize the effectiveness of the support. The entire system aims to adapt to the user's emotional state and provide optimal support.

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

[0385] Step 1:

[0386] The user logs in using their device. They enter their user ID and password on the login screen and send this information to the authentication server. The server verifies the entered authentication information against its database. If authentication is successful, it starts a session and displays the user's goal input screen. A notification of successful authentication is sent to the device.

[0387] Step 2:

[0388] The user enters their goals and ideal self into the device. The entered goal data is sent to the server and stored directly in the database. The server receives this goal data and sends a response message to the device confirming that it has been saved.

[0389] Step 3:

[0390] The server retrieves the stored target data and performs analysis using a generative AI model. The server uses natural language processing techniques to extract keywords and analyze intent from the target data, generating relevant questions based on the results. In this process, prompts are used to instruct the generative AI model to generate responses, resulting in highly relevant questions. The generated questions are formatted into a data format and sent to the terminal.

[0391] Step 4:

[0392] The terminal displays questions received from the server to the user. The user enters answers to each question via the terminal. This answer data is sent to the server in real time and stored in the database. The terminal displays a message to the user confirming that the questions have been successfully submitted.

[0393] Step 5:

[0394] The server analyzes user response data. It uses an emotion engine to analyze the response text and infer the user's emotional state. Text mining techniques are employed to identify emotions, and an emotion score is calculated and recorded in a database. This score is used to generate action plans.

[0395] Step 6:

[0396] The server compares target data with the user's current skill information to identify gaps. Taking into account analysis results regarding emotional state, it generates an action plan tailored to the user's motivation. Using a generative AI model, it creates specific educational activities, skill development suggestions, and participation proposals for social events using prompt messages. This action plan is then sent to the user's device.

[0397] Step 7:

[0398] The device presents the user with an action plan sent from the server. Based on the output of the emotion engine, the plan is displayed in a user-friendly interface that is tailored to the user's emotional state. The content of the feedback is adjusted according to the user's emotional state.

[0399] (Application Example 2)

[0400] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0401] In modern factory environments, improving productivity and optimizing operator work efficiency are key challenges. However, traditional methods struggle to create efficient work plans that take into account the emotions and stress levels of individual operators. Therefore, there is a need for new approaches that provide personalized support tailored to the emotional state of workers, promote efficient production activities, and reduce work-related stress.

[0402] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0403] In this invention, the server includes means for receiving and storing goal information from a user; means for generating relevant questions based on the goal information; means for presenting the questions to the user and collecting answer information; means for analyzing the answer information and identifying the user's emotional elements; means for comparing the goal information with the analysis results and identifying the differences; means for generating an action plan to bridge the differences; means for presenting the action plan to the user and selecting a method of expression based on the emotional state; and means for adjusting work suggestions to the user based on the emotional state. This enables flexible and effective work support tailored to the emotional state of each operator.

[0404] A "user" is an individual or group that uses this system to set goals and strive to achieve them.

[0405] "Goal information" refers to data and information about the goals that users wish to achieve.

[0406] "Relevant questions" are questions generated based on goal information to support the user in achieving their goals.

[0407] "Answer information" refers to data and information about the answers to questions that users have provided to the system.

[0408] "Emotional elements" are elements analyzed to identify the user's emotional and psychological state.

[0409] "Difference" refers to the gap between the user's current situation and their goals, identified by comparing target information with analysis results.

[0410] An "action plan" is a set of specific steps or proposals for action created to bridge identified gaps.

[0411] "Method of presentation" refers to the way and style in which information or plans are presented, which is adjusted according to the user's emotional state.

[0412] A "task proposal" is a specific task suggestion presented to the user while taking their emotional state into consideration.

[0413] This invention is a system designed to support operators in factories and can improve work efficiency based on the user's emotional state. The system is intended for use by operators via smart glasses, allowing them to obtain information in real time even while working.

[0414] The server is responsible for receiving and storing goal information from the user. Based on this goal information, it generates relevant questions and displays them on the smart glasses. The server receives the question answers and analyzes them using natural language processing technology. In doing so, it utilizes an emotion engine to identify the user's emotional elements. This analysis reveals the discrepancies between the user's current situation and their goal information.

[0415] The server then creates an action plan to bridge the gap. This action plan includes specific details such as educational programs, skills development activities, or the introduction of automation tools. The action plan is presented in a way that is tailored to the user's emotional state and is offered as a work suggestion to the user.

[0416] For example, if an operator sets a goal of eliminating bottlenecks in the manufacturing process, the server will generate related questions, such as "What are some areas for improvement in the current process?" Based on these results, line balancing and suggestions for new automation tools will be made.

[0417] Examples of prompt messages are as follows:

[0418] "What actions should be taken to improve the efficiency of the manufacturing line? Please suggest ways to improve current performance based on emotional states."

[0419] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0420] Step 1:

[0421] The user logs into the system via smart glasses. The logged-in information is sent from the device to the server for user authentication. This allows the system to associate the user's environment with their goal information.

[0422] Step 2:

[0423] The user inputs their desired goals through smart glasses. The device retrieves this goal information and sends it to the server. The server stores the goal information in a database and prepares it for data analysis in the next step.

[0424] Step 3:

[0425] The server generates relevant questions based on the stored goal information. Using natural language processing techniques, it generates prompt sentences related to the goal, preparing to extract the information necessary for the user to achieve that goal. The input for this step is the goal information, and the output is the generated prompt sentences.

[0426] Step 4:

[0427] The server presents generated questions to the user via smart glasses. The user answers the presented questions, and the answers are sent from the device to the server. The device controls the display of the questions and provides an interface that makes it easy for the user to answer.

[0428] Step 5:

[0429] The server analyzes the response information received from the user. Here, it utilizes an emotion engine to extract emotional elements from the user's responses. The input is the response information, and the output is the analyzed emotional element data. Through data analysis, it becomes possible to identify the user's emotional state.

[0430] Step 6:

[0431] The server compares the target information with the analyzed emotional elements and identifies the differences between them. By clarifying the gap between the user's current situation and their goals, the server forms the basis for the next necessary action plan.

[0432] Step 7:

[0433] The server generates an action plan to bridge the identified discrepancies. This plan includes specific steps such as implementing training programs or automation tools. The input is the discrepancy information, and the output is the action plan.

[0434] Step 8:

[0435] The server presents the generated action plan to the user. The display style of the action plan is adjusted according to the user's emotional state. In this process, the terminal presents the action plan in a visually clear and easy-to-understand manner, allowing the user to understand it intuitively.

[0436] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0437] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0438] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0439] [Third Embodiment]

[0440] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0441] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0442] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0443] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0444] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0445] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0446] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0447] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0448] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0449] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0450] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0451] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0452] This invention is an AI-based system that supports users in achieving their goals, providing the necessary steps for users to realize their ideal selves. This system is implemented in the following form.

[0453] First, the device provides the user with an interface, allowing them to input their goals and ideal self. The information entered here is sent to the server as "goal data" and stored. Next, the server analyzes this goal data and automatically generates questions based on the direction the user is aiming for.

[0454] The generated questions are presented to the user through the device, and the user enters their answers. These answers are sent to the server as "answer data" and stored there. The server analyzes the collected answer data to identify essential elements such as the user's skills, knowledge, and experience.

[0455] Next, the server compares the target data with the analyzed user's current situation and identifies the "gap" between them. Based on this gap, the server generates an action plan that the user can implement. This action plan includes skills to learn and activities to participate in.

[0456] Finally, the device displays the generated action plan to the user, providing specific action plans and suggestions. Based on this information, the user can take their own steps toward their ideal state.

[0457] As a concrete example, consider a user who sets a goal such as "I want to become a marketing director in the future." The server asks the user questions about their current experience and skills via the terminal and analyzes the provided answers. As a result, it identifies that the user needs to improve their strategic thinking and project management skills. Based on this, the server suggests taking online marketing-related courses or attending industry events. The terminal displays these suggestions to the user and helps them take concrete action.

[0458] The following describes the processing flow.

[0459] Step 1:

[0460] The device displays a login screen to the user, prompting them to log in to the system with their account. Once the user logs in, their dashboard is displayed.

[0461] Step 2:

[0462] The device displays a screen where the user can input their ideal self or goals. The user then describes their goals in detail and sends the entered information to the server as "goal data."

[0463] Step 3:

[0464] The server stores the received goal data and analyzes its content using a text analysis module. Next, it generates questions to obtain the information the user needs to achieve their goals. These questions are created using a knowledge base related to the user's goals.

[0465] Step 4:

[0466] The terminal displays the generated questions to the user sequentially. The user answers each question in detail and sends these answers to the server as "answer data".

[0467] Step 5:

[0468] The server analyzes the response data collected from users using natural language processing technology. From the analysis results, it identifies the user's skills, knowledge, and experience level, and gains a detailed understanding of the user's current situation.

[0469] Step 6:

[0470] The server compares the user's current data with their target data and identifies the gap between them. Next, it generates a specific action plan to bridge this gap.

[0471] Step 7:

[0472] The device visually displays the generated action plan to the user. The user can then plan and execute the next steps based on this plan.

[0473] Step 8:

[0474] The server regularly collects user feedback and progress updates, and updates the action plan as needed. The device notifies the user of new information, supporting continuous growth.

[0475] (Example 1)

[0476] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0477] Traditionally, it has been difficult for users to effectively formulate concrete steps to achieve their goals. In particular, it has been difficult to construct appropriate action plans tailored to each user's individual skill and knowledge level, often resulting in delays in goal achievement. The present invention aims to solve these problems and provide a system that supports users' efficient self-realization.

[0478] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0479] In this invention, the server includes means for receiving and storing information about goals from the user, means for automatically generating relevant information requests based on the information, and means for presenting the information requests to the user and collecting the user's response. This enables the user to quickly obtain a specific and actionable action plan tailored to their individual needs regarding their goals.

[0480] "Information related to goals" refers to information that includes specific data and facts about the state the user aims for or the objectives they wish to achieve.

[0481] An "information request" is a question or request for data generated to uncover details related to the user's goals.

[0482] "User response" refers to the answers and feedback that users provide in response to information requests.

[0483] "Capability elements" refer to fundamental elements that are identified as individual characteristics, such as a user's skills, knowledge, and experience.

[0484] "Difference" refers to the discrepancies or deficiencies that exist between the user's current situation and the information regarding their goals.

[0485] An "action plan" is a plan that includes specific steps and strategies that a user should take to achieve their goals.

[0486] "Natural language processing technology" refers to the technology used to enable computers to understand and generate human language.

[0487] An "educational program" is a learning process organized for users to acquire specific knowledge or skills.

[0488] "Skills enhancement activities" refer to training and practice activities aimed at improving users' skills and expertise.

[0489] A "networking event" is a gathering designed as a place for users to build networks with other individuals and share knowledge and experiences.

[0490] This invention is an AI-based support system that provides users with specific steps to achieve their goals. The invention is implemented utilizing terminals, servers, and generative AI models.

[0491] The terminal provides a user interface and displays a form for the user to input information about their goals. This form allows the user to enter their goals via text boxes and selection menus. The entered goal information is converted into the appropriate data format and sent to the server.

[0492] The server stores the goal information received from the user in a database. Based on the stored data, the server generates information requests. In this process, a generative AI model is used, and relevant questions are automatically generated using natural language processing techniques. For example, by inputting "Generate questions related to the user's goals" as a prompt into the model, an appropriate information request is generated.

[0493] The generated information request is presented to the user via the terminal. The user inputs a response to this information request, and the terminal sends that response to the server. The server analyzes the user's response data and uses machine learning algorithms to identify the user's capability elements. Based on this analysis, the server compares it with target information and identifies any discrepancies.

[0494] Based on the identified differences, the server generates an action plan. This plan includes specific actionable steps, such as educational programs, skills development activities, and social events. Finally, the generated action plan is presented to the user via the terminal.

[0495] For example, if a user sets the goal of "becoming a marketing director," the server generates questions about their past experience and skills and analyzes the user's responses. If the results identify that the user needs to improve their strategic thinking and project management skills, the server can include suitable online courses or industry events in their action plan. This information is displayed to the user on their device, providing concrete steps toward self-actualization.

[0496] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0497] Step 1:

[0498] The terminal provides the user with an interface and presents an input form for goal information. The user enters their goal into a text box and submits the data by pressing the submit button. The input in this process is the user's goal information, and the output is that information converted into a digital data format.

[0499] Step 2:

[0500] The terminal transmits the entered target information as digital data to the server. The server stores this data in a database. The input is digitized target information, and the output is structured data stored in the database.

[0501] Step 3:

[0502] The server analyzes the stored goal data and automatically generates relevant information requests using a generative AI model. The prompt "Generate questions related to the user's goals" is input to the model, and the AI ​​uses natural language processing techniques to generate appropriate questions. The input is the goal data, and the output is the automatically generated questions.

[0503] Step 4:

[0504] The terminal presents the user with a generated information request. The user inputs their response via the interface. The input is the question received from the server, and the output is the user's response data.

[0505] Step 5:

[0506] The device sends the user's responses as "response data" to the server. The server receives this data and stores it again in its database. Simultaneously, it analyzes the response data using a machine learning algorithm to identify the user's ability elements. The input is the user's response data, and the output is the analyzed user ability elements.

[0507] Step 6:

[0508] The server compares the identified user's capability elements with target data and identifies discrepancies. This analysis clarifies the shortcomings and gaps that need to be filled in order to achieve the goals. The input is the analyzed capability elements and target data, and the output is gap information.

[0509] Step 7:

[0510] The server generates an action plan based on the identified gaps. This action plan includes educational programs, skills development activities, and social events, and is structured as concrete steps that the user can take. The input is gap information, and the output is the user-oriented action plan.

[0511] Step 8:

[0512] The terminal displays the generated action plan to the user, indicating the specific actions to take next. Upon completion of this process, the user gains a clear set of steps toward achieving their goals. The input is the action plan received from the server, and the output is the specific action plan displayed in the user interface.

[0513] (Application Example 1)

[0514] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0515] In modern industry, there is a demand for increased efficiency in machine operation and manufacturing processes. However, it is not easy for workers to identify specific steps and skill gaps necessary to achieve their goals and to take action accordingly. In particular, a lack of real-time support and rapid feedback hinders improvements in work efficiency.

[0516] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0517] In this invention, the server includes means for receiving and storing target data from the user, means for presenting information in real time through the user's device, and means for displaying the action plan in a format suitable for the user's environment. This enables workers to identify specific steps and necessary skills to achieve their goals and to immediately put them into practice.

[0518] "Means for receiving and storing goal data from users" refers to technologies for collecting information about the objectives and goals set by users and storing it in a storage device.

[0519] "Means for generating relevant questions based on the aforementioned target data" refers to a technology that automatically creates questions that are in line with the goals set by the user.

[0520] "Means for presenting the aforementioned questions to users and collecting response data" refers to the process of displaying the generated questions to users and collecting their responses.

[0521] "Means for analyzing the aforementioned response data and identifying the essential elements of the user" refers to a technology that analyzes user responses and clarifies the characteristics of the user's skills and knowledge.

[0522] "Means of presenting information in real time through the user's device" refers to methods of providing information instantly through the user's device.

[0523] "Means for comparing the aforementioned target data with the analysis results and identifying the gap" refers to techniques for finding the difference between the user's goals and the current situation.

[0524] "Means for generating an action plan to bridge the gap" refers to a technique for creating a specific action plan to resolve the identified gap.

[0525] "Means for displaying the aforementioned action plan in a format suitable for the user's environment" refers to technology for presenting an action plan in a format appropriate to the user's environment.

[0526] The system that implements this application works by facilitating data communication between a user terminal and a server. The terminal provides a user interface for the user to input target data. This target data is sent from the terminal to the server and stored there.

[0527] The server analyzes the received target data and generates relevant questions based on the user's situation. Natural language processing technology is used for this question generation. The generated questions are presented to the user via the terminal, and the user enters their answers. The answer data is also sent to the server and stored.

[0528] Next, the server analyzes the response data to identify essential elements such as the user's skills, knowledge, and experience. The server compares the user's goals with the analyzed elements to identify skill gaps in achieving those goals. Based on the identified gaps, the server generates an action plan. The action plan includes specific skills to be learned and activities to participate in.

[0529] The generated action plan will be displayed on the device in a format tailored to the user's environment. Users can review these suggestions on the device and take concrete action. Hardware options include smart glasses or similar wearable devices. The software will utilize Python programs and TensorFlow.

[0530] For example, if a factory worker sets a goal to improve the efficiency of the production line, the server can suggest the skills and procedures necessary to improve efficiency.

[0531] An example of a prompt message would be: "Create an AI assistant that suggests the skills needed to improve efficiency and how to improve current work procedures, based on the goals set by the user."

[0532] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0533] Step 1:

[0534] The user inputs goal data through their device. This goal data includes specific objectives they wish to achieve. The device converts this information into a digital format and sends it to the server.

[0535] Step 2:

[0536] The server stores the received target data. This stored data is used to generate relevant questions based on the targets. Utilizing natural language processing techniques, the server automatically creates customized questions based on the target data.

[0537] Step 3:

[0538] The server generates a question and sends it to the terminal, which then displays the question to the user. The user enters and inputs their answer to the displayed question. This answer data then proceeds to the next process.

[0539] Step 4:

[0540] The user's response data is sent from the terminal to the server. The server analyzes this data to identify essential elements such as the user's skills, knowledge, and experience. This process uses a generative AI model and applies regression analysis and classification algorithms.

[0541] Step 5:

[0542] The server compares identified essential elements with target data. This comparison reveals the gap between the user's current state and the conditions necessary to achieve the goals. Data mining techniques are used to identify this gap.

[0543] Step 6:

[0544] The server generates an action plan for the user based on the gaps. The action plan includes specific training and work processes that need improvement. The generated plan is sent to the terminal in JSON format.

[0545] Step 7:

[0546] The device displays the received action plan in a format suitable for the user's environment. The user can then follow the displayed action plan to take steps toward achieving their goals. Through this feedback loop, the user can continuously improve.

[0547] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0548] This invention combines a system that supports users in achieving their goals with an emotion engine that recognizes the user's emotional state. This system provides personalized mentoring tailored to the user's emotions, helping them more effectively realize their ideal self.

[0549] First, the device provides the user with a login screen, and the user logs in. After logging in, the user is taken to a screen where they can enter their goals and ideal self. The goals entered by the user are sent to the server as "goal data" and stored within the system.

[0550] Next, the server uses natural language processing technology to analyze the goal data and generate questions related to the user's goals. Furthermore, the server uses an emotion engine to infer the user's emotional state and adjusts the content and timing of the questions based on the results. The generated questions are then presented to the user via the terminal.

[0551] When a user answers a question, the server receives and stores the response data. The sentiment engine analyzes the text data contained in these responses to identify the user's emotional elements. This clarifies the user's current emotional state.

[0552] Next, the server compares the target data with the user's current situation (skills and experience) and identifies the gap. Taking into account the results of the emotion engine's analysis, it generates an action plan tailored to the user's psychological motivations and drive. This may include recommendations for educational programs, skill-building activities, or industry events.

[0553] Finally, when the device presents an action plan to the user, it utilizes an emotion engine to select a presentation style that matches the user's emotional state. For example, if the user is highly motivated, it will present more challenging content; conversely, if they are feeling anxious, it will provide reassuring information. This allows users to receive optimal support tailored to their emotions and move forward towards achieving their ideals.

[0554] As a concrete example, suppose a user sets the goal of "leading a team to success as a project manager." In this case, the server analyzes the user's experience and skill level and generates questions related to "team leadership" and "project management." Furthermore, if the emotion engine determines that the user is "highly motivated," the terminal will present an action plan that encourages setting challenging goals. On the other hand, if the user is experiencing "anxiety or fear," the plan will focus on reinforcing basic skills. In this way, the system provides flexible support based on emotions.

[0555] The following describes the processing flow.

[0556] Step 1:

[0557] The device displays a login screen to the user, who then logs in using their account information. After logging in, the user's dashboard screen is displayed.

[0558] Step 2:

[0559] The device displays a form for the user to input their goals and ideal self. The user enters their goal data into this form and presses the submit button upon completion. The submitted goal data is sent to the server.

[0560] Step 3:

[0561] The server stores the received goal data and analyzes its content using natural language processing technology. This analysis prepares the server to generate questions related to the user's goal achievement.

[0562] Step 4:

[0563] The server activates the emotion engine and receives data from the sensors and cameras being used to infer the user's emotional state while accessing the system. The analyzed emotion information is used to adjust the content and timing of questions.

[0564] Step 5:

[0565] The server generates questions related to the user's goals. The generated questions are adjusted to the user's emotional state. For example, if the user is highly focused, deep questions are asked; if they are easily distracted, concise questions are prepared.

[0566] Step 6:

[0567] The device displays generated questions to the user sequentially, and the user answers them. The answer data is sent from the device to the server and stored there.

[0568] Step 7:

[0569] The server analyzes user response data using natural language processing technology. This analysis identifies essential elements such as the user's skills, experience, and knowledge, as well as the emotional characteristics expressed in the responses.

[0570] Step 8:

[0571] The server compares the target data with the analysis results and identifies any gaps between them. In addition, it takes into account the user's psychological motivations and motives based on emotional information.

[0572] Step 9:

[0573] The server generates an action plan based on the user's gaps and emotional information. The plan includes skill enhancements, networking events to attend, and learning resources. The plan is designed to be flexible based on the user's emotional state.

[0574] Step 10:

[0575] The device presents the user with a generated action plan, and the emotion engine suggests a way of expressing it that is tailored to each individual user. This ensures that appropriate support is provided according to the user's emotional state.

[0576] Step 11:

[0577] The server continuously collects user feedback and new emotional state data to improve and update action plans. This allows for continuous personalized support and helps users grow.

[0578] (Example 2)

[0579] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0580] Conventional goal-achievement support systems have struggled to provide individualized support that takes into account the user's emotional state. Furthermore, the lack of flexibility in question generation and action plan presentation to adapt to the user's different emotional state has hindered users from effectively progressing towards their goals.

[0581] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0582] In this invention, the server includes means for receiving and storing goal data from the user, means for generating related questions, and means for analyzing the response data to identify the user's emotional state. This makes it possible to improve the quality of support for the user in achieving their goals and to provide individualized and effective support tailored to their emotional state.

[0583] "Target data" refers to information that expresses the goals or ideal state that the user wishes to achieve.

[0584] "Question generation" refers to the process of creating appropriate questions for users based on information about their goal data.

[0585] "Response data" refers to the information and answers that users provide in response to the questions presented to them.

[0586] "Emotional state" refers to the user's psychological state and feelings at any given time.

[0587] An "action plan" refers to a plan that outlines the specific means and steps necessary for a user to achieve their goals.

[0588] A "generative model" refers to an artificial intelligence model that learns from large amounts of data and enables tasks such as natural language generation.

[0589] A "prompt statement" refers to a sentence or phrase that is input to a generative model in order to obtain a specific response.

[0590] This invention is a system that supports users in achieving their goals and provides personalized plans that take into account the user's emotional state. The user first logs in via a terminal and enters their goals. This goal data is then sent to and stored on the server. The server utilizes a generative AI model and analyzes this goal data through natural language processing. Using the results, the server generates questions related to the user's goals. Prompt statements are used in the generation process; for example, appropriate questions are generated for the goal data "I want to lead my team to success as a project manager." An example of a prompt statement is, "Generate emotion-based questions and action plans to support the user in achieving their goals."

[0591] Furthermore, the server uses an emotion engine to infer the user's emotional state and adjusts the content and timing of the questions based on this. This process enables targeting that aligns with the user's emotional needs. The generated questions are presented to the user via the device, and the user's responses are sent back to the server. The server analyzes the response data to reveal the user's emotional state.

[0592] Based on this, the server compares the target data with the user's current skills and experience and generates an action plan necessary for achievement. This plan includes educational programs, skill-building activities, and industry networking events. Finally, the terminal presents this action plan to the user, using a presentation style that matches the user's emotional state to maximize the effectiveness of the support. The entire system aims to adapt to the user's emotional state and provide optimal support.

[0593] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0594] Step 1:

[0595] The user logs in using their device. They enter their user ID and password on the login screen and send this information to the authentication server. The server verifies the entered authentication information against its database. If authentication is successful, it starts a session and displays the user's goal input screen. A notification of successful authentication is sent to the device.

[0596] Step 2:

[0597] The user enters their goals and ideal self into the device. The entered goal data is sent to the server and stored directly in the database. The server receives this goal data and sends a response message to the device confirming that it has been saved.

[0598] Step 3:

[0599] The server retrieves the stored target data and performs analysis using a generative AI model. The server uses natural language processing techniques to extract keywords and analyze intent from the target data, generating relevant questions based on the results. In this process, prompts are used to instruct the generative AI model to generate responses, resulting in highly relevant questions. The generated questions are formatted into a data format and sent to the terminal.

[0600] Step 4:

[0601] The terminal displays questions received from the server to the user. The user enters answers to each question via the terminal. This answer data is sent to the server in real time and stored in the database. The terminal displays a message to the user confirming that the questions have been successfully submitted.

[0602] Step 5:

[0603] The server analyzes user response data. It uses an emotion engine to analyze the response text and infer the user's emotional state. Text mining techniques are employed to identify emotions, and an emotion score is calculated and recorded in a database. This score is used to generate action plans.

[0604] Step 6:

[0605] The server compares target data with the user's current skill information to identify gaps. Taking into account analysis results regarding emotional state, it generates an action plan tailored to the user's motivation. Using a generative AI model, it creates specific educational activities, skill development suggestions, and participation proposals for social events using prompt messages. This action plan is then sent to the user's device.

[0606] Step 7:

[0607] The device presents the user with an action plan sent from the server. Based on the output of the emotion engine, the plan is displayed in a user-friendly interface that is tailored to the user's emotional state. The content of the feedback is adjusted according to the user's emotional state.

[0608] (Application Example 2)

[0609] Next, we will explain Application Example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0610] In modern factory environments, improving productivity and optimizing operator work efficiency are key challenges. However, traditional methods struggle to create efficient work plans that take into account the emotions and stress levels of individual operators. Therefore, there is a need for new approaches that provide personalized support tailored to the emotional state of workers, promote efficient production activities, and reduce work-related stress.

[0611] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0612] In this invention, the server includes means for receiving and storing goal information from a user; means for generating relevant questions based on the goal information; means for presenting the questions to the user and collecting answer information; means for analyzing the answer information and identifying the user's emotional elements; means for comparing the goal information with the analysis results and identifying the differences; means for generating an action plan to bridge the differences; means for presenting the action plan to the user and selecting a method of expression based on the emotional state; and means for adjusting work suggestions to the user based on the emotional state. This enables flexible and effective work support tailored to the emotional state of each operator.

[0613] A "user" is an individual or group that uses this system to set goals and strive to achieve them.

[0614] "Goal information" refers to data and information about the goals that users wish to achieve.

[0615] "Relevant questions" are questions generated based on goal information to support the user in achieving their goals.

[0616] "Answer information" refers to data and information about the answers to questions that users have provided to the system.

[0617] "Emotional elements" are elements analyzed to identify the user's emotional and psychological state.

[0618] "Difference" refers to the gap between the user's current situation and their goals, identified by comparing target information with analysis results.

[0619] An "action plan" is a set of specific steps or proposals for action created to bridge identified gaps.

[0620] "Method of presentation" refers to the way and style in which information or plans are presented, which is adjusted according to the user's emotional state.

[0621] A "task proposal" is a specific task suggestion presented to the user while taking their emotional state into consideration.

[0622] This invention is a system designed to support operators in factories and can improve work efficiency based on the user's emotional state. The system is intended for use by operators via smart glasses, allowing them to obtain information in real time even while working.

[0623] The server is responsible for receiving and storing goal information from the user. Based on this goal information, it generates relevant questions and displays them on the smart glasses. The server receives the question answers and analyzes them using natural language processing technology. In doing so, it utilizes an emotion engine to identify the user's emotional elements. This analysis reveals the discrepancies between the user's current situation and their goal information.

[0624] The server then creates an action plan to bridge the gap. This action plan includes specific details such as educational programs, skills development activities, or the introduction of automation tools. The action plan is presented in a way that is tailored to the user's emotional state and is offered as a work suggestion to the user.

[0625] For example, if an operator sets a goal of eliminating bottlenecks in the manufacturing process, the server will generate related questions, such as "What are some areas for improvement in the current process?" Based on these results, line balancing and suggestions for new automation tools will be made.

[0626] Examples of prompt messages are as follows:

[0627] "What actions should be taken to improve the efficiency of the manufacturing line? Please suggest ways to improve current performance based on emotional states."

[0628] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0629] Step 1:

[0630] The user logs into the system via smart glasses. The logged-in information is sent from the device to the server for user authentication. This allows the system to associate the user's environment with their goal information.

[0631] Step 2:

[0632] The user inputs their desired goals through smart glasses. The device retrieves this goal information and sends it to the server. The server stores the goal information in a database and prepares it for data analysis in the next step.

[0633] Step 3:

[0634] The server generates relevant questions based on the stored goal information. Using natural language processing techniques, it generates prompt sentences related to the goal, preparing to extract the information necessary for the user to achieve that goal. The input for this step is the goal information, and the output is the generated prompt sentences.

[0635] Step 4:

[0636] The server presents generated questions to the user via smart glasses. The user answers the presented questions, and the answers are sent from the device to the server. The device controls the display of the questions and provides an interface that makes it easy for the user to answer.

[0637] Step 5:

[0638] The server analyzes the response information received from the user. Here, it utilizes an emotion engine to extract emotional elements from the user's responses. The input is the response information, and the output is the analyzed emotional element data. Through data analysis, it becomes possible to identify the user's emotional state.

[0639] Step 6:

[0640] The server compares the target information with the analyzed emotional elements and identifies the differences between them. By clarifying the gap between the user's current situation and their goals, the server forms the basis for the next necessary action plan.

[0641] Step 7:

[0642] The server generates an action plan to bridge the identified discrepancies. This plan includes specific steps such as implementing training programs or automation tools. The input is the discrepancy information, and the output is the action plan.

[0643] Step 8:

[0644] The server presents the generated action plan to the user. The display style of the action plan is adjusted according to the user's emotional state. In this process, the terminal presents the action plan in a visually clear and easy-to-understand manner, allowing the user to understand it intuitively.

[0645] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0646] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0647] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0648] [Fourth Embodiment]

[0649] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0650] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0651] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0652] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0653] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0654] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0655] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0656] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0657] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0658] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0659] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0660] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0661] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0662] This invention is an AI-based system that supports users in achieving their goals, providing the necessary steps for users to realize their ideal selves. This system is implemented in the following form.

[0663] First, the device provides the user with an interface, allowing them to input their goals and ideal self. The information entered here is sent to the server as "goal data" and stored. Next, the server analyzes this goal data and automatically generates questions based on the direction the user is aiming for.

[0664] The generated questions are presented to the user through the device, and the user enters their answers. These answers are sent to the server as "answer data" and stored there. The server analyzes the collected answer data to identify essential elements such as the user's skills, knowledge, and experience.

[0665] Next, the server compares the target data with the analyzed user's current situation and identifies the "gap" between them. Based on this gap, the server generates an action plan that the user can implement. This action plan includes skills to learn and activities to participate in.

[0666] Finally, the device displays the generated action plan to the user, providing specific action plans and suggestions. Based on this information, the user can take their own steps toward their ideal state.

[0667] As a concrete example, consider a user who sets a goal such as "I want to become a marketing director in the future." The server asks the user questions about their current experience and skills via the terminal and analyzes the provided answers. As a result, it identifies that the user needs to improve their strategic thinking and project management skills. Based on this, the server suggests taking online marketing-related courses or attending industry events. The terminal displays these suggestions to the user and helps them take concrete action.

[0668] The following describes the processing flow.

[0669] Step 1:

[0670] The device displays a login screen to the user, prompting them to log in to the system with their account. Once the user logs in, their dashboard is displayed.

[0671] Step 2:

[0672] The device displays a screen where the user can input their ideal self or goals. The user then describes their goals in detail and sends the entered information to the server as "goal data."

[0673] Step 3:

[0674] The server stores the received goal data and analyzes its content using a text analysis module. Next, it generates questions to obtain the information the user needs to achieve their goals. These questions are created using a knowledge base related to the user's goals.

[0675] Step 4:

[0676] The terminal displays the generated questions to the user sequentially. The user answers each question in detail and sends these answers to the server as "answer data".

[0677] Step 5:

[0678] The server analyzes the response data collected from users using natural language processing technology. From the analysis results, it identifies the user's skills, knowledge, and experience level, and gains a detailed understanding of the user's current situation.

[0679] Step 6:

[0680] The server compares the user's current data with their target data and identifies the gap between them. Next, it generates a specific action plan to bridge this gap.

[0681] Step 7:

[0682] The device visually displays the generated action plan to the user. The user can then plan and execute the next steps based on this plan.

[0683] Step 8:

[0684] The server regularly collects user feedback and progress updates, and updates the action plan as needed. The device notifies the user of new information, supporting continuous growth.

[0685] (Example 1)

[0686] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0687] Traditionally, it has been difficult for users to effectively formulate concrete steps to achieve their goals. In particular, it has been difficult to construct appropriate action plans tailored to each user's individual skill and knowledge level, often resulting in delays in goal achievement. The present invention aims to solve these problems and provide a system that supports users' efficient self-realization.

[0688] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0689] In this invention, the server includes means for receiving and storing information about goals from the user, means for automatically generating relevant information requests based on the information, and means for presenting the information requests to the user and collecting the user's response. This enables the user to quickly obtain a specific and actionable action plan tailored to their individual needs regarding their goals.

[0690] "Information related to goals" refers to information that includes specific data and facts about the state the user aims for or the objectives they wish to achieve.

[0691] An "information request" is a question or request for data generated to uncover details related to the user's goals.

[0692] "User response" refers to the answers and feedback that users provide in response to information requests.

[0693] "Capability elements" refer to fundamental elements that are identified as individual characteristics, such as a user's skills, knowledge, and experience.

[0694] "Difference" refers to the discrepancies or deficiencies that exist between the user's current situation and the information regarding their goals.

[0695] An "action plan" is a plan that includes specific steps and strategies that a user should take to achieve their goals.

[0696] "Natural language processing technology" refers to the technology used to enable computers to understand and generate human language.

[0697] An "educational program" is a learning process organized for users to acquire specific knowledge or skills.

[0698] "Skills enhancement activities" refer to training and practice activities aimed at improving users' skills and expertise.

[0699] A "networking event" is a gathering designed as a place for users to build networks with other individuals and share knowledge and experiences.

[0700] This invention is an AI-based support system that provides users with specific steps to achieve their goals. The invention is implemented utilizing terminals, servers, and generative AI models.

[0701] The terminal provides a user interface and displays a form for the user to input information about their goals. This form allows the user to enter their goals via text boxes and selection menus. The entered goal information is converted into the appropriate data format and sent to the server.

[0702] The server stores the goal information received from the user in a database. Based on the stored data, the server generates information requests. In this process, a generative AI model is used, and relevant questions are automatically generated using natural language processing techniques. For example, by inputting "Generate questions related to the user's goals" as a prompt into the model, an appropriate information request is generated.

[0703] The generated information request is presented to the user via the terminal. The user inputs a response to this information request, and the terminal sends that response to the server. The server analyzes the user's response data and uses machine learning algorithms to identify the user's capability elements. Based on this analysis, the server compares it with target information and identifies any discrepancies.

[0704] Based on the identified differences, the server generates an action plan. This plan includes specific actionable steps, such as educational programs, skills development activities, and social events. Finally, the generated action plan is presented to the user via the terminal.

[0705] For example, if a user sets the goal of "becoming a marketing director," the server generates questions about their past experience and skills and analyzes the user's responses. If the results identify that the user needs to improve their strategic thinking and project management skills, the server can include suitable online courses or industry events in their action plan. This information is displayed to the user on their device, providing concrete steps toward self-actualization.

[0706] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0707] Step 1:

[0708] The terminal provides the user with an interface and presents an input form for goal information. The user enters their goal into a text box and submits the data by pressing the submit button. The input in this process is the user's goal information, and the output is that information converted into a digital data format.

[0709] Step 2:

[0710] The terminal transmits the entered target information as digital data to the server. The server stores this data in a database. The input is digitized target information, and the output is structured data stored in the database.

[0711] Step 3:

[0712] The server analyzes the stored goal data and automatically generates relevant information requests using a generative AI model. The prompt "Generate questions related to the user's goals" is input to the model, and the AI ​​uses natural language processing techniques to generate appropriate questions. The input is the goal data, and the output is the automatically generated questions.

[0713] Step 4:

[0714] The terminal presents the user with a generated information request. The user inputs their response via the interface. The input is the question received from the server, and the output is the user's response data.

[0715] Step 5:

[0716] The device sends the user's responses as "response data" to the server. The server receives this data and stores it again in its database. Simultaneously, it analyzes the response data using a machine learning algorithm to identify the user's ability elements. The input is the user's response data, and the output is the analyzed user ability elements.

[0717] Step 6:

[0718] The server compares the identified user's capability elements with target data and identifies discrepancies. This analysis clarifies the shortcomings and gaps that need to be filled in order to achieve the goals. The input is the analyzed capability elements and target data, and the output is gap information.

[0719] Step 7:

[0720] The server generates an action plan based on the identified gaps. This action plan includes educational programs, skills development activities, and social events, and is structured as concrete steps that the user can take. The input is gap information, and the output is the user-oriented action plan.

[0721] Step 8:

[0722] The terminal displays the generated action plan to the user, indicating the specific actions to take next. Upon completion of this process, the user gains a clear set of steps toward achieving their goals. The input is the action plan received from the server, and the output is the specific action plan displayed in the user interface.

[0723] (Application Example 1)

[0724] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0725] In modern industry, there is a demand for increased efficiency in machine operation and manufacturing processes. However, it is not easy for workers to identify specific steps and skill gaps necessary to achieve their goals and to take action accordingly. In particular, a lack of real-time support and rapid feedback hinders improvements in work efficiency.

[0726] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0727] In this invention, the server includes means for receiving and storing target data from the user, means for presenting information in real time through the user's device, and means for displaying the action plan in a format suitable for the user's environment. This enables workers to identify specific steps and necessary skills to achieve their goals and to immediately put them into practice.

[0728] "Means for receiving and storing goal data from users" refers to technologies for collecting information about the objectives and goals set by users and storing it in a storage device.

[0729] "Means for generating relevant questions based on the aforementioned target data" refers to a technology that automatically creates questions that are in line with the goals set by the user.

[0730] "Means for presenting the aforementioned questions to users and collecting response data" refers to the process of displaying the generated questions to users and collecting their responses.

[0731] "Means for analyzing the aforementioned response data and identifying the essential elements of the user" refers to a technology that analyzes user responses and clarifies the characteristics of the user's skills and knowledge.

[0732] "Means of presenting information in real time through the user's device" refers to methods of providing information instantly through the user's device.

[0733] "Means for comparing the aforementioned target data with the analysis results and identifying the gap" refers to techniques for finding the difference between the user's goals and the current situation.

[0734] "Means for generating an action plan to bridge the gap" refers to a technique for creating a specific action plan to resolve the identified gap.

[0735] "Means for displaying the aforementioned action plan in a format suitable for the user's environment" refers to technology for presenting an action plan in a format appropriate to the user's environment.

[0736] The system that implements this application works by facilitating data communication between a user terminal and a server. The terminal provides a user interface for the user to input target data. This target data is sent from the terminal to the server and stored there.

[0737] The server analyzes the received target data and generates relevant questions based on the user's situation. Natural language processing technology is used for this question generation. The generated questions are presented to the user via the terminal, and the user enters their answers. The answer data is also sent to the server and stored.

[0738] Next, the server analyzes the response data to identify essential elements such as the user's skills, knowledge, and experience. The server compares the user's goals with the analyzed elements to identify skill gaps in achieving those goals. Based on the identified gaps, the server generates an action plan. The action plan includes specific skills to be learned and activities to participate in.

[0739] The generated action plan will be displayed on the device in a format tailored to the user's environment. Users can review these suggestions on the device and take concrete action. Hardware options include smart glasses or similar wearable devices. The software will utilize Python programs and TensorFlow.

[0740] For example, if a factory worker sets a goal to improve the efficiency of the production line, the server can suggest the skills and procedures necessary to improve efficiency.

[0741] An example of a prompt message would be: "Create an AI assistant that suggests the skills needed to improve efficiency and how to improve current work procedures, based on the goals set by the user."

[0742] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0743] Step 1:

[0744] The user inputs goal data through their device. This goal data includes specific objectives they wish to achieve. The device converts this information into a digital format and sends it to the server.

[0745] Step 2:

[0746] The server stores the received target data. This stored data is used to generate relevant questions based on the targets. Utilizing natural language processing techniques, the server automatically creates customized questions based on the target data.

[0747] Step 3:

[0748] The server generates a question and sends it to the terminal, which then displays the question to the user. The user enters and inputs their answer to the displayed question. This answer data then proceeds to the next process.

[0749] Step 4:

[0750] The user's response data is sent from the terminal to the server. The server analyzes this data to identify essential elements such as the user's skills, knowledge, and experience. This process uses a generative AI model and applies regression analysis and classification algorithms.

[0751] Step 5:

[0752] The server compares identified essential elements with target data. This comparison reveals the gap between the user's current state and the conditions necessary to achieve the goals. Data mining techniques are used to identify this gap.

[0753] Step 6:

[0754] The server generates an action plan for the user based on the gaps. The action plan includes specific training and work processes that need improvement. The generated plan is sent to the terminal in JSON format.

[0755] Step 7:

[0756] The device displays the received action plan in a format suitable for the user's environment. The user can then follow the displayed action plan to take steps toward achieving their goals. Through this feedback loop, the user can continuously improve.

[0757] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0758] This invention combines a system that supports users in achieving their goals with an emotion engine that recognizes the user's emotional state. This system provides personalized mentoring tailored to the user's emotions, helping them more effectively realize their ideal self.

[0759] First, the device provides the user with a login screen, and the user logs in. After logging in, the user is taken to a screen where they can enter their goals and ideal self. The goals entered by the user are sent to the server as "goal data" and stored within the system.

[0760] Next, the server uses natural language processing technology to analyze the goal data and generate questions related to the user's goals. Furthermore, the server uses an emotion engine to infer the user's emotional state and adjusts the content and timing of the questions based on the results. The generated questions are then presented to the user via the terminal.

[0761] When a user answers a question, the server receives and stores the response data. The sentiment engine analyzes the text data contained in these responses to identify the user's emotional elements. This clarifies the user's current emotional state.

[0762] Next, the server compares the target data with the user's current situation (skills and experience) and identifies the gap. Taking into account the results of the emotion engine's analysis, it generates an action plan tailored to the user's psychological motivations and drive. This may include recommendations for educational programs, skill-building activities, or industry events.

[0763] Finally, when the device presents an action plan to the user, it utilizes an emotion engine to select a presentation style that matches the user's emotional state. For example, if the user is highly motivated, it will present more challenging content; conversely, if they are feeling anxious, it will provide reassuring information. This allows users to receive optimal support tailored to their emotions and move forward towards achieving their ideals.

[0764] As a concrete example, suppose a user sets the goal of "leading a team to success as a project manager." In this case, the server analyzes the user's experience and skill level and generates questions related to "team leadership" and "project management." Furthermore, if the emotion engine determines that the user is "highly motivated," the terminal will present an action plan that encourages setting challenging goals. On the other hand, if the user is experiencing "anxiety or fear," the plan will focus on reinforcing basic skills. In this way, the system provides flexible support based on emotions.

[0765] The following describes the processing flow.

[0766] Step 1:

[0767] The device displays a login screen to the user, who then logs in using their account information. After logging in, the user's dashboard screen is displayed.

[0768] Step 2:

[0769] The device displays a form for the user to input their goals and ideal self. The user enters their goal data into this form and presses the submit button upon completion. The submitted goal data is sent to the server.

[0770] Step 3:

[0771] The server stores the received goal data and analyzes its content using natural language processing technology. This analysis prepares the server to generate questions related to the user's goal achievement.

[0772] Step 4:

[0773] The server activates the emotion engine and receives data from the sensors and cameras being used to infer the user's emotional state while accessing the system. The analyzed emotion information is used to adjust the content and timing of questions.

[0774] Step 5:

[0775] The server generates questions related to the user's goals. The generated questions are adjusted to the user's emotional state. For example, if the user is highly focused, deep questions are asked; if they are easily distracted, concise questions are prepared.

[0776] Step 6:

[0777] The device displays generated questions to the user sequentially, and the user answers them. The answer data is sent from the device to the server and stored there.

[0778] Step 7:

[0779] The server analyzes user response data using natural language processing technology. This analysis identifies essential elements such as the user's skills, experience, and knowledge, as well as the emotional characteristics expressed in the responses.

[0780] Step 8:

[0781] The server compares the target data with the analysis results and identifies any gaps between them. In addition, it takes into account the user's psychological motivations and motives based on emotional information.

[0782] Step 9:

[0783] The server generates an action plan based on the user's gaps and emotional information. The plan includes skill enhancements, networking events to attend, and learning resources. The plan is designed to be flexible based on the user's emotional state.

[0784] Step 10:

[0785] The device presents the user with a generated action plan, and the emotion engine suggests a way of expressing it that is tailored to each individual user. This ensures that appropriate support is provided according to the user's emotional state.

[0786] Step 11:

[0787] The server continuously collects user feedback and new emotional state data to improve and update action plans. This allows for continuous personalized support and helps users grow.

[0788] (Example 2)

[0789] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0790] Conventional goal-achievement support systems have struggled to provide individualized support that takes into account the user's emotional state. Furthermore, the lack of flexibility in question generation and action plan presentation to adapt to the user's different emotional state has hindered users from effectively progressing towards their goals.

[0791] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0792] In this invention, the server includes means for receiving and storing goal data from the user, means for generating related questions, and means for analyzing the response data to identify the user's emotional state. This makes it possible to improve the quality of support for the user in achieving their goals and to provide individualized and effective support tailored to their emotional state.

[0793] "Target data" refers to information that expresses the goals or ideal state that the user wishes to achieve.

[0794] "Question generation" refers to the process of creating appropriate questions for users based on information about their goal data.

[0795] "Response data" refers to the information and answers that users provide in response to the questions presented to them.

[0796] "Emotional state" refers to the user's psychological state and feelings at any given time.

[0797] An "action plan" refers to a plan that outlines the specific means and steps necessary for a user to achieve their goals.

[0798] A "generative model" refers to an artificial intelligence model that learns from large amounts of data and enables tasks such as natural language generation.

[0799] A "prompt statement" refers to a sentence or phrase that is input to a generative model in order to obtain a specific response.

[0800] This invention is a system that supports users in achieving their goals and provides personalized plans that take into account the user's emotional state. The user first logs in via a terminal and enters their goals. This goal data is then sent to and stored on the server. The server utilizes a generative AI model and analyzes this goal data through natural language processing. Using the results, the server generates questions related to the user's goals. Prompt statements are used in the generation process; for example, appropriate questions are generated for the goal data "I want to lead my team to success as a project manager." An example of a prompt statement is, "Generate emotion-based questions and action plans to support the user in achieving their goals."

[0801] Furthermore, the server uses an emotion engine to infer the user's emotional state and adjusts the content and timing of the questions based on this. This process enables targeting that aligns with the user's emotional needs. The generated questions are presented to the user via the device, and the user's responses are sent back to the server. The server analyzes the response data to reveal the user's emotional state.

[0802] Based on this, the server compares the target data with the user's current skills and experience and generates an action plan necessary for achievement. This plan includes educational programs, skill-building activities, and industry networking events. Finally, the terminal presents this action plan to the user, using a presentation style that matches the user's emotional state to maximize the effectiveness of the support. The entire system aims to adapt to the user's emotional state and provide optimal support.

[0803] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0804] Step 1:

[0805] The user logs in using their device. They enter their user ID and password on the login screen and send this information to the authentication server. The server verifies the entered authentication information against its database. If authentication is successful, it starts a session and displays the user's goal input screen. A notification of successful authentication is sent to the device.

[0806] Step 2:

[0807] The user enters their goals and ideal self into the device. The entered goal data is sent to the server and stored directly in the database. The server receives this goal data and sends a response message to the device confirming that it has been saved.

[0808] Step 3:

[0809] The server retrieves the stored target data and performs analysis using a generative AI model. The server uses natural language processing techniques to extract keywords and analyze intent from the target data, generating relevant questions based on the results. In this process, prompts are used to instruct the generative AI model to generate responses, resulting in highly relevant questions. The generated questions are formatted into a data format and sent to the terminal.

[0810] Step 4:

[0811] The terminal displays questions received from the server to the user. The user enters answers to each question via the terminal. This answer data is sent to the server in real time and stored in the database. The terminal displays a message to the user confirming that the questions have been successfully submitted.

[0812] Step 5:

[0813] The server analyzes user response data. It uses an emotion engine to analyze the response text and infer the user's emotional state. Text mining techniques are employed to identify emotions, and an emotion score is calculated and recorded in a database. This score is used to generate action plans.

[0814] Step 6:

[0815] The server compares target data with the user's current skill information to identify gaps. Taking into account analysis results regarding emotional state, it generates an action plan tailored to the user's motivation. Using a generative AI model, it creates specific educational activities, skill development suggestions, and participation proposals for social events using prompt messages. This action plan is then sent to the user's device.

[0816] Step 7:

[0817] The device presents the user with an action plan sent from the server. Based on the output of the emotion engine, the plan is displayed in a user-friendly interface that is tailored to the user's emotional state. The content of the feedback is adjusted according to the user's emotional state.

[0818] (Application Example 2)

[0819] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0820] In modern factory environments, improving productivity and optimizing operator work efficiency are key challenges. However, traditional methods struggle to create efficient work plans that take into account the emotions and stress levels of individual operators. Therefore, there is a need for new approaches that provide personalized support tailored to the emotional state of workers, promote efficient production activities, and reduce work-related stress.

[0821] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0822] In this invention, the server includes means for receiving and storing goal information from a user; means for generating relevant questions based on the goal information; means for presenting the questions to the user and collecting answer information; means for analyzing the answer information and identifying the user's emotional elements; means for comparing the goal information with the analysis results and identifying the differences; means for generating an action plan to bridge the differences; means for presenting the action plan to the user and selecting a method of expression based on the emotional state; and means for adjusting work suggestions to the user based on the emotional state. This enables flexible and effective work support tailored to the emotional state of each operator.

[0823] A "user" is an individual or group that uses this system to set goals and strive to achieve them.

[0824] "Goal information" refers to data and information about the goals that users wish to achieve.

[0825] "Relevant questions" are questions generated based on goal information to support the user in achieving their goals.

[0826] "Answer information" refers to data and information about the answers to questions that users have provided to the system.

[0827] "Emotional elements" are elements analyzed to identify the user's emotional and psychological state.

[0828] "Difference" refers to the gap between the user's current situation and their goals, identified by comparing target information with analysis results.

[0829] An "action plan" is a set of specific steps or proposals for action created to bridge identified gaps.

[0830] "Method of presentation" refers to the way and style in which information or plans are presented, which is adjusted according to the user's emotional state.

[0831] A "task proposal" is a specific task suggestion presented to the user while taking their emotional state into consideration.

[0832] This invention is a system designed to support operators in factories and can improve work efficiency based on the user's emotional state. The system is intended for use by operators via smart glasses, allowing them to obtain information in real time even while working.

[0833] The server is responsible for receiving and storing goal information from the user. Based on this goal information, it generates relevant questions and displays them on the smart glasses. The server receives the question answers and analyzes them using natural language processing technology. In doing so, it utilizes an emotion engine to identify the user's emotional elements. This analysis reveals the discrepancies between the user's current situation and their goal information.

[0834] The server then creates an action plan to bridge the gap. This action plan includes specific details such as educational programs, skills development activities, or the introduction of automation tools. The action plan is presented in a way that is tailored to the user's emotional state and is offered as a work suggestion to the user.

[0835] For example, if an operator sets a goal of eliminating bottlenecks in the manufacturing process, the server will generate related questions, such as "What are some areas for improvement in the current process?" Based on these results, line balancing and suggestions for new automation tools will be made.

[0836] Examples of prompt messages are as follows:

[0837] "What actions should be taken to improve the efficiency of the manufacturing line? Please suggest ways to improve current performance based on emotional states."

[0838] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0839] Step 1:

[0840] The user logs into the system via smart glasses. The logged-in information is sent from the device to the server for user authentication. This allows the system to associate the user's environment with their goal information.

[0841] Step 2:

[0842] The user inputs their desired goals through smart glasses. The device retrieves this goal information and sends it to the server. The server stores the goal information in a database and prepares it for data analysis in the next step.

[0843] Step 3:

[0844] The server generates relevant questions based on the stored goal information. Using natural language processing techniques, it generates prompt sentences related to the goal, preparing to extract the information necessary for the user to achieve that goal. The input for this step is the goal information, and the output is the generated prompt sentences.

[0845] Step 4:

[0846] The server presents generated questions to the user via smart glasses. The user answers the presented questions, and the answers are sent from the device to the server. The device controls the display of the questions and provides an interface that makes it easy for the user to answer.

[0847] Step 5:

[0848] The server analyzes the response information received from the user. Here, it utilizes an emotion engine to extract emotional elements from the user's responses. The input is the response information, and the output is the analyzed emotional element data. Through data analysis, it becomes possible to identify the user's emotional state.

[0849] Step 6:

[0850] The server compares the target information with the analyzed emotional elements and identifies the differences between them. By clarifying the gap between the user's current situation and their goals, the server forms the basis for the next necessary action plan.

[0851] Step 7:

[0852] The server generates an action plan to bridge the identified discrepancies. This plan includes specific steps such as implementing training programs or automation tools. The input is the discrepancy information, and the output is the action plan.

[0853] Step 8:

[0854] The server presents the generated action plan to the user. The display style of the action plan is adjusted according to the user's emotional state. In this process, the terminal presents the action plan in a visually clear and easy-to-understand manner, allowing the user to understand it intuitively.

[0855] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0856] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0857] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0858] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0859] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0860] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0861] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0862] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0863] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0864] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0865] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0866] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0867] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0868] 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.

[0869] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0870] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0871] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0872] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0873] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0874] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0875] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0876] The following is further disclosed regarding the embodiments described above.

[0877] (Claim 1)

[0878] A means of receiving and storing target data from users,

[0879] A means for generating relevant questions based on the aforementioned target data,

[0880] A means for presenting the aforementioned questions to users and collecting response data,

[0881] A means of analyzing the aforementioned response data to identify the essential elements of the user,

[0882] A means for comparing the aforementioned target data with the analysis results and identifying the gap,

[0883] Means for generating an action plan to bridge the aforementioned gap,

[0884] Means for presenting the aforementioned action plan to the user

[0885] A system that includes this.

[0886] (Claim 2)

[0887] The system according to claim 1, characterized in that the question generation means uses natural language processing technology.

[0888] (Claim 3)

[0889] The system according to claim 1, characterized in that the action plan includes educational programs, skill development activities, and networking events.

[0890] "Example 1"

[0891] (Claim 1)

[0892] A means of receiving and storing information about goals from users,

[0893] A means for automatically generating related information requests based on the aforementioned information,

[0894] A means for presenting the aforementioned information request to the user and collecting the user's response,

[0895] A means for analyzing the user's response and identifying the user's ability elements,

[0896] A means for comparing information and analysis results related to the aforementioned objectives and identifying differences,

[0897] Means for intelligently generating an action plan to bridge the aforementioned gap,

[0898] Means for presenting the aforementioned action plan to the user

[0899] A system that includes this.

[0900] (Claim 2)

[0901] The system according to claim 1, characterized in that the information request automatic generation means utilizes natural language processing technology.

[0902] (Claim 3)

[0903] The system according to claim 1, characterized in that the action plan includes educational programs, skills development activities, and exchange events.

[0904] "Application Example 1"

[0905] (Claim 1)

[0906] A means of receiving and storing target data from users,

[0907] A means for generating relevant questions based on the aforementioned target data,

[0908] A means for presenting the aforementioned questions to users and collecting response data,

[0909] A means of analyzing the aforementioned response data to identify the essential elements of the user,

[0910] A means of presenting information in real time through the device used by the user,

[0911] A means for comparing the aforementioned target data with the analysis results and identifying the gap,

[0912] Means for generating an action plan to bridge the aforementioned gap,

[0913] Means for displaying the aforementioned action plan in a format suitable for the user's environment.

[0914] A system that includes this.

[0915] (Claim 2)

[0916] The system according to claim 1, characterized in that the question generation means uses natural language processing technology.

[0917] (Claim 3)

[0918] The system according to claim 1, characterized in that the action plan includes suggestions for improving work efficiency.

[0919] "Example 2 of combining an emotion engine"

[0920] (Claim 1)

[0921] A means of receiving and storing target data from users,

[0922] A means for generating relevant questions based on the aforementioned target data,

[0923] A means for presenting the aforementioned questions to users and collecting response data,

[0924] A means for analyzing the aforementioned response data to identify the user's emotional state,

[0925] A means of comparing the aforementioned target data with the analysis results and identifying the gaps necessary for achievement,

[0926] Means for generating an action plan based on the aforementioned gap and emotional state,

[0927] Means for presenting the aforementioned action plan in accordance with the user's emotional state

[0928] A system that includes this.

[0929] (Claim 2)

[0930] The system according to claim 1, characterized in that the question generation means uses a generation model and generates questions using prompt sentences.

[0931] (Claim 3)

[0932] The system according to claim 1, characterized in that the action plan includes educational activities, skills improvement activities, and exchange events.

[0933] "Application example 2 when combining with an emotional engine"

[0934] (Claim 1)

[0935] A means of receiving and storing goal information from users,

[0936] Means for generating related questions based on the aforementioned target information,

[0937] A means of presenting the aforementioned questions to the user and collecting the answer information,

[0938] A means for analyzing the aforementioned response information and identifying the emotional elements of the user,

[0939] A means for comparing the aforementioned target information with the analysis results and identifying the differences,

[0940] Means for generating an action plan to bridge the aforementioned gap,

[0941] A means of presenting the aforementioned action plan to the user and selecting a method of expression based on their emotional state,

[0942] A means of adjusting work suggestions to users based on their emotional state.

[0943] A system that includes this.

[0944] (Claim 2)

[0945] The system according to claim 1, characterized in that the question generation means uses natural language processing technology.

[0946] (Claim 3)

[0947] The system according to claim 1, characterized in that the action plan includes educational programs, capacity building activities, and the introduction of automation tools. [Explanation of Symbols]

[0948] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of receiving and storing target data from users, A means for generating relevant questions based on the aforementioned target data, A means for presenting the aforementioned questions to users and collecting response data, A means of analyzing the aforementioned response data to identify the essential elements of the user, A means for comparing the aforementioned target data with the analysis results and identifying the gap, Means for generating an action plan to bridge the aforementioned gap, Means for presenting the aforementioned action plan to the user A system that includes this.

2. The system according to claim 1, characterized in that the question generation means uses natural language processing technology.

3. The system according to claim 1, characterized in that the action plan includes educational programs, skill development activities, and networking events.

Images