System

Abstract

A system is provided.SOLUTION: A system, comprising: means for receiving a goal or task from a user; means for transmitting the received goal or task to a server; means for setting an alarm for the goal or task on the server; and means for notifying the user of the set alarm.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In today's corporate environment, managers and employees often lack the appropriate support they need to achieve their goals and promote their own growth. In particular, processes such as maintaining awareness of goals, reflecting on daily work, and understanding employees' emotional states place a heavy burden on managers and employees, making effective management difficult. While it is also important to quickly identify problems and stress members are experiencing and take appropriate action, this often takes up time and resources. A centralized platform to address these issues is needed. [Means for solving the problem]

[0005] The present invention provides a system that includes a means for receiving goals and tasks from a user, a means for transmitting the received goals and tasks to a server, a means for setting alarms for the goals and tasks on the server, and a means for notifying the user of the set alarm. The system further includes a means for saving user input data on the server, a means for generating a confirmation message for the saved data, and a means for notifying the user of the confirmation message. The system also includes a means for recording a user's weekly activity log on the server, a means for analyzing the recorded activity log to generate a weekly review, and a means for notifying the user of the generated weekly review. The system further includes a means for using generative artificial intelligence to analyze the user's emotional state, a means for generating alerts based on the emotion analysis results, and a means for sending the generated alerts to managers, thereby providing a system that can comprehensively solve the challenges faced by managers and team members in modern corporate environments.

[0006] The "means for receiving goals and tasks from the user" refers to an interface or device for incorporating goal and task information input by the user into the system.

[0007] The "means for transmitting received goals and tasks to the server" refers to a communication device or software for transferring goal and task information received from the user to the server.

[0008] The "means for setting alarms for goals and tasks on the server" refers to a function for setting notifications and reminders to be generated based on goals and tasks received on the server.

[0009] The "means for notifying the user of the set alarm" refers to a mechanism or communication means for notifying the user's device of the alarm set on the server.

[0010] "Means for saving user-input data on the server" refers to a function for saving data entered by a user in a database or storage within the server.

[0011] The "means for generating a confirmation message for saved data" is a function for generating a message to notify the user that saving has been completed, based on the data saved on the server.

[0012] "Means for notifying the user of a confirmation message" refers to communication means or software for sending and displaying a confirmation message on the user's device that the save has been completed.

[0013] The "means for recording a user's activity log for one week on the server" is a function for recording a user's activity for one week and storing it in a database in the server.

[0014] The "means for analyzing the recorded activity log to generate a weekly review" is a software algorithm for analyzing the recorded log data and generating a summary of the user's activities.

[0015] The "means for notifying the user of the generated weekly review" refers to a communication means or software for sending and displaying the generated weekly review report on the user's device.

[0016] "Means for using generative artificial intelligence to analyze a user's emotional state" refers to artificial intelligence technology for analyzing a user's emotional state from their input and dialogue data.

[0017] The "means for generating an alert based on the emotion analysis results" is a function that generates an alert to alert management as necessary based on the analyzed emotional state.

[0018] The "means for sending the generated alert to the manager" refers to a communication means or software for notifying the manager of the generated alert on his / her device. [Brief explanation of the drawings]

[0019] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0020] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0021] First, the terms used in the following description will be explained.

[0022] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0023] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0024] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0025] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0026] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0027] [First embodiment]

[0028] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0029] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0030] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0031] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0032] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0033] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0034] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0035] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0037] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0038] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0039] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0040] 1. System Configuration

[0041] The system of the present invention is mainly composed of a server and a user terminal (e.g., a smartphone or PC). Through the terminal, the user interacts with "Coach-kun," a generative artificial intelligence (generative AI). Through interaction with Coach-kun, the system is a tool for setting the user's goals and managing their progress.

[0042] 2. Function to receive goals and tasks from users

[0043] The user inputs goals and tasks by speaking to the generative AI using the device. For example, a goal might be set as "rehearsing a presentation next Thursday." The device then sends this goal data to the server.

[0044] 3. Function to send received goals and tasks to the server

[0045] The device formats the information entered by the user and sends it over the Internet or an internal network to a server, which analyzes the data and verifies the objectives and tasks.

[0046] 4. Ability to set alarms for goals and tasks on the server

[0047] The server analyzes the received goal and task data and sets alarms for the goal or task at the appropriate date and time, for example, "to be reminded the day before and the day of a presentation rehearsal."

[0048] 5. Function to notify users of set alarms

[0049] When the set date and time arrives, the server sends a notification to the user's device, which then notifies the user of the alarm with a sound, vibration, or a pop-up notification.

[0050] 6. User data storage function

[0051] The device sends the data entered by the user to the server, which stores it in a database. For example, if a user enters, "My goal this month is to increase my team's productivity by 20%, the server stores this information."

[0052] 7. Data saving confirmation notification function

[0053] If the data is saved successfully, the server generates a confirmation message and sends it to the device, which notifies the user that "the goal has been saved."

[0054] 8. Server activity logging function

[0055] The server records the user's activity log for one week and stores it in a database, including the time it took to complete a task and the progress of that task.

[0056] 9. Activity log analysis function

[0057] At the end of the week, the server analyzes the collected activity logs and uses generative AI to summarize the user's activities over the week and compiles the generated summary into a report.

[0058] 10. Ability to notify users of summary reports

[0059] The generated report is sent from the server to the terminal, and the terminal notifies the user of the report contents, allowing the user to review their activities for the week.

[0060] 11. Sentiment Analysis Function

[0061] The device sends data to a server to analyze the user's emotional state from what they say to the generative AI. For example, if the user says, "I've been feeling very stressed lately and can't concentrate on my work," the server will use the generative AI to analyze that emotional state.

[0062] 12. Alert Generation Function

[0063] The server generates alerts based on the results of emotion analysis. If the stress level is determined to be high, an alert is generated for management.

[0064] 13. Alert notification function

[0065] The generated alerts are sent from the server to the manager's terminal, where they are displayed and the manager is assisted in taking appropriate action.

[0066] Specific examples

[0067] For example, if a user says, "I've been feeling very stressed lately and can't concentrate on my work," the device will send this information to the server. The server will use generative AI to analyze the emotion, and if it determines that the stress level is high, it will send an alert to the manager's device saying, "User A is feeling very stressed." The manager's device will then display this alert, allowing the manager to take appropriate action.

[0068] The above is a description of each function in the embodiment of the present invention.

[0069] The processing flow will be explained below.

[0070] 1. Alarm function processing

[0071] Step 1:

[0072] A user uses a device to input a goal or task into the generative AI, for example, "I'll rehearse my presentation next Thursday."

[0073] Step 2:

[0074] The terminal formats the input target data and transmits it to the server.

[0075] Step 3:

[0076] The server analyzes the received data and checks the content and date / time information of the goals and tasks.

[0077] Step 4:

[0078] The server sets an alarm for the specified date and time, for example, to remind you the day before and the day itself.

[0079] Step 5:

[0080] When the specified date and time arrives, the server will send an alarm notification to the terminal.

[0081] Step 6:

[0082] The device will notify the user of the alarm with a sound, vibration, or pop-up notification.

[0083] 2. Save your goals and feedback

[0084] Step 1:

[0085] The user inputs goals and ideas into the generative AI. For example, "My goal this month is to increase team productivity by 20%."

[0086] Step 2:

[0087] The terminal formats the entered data and sends it to the server.

[0088] Step 3:

[0089] The server stores the received data in a database.

[0090] Step 4:

[0091] Once the save is complete, the server generates a confirmation message and sends it to the device.

[0092] Step 5:

[0093] The device will notify the user with a confirmation message "Goal saved."

[0094] 3. Weekly review summary function

[0095] Step 1:

[0096] The server records a user's activity log for one week and stores it in a database.

[0097] Step 2:

[0098] On weekends, the server analyzes the collected activity logs.

[0099] Step 3:

[0100] The server uses generative AI to summarize activities and generate a weekly review.

[0101] Step 4:

[0102] The server generates a summary report and sends it to the terminal.

[0103] Step 5:

[0104] The terminal notifies the user of the report contents and displays them.

[0105] 4. Alert function

[0106] Step 1:

[0107] The user talks to the generative AI about their feelings and difficulties, for example, saying, "I've been feeling very stressed lately and can't concentrate on my work."

[0108] Step 2:

[0109] The device sends the user's speech to the server.

[0110] Step 3:

[0111] The server uses generative AI to analyze the emotional state from the received data.

[0112] Step 4:

[0113] The server generates an alert based on the results of emotion analysis if it determines that support is required.

[0114] Step 5:

[0115] The server sends an alert to management.

[0116] Step 6:

[0117] The manager's device will display an alert, helping the manager take appropriate action.

[0118] The above are the specific processing steps for each function.

[0119] Example 1

[0120] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0121] In modern society, it is important for users to effectively manage their goals and tasks. It is also necessary to properly understand users' emotional states and provide necessary alerts in advance. However, current systems lack the ability to centrally manage users' goals and analyze their emotions, resulting in a split between task management and responding to changes in emotional states. Furthermore, they lack an alert notification function that allows administrators to provide appropriate follow-up.

[0122] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0123] In this invention, the server includes means for receiving goals and tasks from the user, means for transmitting the received goals and tasks to the server, means for setting an alarm for the goal or task on the server, means for notifying the user of the set alarm, means for analyzing the user's emotional state, means for generating an alert based on the result of the user's emotional analysis, and means for notifying the administrator of the generated alert. This makes it possible to perform user goal management and emotional analysis in an integrated manner, and to generate and provide to the administrator an alarm notification or an alert based on the emotional state at an appropriate time.

[0124] "Means for receiving goals and tasks from a user" refers to an interface that allows a user to input goals and tasks into the system and software for recognizing them.

[0125] "Means for transmitting received goals and tasks to a server" refers to the protocol and communication functions for transferring goal and task data entered by the user to a server via a network.

[0126] "Means for setting goal or task alarms on the server" refers to the software functionality that analyzes the goal or task data received by the server and creates alarms based on corresponding dates, times, and conditions.

[0127] "Means for notifying the user of the set alarm" refers to the communication functions and interface for transmitting the alarm set on the server to the user's device and notifying the user by sound, vibration, pop-up message, etc.

[0128] "Means for analyzing the user's emotional state" refers to generative AI models and natural language processing technologies for analyzing the user's emotional state based on the user's input data.

[0129] "Means for generating alerts based on the results of the user's emotional analysis" refers to the software's functionality for generating alert messages based on the results of the analyzed emotional state, according to stress levels or other emotional states.

[0130] "Means for notifying the administrator of the generated alert" refers to a communication function that sends the generated alert based on the user's emotional state to the administrator's terminal and notifies them so that appropriate follow-up can be carried out.

[0131] 1. System Configuration

[0132] The system of the present invention is primarily composed of a server and a user terminal (e.g., a smartphone or PC). In this system, users set goals and manage progress by interacting with "Coach-kun," a generative AI. It also uses an emotion analysis function to monitor the user's stress level and send alerts to the administrator as necessary.

[0133] 2. Function to receive goals and tasks from users

[0134] The user interactively inputs goals and tasks into the generative AI through the device. For example, the user can set a goal such as "rehearsing a presentation next Thursday." The device is equipped with speech recognition software that converts what the user says into text data. Specific software that can be used is the Google Speech-to-Text API.

[0135] 3. Function to send received goals and tasks to the server

[0136] The device converts the text data into a proprietary format using voice recognition software, then encrypts it for security purposes and sends it to a server over the internet or an internal network using the Transport Layer Security (TLS) protocol.

[0137] 4. Ability to set alarms for goals and tasks on the server

[0138] The server analyzes the received text data and sets an alarm based on the content of the goal or task. For example, it extracts date and time information such as "next Thursday" and sets an alarm. Natural language processing (NLP) technology is used for the analysis, specifically the Python nltk library. A scheduling tool such as a cron job is used to set the alarm.

[0139] 5. Function to notify users of set alarms

[0140] When the set date and time arrives, the server generates a notification message and sends it to the device. The device notifies the user of this message by a pop-up notification, sound, or vibration. Cloud messaging services such as Firebase Cloud Messaging (FCM) can be used for the notification function.

[0141] 6. User data storage function

[0142] The terminal sends the data entered by the user to the server, which stores this data in temporary storage and then stores it permanently using a database management system (DBMS), such as MySQL or PostgreSQL.

[0143] 7. Data saving confirmation notification function

[0144] The server checks whether the data was saved successfully and generates a confirmation message. This message is sent to the device, which notifies the user that the goal has been saved. The communication uses an HTTP response.

[0145] 8. Server activity logging function

[0146] The server keeps a log of users' activities for one week. This log includes the tasks the user has completed and their progress. The log data is stored in a NoSQL database (e.g., MongoDB).

[0147] 9. Activity log analysis function

[0148] At the end of the week, the server analyzes the collected activity logs and uses a generative AI model to summarize the user's activity over the week, using Python data processing libraries (Pandas and Numpy).

[0149] 10. Ability to notify users of summary reports

[0150] The generated report is sent from the server to the device, and the device notifies the user of the report contents via a pop-up notification or email.

[0151] 11. Sentiment Analysis Function

[0152] To perform sentiment analysis of what the user says to the generative AI (e.g., "I've been feeling very stressed lately and can't concentrate on my work"), the device sends the data to a server. The server then uses a generative AI model (e.g., BERT or GPT) to analyze the sentiment. The analysis results identify the user's emotional state.

[0153] 12. Alert Generation Function

[0154] The server generates alerts based on the results of the emotion analysis, if necessary: ​​if a high stress level is detected, an alert message is generated and sent to the administrator.

[0155] 13. Alert notification function

[0156] The server sends an alert message to the administrator's terminal, which displays the alert on its screen to help the administrator take appropriate action.

[0157] Specific examples

[0158] For example, if a user says, "I've been feeling very stressed lately and can't concentrate on my work," the device uses voice recognition software to convert this information into text data and send it to the server. The server then uses a generative AI model to analyze the emotional state. If the server determines that the stress level is high, it sends an alert to the administrator's device stating, "User A is feeling very stressed." The administrator's device then displays this alert, allowing the administrator to take appropriate action.

[0159] The above is a description of each function in the embodiment of the present invention.

[0160] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0161] Step 1:

[0162] The user speaks through the terminal. The user sets a goal, such as "I will rehearse my presentation next Thursday." This information is input as voice.

[0163] Step 2:

[0164] The device uses speech recognition software (e.g., Google Speech-to-Text API) to convert voice data into text data. The input is voice data and the output is text data.

[0165] Step 3:

[0166] The terminal adapts the text data to a proprietary format. At this stage the text data is prepared for further data processing. The input is text data and the output is formatted text data.

[0167] Step 4:

[0168] The terminal encrypts the formatted text data and sends it to the server over the Internet or an internal network. The encryption is performed using the TLS protocol. The input is the formatted text data, and the output is the encrypted data.

[0169] Step 5:

[0170] The server decrypts the received data and uses natural language processing (NLP) techniques to parse the data, for example to extract date and time information such as "next Thursday." The input is the encrypted data, and the output is the parsed date and time information.

[0171] Step 6:

[0172] The server sets an alarm based on the analyzed date and time information using a scheduling tool such as a cron job. The input is the date and time information, and the output is the set alarm.

[0173] Step 7:

[0174] When the set date and time arrives, the server generates a notification message and sends it to the user's terminal. The input is the set alarm, and the output is the notification message.

[0175] Step 8:

[0176] The device notifies the user of the received notification message by pop-up notification, sound, vibration, etc. The input is the notification message, and the output is the notification to the user.

[0177] Step 9:

[0178] The terminal stores all data entered by the user in temporary storage and then sends it to the server, which stores the data persistently using a database management system (e.g., MySQL or PostgreSQL). The input is the user data and the output is the stored data.

[0179] Step 10:

[0180] The server checks whether the data was saved correctly and generates a confirmation message. This message is sent to the user's device, informing the user that "the goal has been saved." The input is the saved data, and the output is the confirmation message.

[0181] Step 11:

[0182] The server records a user's activity log for one week. This log includes the tasks the user has completed and their progress information. The log data is stored in a NoSQL database (e.g., MongoDB). The input is the task data, and the output is the recorded activity log.

[0183] Step 12:

[0184] At the end of the week, the server analyzes the collected activity logs and uses a generative AI model (e.g., GPT-3) to summarize the user's activities for the week. The analysis is performed using Python data processing libraries (Pandas and Numpy). The input is the activity log, and the output is a summary report.

[0185] Step 13:

[0186] The generated report is sent from the server to the terminal, and the terminal notifies the user of the report contents via a pop-up notification, email, etc. The input is a summary report, and the output is a notification to the user.

[0187] Step 14:

[0188] The device sends what the user says to the generative AI to the server for emotion analysis. The input is the user's speech data, and the output is the data sent to the server.

[0189] Step 15:

[0190] The server uses a generative AI model (e.g., BERT or GPT-3) to analyze the user's utterances and identify their emotional state. The input is the utterance data, and the output is the emotion analysis result.

[0191] Step 16:

[0192] The server generates alerts as needed based on the emotion analysis results. If a high stress level is detected, an alert message is generated. The input is the emotion analysis results, and the output is the alert message.

[0193] Step 17:

[0194] The generated alert is sent from the server to the administrator's terminal, where it is displayed. The input is the alert message, and the output is a notification to the administrator.

[0195] The above is a specific description of each processing step in the system of the present invention.

[0196] (Application example 1)

[0197] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0198] Improving work efficiency and providing mental health care for workers at the same time are extremely important in production sites, but it is difficult to achieve these goals simultaneously using conventional methods.In addition, while there is a demand for the introduction of systems that improve the efficiency of work progress and task management, there are not yet enough systems that can analyze the emotional state of workers and take appropriate action based on that.

[0199] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0200] In this invention, the server includes means for receiving goals and tasks from users, means for transmitting the received goals and tasks to the server, means for setting alarms for the goals and tasks on the server, means for notifying the user of the set alarm, means for analyzing the emotional state of factory workers from their input, means for generating alerts based on the emotion analysis results, and means for notifying a manager of the generated alert. This not only improves work efficiency but also supports the mental health of workers.

[0201] The "means for receiving goals and tasks from a user" is an interface for acquiring information on work goals and tasks from factory workers.

[0202] The "means for transmitting the received goal or task to the server" is a mechanism for transferring the information on the acquired goal or task to the server via a data network.

[0203] The "means for setting alarms for goals and tasks on the server" is a program for setting the date and time for reminder notifications for goals and tasks received in the server.

[0204] The "means for notifying the user of the set alarm" is a mechanism for notifying the user terminal at the set date and time.

[0205] The "means for analyzing the emotional state of a factory worker from input" is an algorithm for analyzing the emotional state of a factory worker from the voice uttered by the worker or the text data entered by the worker.

[0206] The "means for generating an alert based on the results of emotion analysis" is a mechanism that generates a warning when high stress, etc. is detected based on the results of emotion analysis.

[0207] The "means for notifying the manager of the generated alert" is a mechanism for sending the generated warning to the manager of the factory and prompting him to take action.

[0208] This invention is a system that enables factory workers and managers to set goals and tasks, manage progress, and analyze workers' emotional states to take appropriate action. The system consists of a user terminal and a server, and realizes each function using a generative AI model.

[0209] The system program works as follows:

[0210] Receive and send goals and tasks

[0211] The user device receives voice or text input of goals and tasks set by factory workers, such as "inspect the machine next Monday." This data is analyzed and formatted using a generative AI model and then sent to a server over the internet or an internal network.

[0212] Processing on the server

[0213] The server analyzes the received goal and task data and sets reminders for the appropriate dates and times. For example, if you set "machine inspection next Monday," reminders are set for the day before and the day itself.

[0214] Notification function

[0215] When the set reminder date and time arrives, the server sends a notification to the user's device, which then notifies the worker of this notification as a pop-up or audio alarm, urging them to complete the task without forgetting.

[0216] Saving and checking data

[0217] The goal and task data entered by the user is saved in the server's database. Once the saving is complete, the server generates a confirmation message and sends it to the user's terminal. The user's terminal then notifies the worker of the message "Task saved" and asks them to confirm that the data has been saved correctly.

[0218] Sentiment analysis and alert generation

[0219] The user device receives the worker's voice input and text data and sends it to the server. The server uses a generative AI model to analyze the worker's emotional state. For example, if a worker inputs, "I've been feeling very stressed recently and can't concentrate on my work," the emotional state is determined to be high stress. In this case, the server generates and sends an alert to the manager stating, "The worker is feeling high stress." The manager can receive this alert and take appropriate action.

[0220] Examples and prompts

[0221] For example, if a worker specifies "I will inspect the machine next Monday," the system will analyze that data, set a reminder, and send a notification. Also, if a worker specifies "I've been feeling very stressed lately and can't concentrate on my work," the system will analyze that emotion and send an alert to the manager.

[0222] Example prompt sentence:

[0223] "Please set a task to inspect the machine next Monday."

[0224] "I've been feeling very stressed lately and can't concentrate on my work."

[0225] In this way, the present invention can improve the work efficiency of a factory while also providing mental health care for workers.

[0226] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0227] Step 1:

[0228] The user inputs their goals and tasks into the device using voice or text. The input data is passed to the generative AI model, which analyzes the content of the goals and tasks. The generative AI model then formats the data and converts it into a format that can be sent to the server.

[0229] Input: Worker inputs by voice or text, "I will inspect the machine next Monday."

[0230] Output: Formatted goal and task data

[0231] Step 2:

[0232] The device sends formatted goal and task data to the server, which verifies the received data and stores it in a database. If the data is successfully stored, the server generates a confirmation message and sends it to the device.

[0233] Input: Formatted goal and task data

[0234] Output: Confirmation message "Task saved"

[0235] Step 3:

[0236] The server analyzes the received goal and task data and sets reminder notifications at appropriate dates and times. Specifically, it generates a schedule of reminder notifications for the previous day and the current day based on the date and time information of the goal or task.

[0237] Input: Goal and task data stored in the database

[0238] Output: Scheduled date and time of the reminder notification

[0239] Step 4:

[0240] When the set reminder date and time arrives, the server sends a reminder notification to the terminal, which then notifies the worker as a pop-up or audio alarm.

[0241] Input: Scheduled date and time of the reminder notification

[0242] Output: Pop-up notification and audio alarm

[0243] Step 5:

[0244] The user device receives the worker's voice input and text data and sends it to the server, which uses a generative AI model to analyze the data and evaluate the worker's emotional state. If high stress is detected, an alert is generated.

[0245] Input: Worker's voice input or text data (e.g., "I've been feeling very stressed lately and can't concentrate on my work.")

[0246] Output: Sentiment analysis results and alert information

[0247] Step 6:

[0248] The server notifies the administrator of the generated alert, and the alert information is sent to the administrator's terminal, helping the administrator to take appropriate action.

[0249] Input: Alert information

[0250] Output: Alert notification to administrator

[0251] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0252] 1. System Configuration

[0253] This invention is a system for setting user goals, managing progress, and monitoring emotional states. The system mainly consists of a server and a user device (smartphone or PC). Users interact with a generative artificial intelligence (generative AI) through the device, and an emotion engine is used to recognize their emotional state and provide appropriate feedback.

[0254] 2. Function to receive goals and tasks from users

[0255] The user inputs goals and tasks by speaking to the generative AI using the device. For example, the user might set a goal such as "rehearsing a presentation next Thursday." The device then sends this goal data to the server.

[0256] 3. Function to send received goals and tasks to the server

[0257] The terminal formats the entered goal data and sends it to a server via the Internet or an internal network. The server analyzes the received data and verifies the goal or task.

[0258] 4. Ability to set alarms for goals and tasks on the server

[0259] The server analyzes the received goal or task data and sets an alarm for the goal or task at the appropriate date and time, for example, setting a reminder for the day before and the day of the goal or task.

[0260] 5. Function to notify users of set alarms

[0261] When the set date and time arrives, the server sends a notification to the user's device. The device notifies the user with an alarm sound, vibration, or a pop-up notification. For example, it may notify the user, "There is a rehearsal for your presentation tomorrow."

[0262] 6. User data storage function

[0263] The device sends the data entered by the user to the server, which stores it in a database. For example, if a user enters "My goal this month is to increase my team's productivity by 20%," the server stores this information in a database.

[0264] 7. Data saving confirmation notification function

[0265] If the data is saved successfully, the server generates a confirmation message and sends it to the device, which notifies the user that the goal has been saved.

[0266] 8. Server activity logging function

[0267] The server records the user's activity log for one week and stores it in a database, including the time it took to complete a task and the progress of that task.

[0268] 9. Activity log analysis function

[0269] At the end of the week, the server analyzes the collected activity logs and uses generative AI to summarize the user's activities over the week and compiles the generated summary into a report.

[0270] 10. Ability to notify users of summary reports

[0271] The generated report is sent from the server to the device, and the device notifies the user of the report contents, for example, "This week, we completed three major tasks, and our team's productivity increased by 15%."

[0272] 11. Emotion recognition function using emotion engine

[0273] The emotion engine recognizes the user's emotional state based on what the user says to the generative AI. For example, if the user says, "I've been feeling very stressed lately and can't concentrate on my work," the device will send this information to the server.

[0274] 12. Emotion data analysis function

[0275] The server analyzes the received emotional data and provides a detailed assessment of the user's emotional state, identifying high stress levels and other emotional states.

[0276] 13. Alert Generation Function

[0277] Based on the sentiment analysis results, the server generates an alert if it determines that support is needed, for example, if it determines that the user is experiencing high stress levels.

[0278] 14. Alert notification function

[0279] The generated alerts are sent from the server to the manager's terminal, where they are displayed. The manager is supported to take appropriate action based on the alerts.

[0280] Specific examples

[0281] For example, if a user says, "I've been feeling very stressed lately and can't concentrate on my work," the device will send this data to the server. The server will analyze it using an emotion engine and confirm the high stress level. Based on the judgment, it will generate an alert saying, "User A is feeling very stressed," and send it to the manager's device. The manager will receive this alert and can follow up with User A.

[0282] The above is a detailed description of each function in the embodiment of the present invention.

[0283] The processing flow will be explained below.

[0284] Goal and task management features

[0285] Step 1:

[0286] A user uses a device to input a goal or task into the generative AI, for example, "I'll rehearse my presentation next Thursday."

[0287] Step 2:

[0288] The terminal formats the input target data and transmits it to the server.

[0289] Step 3:

[0290] The server analyzes the received data and checks the content and date / time information of the goals and tasks.

[0291] Step 4:

[0292] The server sets an alarm for the specified date and time, for example, to remind you the day before and the day itself.

[0293] Step 5:

[0294] When the specified date and time arrives, the server will send an alarm notification to the terminal.

[0295] Step 6:

[0296] The device will notify the user of the alarm with a sound, vibration, or pop-up notification.

[0297] Data storage function

[0298] Step 1:

[0299] The user inputs goals and ideas into the generative AI. For example, "My goal this month is to increase team productivity by 20%."

[0300] Step 2:

[0301] The terminal formats the entered data and sends it to the server.

[0302] Step 3:

[0303] The server stores the received data in a database.

[0304] Step 4:

[0305] Once the save is complete, the server generates a confirmation message and sends it to the device.

[0306] Step 5:

[0307] The device will notify the user with a confirmation message "Goal saved."

[0308] Weekly review function

[0309] Step 1:

[0310] The server records a user's activity log for one week and stores it in a database.

[0311] Step 2:

[0312] On weekends, the server analyzes the collected activity logs.

[0313] Step 3:

[0314] The server uses generative AI to summarize activities and generate a weekly review.

[0315] Step 4:

[0316] The server generates a summary report and sends it to the terminal.

[0317] Step 5:

[0318] The terminal notifies the user of the report contents and displays them.

[0319] Emotion recognition function using emotion engine

[0320] Step 1:

[0321] The user inputs dialogue into the generative AI, for example, saying, "I've been feeling very stressed lately and can't concentrate on my work."

[0322] Step 2:

[0323] The terminal transmits the input dialogue content to the server.

[0324] Step 3:

[0325] The server uses an emotion engine to analyze the content of the user's dialogue and recognize the user's emotional state.

[0326] Step 4:

[0327] The server evaluates the recognized emotional data and detects abnormalities such as high stress levels.

[0328] Alerting and Notification

[0329] Step 1:

[0330] The server generates an alert based on the analysis results of the emotion engine when it determines that support is required.

[0331] Step 2:

[0332] The server sends the generated alert to the manager's terminal.

[0333] Step 3:

[0334] The manager's device will display an alert, helping the manager take appropriate action.

[0335] Specific examples

[0336] 1. The user tells the generative AI, "I've been feeling very stressed lately and can't concentrate on my work."

[0337] 2. The device sends the conversation content to the server.

[0338] 3. The server uses an emotion engine to analyze the content of the conversation and determine that the stress level is high.

[0339] 4. The server generates an alert saying "User A is experiencing high stress."

[0340] 5. The server sends an alert to the manager's terminal.

[0341] 6. The manager's device displays an alert and the manager follows up with User A.

[0342] The above are the specific processing steps of each function in the embodiment of the present invention in which an emotion engine is combined.

[0343] Example 2

[0344] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0345] While conventional goal management systems can manage the goals and tasks entered by users, they lack the ability to grasp the user's emotional state in real time and provide appropriate feedback and support as needed. As a result, users who are particularly stressed may not receive the support they need, which can lead to a decline in productivity and mental health. Furthermore, the lack of analysis of activity logs and feedback on goal achievement makes it difficult for users to create specific plans for self-improvement.

[0346] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for receiving goals and tasks from the user, means for transmitting the received goals and tasks to the server, means for setting alarms for the goals and tasks on the server, means for notifying the user of the set alarm, means for transmitting emotional data entered by the user to the server, means for the server to analyze the emotional data using an emotion engine and evaluate the user's emotional state, means for the server to generate an alert if necessary based on the analysis results, and means for notifying the administrator's terminal of the generated alert. This enables progress management of the goals and tasks set by the user, as well as monitoring of the emotional state and providing appropriate feedback. Furthermore, adding a function for analyzing a one-week activity log and providing feedback based on the log allows the user to create a specific action plan for self-improvement and improve overall performance.

[0347] "Goals and tasks" refer to the objectives that a user is trying to achieve or the specific work that needs to be done.

[0348] "User" refers to a person who uses this system to set goals, manage progress, and monitor emotions.

[0349] The "means for receiving" refers to a process or device by which the terminal acquires data on goals or tasks input by the user.

[0350] "Means for transmitting" refers to the process or device for sending received data from the terminal to the server and communicating.

[0351] "Server" refers to a central computing device for analyzing, storing, and managing received data.

[0352] "Means for setting an alarm" refers to a mechanism or device for sending a notification based on a specified date, time, or conditions.

[0353] "Means for notifying" refers to a device or process for notifying a user or administrator of configured alarms or confirmation messages.

[0354] "Emotion data" is data that indicates the user's emotional state, and includes psychological factors such as stress and satisfaction.

[0355] An "emotion engine" refers to software or algorithms that analyze emotional data and assess a user's emotional state.

[0356] "Means for generating alerts" refers to a mechanism or device that generates warnings or notifications when certain conditions are met based on the results of analyzing emotional data.

[0357] "Administrator" refers to a person whose job is to operate this system and support users.

[0358] An "activity log" refers to data that records a user's daily activities and task progress.

[0359] "Weekly Review" refers to a report that analyzes recorded activity logs and summarizes the user's actions and achievements over the week.

[0360] This invention is a system that manages the goals and tasks set by the user and monitors the emotional state. This system is mainly composed of a server and a user terminal (smartphone or PC).

[0361] System Configuration

[0362] Users can interact with the generative AI model through their device and receive appropriate feedback and recognition of their emotional state using the emotion engine.

[0363] Entering goals and tasks

[0364] Using a smartphone or PC, a user speaks to the generative AI model about their goals and tasks. For example, they might set a goal like "I'll rehearse my presentation next Thursday." The device then converts this goal data from speech to text and sends it to the server.

[0365] Receiving data and setting alarms

[0366] The server analyzes the received goal and task data and checks the details. Once the analysis is complete, an alarm is set for the appropriate date and time according to the goal. For example, it can set a reminder for the day before and the day itself.

[0367] Alarm notifications

[0368] When the set date and time arrives, the server sends a notification to the user's device. The device notifies the user of this notification by sound, vibration, or a pop-up notification. For example, it may notify the user that "there is a rehearsal for the presentation tomorrow."

[0369] User Data Storage

[0370] The device sends data on the goals and tasks set by the user to the server, which then stores the data in a database. For example, if a user enters "This month's goal is to increase team productivity by 20%, that information is stored.

[0371] Data storage confirmation notice

[0372] When the server confirms that the data has been saved successfully, it generates a confirmation message and sends it to the device, which then notifies the user that "the goal has been saved."

[0373] Activity log recording and analysis

[0374] The server records the user's activity log for the week and stores it in a database. For example, it records the time the user completed tasks and their progress. At the end of the week, the server analyzes the collected activity log using a generative AI model and generates a report summarizing the week's activities. The server then sends the generated report to the device, and the device notifies the user. For example, the server may inform the user that "three major tasks were completed this week, increasing the team's productivity by 15%."

[0375] Emotional state recognition and alert generation

[0376] The emotion engine recognizes the user's emotional state based on what the user says to the generative AI model. For example, if the user says, "I've been feeling very stressed lately and can't concentrate on my work," the device sends this information to the server. The server analyzes the emotional data and evaluates high stress levels and other emotional states. Based on the analysis results, the server generates an alert if necessary and notifies the administrator's device. The administrator can then take appropriate action based on this alert.

[0377] Specific examples

[0378] For example, if a user says, "I've been feeling very stressed lately and can't concentrate on my work," the device will send this data to the server. The server will analyze it using an emotion engine and confirm the high stress level. Based on the judgment, it will generate an alert saying, "User A is feeling very stressed," and send it to the administrator's device. The administrator will receive this alert and can follow up with User A.

[0379] The above is a detailed description of each function in the embodiment of the present invention. By using this system, users can efficiently manage their goals and monitor their emotions.

[0380] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0381] Step 1:

[0382] The user speaks to the generative AI model about their goals and tasks. For example, they can input a goal like "I'll rehearse my presentation next Thursday." The input voice data is then converted into text data.

[0383] Step 2:

[0384] The device receives the converted text data, formats it, and sends it to the server. Specifically, the voice data is recognized as text and sent to the server as target data, such as "I will rehearse the presentation next Thursday." In this process, a voice recognition algorithm is used to convert the voice to text.

[0385] Step 3:

[0386] The server analyzes the received goal data and checks its contents. After receiving the user's goal data, the server passes it to the analysis engine, which extracts the goal date and content. For example, the server analyzes the date and time information, such as "next Thursday," and the task content, such as "rehearse the presentation."

[0387] Step 4:

[0388] The server sets alarms for goals and tasks based on the analyzed date information. Specifically, it sets the data to set reminder alarms for the day before and the day of the goal, and sets notifications to be sent at the appropriate date and time. The input is the analyzed goal data, and the output is the set alarm information.

[0389] Step 5:

[0390] When the set date and time arrives, the server sends a notification to the user device. For example, notification data such as "There is a presentation rehearsal tomorrow" is generated and sent to the user device. The device receives this notification data and notifies the user with a sound, vibration, or pop-up notification.

[0391] Step 6:

[0392] The data of the goals and tasks set by the user is sent from the terminal to the server and saved in the database. When saving to the database, the input is the goal data set by the user, and the output is save confirmation information.

[0393] Step 7:

[0394] When the server confirms that the data has been saved successfully, it generates a confirmation message and sends it to the device. The device receives this confirmation message and notifies the user that "the goal has been saved." In the confirmation message generation process, the confirmation message is created using the ID of the saved data.

[0395] Step 8:

[0396] The server records a user's activity log for one week and stores it in a database. The activity log records the time and progress of daily tasks. The input is the user's activity data, and the output is the activity log data.

[0397] Step 9:

[0398] At the end of the week, the server analyzes the collected activity logs and generates a weekly activity summary report using a generative AI model. The input is the activity log data, and the output is the generated summary report. A machine learning algorithm is used for the analysis.

[0399] Step 10:

[0400] The generated report is sent from the server to the device, and the device notifies the user of the report contents, such as "This week, three major tasks were completed, and the team's productivity increased by 15%."

[0401] Step 11:

[0402] The user inputs emotional data into the generative AI model, for example, by saying, "I've been feeling very stressed lately and can't concentrate on my work." The input voice data is converted into text data.

[0403] Step 12:

[0404] The device sends this text data to the server, which then analyzes the received emotional data using an emotion engine to evaluate the user's emotional state. The input is the user's emotional data, and the output is the evaluated emotional state.

[0405] Step 13:

[0406] The server generates alerts based on the analysis results if necessary. For example, if the user is judged to be at a high stress level, an alert is generated. The input is the assessed emotional state, and the output is the generated alert.

[0407] Step 14:

[0408] The generated alert is sent from the server to the administrator's terminal, and the administrator takes appropriate action based on the alert. The terminal receives the alert and displays it to the administrator.

[0409] The above processing steps enable efficient management of user goals and monitoring of emotions.

[0410] (Application example 2)

[0411] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0412] Conventional goal management and progress management systems do not monitor or provide feedback that takes into account the user's emotional state, which means they are unable to provide appropriate support even when the user reaches a high stress level. This can lead to long-term declines in productivity and work efficiency. Furthermore, even in factory environments using robots, there is also the issue of overall work efficiency not improving due to the inability to communicate smoothly with workers or manage tasks appropriately.

[0413] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving goals and tasks from the user, means for transmitting the received goals and tasks to the server, means for recognizing the user's emotional state using an emotion engine, means for transmitting the recognized emotional state to the server, means for analyzing the emotion data and generating an alert based on the emotional state, and means for notifying the administrator of the alert. This improves the user's work efficiency and enables appropriate support based on the user's emotional state.

[0414] The "means for receiving goals and tasks from the user" is a mechanism for receiving goals and tasks set by the user through voice input or text input.

[0415] The "means for transmitting received goals and tasks to a server" is a mechanism for transmitting data on goals and tasks received from a user to a server via the Internet or an internal network.

[0416] "Means for setting alarms for goals and tasks on the server" refers to a function for setting alarms for specific dates and times based on goals and tasks received by the server.

[0417] The "means for notifying the user of the set alarm" is a mechanism for sending a notification to the user's terminal at the set alarm date and time, and notifying the user by sound, vibration, or pop-up notification.

[0418] The "means for recognizing the emotional state of the user using an emotion engine" is a function that analyzes the voice or text input by the user and recognizes the emotional state of the user using an emotion engine.

[0419] The "means for transmitting the recognized emotional state to the server" is a mechanism for transmitting data on the user's emotional state recognized by the emotion engine to the server.

[0420] The "means for analyzing emotional data and generating an alert based on the emotional state" is a function that analyzes the emotional data received by the server and generates an alert if a specific emotional state is confirmed.

[0421] The "means for notifying the administrator of the alert" is a mechanism for notifying the administrator of the generated alert on his / her terminal, so that the administrator can take appropriate action.

[0422] The "means for saving user input data on the server" is a function for saving data on goals and tasks entered by the user on the server.

[0423] The "means for generating a confirmation message for saved data" is a function for generating a message for confirming that saving has been successful.

[0424] The "means for notifying the user of a confirmation message" is a mechanism for sending the generated confirmation message to the user terminal and notifying the user.

[0425] The "means for providing feedback to the worker based on the emotional state" is a function for providing appropriate feedback to the worker based on the analyzed emotional state.

[0426] The "means for recording a user's activity log for one week on the server" is a function for recording a user's activity data for one week on the server.

[0427] The "means for analyzing the recorded activity log and generating a weekly review" is a function for analyzing the recorded activity log and generating a weekly review report.

[0428] The "means for notifying the user of the generated weekly review" is a mechanism for sending the generated weekly review report to the user terminal and notifying the user.

[0429] "Means for generating prompt sentences based on one week's activity data and inputting them into the generative AI model" refers to a function that generates prompt sentences for the generative AI model based on one week's activity data and inputs them into the generative AI model.

[0430] This invention is a system for setting user goals, managing progress, and monitoring emotional states. The system consists of a server, a user terminal (a smartphone or personal computer), and a robot. The user interacts with a generative artificial intelligence (generative AI model) through the terminal or robot, and the emotion engine recognizes the user's emotional state and provides appropriate feedback.

[0431] 1. User Interface

[0432] The user sets goals and tasks using a terminal or robot by voice input or text input, and the entered goals and tasks are sent to a server via the Internet.

[0433] 2. Data transmission and storage

[0434] The received goal and task data is sent to the server, which stores the data in a database. If the data is successfully stored, the server generates a confirmation message and sends it to the user's device.

[0435] 3. Alarm settings and notifications

[0436] The server sets an alarm based on the received goals and tasks. The alarm is notified to the user's device or robot at a specific date and time, and the user is notified by sound, vibration, or a pop-up notification.

[0437] 4. Monitoring your emotional state

[0438] When a user interacts with a generative AI model, the emotion engine analyzes the voice and text to recognize the emotional state. The recognized emotional state is sent to the server, which then analyzes the emotional data.

[0439] 5. Alerting and Notification

[0440] Based on the analysis results, the server generates an alert if it determines that support is required. For example, if it determines that a user is at a high stress level, an alert is generated and sent to the administrator's device. The administrator can then take appropriate action based on this alert.

[0441] 6. Activity log and review

[0442] The server records the user's activity log for one week and stores it in a database. At the end of the week, the server analyzes the activity log and generates a weekly review report using a generative AI model. The generated report is sent to the user's device and the user is notified.

[0443] Hardware and software used

[0444] Hardware: Smartphone, personal computer, robot-integrated microphone, speaker, and internet connection

[0445] Software: Python, speech_recognition, pyttsx3, requests, TextBlob

[0446] Specific examples

[0447] For example, if a user says, "I'll rehearse my presentation next Thursday," the speech is converted into text and sent to the server. The server saves the goal data and notifies the user at the specified date and time, saying, "I'll rehearse my presentation tomorrow."

[0448] Furthermore, if a user says, "I've been feeling very stressed lately and can't concentrate on my work," the emotion engine analyzes the situation and confirms the high stress level. The server generates an alert saying, "User A is feeling very stressed," and sends it to the administrator's device. The administrator receives this and follows up with User A.

[0449] Examples of prompts for generative AI models:

[0450] "User set goal: Increase team productivity by 20%, User's emotional state: High stress, Alarm set time: Tomorrow at 2 PM"

[0451] The above is an embodiment of the present invention.

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

[0453] Step 1:

[0454] A user sets goals and tasks using a terminal or robot by voice or text input. For example, if a user sets a goal such as "I will rehearse my presentation next Thursday," the terminal receives this voice as text data. In this case, the input is voice data and the output is text data.

[0455] Step 2:

[0456] The device sends the acquired text data to a server via the Internet. Specifically, the device converts the text data into JSON format and sends the data to the server's API endpoint using an HTTP request. Here, the input is the text data and the output is the HTTP request sent to the server.

[0457] Step 3:

[0458] The server analyzes the received goal and task data and saves it in a database. If successful, the server generates a confirmation message and sends it to the terminal. The input is the text data sent to the server, and the output is the saved status in the database and the confirmation message.

[0459] Step 4:

[0460] The server sets an alarm based on the received goals and tasks. For example, it sets a notification for a specific date and time (for example, the day before or the day itself). It analyzes the date and time data of the goals set by the user and determines the alarm setting time. The input is the date and time data of the goals and tasks, and the output is the alarm setting data.

[0461] Step 5:

[0462] The server sends an alarm notification to the device at the set date and time. The device notifies the user of this notification by sound, vibration, or a pop-up notification. The input is the alarm setting data, and the output is the alarm notified to the user.

[0463] Step 6:

[0464] The user interacts with the generative AI model through a device or robot, making statements that express their emotional state. The emotion engine analyzes these statements and recognizes the user's emotional state. For example, if a user says, "I've been feeling very stressed lately and can't concentrate on my work," the emotion engine recognizes this as high stress. The input is the user's utterance data, and the output is the recognized emotion data.

[0465] Step 7:

[0466] The device sends the recognized emotional data to the server. The server analyzes this emotional data and generates an alert if a specific emotional state (e.g., high stress) is confirmed. For example, an alert may be generated stating, "User A is experiencing high stress." The input is the emotional data, and the output is the generated alert.

[0467] Step 8:

[0468] The generated alert is sent from the server to the administrator's terminal. The administrator's terminal displays the alert and supports the administrator in taking appropriate action. The input is the generated alert data, and the output is the alert notified to the administrator's terminal.

[0469] Step 9:

[0470] The server records a week's worth of user activity logs and stores them in a database. The activity logs include the user's goals, task progress, completion time, emotional state, etc. The input is the user activity data, and the output is the stored activity logs.

[0471] Step 10:

[0472] At the end of the week, the server analyzes the activity log and generates a weekly review report using a generative AI model. The report includes a summary of the user's work efficiency and emotional state. The input is the activity log data, and the output is the generated weekly review report.

[0473] Step 11:

[0474] The generated weekly review report is sent to the user terminal. The user terminal notifies the user of this report and displays its contents. The input is the generated report, and the output is the report notified to the user.

[0475] Step 12:

[0476] A prompt sentence is generated based on one week's activity data and input into the generative AI model. The generative AI model uses this prompt sentence to generate improvement suggestions and advice on setting goals for the next week. For example, a prompt sentence such as "User-set goal: Increase team productivity by 20%, User's emotional state: High stress, Alarm setting time: Tomorrow at 2 p.m." is generated. The input is activity data, and the output is the generated prompt sentence and improvement suggestions.

[0477] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0478] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0479] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0480] [Second embodiment]

[0481] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0482] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0483] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0484] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0485] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0486] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0487] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0488] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0489] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0490] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0491] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0492] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0493] 1. System Configuration

[0494] The system of the present invention is mainly composed of a server and a user terminal (e.g., a smartphone or PC). Through the terminal, the user interacts with "Coach-kun," a generative artificial intelligence (generative AI). Through interaction with Coach-kun, the system is a tool for setting the user's goals and managing their progress.

[0495] 2. Function to receive goals and tasks from users

[0496] The user inputs goals and tasks by speaking to the generative AI using the device. For example, a goal might be set as "rehearsing a presentation next Thursday." The device then sends this goal data to the server.

[0497] 3. Function to send received goals and tasks to the server

[0498] The device formats the information entered by the user and sends it over the Internet or an internal network to a server, which analyzes the data and verifies the objectives and tasks.

[0499] 4. Ability to set alarms for goals and tasks on the server

[0500] The server analyzes the received goal and task data and sets alarms for the goal or task at the appropriate date and time, for example, "to be reminded the day before and the day of a presentation rehearsal."

[0501] 5. Function to notify users of set alarms

[0502] When the set date and time arrives, the server sends a notification to the user's device, which then notifies the user of the alarm with a sound, vibration, or a pop-up notification.

[0503] 6. User data storage function

[0504] The device sends the data entered by the user to the server, which stores it in a database. For example, if a user enters, "My goal this month is to increase my team's productivity by 20%, the server stores this information."

[0505] 7. Data saving confirmation notification function

[0506] If the data is saved successfully, the server generates a confirmation message and sends it to the device, which notifies the user that "the goal has been saved."

[0507] 8. Server activity logging function

[0508] The server records the user's activity log for one week and stores it in a database, including the time it took to complete a task and the progress of that task.

[0509] 9. Activity log analysis function

[0510] At the end of the week, the server analyzes the collected activity logs and uses generative AI to summarize the user's activities over the week and compiles the generated summary into a report.

[0511] 10. Ability to notify users of summary reports

[0512] The generated report is sent from the server to the terminal, and the terminal notifies the user of the report contents, allowing the user to review their activities for the week.

[0513] 11. Sentiment Analysis Function

[0514] The device sends data to a server to analyze the user's emotional state from what they say to the generative AI. For example, if the user says, "I've been feeling very stressed lately and can't concentrate on my work," the server will use the generative AI to analyze that emotional state.

[0515] 12. Alert Generation Function

[0516] The server generates alerts based on the results of emotion analysis. If the stress level is determined to be high, an alert is generated for management.

[0517] 13. Alert notification function

[0518] The generated alerts are sent from the server to the manager's terminal, where they are displayed and the manager is assisted in taking appropriate action.

[0519] Specific examples

[0520] For example, if a user says, "I've been feeling very stressed lately and can't concentrate on my work," the device will send this information to the server. The server will use generative AI to analyze the emotion, and if it determines that the stress level is high, it will send an alert to the manager's device saying, "User A is feeling very stressed." The manager's device will then display this alert, allowing the manager to take appropriate action.

[0521] The above is a description of each function in the embodiment of the present invention.

[0522] The processing flow will be explained below.

[0523] 1. Alarm function processing

[0524] Step 1:

[0525] A user uses a device to input a goal or task into the generative AI, for example, "I'll rehearse my presentation next Thursday."

[0526] Step 2:

[0527] The terminal formats the input target data and transmits it to the server.

[0528] Step 3:

[0529] The server analyzes the received data and checks the content and date / time information of the goals and tasks.

[0530] Step 4:

[0531] The server sets an alarm for the specified date and time, for example, to remind you the day before and the day itself.

[0532] Step 5:

[0533] When the specified date and time arrives, the server will send an alarm notification to the terminal.

[0534] Step 6:

[0535] The device will notify the user of the alarm with a sound, vibration, or pop-up notification.

[0536] 2. Save your goals and feedback

[0537] Step 1:

[0538] The user inputs goals and ideas into the generative AI. For example, "My goal this month is to increase team productivity by 20%."

[0539] Step 2:

[0540] The terminal formats the entered data and sends it to the server.

[0541] Step 3:

[0542] The server stores the received data in a database.

[0543] Step 4:

[0544] Once the save is complete, the server generates a confirmation message and sends it to the device.

[0545] Step 5:

[0546] The device will notify the user with a confirmation message "Goal saved."

[0547] 3. Weekly review summary function

[0548] Step 1:

[0549] The server records a user's activity log for one week and stores it in a database.

[0550] Step 2:

[0551] On weekends, the server analyzes the collected activity logs.

[0552] Step 3:

[0553] The server uses generative AI to summarize activities and generate a weekly review.

[0554] Step 4:

[0555] The server generates a summary report and sends it to the terminal.

[0556] Step 5:

[0557] The terminal notifies the user of the report contents and displays them.

[0558] 4. Alert function

[0559] Step 1:

[0560] The user talks to the generative AI about their feelings and difficulties, for example, saying, "I've been feeling very stressed lately and can't concentrate on my work."

[0561] Step 2:

[0562] The device sends the user's speech to the server.

[0563] Step 3:

[0564] The server uses generative AI to analyze the emotional state from the received data.

[0565] Step 4:

[0566] The server generates an alert based on the results of emotion analysis if it determines that support is required.

[0567] Step 5:

[0568] The server sends an alert to management.

[0569] Step 6:

[0570] The manager's device will display an alert, helping the manager take appropriate action.

[0571] The above are the specific processing steps for each function.

[0572] Example 1

[0573] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0574] In modern society, it is important for users to effectively manage their goals and tasks. It is also necessary to properly understand users' emotional states and provide necessary alerts in advance. However, current systems lack the ability to centrally manage users' goals and analyze their emotions, resulting in a split between task management and responding to changes in emotional states. Furthermore, they lack an alert notification function that allows administrators to provide appropriate follow-up.

[0575] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0576] In this invention, the server includes means for receiving goals and tasks from the user, means for transmitting the received goals and tasks to the server, means for setting an alarm for the goal or task on the server, means for notifying the user of the set alarm, means for analyzing the user's emotional state, means for generating an alert based on the result of the user's emotional analysis, and means for notifying the administrator of the generated alert. This makes it possible to perform user goal management and emotional analysis in an integrated manner, and to generate and provide to the administrator an alarm notification or an alert based on the emotional state at an appropriate time.

[0577] "Means for receiving goals and tasks from a user" refers to an interface that allows a user to input goals and tasks into the system and software for recognizing them.

[0578] "Means for transmitting received goals and tasks to a server" refers to the protocol and communication functions for transferring goal and task data entered by the user to a server via a network.

[0579] "Means for setting goal or task alarms on the server" refers to the software functionality that analyzes the goal or task data received by the server and creates alarms based on corresponding dates, times, and conditions.

[0580] "Means for notifying the user of the set alarm" refers to the communication functions and interface for transmitting the alarm set on the server to the user's device and notifying the user by sound, vibration, pop-up message, etc.

[0581] "Means for analyzing the user's emotional state" refers to generative AI models and natural language processing technologies for analyzing the user's emotional state based on the user's input data.

[0582] "Means for generating alerts based on the results of the user's emotional analysis" refers to the software's functionality for generating alert messages based on the results of the analyzed emotional state, according to stress levels or other emotional states.

[0583] "Means for notifying the administrator of the generated alert" refers to a communication function that sends the generated alert based on the user's emotional state to the administrator's terminal and notifies them so that appropriate follow-up can be carried out.

[0584] 1. System Configuration

[0585] The system of the present invention is primarily composed of a server and a user terminal (e.g., a smartphone or PC). In this system, users set goals and manage progress by interacting with "Coach-kun," a generative AI. It also uses an emotion analysis function to monitor the user's stress level and send alerts to the administrator as necessary.

[0586] 2. Function to receive goals and tasks from users

[0587] The user interactively inputs goals and tasks into the generative AI through the device. For example, the user can set a goal such as "rehearsing a presentation next Thursday." The device is equipped with speech recognition software that converts what the user says into text data. Specific software that can be used is the Google Speech-to-Text API.

[0588] 3. Function to send received goals and tasks to the server

[0589] The device converts the text data into a proprietary format using voice recognition software, then encrypts it for security purposes and sends it to a server over the internet or an internal network using the Transport Layer Security (TLS) protocol.

[0590] 4. Ability to set alarms for goals and tasks on the server

[0591] The server analyzes the received text data and sets an alarm based on the content of the goal or task. For example, it extracts date and time information such as "next Thursday" and sets an alarm. Natural language processing (NLP) technology is used for the analysis, specifically the Python nltk library. A scheduling tool such as a cron job is used to set the alarm.

[0592] 5. Function to notify users of set alarms

[0593] When the set date and time arrives, the server generates a notification message and sends it to the device. The device notifies the user of this message by a pop-up notification, sound, or vibration. Cloud messaging services such as Firebase Cloud Messaging (FCM) can be used for the notification function.

[0594] 6. User data storage function

[0595] The terminal sends the data entered by the user to the server, which stores this data in temporary storage and then stores it permanently using a database management system (DBMS), such as MySQL or PostgreSQL.

[0596] 7. Data saving confirmation notification function

[0597] The server checks whether the data was saved successfully and generates a confirmation message. This message is sent to the device, which notifies the user that the goal has been saved. The communication uses an HTTP response.

[0598] 8. Server activity logging function

[0599] The server keeps a log of users' activities for one week. This log includes the tasks the user has completed and their progress. The log data is stored in a NoSQL database (e.g., MongoDB).

[0600] 9. Activity log analysis function

[0601] At the end of the week, the server analyzes the collected activity logs and uses a generative AI model to summarize the user's activity over the week, using Python data processing libraries (Pandas and Numpy).

[0602] 10. Ability to notify users of summary reports

[0603] The generated report is sent from the server to the device, and the device notifies the user of the report contents via a pop-up notification or email.

[0604] 11. Sentiment Analysis Function

[0605] To perform sentiment analysis of what the user says to the generative AI (e.g., "I've been feeling very stressed lately and can't concentrate on my work"), the device sends the data to a server. The server then uses a generative AI model (e.g., BERT or GPT) to analyze the sentiment. The analysis results identify the user's emotional state.

[0606] 12. Alert Generation Function

[0607] The server generates alerts based on the results of the emotion analysis, if necessary: ​​if a high stress level is detected, an alert message is generated and sent to the administrator.

[0608] 13. Alert notification function

[0609] The server sends an alert message to the administrator's terminal, which displays the alert on its screen to help the administrator take appropriate action.

[0610] Specific examples

[0611] For example, if a user says, "I've been feeling very stressed lately and can't concentrate on my work," the device uses voice recognition software to convert this information into text data and send it to the server. The server then uses a generative AI model to analyze the emotional state. If the server determines that the stress level is high, it sends an alert to the administrator's device stating, "User A is feeling very stressed." The administrator's device then displays this alert, allowing the administrator to take appropriate action.

[0612] The above is a description of each function in the embodiment of the present invention.

[0613] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0614] Step 1:

[0615] The user speaks through the terminal. The user sets a goal, such as "I will rehearse my presentation next Thursday." This information is input as voice.

[0616] Step 2:

[0617] The device uses speech recognition software (e.g., Google Speech-to-Text API) to convert voice data into text data. The input is voice data and the output is text data.

[0618] Step 3:

[0619] The terminal adapts the text data to a proprietary format. At this stage the text data is prepared for further data processing. The input is text data and the output is formatted text data.

[0620] Step 4:

[0621] The terminal encrypts the formatted text data and sends it to the server over the Internet or an internal network. The encryption is performed using the TLS protocol. The input is the formatted text data, and the output is the encrypted data.

[0622] Step 5:

[0623] The server decrypts the received data and uses natural language processing (NLP) techniques to parse the data, for example to extract date and time information such as "next Thursday." The input is the encrypted data, and the output is the parsed date and time information.

[0624] Step 6:

[0625] The server sets an alarm based on the analyzed date and time information using a scheduling tool such as a cron job. The input is the date and time information, and the output is the set alarm.

[0626] Step 7:

[0627] When the set date and time arrives, the server generates a notification message and sends it to the user's terminal. The input is the set alarm, and the output is the notification message.

[0628] Step 8:

[0629] The device notifies the user of the received notification message by pop-up notification, sound, vibration, etc. The input is the notification message, and the output is the notification to the user.

[0630] Step 9:

[0631] The terminal stores all data entered by the user in temporary storage and then sends it to the server, which stores the data persistently using a database management system (e.g., MySQL or PostgreSQL). The input is the user data and the output is the stored data.

[0632] Step 10:

[0633] The server checks whether the data was saved correctly and generates a confirmation message. This message is sent to the user's device, informing the user that "the goal has been saved." The input is the saved data, and the output is the confirmation message.

[0634] Step 11:

[0635] The server records a user's activity log for one week. This log includes the tasks the user has completed and their progress information. The log data is stored in a NoSQL database (e.g., MongoDB). The input is the task data, and the output is the recorded activity log.

[0636] Step 12:

[0637] At the end of the week, the server analyzes the collected activity logs and uses a generative AI model (e.g., GPT-3) to summarize the user's activities for the week. The analysis is performed using Python data processing libraries (Pandas and Numpy). The input is the activity log, and the output is a summary report.

[0638] Step 13:

[0639] The generated report is sent from the server to the terminal, and the terminal notifies the user of the report contents via a pop-up notification, email, etc. The input is a summary report, and the output is a notification to the user.

[0640] Step 14:

[0641] The device sends what the user says to the generative AI to the server for emotion analysis. The input is the user's speech data, and the output is the data sent to the server.

[0642] Step 15:

[0643] The server uses a generative AI model (e.g., BERT or GPT-3) to analyze the user's utterances and identify their emotional state. The input is the utterance data, and the output is the emotion analysis result.

[0644] Step 16:

[0645] The server generates alerts as needed based on the emotion analysis results. If a high stress level is detected, an alert message is generated. The input is the emotion analysis results, and the output is the alert message.

[0646] Step 17:

[0647] The generated alert is sent from the server to the administrator's terminal, where it is displayed. The input is the alert message, and the output is a notification to the administrator.

[0648] The above is a specific description of each processing step in the system of the present invention.

[0649] (Application example 1)

[0650] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0651] Improving work efficiency and providing mental health care for workers at the same time are extremely important in production sites, but it is difficult to achieve these goals simultaneously using conventional methods.In addition, while there is a demand for the introduction of systems that improve the efficiency of work progress and task management, there are not yet enough systems that can analyze the emotional state of workers and take appropriate action based on that.

[0652] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0653] In this invention, the server includes means for receiving goals and tasks from users, means for transmitting the received goals and tasks to the server, means for setting alarms for the goals and tasks on the server, means for notifying the user of the set alarm, means for analyzing the emotional state of factory workers from their input, means for generating alerts based on the emotion analysis results, and means for notifying a manager of the generated alert. This not only improves work efficiency but also supports the mental health of workers.

[0654] The "means for receiving goals and tasks from a user" is an interface for acquiring information on work goals and tasks from factory workers.

[0655] The "means for transmitting the received goal or task to the server" is a mechanism for transferring the information on the acquired goal or task to the server via a data network.

[0656] The "means for setting alarms for goals and tasks on the server" is a program for setting the date and time for reminder notifications for goals and tasks received in the server.

[0657] The "means for notifying the user of the set alarm" is a mechanism for notifying the user terminal at the set date and time.

[0658] The "means for analyzing the emotional state of a factory worker from input" is an algorithm for analyzing the emotional state of a factory worker from the voice uttered by the worker or the text data entered by the worker.

[0659] The "means for generating an alert based on the results of emotion analysis" is a mechanism that generates a warning when high stress, etc. is detected based on the results of emotion analysis.

[0660] The "means for notifying the manager of the generated alert" is a mechanism for sending the generated warning to the manager of the factory and prompting him to take action.

[0661] This invention is a system that enables factory workers and managers to set goals and tasks, manage progress, and analyze workers' emotional states to take appropriate action. The system consists of a user terminal and a server, and realizes each function using a generative AI model.

[0662] The system program works as follows:

[0663] Receive and send goals and tasks

[0664] The user device receives voice or text input of goals and tasks set by factory workers, such as "inspect the machine next Monday." This data is analyzed and formatted using a generative AI model and then sent to a server over the internet or an internal network.

[0665] Processing on the server

[0666] The server analyzes the received goal and task data and sets reminders for the appropriate dates and times. For example, if you set "machine inspection next Monday," reminders are set for the day before and the day itself.

[0667] Notification function

[0668] When the set reminder date and time arrives, the server sends a notification to the user's device, which then notifies the worker of this notification as a pop-up or audio alarm, urging them to complete the task without forgetting.

[0669] Saving and checking data

[0670] The goal and task data entered by the user is saved in the server's database. Once the saving is complete, the server generates a confirmation message and sends it to the user's terminal. The user's terminal then notifies the worker of the message "Task saved" and asks them to confirm that the data has been saved correctly.

[0671] Sentiment analysis and alert generation

[0672] The user device receives the worker's voice input and text data and sends it to the server. The server uses a generative AI model to analyze the worker's emotional state. For example, if a worker inputs, "I've been feeling very stressed recently and can't concentrate on my work," the emotional state is determined to be high stress. In this case, the server generates and sends an alert to the manager stating, "The worker is feeling high stress." The manager can receive this alert and take appropriate action.

[0673] Examples and prompts

[0674] For example, if a worker specifies "I will inspect the machine next Monday," the system will analyze that data, set a reminder, and send a notification. Also, if a worker specifies "I've been feeling very stressed lately and can't concentrate on my work," the system will analyze that emotion and send an alert to the manager.

[0675] Example prompt sentence:

[0676] "Please set a task to inspect the machine next Monday."

[0677] "I've been feeling very stressed lately and can't concentrate on my work."

[0678] In this way, the present invention can improve the work efficiency of a factory while also providing mental health care for workers.

[0679] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0680] Step 1:

[0681] The user inputs their goals and tasks into the device using voice or text. The input data is passed to the generative AI model, which analyzes the content of the goals and tasks. The generative AI model then formats the data and converts it into a format that can be sent to the server.

[0682] Input: Worker inputs by voice or text, "I will inspect the machine next Monday."

[0683] Output: Formatted goal and task data

[0684] Step 2:

[0685] The device sends formatted goal and task data to the server, which verifies the received data and stores it in a database. If the data is successfully stored, the server generates a confirmation message and sends it to the device.

[0686] Input: Formatted goal and task data

[0687] Output: Confirmation message "Task saved"

[0688] Step 3:

[0689] The server analyzes the received goal and task data and sets reminder notifications at appropriate dates and times. Specifically, it generates a schedule of reminder notifications for the previous day and the current day based on the date and time information of the goal or task.

[0690] Input: Goal and task data stored in the database

[0691] Output: Scheduled date and time of the reminder notification

[0692] Step 4:

[0693] When the set reminder date and time arrives, the server sends a reminder notification to the terminal, which then notifies the worker as a pop-up or audio alarm.

[0694] Input: Scheduled date and time of the reminder notification

[0695] Output: Pop-up notification and audio alarm

[0696] Step 5:

[0697] The user device receives the worker's voice input and text data and sends it to the server, which uses a generative AI model to analyze the data and evaluate the worker's emotional state. If high stress is detected, an alert is generated.

[0698] Input: Worker's voice input or text data (e.g., "I've been feeling very stressed lately and can't concentrate on my work.")

[0699] Output: Sentiment analysis results and alert information

[0700] Step 6:

[0701] The server notifies the administrator of the generated alert, and the alert information is sent to the administrator's terminal, helping the administrator to take appropriate action.

[0702] Input: Alert information

[0703] Output: Alert notification to administrator

[0704] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0705] 1. System Configuration

[0706] This invention is a system for setting user goals, managing progress, and monitoring emotional states. The system mainly consists of a server and a user device (smartphone or PC). Users interact with a generative artificial intelligence (generative AI) through the device, and an emotion engine is used to recognize their emotional state and provide appropriate feedback.

[0707] 2. Function to receive goals and tasks from users

[0708] The user inputs goals and tasks by speaking to the generative AI using the device. For example, the user might set a goal such as "rehearsing a presentation next Thursday." The device then sends this goal data to the server.

[0709] 3. Function to send received goals and tasks to the server

[0710] The terminal formats the entered goal data and sends it to a server via the Internet or an internal network. The server analyzes the received data and verifies the goal or task.

[0711] 4. Ability to set alarms for goals and tasks on the server

[0712] The server analyzes the received goal or task data and sets an alarm for the goal or task at the appropriate date and time, for example, setting a reminder for the day before and the day of the goal or task.

[0713] 5. Function to notify users of set alarms

[0714] When the set date and time arrives, the server sends a notification to the user's device. The device notifies the user with an alarm sound, vibration, or a pop-up notification. For example, it may notify the user, "There is a rehearsal for your presentation tomorrow."

[0715] 6. User data storage function

[0716] The device sends the data entered by the user to the server, which stores it in a database. For example, if a user enters "My goal this month is to increase my team's productivity by 20%," the server stores this information in a database.

[0717] 7. Data saving confirmation notification function

[0718] If the data is saved successfully, the server generates a confirmation message and sends it to the device, which notifies the user that the goal has been saved.

[0719] 8. Server activity logging function

[0720] The server records the user's activity log for one week and stores it in a database, including the time it took to complete a task and the progress of that task.

[0721] 9. Activity log analysis function

[0722] At the end of the week, the server analyzes the collected activity logs and uses generative AI to summarize the user's activities over the week and compiles the generated summary into a report.

[0723] 10. Ability to notify users of summary reports

[0724] The generated report is sent from the server to the device, and the device notifies the user of the report contents, for example, "This week, we completed three major tasks, and our team's productivity increased by 15%."

[0725] 11. Emotion recognition function using emotion engine

[0726] The emotion engine recognizes the user's emotional state based on what the user says to the generative AI. For example, if the user says, "I've been feeling very stressed lately and can't concentrate on my work," the device will send this information to the server.

[0727] 12. Emotion data analysis function

[0728] The server analyzes the received emotional data and provides a detailed assessment of the user's emotional state, identifying high stress levels and other emotional states.

[0729] 13. Alert Generation Function

[0730] Based on the sentiment analysis results, the server generates an alert if it determines that support is needed, for example, if it determines that the user is experiencing high stress levels.

[0731] 14. Alert notification function

[0732] The generated alerts are sent from the server to the manager's terminal, where they are displayed. The manager is supported to take appropriate action based on the alerts.

[0733] Specific examples

[0734] For example, if a user says, "I've been feeling very stressed lately and can't concentrate on my work," the device will send this data to the server. The server will analyze it using an emotion engine and confirm the high stress level. Based on the judgment, it will generate an alert saying, "User A is feeling very stressed," and send it to the manager's device. The manager will receive this alert and can follow up with User A.

[0735] The above is a detailed description of each function in the embodiment of the present invention.

[0736] The processing flow will be explained below.

[0737] Goal and task management features

[0738] Step 1:

[0739] A user uses a device to input a goal or task into the generative AI, for example, "I'll rehearse my presentation next Thursday."

[0740] Step 2:

[0741] The terminal formats the input target data and transmits it to the server.

[0742] Step 3:

[0743] The server analyzes the received data and checks the content and date / time information of the goals and tasks.

[0744] Step 4:

[0745] The server sets an alarm for the specified date and time, for example, to remind you the day before and the day itself.

[0746] Step 5:

[0747] When the specified date and time arrives, the server will send an alarm notification to the terminal.

[0748] Step 6:

[0749] The device will notify the user of the alarm with a sound, vibration, or pop-up notification.

[0750] Data storage function

[0751] Step 1:

[0752] The user inputs goals and ideas into the generative AI. For example, "My goal this month is to increase team productivity by 20%."

[0753] Step 2:

[0754] The terminal formats the entered data and sends it to the server.

[0755] Step 3:

[0756] The server stores the received data in a database.

[0757] Step 4:

[0758] Once the save is complete, the server generates a confirmation message and sends it to the device.

[0759] Step 5:

[0760] The device will notify the user with a confirmation message "Goal saved."

[0761] Weekly review function

[0762] Step 1:

[0763] The server records a user's activity log for one week and stores it in a database.

[0764] Step 2:

[0765] On weekends, the server analyzes the collected activity logs.

[0766] Step 3:

[0767] The server uses generative AI to summarize activities and generate a weekly review.

[0768] Step 4:

[0769] The server generates a summary report and sends it to the terminal.

[0770] Step 5:

[0771] The terminal notifies the user of the report contents and displays them.

[0772] Emotion recognition function using emotion engine

[0773] Step 1:

[0774] The user inputs dialogue into the generative AI, for example, saying, "I've been feeling very stressed lately and can't concentrate on my work."

[0775] Step 2:

[0776] The terminal transmits the input dialogue content to the server.

[0777] Step 3:

[0778] The server uses an emotion engine to analyze the content of the user's dialogue and recognize the user's emotional state.

[0779] Step 4:

[0780] The server evaluates the recognized emotional data and detects abnormalities such as high stress levels.

[0781] Alerting and Notification

[0782] Step 1:

[0783] The server generates an alert based on the analysis results of the emotion engine when it determines that support is required.

[0784] Step 2:

[0785] The server sends the generated alert to the manager's terminal.

[0786] Step 3:

[0787] The manager's device will display an alert, helping the manager take appropriate action.

[0788] Specific examples

[0789] 1. The user tells the generative AI, "I've been feeling very stressed lately and can't concentrate on my work."

[0790] 2. The device sends the conversation content to the server.

[0791] 3. The server uses an emotion engine to analyze the content of the conversation and determine that the stress level is high.

[0792] 4. The server generates an alert saying "User A is experiencing high stress."

[0793] 5. The server sends an alert to the manager's terminal.

[0794] 6. The manager's device displays an alert and the manager follows up with User A.

[0795] The above are the specific processing steps of each function in the embodiment of the present invention in which an emotion engine is combined.

[0796] Example 2

[0797] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0798] While conventional goal management systems can manage the goals and tasks entered by users, they lack the ability to grasp the user's emotional state in real time and provide appropriate feedback and support as needed. As a result, users who are particularly stressed may not receive the support they need, which can lead to a decline in productivity and mental health. Furthermore, the lack of analysis of activity logs and feedback on goal achievement makes it difficult for users to create specific plans for self-improvement.

[0799] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for receiving goals and tasks from the user, means for transmitting the received goals and tasks to the server, means for setting alarms for the goals and tasks on the server, means for notifying the user of the set alarm, means for transmitting emotional data entered by the user to the server, means for the server to analyze the emotional data using an emotion engine and evaluate the user's emotional state, means for the server to generate an alert if necessary based on the analysis results, and means for notifying the administrator's terminal of the generated alert. This enables progress management of the goals and tasks set by the user, as well as monitoring of the emotional state and providing appropriate feedback. Furthermore, adding a function for analyzing a one-week activity log and providing feedback based on the log allows the user to create a specific action plan for self-improvement and improve overall performance.

[0800] "Goals and tasks" refer to the objectives that a user is trying to achieve or the specific work that needs to be done.

[0801] "User" refers to a person who uses this system to set goals, manage progress, and monitor emotions.

[0802] The "means for receiving" refers to a process or device by which the terminal acquires data on goals or tasks input by the user.

[0803] "Means for transmitting" refers to the process or device for sending received data from the terminal to the server and communicating.

[0804] "Server" refers to a central computing device for analyzing, storing, and managing received data.

[0805] "Means for setting an alarm" refers to a mechanism or device for sending a notification based on a specified date, time, or conditions.

[0806] "Means for notifying" refers to a device or process for notifying a user or administrator of configured alarms or confirmation messages.

[0807] "Emotion data" is data that indicates the user's emotional state, and includes psychological factors such as stress and satisfaction.

[0808] An "emotion engine" refers to software or algorithms that analyze emotional data and assess a user's emotional state.

[0809] "Means for generating alerts" refers to a mechanism or device that generates warnings or notifications when certain conditions are met based on the results of analyzing emotional data.

[0810] "Administrator" refers to a person whose job is to operate this system and support users.

[0811] An "activity log" refers to data that records a user's daily activities and task progress.

[0812] "Weekly Review" refers to a report that analyzes recorded activity logs and summarizes the user's actions and achievements over the week.

[0813] This invention is a system that manages the goals and tasks set by the user and monitors the emotional state. This system is mainly composed of a server and a user terminal (smartphone or PC).

[0814] System Configuration

[0815] Users can interact with the generative AI model through their device and receive appropriate feedback and recognition of their emotional state using the emotion engine.

[0816] Entering goals and tasks

[0817] Using a smartphone or PC, a user speaks to the generative AI model about their goals and tasks. For example, they might set a goal like "I'll rehearse my presentation next Thursday." The device then converts this goal data from speech to text and sends it to the server.

[0818] Receiving data and setting alarms

[0819] The server analyzes the received goal and task data and checks the details. Once the analysis is complete, an alarm is set for the appropriate date and time according to the goal. For example, it can set a reminder for the day before and the day itself.

[0820] Alarm notifications

[0821] When the set date and time arrives, the server sends a notification to the user's device. The device notifies the user of this notification by sound, vibration, or a pop-up notification. For example, it may notify the user that "there is a rehearsal for the presentation tomorrow."

[0822] User Data Storage

[0823] The device sends data on the goals and tasks set by the user to the server, which then stores the data in a database. For example, if a user enters "This month's goal is to increase team productivity by 20%, that information is stored.

[0824] Data storage confirmation notice

[0825] When the server confirms that the data has been saved successfully, it generates a confirmation message and sends it to the device, which then notifies the user that "the goal has been saved."

[0826] Activity log recording and analysis

[0827] The server records the user's activity log for the week and stores it in a database. For example, it records the time the user completed tasks and their progress. At the end of the week, the server analyzes the collected activity log using a generative AI model and generates a report summarizing the week's activities. The server then sends the generated report to the device, and the device notifies the user. For example, the server may inform the user that "three major tasks were completed this week, increasing the team's productivity by 15%."

[0828] Emotional state recognition and alert generation

[0829] The emotion engine recognizes the user's emotional state based on what the user says to the generative AI model. For example, if the user says, "I've been feeling very stressed lately and can't concentrate on my work," the device sends this information to the server. The server analyzes the emotional data and evaluates high stress levels and other emotional states. Based on the analysis results, the server generates an alert if necessary and notifies the administrator's device. The administrator can then take appropriate action based on this alert.

[0830] Specific examples

[0831] For example, if a user says, "I've been feeling very stressed lately and can't concentrate on my work," the device will send this data to the server. The server will analyze it using an emotion engine and confirm the high stress level. Based on the judgment, it will generate an alert saying, "User A is feeling very stressed," and send it to the administrator's device. The administrator will receive this alert and can follow up with User A.

[0832] The above is a detailed description of each function in the embodiment of the present invention. By using this system, users can efficiently manage their goals and monitor their emotions.

[0833] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0834] Step 1:

[0835] The user speaks to the generative AI model about their goals and tasks. For example, they can input a goal like "I'll rehearse my presentation next Thursday." The input voice data is then converted into text data.

[0836] Step 2:

[0837] The device receives the converted text data, formats it, and sends it to the server. Specifically, the voice data is recognized as text and sent to the server as target data, such as "I will rehearse the presentation next Thursday." In this process, a voice recognition algorithm is used to convert the voice to text.

[0838] Step 3:

[0839] The server analyzes the received goal data and checks its contents. After receiving the user's goal data, the server passes it to the analysis engine, which extracts the goal date and content. For example, the server analyzes the date and time information, such as "next Thursday," and the task content, such as "rehearse the presentation."

[0840] Step 4:

[0841] The server sets alarms for goals and tasks based on the analyzed date information. Specifically, it sets the data to set reminder alarms for the day before and the day of the goal, and sets notifications to be sent at the appropriate date and time. The input is the analyzed goal data, and the output is the set alarm information.

[0842] Step 5:

[0843] When the set date and time arrives, the server sends a notification to the user device. For example, notification data such as "There is a presentation rehearsal tomorrow" is generated and sent to the user device. The device receives this notification data and notifies the user with a sound, vibration, or pop-up notification.

[0844] Step 6:

[0845] The data of the goals and tasks set by the user is sent from the terminal to the server and saved in the database. When saving to the database, the input is the goal data set by the user, and the output is save confirmation information.

[0846] Step 7:

[0847] When the server confirms that the data has been saved successfully, it generates a confirmation message and sends it to the device. The device receives this confirmation message and notifies the user that "the goal has been saved." In the confirmation message generation process, the confirmation message is created using the ID of the saved data.

[0848] Step 8:

[0849] The server records a user's activity log for one week and stores it in a database. The activity log records the time and progress of daily tasks. The input is the user's activity data, and the output is the activity log data.

[0850] Step 9:

[0851] At the end of the week, the server analyzes the collected activity logs and generates a weekly activity summary report using a generative AI model. The input is the activity log data, and the output is the generated summary report. A machine learning algorithm is used for the analysis.

[0852] Step 10:

[0853] The generated report is sent from the server to the device, and the device notifies the user of the report contents, such as "This week, three major tasks were completed, and the team's productivity increased by 15%."

[0854] Step 11:

[0855] The user inputs emotional data into the generative AI model, for example, by saying, "I've been feeling very stressed lately and can't concentrate on my work." The input voice data is converted into text data.

[0856] Step 12:

[0857] The device sends this text data to the server, which then analyzes the received emotional data using an emotion engine to evaluate the user's emotional state. The input is the user's emotional data, and the output is the evaluated emotional state.

[0858] Step 13:

[0859] The server generates alerts based on the analysis results if necessary. For example, if the user is judged to be at a high stress level, an alert is generated. The input is the assessed emotional state, and the output is the generated alert.

[0860] Step 14:

[0861] The generated alert is sent from the server to the administrator's terminal, and the administrator takes appropriate action based on the alert. The terminal receives the alert and displays it to the administrator.

[0862] The above processing steps enable efficient management of user goals and monitoring of emotions.

[0863] (Application example 2)

[0864] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0865] Conventional goal management and progress management systems do not monitor or provide feedback that takes into account the user's emotional state, which means they are unable to provide appropriate support even when the user reaches a high stress level. This can lead to long-term declines in productivity and work efficiency. Furthermore, even in factory environments using robots, there is also the issue of overall work efficiency not improving due to the inability to communicate smoothly with workers or manage tasks appropriately.

[0866] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving goals and tasks from the user, means for transmitting the received goals and tasks to the server, means for recognizing the user's emotional state using an emotion engine, means for transmitting the recognized emotional state to the server, means for analyzing the emotion data and generating an alert based on the emotional state, and means for notifying the administrator of the alert. This improves the user's work efficiency and enables appropriate support based on the user's emotional state.

[0867] The "means for receiving goals and tasks from the user" is a mechanism for receiving goals and tasks set by the user through voice input or text input.

[0868] The "means for transmitting received goals and tasks to a server" is a mechanism for transmitting data on goals and tasks received from a user to a server via the Internet or an internal network.

[0869] "Means for setting alarms for goals and tasks on the server" refers to a function for setting alarms for specific dates and times based on goals and tasks received by the server.

[0870] The "means for notifying the user of the set alarm" is a mechanism for sending a notification to the user's terminal at the set alarm date and time, and notifying the user by sound, vibration, or pop-up notification.

[0871] The "means for recognizing the emotional state of the user using an emotion engine" is a function that analyzes the voice or text input by the user and recognizes the emotional state of the user using an emotion engine.

[0872] The "means for transmitting the recognized emotional state to the server" is a mechanism for transmitting data on the user's emotional state recognized by the emotion engine to the server.

[0873] The "means for analyzing emotional data and generating an alert based on the emotional state" is a function that analyzes the emotional data received by the server and generates an alert if a specific emotional state is confirmed.

[0874] The "means for notifying the administrator of the alert" is a mechanism for notifying the administrator of the generated alert on his / her terminal, so that the administrator can take appropriate action.

[0875] The "means for saving user input data on the server" is a function for saving data on goals and tasks entered by the user on the server.

[0876] The "means for generating a confirmation message for saved data" is a function for generating a message for confirming that saving has been successful.

[0877] The "means for notifying the user of a confirmation message" is a mechanism for sending the generated confirmation message to the user terminal and notifying the user.

[0878] The "means for providing feedback to the worker based on the emotional state" is a function for providing appropriate feedback to the worker based on the analyzed emotional state.

[0879] The "means for recording a user's activity log for one week on the server" is a function for recording a user's activity data for one week on the server.

[0880] The "means for analyzing the recorded activity log and generating a weekly review" is a function for analyzing the recorded activity log and generating a weekly review report.

[0881] The "means for notifying the user of the generated weekly review" is a mechanism for sending the generated weekly review report to the user terminal and notifying the user.

[0882] "Means for generating prompt sentences based on one week's activity data and inputting them into the generative AI model" refers to a function that generates prompt sentences for the generative AI model based on one week's activity data and inputs them into the generative AI model.

[0883] This invention is a system for setting user goals, managing progress, and monitoring emotional states. The system consists of a server, a user terminal (a smartphone or personal computer), and a robot. The user interacts with a generative artificial intelligence (generative AI model) through the terminal or robot, and the emotion engine recognizes the user's emotional state and provides appropriate feedback.

[0884] 1. User Interface

[0885] The user sets goals and tasks using a terminal or robot by voice input or text input, and the entered goals and tasks are sent to a server via the Internet.

[0886] 2. Data transmission and storage

[0887] The received goal and task data is sent to the server, which stores the data in a database. If the data is successfully stored, the server generates a confirmation message and sends it to the user's device.

[0888] 3. Alarm settings and notifications

[0889] The server sets an alarm based on the received goals and tasks. The alarm is notified to the user's device or robot at a specific date and time, and the user is notified by sound, vibration, or a pop-up notification.

[0890] 4. Monitoring your emotional state

[0891] When a user interacts with a generative AI model, the emotion engine analyzes the voice and text to recognize the emotional state. The recognized emotional state is sent to the server, which then analyzes the emotional data.

[0892] 5. Alerting and Notification

[0893] Based on the analysis results, the server generates an alert if it determines that support is required. For example, if it determines that a user is at a high stress level, an alert is generated and sent to the administrator's device. The administrator can then take appropriate action based on this alert.

[0894] 6. Activity log and review

[0895] The server records the user's activity log for one week and stores it in a database. At the end of the week, the server analyzes the activity log and generates a weekly review report using a generative AI model. The generated report is sent to the user's device and the user is notified.

[0896] Hardware and software used

[0897] Hardware: Smartphone, personal computer, robot-integrated microphone, speaker, and internet connection

[0898] Software: Python, speech_recognition, pyttsx3, requests, TextBlob

[0899] Specific examples

[0900] For example, if a user says, "I'll rehearse my presentation next Thursday," the speech is converted into text and sent to the server. The server saves the goal data and notifies the user at the specified date and time, saying, "I'll rehearse my presentation tomorrow."

[0901] Furthermore, if a user says, "I've been feeling very stressed lately and can't concentrate on my work," the emotion engine analyzes the situation and confirms the high stress level. The server generates an alert saying, "User A is feeling very stressed," and sends it to the administrator's device. The administrator receives this and follows up with User A.

[0902] Examples of prompts for generative AI models:

[0903] "User set goal: Increase team productivity by 20%, User's emotional state: High stress, Alarm set time: Tomorrow at 2 PM"

[0904] The above is an embodiment of the present invention.

[0905] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0906] Step 1:

[0907] A user sets goals and tasks using a terminal or robot by voice or text input. For example, if a user sets a goal such as "I will rehearse my presentation next Thursday," the terminal receives this voice as text data. In this case, the input is voice data and the output is text data.

[0908] Step 2:

[0909] The device sends the acquired text data to a server via the Internet. Specifically, the device converts the text data into JSON format and sends the data to the server's API endpoint using an HTTP request. Here, the input is the text data and the output is the HTTP request sent to the server.

[0910] Step 3:

[0911] The server analyzes the received goal and task data and saves it in a database. If successful, the server generates a confirmation message and sends it to the terminal. The input is the text data sent to the server, and the output is the saved status in the database and the confirmation message.

[0912] Step 4:

[0913] The server sets an alarm based on the received goals and tasks. For example, it sets a notification for a specific date and time (for example, the day before or the day itself). It analyzes the date and time data of the goals set by the user and determines the alarm setting time. The input is the date and time data of the goals and tasks, and the output is the alarm setting data.

[0914] Step 5:

[0915] The server sends an alarm notification to the device at the set date and time. The device notifies the user of this notification by sound, vibration, or a pop-up notification. The input is the alarm setting data, and the output is the alarm notified to the user.

[0916] Step 6:

[0917] The user interacts with the generative AI model through a device or robot, making statements that express their emotional state. The emotion engine analyzes these statements and recognizes the user's emotional state. For example, if a user says, "I've been feeling very stressed lately and can't concentrate on my work," the emotion engine recognizes this as high stress. The input is the user's utterance data, and the output is the recognized emotion data.

[0918] Step 7:

[0919] The device sends the recognized emotional data to the server. The server analyzes this emotional data and generates an alert if a specific emotional state (e.g., high stress) is confirmed. For example, an alert may be generated stating, "User A is experiencing high stress." The input is the emotional data, and the output is the generated alert.

[0920] Step 8:

[0921] The generated alert is sent from the server to the administrator's terminal. The administrator's terminal displays the alert and supports the administrator in taking appropriate action. The input is the generated alert data, and the output is the alert notified to the administrator's terminal.

[0922] Step 9:

[0923] The server records a week's worth of user activity logs and stores them in a database. The activity logs include the user's goals, task progress, completion time, emotional state, etc. The input is the user activity data, and the output is the stored activity logs.

[0924] Step 10:

[0925] At the end of the week, the server analyzes the activity log and generates a weekly review report using a generative AI model. The report includes a summary of the user's work efficiency and emotional state. The input is the activity log data, and the output is the generated weekly review report.

[0926] Step 11:

[0927] The generated weekly review report is sent to the user terminal. The user terminal notifies the user of this report and displays its contents. The input is the generated report, and the output is the report notified to the user.

[0928] Step 12:

[0929] A prompt sentence is generated based on one week's activity data and input into the generative AI model. The generative AI model uses this prompt sentence to generate improvement suggestions and advice on setting goals for the next week. For example, a prompt sentence such as "User-set goal: Increase team productivity by 20%, User's emotional state: High stress, Alarm setting time: Tomorrow at 2 p.m." is generated. The input is activity data, and the output is the generated prompt sentence and improvement suggestions.

[0930] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0931] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0932] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0933] [Third embodiment]

[0934] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0935] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0936] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0937] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0938] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0939] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0940] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0941] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0942] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0943] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0944] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0945] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0946] 1. System Configuration

[0947] The system of the present invention is mainly composed of a server and a user terminal (e.g., a smartphone or PC). Through the terminal, the user interacts with "Coach-kun," a generative artificial intelligence (generative AI). Through interaction with Coach-kun, the system is a tool for setting the user's goals and managing their progress.

[0948] 2. Function to receive goals and tasks from users

[0949] The user inputs goals and tasks by speaking to the generative AI using the device. For example, a goal might be set as "rehearsing a presentation next Thursday." The device then sends this goal data to the server.

[0950] 3. Function to send received goals and tasks to the server

[0951] The device formats the information entered by the user and sends it over the Internet or an internal network to a server, which analyzes the data and verifies the objectives and tasks.

[0952] 4. Ability to set alarms for goals and tasks on the server

[0953] The server analyzes the received goal and task data and sets alarms for the goal or task at the appropriate date and time, for example, "to be reminded the day before and the day of a presentation rehearsal."

[0954] 5. Function to notify users of set alarms

[0955] When the set date and time arrives, the server sends a notification to the user's device, which then notifies the user of the alarm with a sound, vibration, or a pop-up notification.

[0956] 6. User data storage function

[0957] The device sends the data entered by the user to the server, which stores it in a database. For example, if a user enters, "My goal this month is to increase my team's productivity by 20%, the server stores this information."

[0958] 7. Data saving confirmation notification function

[0959] If the data is saved successfully, the server generates a confirmation message and sends it to the device, which notifies the user that "the goal has been saved."

[0960] 8. Server activity logging function

[0961] The server records the user's activity log for one week and stores it in a database, including the time it took to complete a task and the progress of that task.

[0962] 9. Activity log analysis function

[0963] At the end of the week, the server analyzes the collected activity logs and uses generative AI to summarize the user's activities over the week and compiles the generated summary into a report.

[0964] 10. Ability to notify users of summary reports

[0965] The generated report is sent from the server to the terminal, and the terminal notifies the user of the report contents, allowing the user to review their activities for the week.

[0966] 11. Sentiment Analysis Function

[0967] The device sends data to a server to analyze the user's emotional state from what they say to the generative AI. For example, if the user says, "I've been feeling very stressed lately and can't concentrate on my work," the server will use the generative AI to analyze that emotional state.

[0968] 12. Alert Generation Function

[0969] The server generates alerts based on the results of emotion analysis. If the stress level is determined to be high, an alert is generated for management.

[0970] 13. Alert notification function

[0971] The generated alerts are sent from the server to the manager's terminal, where they are displayed and the manager is assisted in taking appropriate action.

[0972] Specific examples

[0973] For example, if a user says, "I've been feeling very stressed lately and can't concentrate on my work," the device will send this information to the server. The server will use generative AI to analyze the emotion, and if it determines that the stress level is high, it will send an alert to the manager's device saying, "User A is feeling very stressed." The manager's device will then display this alert, allowing the manager to take appropriate action.

[0974] The above is a description of each function in the embodiment of the present invention.

[0975] The processing flow will be explained below.

[0976] 1. Alarm function processing

[0977] Step 1:

[0978] A user uses a device to input a goal or task into the generative AI, for example, "I'll rehearse my presentation next Thursday."

[0979] Step 2:

[0980] The terminal formats the input target data and transmits it to the server.

[0981] Step 3:

[0982] The server analyzes the received data and checks the content and date / time information of the goals and tasks.

[0983] Step 4:

[0984] The server sets an alarm for the specified date and time, for example, to remind you the day before and the day itself.

[0985] Step 5:

[0986] When the specified date and time arrives, the server will send an alarm notification to the terminal.

[0987] Step 6:

[0988] The device will notify the user of the alarm with a sound, vibration, or pop-up notification.

[0989] 2. Save your goals and feedback

[0990] Step 1:

[0991] The user inputs goals and ideas into the generative AI. For example, "My goal this month is to increase team productivity by 20%."

[0992] Step 2:

[0993] The terminal formats the entered data and sends it to the server.

[0994] Step 3:

[0995] The server stores the received data in a database.

[0996] Step 4:

[0997] Once the save is complete, the server generates a confirmation message and sends it to the device.

[0998] Step 5:

[0999] The device will notify the user with a confirmation message "Goal saved."

[1000] 3. Weekly review summary function

[1001] Step 1:

[1002] The server records a user's activity log for one week and stores it in a database.

[1003] Step 2:

[1004] On weekends, the server analyzes the collected activity logs.

[1005] Step 3:

[1006] The server uses generative AI to summarize activities and generate a weekly review.

[1007] Step 4:

[1008] The server generates a summary report and sends it to the terminal.

[1009] Step 5:

[1010] The terminal notifies the user of the report contents and displays them.

[1011] 4. Alert function

[1012] Step 1:

[1013] The user talks to the generative AI about their feelings and difficulties, for example, saying, "I've been feeling very stressed lately and can't concentrate on my work."

[1014] Step 2:

[1015] The device sends the user's speech to the server.

[1016] Step 3:

[1017] The server uses generative AI to analyze the emotional state from the received data.

[1018] Step 4:

[1019] The server generates an alert based on the results of emotion analysis if it determines that support is required.

[1020] Step 5:

[1021] The server sends an alert to management.

[1022] Step 6:

[1023] The manager's device will display an alert, helping the manager take appropriate action.

[1024] The above are the specific processing steps for each function.

[1025] Example 1

[1026] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1027] In modern society, it is important for users to effectively manage their goals and tasks. It is also necessary to properly understand users' emotional states and provide necessary alerts in advance. However, current systems lack the ability to centrally manage users' goals and analyze their emotions, resulting in a split between task management and responding to changes in emotional states. Furthermore, they lack an alert notification function that allows administrators to provide appropriate follow-up.

[1028] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1029] In this invention, the server includes means for receiving goals and tasks from the user, means for transmitting the received goals and tasks to the server, means for setting an alarm for the goal or task on the server, means for notifying the user of the set alarm, means for analyzing the user's emotional state, means for generating an alert based on the result of the user's emotional analysis, and means for notifying the administrator of the generated alert. This makes it possible to perform user goal management and emotional analysis in an integrated manner, and to generate and provide to the administrator an alarm notification or an alert based on the emotional state at an appropriate time.

[1030] "Means for receiving goals and tasks from a user" refers to an interface that allows a user to input goals and tasks into the system and software for recognizing them.

[1031] "Means for transmitting received goals and tasks to a server" refers to the protocol and communication functions for transferring goal and task data entered by the user to a server via a network.

[1032] "Means for setting goal or task alarms on the server" refers to the software functionality that analyzes the goal or task data received by the server and creates alarms based on corresponding dates, times, and conditions.

[1033] "Means for notifying the user of the set alarm" refers to the communication functions and interface for transmitting the alarm set on the server to the user's device and notifying the user by sound, vibration, pop-up message, etc.

[1034] "Means for analyzing the user's emotional state" refers to generative AI models and natural language processing technologies for analyzing the user's emotional state based on the user's input data.

[1035] "Means for generating alerts based on the results of the user's emotional analysis" refers to the software's functionality for generating alert messages based on the results of the analyzed emotional state, according to stress levels or other emotional states.

[1036] "Means for notifying the administrator of the generated alert" refers to a communication function that sends the generated alert based on the user's emotional state to the administrator's terminal and notifies them so that appropriate follow-up can be carried out.

[1037] 1. System Configuration

[1038] The system of the present invention is primarily composed of a server and a user terminal (e.g., a smartphone or PC). In this system, users set goals and manage progress by interacting with "Coach-kun," a generative AI. It also uses an emotion analysis function to monitor the user's stress level and send alerts to the administrator as necessary.

[1039] 2. Function to receive goals and tasks from users

[1040] The user interactively inputs goals and tasks into the generative AI through the device. For example, the user can set a goal such as "rehearsing a presentation next Thursday." The device is equipped with speech recognition software that converts what the user says into text data. Specific software that can be used is the Google Speech-to-Text API.

[1041] 3. Function to send received goals and tasks to the server

[1042] The device converts the text data into a proprietary format using voice recognition software, then encrypts it for security purposes and sends it to a server over the internet or an internal network using the Transport Layer Security (TLS) protocol.

[1043] 4. Ability to set alarms for goals and tasks on the server

[1044] The server analyzes the received text data and sets an alarm based on the content of the goal or task. For example, it extracts date and time information such as "next Thursday" and sets an alarm. Natural language processing (NLP) technology is used for the analysis, specifically the Python nltk library. A scheduling tool such as a cron job is used to set the alarm.

[1045] 5. Function to notify users of set alarms

[1046] When the set date and time arrives, the server generates a notification message and sends it to the device. The device notifies the user of this message by a pop-up notification, sound, or vibration. Cloud messaging services such as Firebase Cloud Messaging (FCM) can be used for the notification function.

[1047] 6. User data storage function

[1048] The terminal sends the data entered by the user to the server, which stores this data in temporary storage and then stores it permanently using a database management system (DBMS), such as MySQL or PostgreSQL.

[1049] 7. Data saving confirmation notification function

[1050] The server checks whether the data was saved successfully and generates a confirmation message. This message is sent to the device, which notifies the user that the goal has been saved. The communication uses an HTTP response.

[1051] 8. Server activity logging function

[1052] The server keeps a log of users' activities for one week. This log includes the tasks the user has completed and their progress. The log data is stored in a NoSQL database (e.g., MongoDB).

[1053] 9. Activity log analysis function

[1054] At the end of the week, the server analyzes the collected activity logs and uses a generative AI model to summarize the user's activity over the week, using Python data processing libraries (Pandas and Numpy).

[1055] 10. Ability to notify users of summary reports

[1056] The generated report is sent from the server to the device, and the device notifies the user of the report contents via a pop-up notification or email.

[1057] 11. Sentiment Analysis Function

[1058] To perform sentiment analysis of what the user says to the generative AI (e.g., "I've been feeling very stressed lately and can't concentrate on my work"), the device sends the data to a server. The server then uses a generative AI model (e.g., BERT or GPT) to analyze the sentiment. The analysis results identify the user's emotional state.

[1059] 12. Alert Generation Function

[1060] The server generates alerts based on the results of the emotion analysis, if necessary: ​​if a high stress level is detected, an alert message is generated and sent to the administrator.

[1061] 13. Alert notification function

[1062] The server sends an alert message to the administrator's terminal, which displays the alert on its screen to help the administrator take appropriate action.

[1063] Specific examples

[1064] For example, if a user says, "I've been feeling very stressed lately and can't concentrate on my work," the device uses voice recognition software to convert this information into text data and send it to the server. The server then uses a generative AI model to analyze the emotional state. If the server determines that the stress level is high, it sends an alert to the administrator's device stating, "User A is feeling very stressed." The administrator's device then displays this alert, allowing the administrator to take appropriate action.

[1065] The above is a description of each function in the embodiment of the present invention.

[1066] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1067] Step 1:

[1068] The user speaks through the terminal. The user sets a goal, such as "I will rehearse my presentation next Thursday." This information is input as voice.

[1069] Step 2:

[1070] The device uses speech recognition software (e.g., Google Speech-to-Text API) to convert voice data into text data. The input is voice data and the output is text data.

[1071] Step 3:

[1072] The terminal adapts the text data to a proprietary format. At this stage the text data is prepared for further data processing. The input is text data and the output is formatted text data.

[1073] Step 4:

[1074] The terminal encrypts the formatted text data and sends it to the server over the Internet or an internal network. The encryption is performed using the TLS protocol. The input is the formatted text data, and the output is the encrypted data.

[1075] Step 5:

[1076] The server decrypts the received data and uses natural language processing (NLP) techniques to parse the data, for example to extract date and time information such as "next Thursday." The input is the encrypted data, and the output is the parsed date and time information.

[1077] Step 6:

[1078] The server sets an alarm based on the analyzed date and time information using a scheduling tool such as a cron job. The input is the date and time information, and the output is the set alarm.

[1079] Step 7:

[1080] When the set date and time arrives, the server generates a notification message and sends it to the user's terminal. The input is the set alarm, and the output is the notification message.

[1081] Step 8:

[1082] The device notifies the user of the received notification message by pop-up notification, sound, vibration, etc. The input is the notification message, and the output is the notification to the user.

[1083] Step 9:

[1084] The terminal stores all data entered by the user in temporary storage and then sends it to the server, which stores the data persistently using a database management system (e.g., MySQL or PostgreSQL). The input is the user data and the output is the stored data.

[1085] Step 10:

[1086] The server checks whether the data was saved correctly and generates a confirmation message. This message is sent to the user's device, informing the user that "the goal has been saved." The input is the saved data, and the output is the confirmation message.

[1087] Step 11:

[1088] The server records a user's activity log for one week. This log includes the tasks the user has completed and their progress information. The log data is stored in a NoSQL database (e.g., MongoDB). The input is the task data, and the output is the recorded activity log.

[1089] Step 12:

[1090] At the end of the week, the server analyzes the collected activity logs and uses a generative AI model (e.g., GPT-3) to summarize the user's activities for the week. The analysis is performed using Python data processing libraries (Pandas and Numpy). The input is the activity log, and the output is a summary report.

[1091] Step 13:

[1092] The generated report is sent from the server to the terminal, and the terminal notifies the user of the report contents via a pop-up notification, email, etc. The input is a summary report, and the output is a notification to the user.

[1093] Step 14:

[1094] The device sends what the user says to the generative AI to the server for emotion analysis. The input is the user's speech data, and the output is the data sent to the server.

[1095] Step 15:

[1096] The server uses a generative AI model (e.g., BERT or GPT-3) to analyze the user's utterances and identify their emotional state. The input is the utterance data, and the output is the emotion analysis result.

[1097] Step 16:

[1098] The server generates alerts as needed based on the emotion analysis results. If a high stress level is detected, an alert message is generated. The input is the emotion analysis results, and the output is the alert message.

[1099] Step 17:

[1100] The generated alert is sent from the server to the administrator's terminal, where it is displayed. The input is the alert message, and the output is a notification to the administrator.

[1101] The above is a specific description of each processing step in the system of the present invention.

[1102] (Application example 1)

[1103] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1104] Improving work efficiency and providing mental health care for workers at the same time are extremely important in production sites, but it is difficult to achieve these goals simultaneously using conventional methods.In addition, while there is a demand for the introduction of systems that improve the efficiency of work progress and task management, there are not yet enough systems that can analyze the emotional state of workers and take appropriate action based on that.

[1105] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1106] In this invention, the server includes means for receiving goals and tasks from users, means for transmitting the received goals and tasks to the server, means for setting alarms for the goals and tasks on the server, means for notifying the user of the set alarm, means for analyzing the emotional state of factory workers from their input, means for generating alerts based on the emotion analysis results, and means for notifying a manager of the generated alert. This not only improves work efficiency but also supports the mental health of workers.

[1107] The "means for receiving goals and tasks from a user" is an interface for acquiring information on work goals and tasks from factory workers.

[1108] The "means for transmitting the received goal or task to the server" is a mechanism for transferring the information on the acquired goal or task to the server via a data network.

[1109] The "means for setting alarms for goals and tasks on the server" is a program for setting the date and time for reminder notifications for goals and tasks received in the server.

[1110] The "means for notifying the user of the set alarm" is a mechanism for notifying the user terminal at the set date and time.

[1111] The "means for analyzing the emotional state of a factory worker from input" is an algorithm for analyzing the emotional state of a factory worker from the voice uttered by the worker or the text data entered by the worker.

[1112] The "means for generating an alert based on the results of emotion analysis" is a mechanism that generates a warning when high stress, etc. is detected based on the results of emotion analysis.

[1113] The "means for notifying the manager of the generated alert" is a mechanism for sending the generated warning to the manager of the factory and prompting him to take action.

[1114] This invention is a system that enables factory workers and managers to set goals and tasks, manage progress, and analyze workers' emotional states to take appropriate action. The system consists of a user terminal and a server, and realizes each function using a generative AI model.

[1115] The system program works as follows:

[1116] Receive and send goals and tasks

[1117] The user device receives voice or text input of goals and tasks set by factory workers, such as "inspect the machine next Monday." This data is analyzed and formatted using a generative AI model and then sent to a server over the internet or an internal network.

[1118] Processing on the server

[1119] The server analyzes the received goal and task data and sets reminders for the appropriate dates and times. For example, if you set "machine inspection next Monday," reminders are set for the day before and the day itself.

[1120] Notification function

[1121] When the set reminder date and time arrives, the server sends a notification to the user's device, which then notifies the worker of this notification as a pop-up or audio alarm, urging them to complete the task without forgetting.

[1122] Saving and checking data

[1123] The goal and task data entered by the user is saved in the server's database. Once the saving is complete, the server generates a confirmation message and sends it to the user's terminal. The user's terminal then notifies the worker of the message "Task saved" and asks them to confirm that the data has been saved correctly.

[1124] Sentiment analysis and alert generation

[1125] The user device receives the worker's voice input and text data and sends it to the server. The server uses a generative AI model to analyze the worker's emotional state. For example, if a worker inputs, "I've been feeling very stressed recently and can't concentrate on my work," the emotional state is determined to be high stress. In this case, the server generates and sends an alert to the manager stating, "The worker is feeling high stress." The manager can receive this alert and take appropriate action.

[1126] Examples and prompts

[1127] For example, if a worker specifies "I will inspect the machine next Monday," the system will analyze that data, set a reminder, and send a notification. Also, if a worker specifies "I've been feeling very stressed lately and can't concentrate on my work," the system will analyze that emotion and send an alert to the manager.

[1128] Example prompt sentence:

[1129] "Please set a task to inspect the machine next Monday."

[1130] "I've been feeling very stressed lately and can't concentrate on my work."

[1131] In this way, the present invention can improve the work efficiency of a factory while also providing mental health care for workers.

[1132] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1133] Step 1:

[1134] The user inputs their goals and tasks into the device using voice or text. The input data is passed to the generative AI model, which analyzes the content of the goals and tasks. The generative AI model then formats the data and converts it into a format that can be sent to the server.

[1135] Input: Worker inputs by voice or text, "I will inspect the machine next Monday."

[1136] Output: Formatted goal and task data

[1137] Step 2:

[1138] The device sends formatted goal and task data to the server, which verifies the received data and stores it in a database. If the data is successfully stored, the server generates a confirmation message and sends it to the device.

[1139] Input: Formatted goal and task data

[1140] Output: Confirmation message "Task saved"

[1141] Step 3:

[1142] The server analyzes the received goal and task data and sets reminder notifications at appropriate dates and times. Specifically, it generates a schedule of reminder notifications for the previous day and the current day based on the date and time information of the goal or task.

[1143] Input: Goal and task data stored in the database

[1144] Output: Scheduled date and time of the reminder notification

[1145] Step 4:

[1146] When the set reminder date and time arrives, the server sends a reminder notification to the terminal, which then notifies the worker as a pop-up or audio alarm.

[1147] Input: Scheduled date and time of the reminder notification

[1148] Output: Pop-up notification and audio alarm

[1149] Step 5:

[1150] The user device receives the worker's voice input and text data and sends it to the server, which uses a generative AI model to analyze the data and evaluate the worker's emotional state. If high stress is detected, an alert is generated.

[1151] Input: Worker's voice input or text data (e.g., "I've been feeling very stressed lately and can't concentrate on my work.")

[1152] Output: Sentiment analysis results and alert information

[1153] Step 6:

[1154] The server notifies the administrator of the generated alert, and the alert information is sent to the administrator's terminal, helping the administrator to take appropriate action.

[1155] Input: Alert information

[1156] Output: Alert notification to administrator

[1157] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1158] 1. System Configuration

[1159] This invention is a system for setting user goals, managing progress, and monitoring emotional states. The system mainly consists of a server and a user device (smartphone or PC). Users interact with a generative artificial intelligence (generative AI) through the device, and an emotion engine is used to recognize their emotional state and provide appropriate feedback.

[1160] 2. Function to receive goals and tasks from users

[1161] The user inputs goals and tasks by speaking to the generative AI using the device. For example, the user might set a goal such as "rehearsing a presentation next Thursday." The device then sends this goal data to the server.

[1162] 3. Function to send received goals and tasks to the server

[1163] The terminal formats the entered goal data and sends it to a server via the Internet or an internal network. The server analyzes the received data and verifies the goal or task.

[1164] 4. Ability to set alarms for goals and tasks on the server

[1165] The server analyzes the received goal or task data and sets an alarm for the goal or task at the appropriate date and time, for example, setting a reminder for the day before and the day of the goal or task.

[1166] 5. Function to notify users of set alarms

[1167] When the set date and time arrives, the server sends a notification to the user's device. The device notifies the user with an alarm sound, vibration, or a pop-up notification. For example, it may notify the user, "There is a rehearsal for your presentation tomorrow."

[1168] 6. User data storage function

[1169] The device sends the data entered by the user to the server, which stores it in a database. For example, if a user enters "My goal this month is to increase my team's productivity by 20%," the server stores this information in a database.

[1170] 7. Data saving confirmation notification function

[1171] If the data is saved successfully, the server generates a confirmation message and sends it to the device, which notifies the user that the goal has been saved.

[1172] 8. Server activity logging function

[1173] The server records the user's activity log for one week and stores it in a database, including the time it took to complete a task and the progress of that task.

[1174] 9. Activity log analysis function

[1175] At the end of the week, the server analyzes the collected activity logs and uses generative AI to summarize the user's activities over the week and compiles the generated summary into a report.

[1176] 10. Ability to notify users of summary reports

[1177] The generated report is sent from the server to the device, and the device notifies the user of the report contents, for example, "This week, we completed three major tasks, and our team's productivity increased by 15%."

[1178] 11. Emotion recognition function using emotion engine

[1179] The emotion engine recognizes the user's emotional state based on what the user says to the generative AI. For example, if the user says, "I've been feeling very stressed lately and can't concentrate on my work," the device will send this information to the server.

[1180] 12. Emotion data analysis function

[1181] The server analyzes the received emotional data and provides a detailed assessment of the user's emotional state, identifying high stress levels and other emotional states.

[1182] 13. Alert Generation Function

[1183] Based on the sentiment analysis results, the server generates an alert if it determines that support is needed, for example, if it determines that the user is experiencing high stress levels.

[1184] 14. Alert notification function

[1185] The generated alerts are sent from the server to the manager's terminal, where they are displayed. The manager is supported to take appropriate action based on the alerts.

[1186] Specific examples

[1187] For example, if a user says, "I've been feeling very stressed lately and can't concentrate on my work," the device will send this data to the server. The server will analyze it using an emotion engine and confirm the high stress level. Based on the judgment, it will generate an alert saying, "User A is feeling very stressed," and send it to the manager's device. The manager will receive this alert and can follow up with User A.

[1188] The above is a detailed description of each function in the embodiment of the present invention.

[1189] The processing flow will be explained below.

[1190] Goal and task management features

[1191] Step 1:

[1192] A user uses a device to input a goal or task into the generative AI, for example, "I'll rehearse my presentation next Thursday."

[1193] Step 2:

[1194] The terminal formats the input target data and transmits it to the server.

[1195] Step 3:

[1196] The server analyzes the received data and checks the content and date / time information of the goals and tasks.

[1197] Step 4:

[1198] The server sets an alarm for the specified date and time, for example, to remind you the day before and the day itself.

[1199] Step 5:

[1200] When the specified date and time arrives, the server will send an alarm notification to the terminal.

[1201] Step 6:

[1202] The device will notify the user of the alarm with a sound, vibration, or pop-up notification.

[1203] Data storage function

[1204] Step 1:

[1205] The user inputs goals and ideas into the generative AI. For example, "My goal this month is to increase team productivity by 20%."

[1206] Step 2:

[1207] The terminal formats the entered data and sends it to the server.

[1208] Step 3:

[1209] The server stores the received data in a database.

[1210] Step 4:

[1211] Once the save is complete, the server generates a confirmation message and sends it to the device.

[1212] Step 5:

[1213] The device will notify the user with a confirmation message "Goal saved."

[1214] Weekly review function

[1215] Step 1:

[1216] The server records a user's activity log for one week and stores it in a database.

[1217] Step 2:

[1218] On weekends, the server analyzes the collected activity logs.

[1219] Step 3:

[1220] The server uses generative AI to summarize activities and generate a weekly review.

[1221] Step 4:

[1222] The server generates a summary report and sends it to the terminal.

[1223] Step 5:

[1224] The terminal notifies the user of the report contents and displays them.

[1225] Emotion recognition function using emotion engine

[1226] Step 1:

[1227] The user inputs dialogue into the generative AI, for example, saying, "I've been feeling very stressed lately and can't concentrate on my work."

[1228] Step 2:

[1229] The terminal transmits the input dialogue content to the server.

[1230] Step 3:

[1231] The server uses an emotion engine to analyze the content of the user's dialogue and recognize the user's emotional state.

[1232] Step 4:

[1233] The server evaluates the recognized emotional data and detects abnormalities such as high stress levels.

[1234] Alerting and Notification

[1235] Step 1:

[1236] The server generates an alert based on the analysis results of the emotion engine when it determines that support is required.

[1237] Step 2:

[1238] The server sends the generated alert to the manager's terminal.

[1239] Step 3:

[1240] The manager's device will display an alert, helping the manager take appropriate action.

[1241] Specific examples

[1242] 1. The user tells the generative AI, "I've been feeling very stressed lately and can't concentrate on my work."

[1243] 2. The device sends the conversation content to the server.

[1244] 3. The server uses an emotion engine to analyze the content of the conversation and determine that the stress level is high.

[1245] 4. The server generates an alert saying "User A is experiencing high stress."

[1246] 5. The server sends an alert to the manager's terminal.

[1247] 6. The manager's device displays an alert and the manager follows up with User A.

[1248] The above are the specific processing steps of each function in the embodiment of the present invention in which an emotion engine is combined.

[1249] Example 2

[1250] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1251] While conventional goal management systems can manage the goals and tasks entered by users, they lack the ability to grasp the user's emotional state in real time and provide appropriate feedback and support as needed. As a result, users who are particularly stressed may not receive the support they need, which can lead to a decline in productivity and mental health. Furthermore, the lack of analysis of activity logs and feedback on goal achievement makes it difficult for users to create specific plans for self-improvement.

[1252] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for receiving goals and tasks from the user, means for transmitting the received goals and tasks to the server, means for setting alarms for the goals and tasks on the server, means for notifying the user of the set alarm, means for transmitting emotional data entered by the user to the server, means for the server to analyze the emotional data using an emotion engine and evaluate the user's emotional state, means for the server to generate an alert if necessary based on the analysis results, and means for notifying the administrator's terminal of the generated alert. This enables progress management of the goals and tasks set by the user, as well as monitoring of the emotional state and providing appropriate feedback. Furthermore, adding a function for analyzing a one-week activity log and providing feedback based on the log allows the user to create a specific action plan for self-improvement and improve overall performance.

[1253] "Goals and tasks" refer to the objectives that a user is trying to achieve or the specific work that needs to be done.

[1254] "User" refers to a person who uses this system to set goals, manage progress, and monitor emotions.

[1255] The "means for receiving" refers to a process or device by which the terminal acquires data on goals or tasks input by the user.

[1256] "Means for transmitting" refers to the process or device for sending received data from the terminal to the server and communicating.

[1257] "Server" refers to a central computing device for analyzing, storing, and managing received data.

[1258] "Means for setting an alarm" refers to a mechanism or device for sending a notification based on a specified date, time, or conditions.

[1259] "Means for notifying" refers to a device or process for notifying a user or administrator of configured alarms or confirmation messages.

[1260] "Emotion data" is data that indicates the user's emotional state, and includes psychological factors such as stress and satisfaction.

[1261] An "emotion engine" refers to software or algorithms that analyze emotional data and assess a user's emotional state.

[1262] "Means for generating alerts" refers to a mechanism or device that generates warnings or notifications when certain conditions are met based on the results of analyzing emotional data.

[1263] "Administrator" refers to a person whose job is to operate this system and support users.

[1264] An "activity log" refers to data that records a user's daily activities and task progress.

[1265] "Weekly Review" refers to a report that analyzes recorded activity logs and summarizes the user's actions and achievements over the week.

[1266] This invention is a system that manages the goals and tasks set by the user and monitors the emotional state. This system is mainly composed of a server and a user terminal (smartphone or PC).

[1267] System Configuration

[1268] Users can interact with the generative AI model through their device and receive appropriate feedback and recognition of their emotional state using the emotion engine.

[1269] Entering goals and tasks

[1270] Using a smartphone or PC, a user speaks to the generative AI model about their goals and tasks. For example, they might set a goal like "I'll rehearse my presentation next Thursday." The device then converts this goal data from speech to text and sends it to the server.

[1271] Receiving data and setting alarms

[1272] The server analyzes the received goal and task data and checks the details. Once the analysis is complete, an alarm is set for the appropriate date and time according to the goal. For example, it can set a reminder for the day before and the day itself.

[1273] Alarm notifications

[1274] When the set date and time arrives, the server sends a notification to the user's device. The device notifies the user of this notification by sound, vibration, or a pop-up notification. For example, it may notify the user that "there is a rehearsal for the presentation tomorrow."

[1275] User Data Storage

[1276] The device sends data on the goals and tasks set by the user to the server, which then stores the data in a database. For example, if a user enters "This month's goal is to increase team productivity by 20%, that information is stored.

[1277] Data storage confirmation notice

[1278] When the server confirms that the data has been saved successfully, it generates a confirmation message and sends it to the device, which then notifies the user that "the goal has been saved."

[1279] Activity log recording and analysis

[1280] The server records the user's activity log for the week and stores it in a database. For example, it records the time the user completed tasks and their progress. At the end of the week, the server analyzes the collected activity log using a generative AI model and generates a report summarizing the week's activities. The server then sends the generated report to the device, and the device notifies the user. For example, the server may inform the user that "three major tasks were completed this week, increasing the team's productivity by 15%."

[1281] Emotional state recognition and alert generation

[1282] The emotion engine recognizes the user's emotional state based on what the user says to the generative AI model. For example, if the user says, "I've been feeling very stressed lately and can't concentrate on my work," the device sends this information to the server. The server analyzes the emotional data and evaluates high stress levels and other emotional states. Based on the analysis results, the server generates an alert if necessary and notifies the administrator's device. The administrator can then take appropriate action based on this alert.

[1283] Specific examples

[1284] For example, if a user says, "I've been feeling very stressed lately and can't concentrate on my work," the device will send this data to the server. The server will analyze it using an emotion engine and confirm the high stress level. Based on the judgment, it will generate an alert saying, "User A is feeling very stressed," and send it to the administrator's device. The administrator will receive this alert and can follow up with User A.

[1285] The above is a detailed description of each function in the embodiment of the present invention. By using this system, users can efficiently manage their goals and monitor their emotions.

[1286] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1287] Step 1:

[1288] The user speaks to the generative AI model about their goals and tasks. For example, they can input a goal like "I'll rehearse my presentation next Thursday." The input voice data is then converted into text data.

[1289] Step 2:

[1290] The device receives the converted text data, formats it, and sends it to the server. Specifically, the voice data is recognized as text and sent to the server as target data, such as "I will rehearse the presentation next Thursday." In this process, a voice recognition algorithm is used to convert the voice to text.

[1291] Step 3:

[1292] The server analyzes the received goal data and checks its contents. After receiving the user's goal data, the server passes it to the analysis engine, which extracts the goal date and content. For example, the server analyzes the date and time information, such as "next Thursday," and the task content, such as "rehearse the presentation."

[1293] Step 4:

[1294] The server sets alarms for goals and tasks based on the analyzed date information. Specifically, it sets the data to set reminder alarms for the day before and the day of the goal, and sets notifications to be sent at the appropriate date and time. The input is the analyzed goal data, and the output is the set alarm information.

[1295] Step 5:

[1296] When the set date and time arrives, the server sends a notification to the user device. For example, notification data such as "There is a presentation rehearsal tomorrow" is generated and sent to the user device. The device receives this notification data and notifies the user with a sound, vibration, or pop-up notification.

[1297] Step 6:

[1298] The data of the goals and tasks set by the user is sent from the terminal to the server and saved in the database. When saving to the database, the input is the goal data set by the user, and the output is save confirmation information.

[1299] Step 7:

[1300] When the server confirms that the data has been saved successfully, it generates a confirmation message and sends it to the device. The device receives this confirmation message and notifies the user that "the goal has been saved." In the confirmation message generation process, the confirmation message is created using the ID of the saved data.

[1301] Step 8:

[1302] The server records a user's activity log for one week and stores it in a database. The activity log records the time and progress of daily tasks. The input is the user's activity data, and the output is the activity log data.

[1303] Step 9:

[1304] At the end of the week, the server analyzes the collected activity logs and generates a weekly activity summary report using a generative AI model. The input is the activity log data, and the output is the generated summary report. A machine learning algorithm is used for the analysis.

[1305] Step 10:

[1306] The generated report is sent from the server to the device, and the device notifies the user of the report contents, such as "This week, three major tasks were completed, and the team's productivity increased by 15%."

[1307] Step 11:

[1308] The user inputs emotional data into the generative AI model, for example, by saying, "I've been feeling very stressed lately and can't concentrate on my work." The input voice data is converted into text data.

[1309] Step 12:

[1310] The device sends this text data to the server, which then analyzes the received emotional data using an emotion engine to evaluate the user's emotional state. The input is the user's emotional data, and the output is the evaluated emotional state.

[1311] Step 13:

[1312] The server generates alerts based on the analysis results if necessary. For example, if the user is judged to be at a high stress level, an alert is generated. The input is the assessed emotional state, and the output is the generated alert.

[1313] Step 14:

[1314] The generated alert is sent from the server to the administrator's terminal, and the administrator takes appropriate action based on the alert. The terminal receives the alert and displays it to the administrator.

[1315] The above processing steps enable efficient management of user goals and monitoring of emotions.

[1316] (Application example 2)

[1317] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1318] Conventional goal management and progress management systems do not monitor or provide feedback that takes into account the user's emotional state, which means they are unable to provide appropriate support even when the user reaches a high stress level. This can lead to long-term declines in productivity and work efficiency. Furthermore, even in factory environments using robots, there is also the issue of overall work efficiency not improving due to the inability to communicate smoothly with workers or manage tasks appropriately.

[1319] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving goals and tasks from the user, means for transmitting the received goals and tasks to the server, means for recognizing the user's emotional state using an emotion engine, means for transmitting the recognized emotional state to the server, means for analyzing the emotion data and generating an alert based on the emotional state, and means for notifying the administrator of the alert. This improves the user's work efficiency and enables appropriate support based on the user's emotional state.

[1320] The "means for receiving goals and tasks from the user" is a mechanism for receiving goals and tasks set by the user through voice input or text input.

[1321] The "means for transmitting received goals and tasks to a server" is a mechanism for transmitting data on goals and tasks received from a user to a server via the Internet or an internal network.

[1322] "Means for setting alarms for goals and tasks on the server" refers to a function for setting alarms for specific dates and times based on goals and tasks received by the server.

[1323] The "means for notifying the user of the set alarm" is a mechanism for sending a notification to the user's terminal at the set alarm date and time, and notifying the user by sound, vibration, or pop-up notification.

[1324] The "means for recognizing the emotional state of the user using an emotion engine" is a function that analyzes the voice or text input by the user and recognizes the emotional state of the user using an emotion engine.

[1325] The "means for transmitting the recognized emotional state to the server" is a mechanism for transmitting data on the user's emotional state recognized by the emotion engine to the server.

[1326] The "means for analyzing emotional data and generating an alert based on the emotional state" is a function that analyzes the emotional data received by the server and generates an alert if a specific emotional state is confirmed.

[1327] The "means for notifying the administrator of the alert" is a mechanism for notifying the administrator of the generated alert on his / her terminal, so that the administrator can take appropriate action.

[1328] The "means for saving user input data on the server" is a function for saving data on goals and tasks entered by the user on the server.

[1329] The "means for generating a confirmation message for saved data" is a function for generating a message for confirming that saving has been successful.

[1330] The "means for notifying the user of a confirmation message" is a mechanism for sending the generated confirmation message to the user terminal and notifying the user.

[1331] The "means for providing feedback to the worker based on the emotional state" is a function for providing appropriate feedback to the worker based on the analyzed emotional state.

[1332] The "means for recording a user's activity log for one week on the server" is a function for recording a user's activity data for one week on the server.

[1333] The "means for analyzing the recorded activity log and generating a weekly review" is a function for analyzing the recorded activity log and generating a weekly review report.

[1334] The "means for notifying the user of the generated weekly review" is a mechanism for sending the generated weekly review report to the user terminal and notifying the user.

[1335] "Means for generating prompt sentences based on one week's activity data and inputting them into the generative AI model" refers to a function that generates prompt sentences for the generative AI model based on one week's activity data and inputs them into the generative AI model.

[1336] This invention is a system for setting user goals, managing progress, and monitoring emotional states. The system consists of a server, a user terminal (a smartphone or personal computer), and a robot. The user interacts with a generative artificial intelligence (generative AI model) through the terminal or robot, and the emotion engine recognizes the user's emotional state and provides appropriate feedback.

[1337] 1. User Interface

[1338] The user sets goals and tasks using a terminal or robot by voice input or text input, and the entered goals and tasks are sent to a server via the Internet.

[1339] 2. Data transmission and storage

[1340] The received goal and task data is sent to the server, which stores the data in a database. If the data is successfully stored, the server generates a confirmation message and sends it to the user's device.

[1341] 3. Alarm settings and notifications

[1342] The server sets an alarm based on the received goals and tasks. The alarm is notified to the user's device or robot at a specific date and time, and the user is notified by sound, vibration, or a pop-up notification.

[1343] 4. Monitoring your emotional state

[1344] When a user interacts with a generative AI model, the emotion engine analyzes the voice and text to recognize the emotional state. The recognized emotional state is sent to the server, which then analyzes the emotional data.

[1345] 5. Alerting and Notification

[1346] Based on the analysis results, the server generates an alert if it determines that support is required. For example, if it determines that a user is at a high stress level, an alert is generated and sent to the administrator's device. The administrator can then take appropriate action based on this alert.

[1347] 6. Activity log and review

[1348] The server records the user's activity log for one week and stores it in a database. At the end of the week, the server analyzes the activity log and generates a weekly review report using a generative AI model. The generated report is sent to the user's device and the user is notified.

[1349] Hardware and software used

[1350] Hardware: Smartphone, personal computer, robot-integrated microphone, speaker, and internet connection

[1351] Software: Python, speech_recognition, pyttsx3, requests, TextBlob

[1352] Specific examples

[1353] For example, if a user says, "I'll rehearse my presentation next Thursday," the speech is converted into text and sent to the server. The server saves the goal data and notifies the user at the specified date and time, saying, "I'll rehearse my presentation tomorrow."

[1354] Furthermore, if a user says, "I've been feeling very stressed lately and can't concentrate on my work," the emotion engine analyzes the situation and confirms the high stress level. The server generates an alert saying, "User A is feeling very stressed," and sends it to the administrator's device. The administrator receives this and follows up with User A.

[1355] Examples of prompts for generative AI models:

[1356] "User set goal: Increase team productivity by 20%, User's emotional state: High stress, Alarm set time: Tomorrow at 2 PM"

[1357] The above is an embodiment of the present invention.

[1358] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1359] Step 1:

[1360] A user sets goals and tasks using a terminal or robot by voice or text input. For example, if a user sets a goal such as "I will rehearse my presentation next Thursday," the terminal receives this voice as text data. In this case, the input is voice data and the output is text data.

[1361] Step 2:

[1362] The device sends the acquired text data to a server via the Internet. Specifically, the device converts the text data into JSON format and sends the data to the server's API endpoint using an HTTP request. Here, the input is the text data and the output is the HTTP request sent to the server.

[1363] Step 3:

[1364] The server analyzes the received goal and task data and saves it in a database. If successful, the server generates a confirmation message and sends it to the terminal. The input is the text data sent to the server, and the output is the saved status in the database and the confirmation message.

[1365] Step 4:

[1366] The server sets an alarm based on the received goals and tasks. For example, it sets a notification for a specific date and time (for example, the day before or the day itself). It analyzes the date and time data of the goals set by the user and determines the alarm setting time. The input is the date and time data of the goals and tasks, and the output is the alarm setting data.

[1367] Step 5:

[1368] The server sends an alarm notification to the device at the set date and time. The device notifies the user of this notification by sound, vibration, or a pop-up notification. The input is the alarm setting data, and the output is the alarm notified to the user.

[1369] Step 6:

[1370] The user interacts with the generative AI model through a device or robot, making statements that express their emotional state. The emotion engine analyzes these statements and recognizes the user's emotional state. For example, if a user says, "I've been feeling very stressed lately and can't concentrate on my work," the emotion engine recognizes this as high stress. The input is the user's utterance data, and the output is the recognized emotion data.

[1371] Step 7:

[1372] The device sends the recognized emotional data to the server. The server analyzes this emotional data and generates an alert if a specific emotional state (e.g., high stress) is confirmed. For example, an alert may be generated stating, "User A is experiencing high stress." The input is the emotional data, and the output is the generated alert.

[1373] Step 8:

[1374] The generated alert is sent from the server to the administrator's terminal. The administrator's terminal displays the alert and supports the administrator in taking appropriate action. The input is the generated alert data, and the output is the alert notified to the administrator's terminal.

[1375] Step 9:

[1376] The server records a week's worth of user activity logs and stores them in a database. The activity logs include the user's goals, task progress, completion time, emotional state, etc. The input is the user activity data, and the output is the stored activity logs.

[1377] Step 10:

[1378] At the end of the week, the server analyzes the activity log and generates a weekly review report using a generative AI model. The report includes a summary of the user's work efficiency and emotional state. The input is the activity log data, and the output is the generated weekly review report.

[1379] Step 11:

[1380] The generated weekly review report is sent to the user terminal. The user terminal notifies the user of this report and displays its contents. The input is the generated report, and the output is the report notified to the user.

[1381] Step 12:

[1382] A prompt sentence is generated based on one week's activity data and input into the generative AI model. The generative AI model uses this prompt sentence to generate improvement suggestions and advice on setting goals for the next week. For example, a prompt sentence such as "User-set goal: Increase team productivity by 20%, User's emotional state: High stress, Alarm setting time: Tomorrow at 2 p.m." is generated. The input is activity data, and the output is the generated prompt sentence and improvement suggestions.

[1383] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1384] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1385] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1386] [Fourth embodiment]

[1387] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1388] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1389] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1390] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1391] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1392] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1393] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1394] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1395] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1396] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1397] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1398] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1399] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1400] 1. System Configuration

[1401] The system of the present invention is mainly composed of a server and a user terminal (e.g., a smartphone or PC). Through the terminal, the user interacts with "Coach-kun," a generative artificial intelligence (generative AI). Through interaction with Coach-kun, the system is a tool for setting the user's goals and managing their progress.

[1402] 2. Function to receive goals and tasks from users

[1403] The user inputs goals and tasks by speaking to the generative AI using the device. For example, a goal might be set as "rehearsing a presentation next Thursday." The device then sends this goal data to the server.

[1404] 3. Function to send received goals and tasks to the server

[1405] The device formats the information entered by the user and sends it over the Internet or an internal network to a server, which analyzes the data and verifies the objectives and tasks.

[1406] 4. Ability to set alarms for goals and tasks on the server

[1407] The server analyzes the received goal and task data and sets alarms for the goal or task at the appropriate date and time, for example, "to be reminded the day before and the day of a presentation rehearsal."

[1408] 5. Function to notify users of set alarms

[1409] When the set date and time arrives, the server sends a notification to the user's device, which then notifies the user of the alarm with a sound, vibration, or a pop-up notification.

[1410] 6. User data storage function

[1411] The device sends the data entered by the user to the server, which stores it in a database. For example, if a user enters, "My goal this month is to increase my team's productivity by 20%, the server stores this information."

[1412] 7. Data saving confirmation notification function

[1413] If the data is saved successfully, the server generates a confirmation message and sends it to the device, which notifies the user that "the goal has been saved."

[1414] 8. Server activity logging function

[1415] The server records the user's activity log for one week and stores it in a database, including the time it took to complete a task and the progress of that task.

[1416] 9. Activity log analysis function

[1417] At the end of the week, the server analyzes the collected activity logs and uses generative AI to summarize the user's activities over the week and compiles the generated summary into a report.

[1418] 10. Ability to notify users of summary reports

[1419] The generated report is sent from the server to the terminal, and the terminal notifies the user of the report contents, allowing the user to review their activities for the week.

[1420] 11. Sentiment Analysis Function

[1421] The device sends data to a server to analyze the user's emotional state from what they say to the generative AI. For example, if the user says, "I've been feeling very stressed lately and can't concentrate on my work," the server will use the generative AI to analyze that emotional state.

[1422] 12. Alert Generation Function

[1423] The server generates alerts based on the results of emotion analysis. If the stress level is determined to be high, an alert is generated for management.

[1424] 13. Alert notification function

[1425] The generated alerts are sent from the server to the manager's terminal, where they are displayed and the manager is assisted in taking appropriate action.

[1426] Specific examples

[1427] For example, if a user says, "I've been feeling very stressed lately and can't concentrate on my work," the device will send this information to the server. The server will use generative AI to analyze the emotion, and if it determines that the stress level is high, it will send an alert to the manager's device saying, "User A is feeling very stressed." The manager's device will then display this alert, allowing the manager to take appropriate action.

[1428] The above is a description of each function in the embodiment of the present invention.

[1429] The processing flow will be explained below.

[1430] 1. Alarm function processing

[1431] Step 1:

[1432] A user uses a device to input a goal or task into the generative AI, for example, "I'll rehearse my presentation next Thursday."

[1433] Step 2:

[1434] The terminal formats the input target data and transmits it to the server.

[1435] Step 3:

[1436] The server analyzes the received data and checks the content and date / time information of the goals and tasks.

[1437] Step 4:

[1438] The server sets an alarm for the specified date and time, for example, to remind you the day before and the day itself.

[1439] Step 5:

[1440] When the specified date and time arrives, the server will send an alarm notification to the terminal.

[1441] Step 6:

[1442] The device will notify the user of the alarm with a sound, vibration, or pop-up notification.

[1443] 2. Save your goals and feedback

[1444] Step 1:

[1445] The user inputs goals and ideas into the generative AI. For example, "My goal this month is to increase team productivity by 20%."

[1446] Step 2:

[1447] The terminal formats the entered data and sends it to the server.

[1448] Step 3:

[1449] The server stores the received data in a database.

[1450] Step 4:

[1451] Once the save is complete, the server generates a confirmation message and sends it to the device.

[1452] Step 5:

[1453] The device will notify the user with a confirmation message "Goal saved."

[1454] 3. Weekly review summary function

[1455] Step 1:

[1456] The server records a user's activity log for one week and stores it in a database.

[1457] Step 2:

[1458] On weekends, the server analyzes the collected activity logs.

[1459] Step 3:

[1460] The server uses generative AI to summarize activities and generate a weekly review.

[1461] Step 4:

[1462] The server generates a summary report and sends it to the terminal.

[1463] Step 5:

[1464] The terminal notifies the user of the report contents and displays them.

[1465] 4. Alert function

[1466] Step 1:

[1467] The user talks to the generative AI about their feelings and difficulties, for example, saying, "I've been feeling very stressed lately and can't concentrate on my work."

[1468] Step 2:

[1469] The device sends the user's speech to the server.

[1470] Step 3:

[1471] The server uses generative AI to analyze the emotional state from the received data.

[1472] Step 4:

[1473] The server generates an alert based on the results of emotion analysis if it determines that support is required.

[1474] Step 5:

[1475] The server sends an alert to management.

[1476] Step 6:

[1477] The manager's device will display an alert, helping the manager take appropriate action.

[1478] The above are the specific processing steps for each function.

[1479] Example 1

[1480] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1481] In modern society, it is important for users to effectively manage their goals and tasks. It is also necessary to properly understand users' emotional states and provide necessary alerts in advance. However, current systems lack the ability to centrally manage users' goals and analyze their emotions, resulting in a split between task management and responding to changes in emotional states. Furthermore, they lack an alert notification function that allows administrators to provide appropriate follow-up.

[1482] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1483] In this invention, the server includes means for receiving goals and tasks from the user, means for transmitting the received goals and tasks to the server, means for setting an alarm for the goal or task on the server, means for notifying the user of the set alarm, means for analyzing the user's emotional state, means for generating an alert based on the result of the user's emotional analysis, and means for notifying the administrator of the generated alert. This makes it possible to perform user goal management and emotional analysis in an integrated manner, and to generate and provide to the administrator an alarm notification or an alert based on the emotional state at an appropriate time.

[1484] "Means for receiving goals and tasks from a user" refers to an interface that allows a user to input goals and tasks into the system and software for recognizing them.

[1485] "Means for transmitting received goals and tasks to a server" refers to the protocol and communication functions for transferring goal and task data entered by the user to a server via a network.

[1486] "Means for setting goal or task alarms on the server" refers to the software functionality that analyzes the goal or task data received by the server and creates alarms based on corresponding dates, times, and conditions.

[1487] "Means for notifying the user of the set alarm" refers to the communication functions and interface for transmitting the alarm set on the server to the user's device and notifying the user by sound, vibration, pop-up message, etc.

[1488] "Means for analyzing the user's emotional state" refers to generative AI models and natural language processing technologies for analyzing the user's emotional state based on the user's input data.

[1489] "Means for generating alerts based on the results of the user's emotional analysis" refers to the software's functionality for generating alert messages based on the results of the analyzed emotional state, according to stress levels or other emotional states.

[1490] "Means for notifying the administrator of the generated alert" refers to a communication function that sends the generated alert based on the user's emotional state to the administrator's terminal and notifies them so that appropriate follow-up can be carried out.

[1491] 1. System Configuration

[1492] The system of the present invention is primarily composed of a server and a user terminal (e.g., a smartphone or PC). In this system, users set goals and manage progress by interacting with "Coach-kun," a generative AI. It also uses an emotion analysis function to monitor the user's stress level and send alerts to the administrator as necessary.

[1493] 2. Function to receive goals and tasks from users

[1494] The user interactively inputs goals and tasks into the generative AI through the device. For example, the user can set a goal such as "rehearsing a presentation next Thursday." The device is equipped with speech recognition software that converts what the user says into text data. Specific software that can be used is the Google Speech-to-Text API.

[1495] 3. Function to send received goals and tasks to the server

[1496] The device converts the text data into a proprietary format using voice recognition software, then encrypts it for security purposes and sends it to a server over the internet or an internal network using the Transport Layer Security (TLS) protocol.

[1497] 4. Ability to set alarms for goals and tasks on the server

[1498] The server analyzes the received text data and sets an alarm based on the content of the goal or task. For example, it extracts date and time information such as "next Thursday" and sets an alarm. Natural language processing (NLP) technology is used for the analysis, specifically the Python nltk library. A scheduling tool such as a cron job is used to set the alarm.

[1499] 5. Function to notify users of set alarms

[1500] When the set date and time arrives, the server generates a notification message and sends it to the device. The device notifies the user of this message by a pop-up notification, sound, or vibration. Cloud messaging services such as Firebase Cloud Messaging (FCM) can be used for the notification function.

[1501] 6. User data storage function

[1502] The terminal sends the data entered by the user to the server, which stores this data in temporary storage and then stores it permanently using a database management system (DBMS), such as MySQL or PostgreSQL.

[1503] 7. Data saving confirmation notification function

[1504] The server checks whether the data was saved successfully and generates a confirmation message. This message is sent to the device, which notifies the user that the goal has been saved. The communication uses an HTTP response.

[1505] 8. Server activity logging function

[1506] The server keeps a log of users' activities for one week. This log includes the tasks the user has completed and their progress. The log data is stored in a NoSQL database (e.g., MongoDB).

[1507] 9. Activity log analysis function

[1508] At the end of the week, the server analyzes the collected activity logs and uses a generative AI model to summarize the user's activity over the week, using Python data processing libraries (Pandas and Numpy).

[1509] 10. Ability to notify users of summary reports

[1510] The generated report is sent from the server to the device, and the device notifies the user of the report contents via a pop-up notification or email.

[1511] 11. Sentiment Analysis Function

[1512] To perform sentiment analysis of what the user says to the generative AI (e.g., "I've been feeling very stressed lately and can't concentrate on my work"), the device sends the data to a server. The server then uses a generative AI model (e.g., BERT or GPT) to analyze the sentiment. The analysis results identify the user's emotional state.

[1513] 12. Alert Generation Function

[1514] The server generates alerts based on the results of the emotion analysis, if necessary: ​​if a high stress level is detected, an alert message is generated and sent to the administrator.

[1515] 13. Alert notification function

[1516] The server sends an alert message to the administrator's terminal, which displays the alert on its screen to help the administrator take appropriate action.

[1517] Specific examples

[1518] For example, if a user says, "I've been feeling very stressed lately and can't concentrate on my work," the device uses voice recognition software to convert this information into text data and send it to the server. The server then uses a generative AI model to analyze the emotional state. If the server determines that the stress level is high, it sends an alert to the administrator's device stating, "User A is feeling very stressed." The administrator's device then displays this alert, allowing the administrator to take appropriate action.

[1519] The above is a description of each function in the embodiment of the present invention.

[1520] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1521] Step 1:

[1522] The user speaks through the terminal. The user sets a goal, such as "I will rehearse my presentation next Thursday." This information is input as voice.

[1523] Step 2:

[1524] The device uses speech recognition software (e.g., Google Speech-to-Text API) to convert voice data into text data. The input is voice data and the output is text data.

[1525] Step 3:

[1526] The terminal adapts the text data to a proprietary format. At this stage the text data is prepared for further data processing. The input is text data and the output is formatted text data.

[1527] Step 4:

[1528] The terminal encrypts the formatted text data and sends it to the server over the Internet or an internal network. The encryption is performed using the TLS protocol. The input is the formatted text data, and the output is the encrypted data.

[1529] Step 5:

[1530] The server decrypts the received data and uses natural language processing (NLP) techniques to parse the data, for example to extract date and time information such as "next Thursday." The input is the encrypted data, and the output is the parsed date and time information.

[1531] Step 6:

[1532] The server sets an alarm based on the analyzed date and time information using a scheduling tool such as a cron job. The input is the date and time information, and the output is the set alarm.

[1533] Step 7:

[1534] When the set date and time arrives, the server generates a notification message and sends it to the user's terminal. The input is the set alarm, and the output is the notification message.

[1535] Step 8:

[1536] The device notifies the user of the received notification message by pop-up notification, sound, vibration, etc. The input is the notification message, and the output is the notification to the user.

[1537] Step 9:

[1538] The terminal stores all data entered by the user in temporary storage and then sends it to the server, which stores the data persistently using a database management system (e.g., MySQL or PostgreSQL). The input is the user data and the output is the stored data.

[1539] Step 10:

[1540] The server checks whether the data was saved correctly and generates a confirmation message. This message is sent to the user's device, informing the user that "the goal has been saved." The input is the saved data, and the output is the confirmation message.

[1541] Step 11:

[1542] The server records a user's activity log for one week. This log includes the tasks the user has completed and their progress information. The log data is stored in a NoSQL database (e.g., MongoDB). The input is the task data, and the output is the recorded activity log.

[1543] Step 12:

[1544] At the end of the week, the server analyzes the collected activity logs and uses a generative AI model (e.g., GPT-3) to summarize the user's activities for the week. The analysis is performed using Python data processing libraries (Pandas and Numpy). The input is the activity log, and the output is a summary report.

[1545] Step 13:

[1546] The generated report is sent from the server to the terminal, and the terminal notifies the user of the report contents via a pop-up notification, email, etc. The input is a summary report, and the output is a notification to the user.

[1547] Step 14:

[1548] The device sends what the user says to the generative AI to the server for emotion analysis. The input is the user's speech data, and the output is the data sent to the server.

[1549] Step 15:

[1550] The server uses a generative AI model (e.g., BERT or GPT-3) to analyze the user's utterances and identify their emotional state. The input is the utterance data, and the output is the emotion analysis result.

[1551] Step 16:

[1552] The server generates alerts as needed based on the emotion analysis results. If a high stress level is detected, an alert message is generated. The input is the emotion analysis results, and the output is the alert message.

[1553] Step 17:

[1554] The generated alert is sent from the server to the administrator's terminal, where it is displayed. The input is the alert message, and the output is a notification to the administrator.

[1555] The above is a specific description of each processing step in the system of the present invention.

[1556] (Application example 1)

[1557] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1558] Improving work efficiency and providing mental health care for workers at the same time are extremely important in production sites, but it is difficult to achieve these goals simultaneously using conventional methods.In addition, while there is a demand for the introduction of systems that improve the efficiency of work progress and task management, there are not yet enough systems that can analyze the emotional state of workers and take appropriate action based on that.

[1559] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1560] In this invention, the server includes means for receiving goals and tasks from users, means for transmitting the received goals and tasks to the server, means for setting alarms for the goals and tasks on the server, means for notifying the user of the set alarm, means for analyzing the emotional state of factory workers from their input, means for generating alerts based on the emotion analysis results, and means for notifying a manager of the generated alert. This not only improves work efficiency but also supports the mental health of workers.

[1561] The "means for receiving goals and tasks from a user" is an interface for acquiring information on work goals and tasks from factory workers.

[1562] The "means for transmitting the received goal or task to the server" is a mechanism for transferring the information on the acquired goal or task to the server via a data network.

[1563] The "means for setting alarms for goals and tasks on the server" is a program for setting the date and time for reminder notifications for goals and tasks received in the server.

[1564] The "means for notifying the user of the set alarm" is a mechanism for notifying the user terminal at the set date and time.

[1565] The "means for analyzing the emotional state of a factory worker from input" is an algorithm for analyzing the emotional state of a factory worker from the voice uttered by the worker or the text data entered by the worker.

[1566] The "means for generating an alert based on the results of emotion analysis" is a mechanism that generates a warning when high stress, etc. is detected based on the results of emotion analysis.

[1567] The "means for notifying the manager of the generated alert" is a mechanism for sending the generated warning to the manager of the factory and prompting him to take action.

[1568] This invention is a system that enables factory workers and managers to set goals and tasks, manage progress, and analyze workers' emotional states to take appropriate action. The system consists of a user terminal and a server, and realizes each function using a generative AI model.

[1569] The system program works as follows:

[1570] Receive and send goals and tasks

[1571] The user device receives voice or text input of goals and tasks set by factory workers, such as "inspect the machine next Monday." This data is analyzed and formatted using a generative AI model and then sent to a server over the internet or an internal network.

[1572] Processing on the server

[1573] The server analyzes the received goal and task data and sets reminders for the appropriate dates and times. For example, if you set "machine inspection next Monday," reminders are set for the day before and the day itself.

[1574] Notification function

[1575] When the set reminder date and time arrives, the server sends a notification to the user's device, which then notifies the worker of this notification as a pop-up or audio alarm, urging them to complete the task without forgetting.

[1576] Saving and checking data

[1577] The goal and task data entered by the user is saved in the server's database. Once the saving is complete, the server generates a confirmation message and sends it to the user's terminal. The user's terminal then notifies the worker of the message "Task saved" and asks them to confirm that the data has been saved correctly.

[1578] Sentiment analysis and alert generation

[1579] The user device receives the worker's voice input and text data and sends it to the server. The server uses a generative AI model to analyze the worker's emotional state. For example, if a worker inputs, "I've been feeling very stressed recently and can't concentrate on my work," the emotional state is determined to be high stress. In this case, the server generates and sends an alert to the manager stating, "The worker is feeling high stress." The manager can receive this alert and take appropriate action.

[1580] Examples and prompts

[1581] For example, if a worker specifies "I will inspect the machine next Monday," the system will analyze that data, set a reminder, and send a notification. Also, if a worker specifies "I've been feeling very stressed lately and can't concentrate on my work," the system will analyze that emotion and send an alert to the manager.

[1582] Example prompt sentence:

[1583] "Please set a task to inspect the machine next Monday."

[1584] "I've been feeling very stressed lately and can't concentrate on my work."

[1585] In this way, the present invention can improve the work efficiency of a factory while also providing mental health care for workers.

[1586] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1587] Step 1:

[1588] The user inputs their goals and tasks into the device using voice or text. The input data is passed to the generative AI model, which analyzes the content of the goals and tasks. The generative AI model then formats the data and converts it into a format that can be sent to the server.

[1589] Input: Worker inputs by voice or text, "I will inspect the machine next Monday."

[1590] Output: Formatted goal and task data

[1591] Step 2:

[1592] The device sends formatted goal and task data to the server, which verifies the received data and stores it in a database. If the data is successfully stored, the server generates a confirmation message and sends it to the device.

[1593] Input: Formatted goal and task data

[1594] Output: Confirmation message "Task saved"

[1595] Step 3:

[1596] The server analyzes the received goal and task data and sets reminder notifications at appropriate dates and times. Specifically, it generates a schedule of reminder notifications for the previous day and the current day based on the date and time information of the goal or task.

[1597] Input: Goal and task data stored in the database

[1598] Output: Scheduled date and time of the reminder notification

[1599] Step 4:

[1600] When the set reminder date and time arrives, the server sends a reminder notification to the terminal, which then notifies the worker as a pop-up or audio alarm.

[1601] Input: Scheduled date and time of the reminder notification

[1602] Output: Pop-up notification and audio alarm

[1603] Step 5:

[1604] The user device receives the worker's voice input and text data and sends it to the server, which uses a generative AI model to analyze the data and evaluate the worker's emotional state. If high stress is detected, an alert is generated.

[1605] Input: Worker's voice input or text data (e.g., "I've been feeling very stressed lately and can't concentrate on my work.")

[1606] Output: Sentiment analysis results and alert information

[1607] Step 6:

[1608] The server notifies the administrator of the generated alert, and the alert information is sent to the administrator's terminal, helping the administrator to take appropriate action.

[1609] Input: Alert information

[1610] Output: Alert notification to administrator

[1611] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1612] 1. System Configuration

[1613] This invention is a system for setting user goals, managing progress, and monitoring emotional states. The system mainly consists of a server and a user device (smartphone or PC). Users interact with a generative artificial intelligence (generative AI) through the device, and an emotion engine is used to recognize their emotional state and provide appropriate feedback.

[1614] 2. Function to receive goals and tasks from users

[1615] The user inputs goals and tasks by speaking to the generative AI using the device. For example, the user might set a goal such as "rehearsing a presentation next Thursday." The device then sends this goal data to the server.

[1616] 3. Function to send received goals and tasks to the server

[1617] The terminal formats the entered goal data and sends it to a server via the Internet or an internal network. The server analyzes the received data and verifies the goal or task.

[1618] 4. Ability to set alarms for goals and tasks on the server

[1619] The server analyzes the received goal or task data and sets an alarm for the goal or task at the appropriate date and time, for example, setting a reminder for the day before and the day of the goal or task.

[1620] 5. Function to notify users of set alarms

[1621] When the set date and time arrives, the server sends a notification to the user's device. The device notifies the user with an alarm sound, vibration, or a pop-up notification. For example, it may notify the user, "There is a rehearsal for your presentation tomorrow."

[1622] 6. User data storage function

[1623] The device sends the data entered by the user to the server, which stores it in a database. For example, if a user enters "My goal this month is to increase my team's productivity by 20%," the server stores this information in a database.

[1624] 7. Data saving confirmation notification function

[1625] If the data is saved successfully, the server generates a confirmation message and sends it to the device, which notifies the user that the goal has been saved.

[1626] 8. Server activity logging function

[1627] The server records the user's activity log for one week and stores it in a database, including the time it took to complete a task and the progress of that task.

[1628] 9. Activity log analysis function

[1629] At the end of the week, the server analyzes the collected activity logs and uses generative AI to summarize the user's activities over the week and compiles the generated summary into a report.

[1630] 10. Ability to notify users of summary reports

[1631] The generated report is sent from the server to the device, and the device notifies the user of the report contents, for example, "This week, we completed three major tasks, and our team's productivity increased by 15%."

[1632] 11. Emotion recognition function using emotion engine

[1633] The emotion engine recognizes the user's emotional state based on what the user says to the generative AI. For example, if the user says, "I've been feeling very stressed lately and can't concentrate on my work," the device will send this information to the server.

[1634] 12. Emotion data analysis function

[1635] The server analyzes the received emotional data and provides a detailed assessment of the user's emotional state, identifying high stress levels and other emotional states.

[1636] 13. Alert Generation Function

[1637] Based on the sentiment analysis results, the server generates an alert if it determines that support is needed, for example, if it determines that the user is experiencing high stress levels.

[1638] 14. Alert notification function

[1639] The generated alerts are sent from the server to the manager's terminal, where they are displayed. The manager is supported to take appropriate action based on the alerts.

[1640] Specific examples

[1641] For example, if a user says, "I've been feeling very stressed lately and can't concentrate on my work," the device will send this data to the server. The server will analyze it using an emotion engine and confirm the high stress level. Based on the judgment, it will generate an alert saying, "User A is feeling very stressed," and send it to the manager's device. The manager will receive this alert and can follow up with User A.

[1642] The above is a detailed description of each function in the embodiment of the present invention.

[1643] The processing flow will be explained below.

[1644] Goal and task management features

[1645] Step 1:

[1646] A user uses a device to input a goal or task into the generative AI, for example, "I'll rehearse my presentation next Thursday."

[1647] Step 2:

[1648] The terminal formats the input target data and transmits it to the server.

[1649] Step 3:

[1650] The server analyzes the received data and checks the content and date / time information of the goals and tasks.

[1651] Step 4:

[1652] The server sets an alarm for the specified date and time, for example, to remind you the day before and the day itself.

[1653] Step 5:

[1654] When the specified date and time arrives, the server will send an alarm notification to the terminal.

[1655] Step 6:

[1656] The device will notify the user of the alarm with a sound, vibration, or pop-up notification.

[1657] Data storage function

[1658] Step 1:

[1659] The user inputs goals and ideas into the generative AI. For example, "My goal this month is to increase team productivity by 20%."

[1660] Step 2:

[1661] The terminal formats the entered data and sends it to the server.

[1662] Step 3:

[1663] The server stores the received data in a database.

[1664] Step 4:

[1665] Once the save is complete, the server generates a confirmation message and sends it to the device.

[1666] Step 5:

[1667] The device will notify the user with a confirmation message "Goal saved."

[1668] Weekly review function

[1669] Step 1:

[1670] The server records a user's activity log for one week and stores it in a database.

[1671] Step 2:

[1672] On weekends, the server analyzes the collected activity logs.

[1673] Step 3:

[1674] The server uses generative AI to summarize activities and generate a weekly review.

[1675] Step 4:

[1676] The server generates a summary report and sends it to the terminal.

[1677] Step 5:

[1678] The terminal notifies the user of the report contents and displays them.

[1679] Emotion recognition function using emotion engine

[1680] Step 1:

[1681] The user inputs dialogue into the generative AI, for example, saying, "I've been feeling very stressed lately and can't concentrate on my work."

[1682] Step 2:

[1683] The terminal transmits the input dialogue content to the server.

[1684] Step 3:

[1685] The server uses an emotion engine to analyze the content of the user's dialogue and recognize the user's emotional state.

[1686] Step 4:

[1687] The server evaluates the recognized emotional data and detects abnormalities such as high stress levels.

[1688] Alerting and Notification

[1689] Step 1:

[1690] The server generates an alert based on the analysis results of the emotion engine when it determines that support is required.

[1691] Step 2:

[1692] The server sends the generated alert to the manager's terminal.

[1693] Step 3:

[1694] The manager's device will display an alert, helping the manager take appropriate action.

[1695] Specific examples

[1696] 1. The user tells the generative AI, "I've been feeling very stressed lately and can't concentrate on my work."

[1697] 2. The device sends the conversation content to the server.

[1698] 3. The server uses an emotion engine to analyze the content of the conversation and determine that the stress level is high.

[1699] 4. The server generates an alert saying "User A is experiencing high stress."

[1700] 5. The server sends an alert to the manager's terminal.

[1701] 6. The manager's device displays an alert and the manager follows up with User A.

[1702] The above are the specific processing steps of each function in the embodiment of the present invention in which an emotion engine is combined.

[1703] Example 2

[1704] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1705] While conventional goal management systems can manage the goals and tasks entered by users, they lack the ability to grasp the user's emotional state in real time and provide appropriate feedback and support as needed. As a result, users who are particularly stressed may not receive the support they need, which can lead to a decline in productivity and mental health. Furthermore, the lack of analysis of activity logs and feedback on goal achievement makes it difficult for users to create specific plans for self-improvement.

[1706] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for receiving goals and tasks from the user, means for transmitting the received goals and tasks to the server, means for setting alarms for the goals and tasks on the server, means for notifying the user of the set alarm, means for transmitting emotional data entered by the user to the server, means for the server to analyze the emotional data using an emotion engine and evaluate the user's emotional state, means for the server to generate an alert if necessary based on the analysis results, and means for notifying the administrator's terminal of the generated alert. This enables progress management of the goals and tasks set by the user, as well as monitoring of the emotional state and providing appropriate feedback. Furthermore, adding a function for analyzing a one-week activity log and providing feedback based on the log allows the user to create a specific action plan for self-improvement and improve overall performance.

[1707] "Goals and tasks" refer to the objectives that a user is trying to achieve or the specific work that needs to be done.

[1708] "User" refers to a person who uses this system to set goals, manage progress, and monitor emotions.

[1709] The "means for receiving" refers to a process or device by which the terminal acquires data on goals or tasks input by the user.

[1710] "Means for transmitting" refers to the process or device for sending received data from the terminal to the server and communicating.

[1711] "Server" refers to a central computing device for analyzing, storing, and managing received data.

[1712] "Means for setting an alarm" refers to a mechanism or device for sending a notification based on a specified date, time, or conditions.

[1713] "Means for notifying" refers to a device or process for notifying a user or administrator of configured alarms or confirmation messages.

[1714] "Emotion data" is data that indicates the user's emotional state, and includes psychological factors such as stress and satisfaction.

[1715] An "emotion engine" refers to software or algorithms that analyze emotional data and assess a user's emotional state.

[1716] "Means for generating alerts" refers to a mechanism or device that generates warnings or notifications when certain conditions are met based on the results of analyzing emotional data.

[1717] "Administrator" refers to a person whose job is to operate this system and support users.

[1718] An "activity log" refers to data that records a user's daily activities and task progress.

[1719] "Weekly Review" refers to a report that analyzes recorded activity logs and summarizes the user's actions and achievements over the week.

[1720] This invention is a system that manages the goals and tasks set by the user and monitors the emotional state. This system is mainly composed of a server and a user terminal (smartphone or PC).

[1721] System Configuration

[1722] Users can interact with the generative AI model through their device and receive appropriate feedback and recognition of their emotional state using the emotion engine.

[1723] Entering goals and tasks

[1724] Using a smartphone or PC, a user speaks to the generative AI model about their goals and tasks. For example, they might set a goal like "I'll rehearse my presentation next Thursday." The device then converts this goal data from speech to text and sends it to the server.

[1725] Receiving data and setting alarms

[1726] The server analyzes the received goal and task data and checks the details. Once the analysis is complete, an alarm is set for the appropriate date and time according to the goal. For example, it can set a reminder for the day before and the day itself.

[1727] Alarm notifications

[1728] When the set date and time arrives, the server sends a notification to the user's device. The device notifies the user of this notification by sound, vibration, or a pop-up notification. For example, it may notify the user that "there is a rehearsal for the presentation tomorrow."

[1729] User Data Storage

[1730] The device sends data on the goals and tasks set by the user to the server, which then stores the data in a database. For example, if a user enters "This month's goal is to increase team productivity by 20%, that information is stored.

[1731] Data storage confirmation notice

[1732] When the server confirms that the data has been saved successfully, it generates a confirmation message and sends it to the device, which then notifies the user that "the goal has been saved."

[1733] Activity log recording and analysis

[1734] The server records the user's activity log for the week and stores it in a database. For example, it records the time the user completed tasks and their progress. At the end of the week, the server analyzes the collected activity log using a generative AI model and generates a report summarizing the week's activities. The server then sends the generated report to the device, and the device notifies the user. For example, the server may inform the user that "three major tasks were completed this week, increasing the team's productivity by 15%."

[1735] Emotional state recognition and alert generation

[1736] The emotion engine recognizes the user's emotional state based on what the user says to the generative AI model. For example, if the user says, "I've been feeling very stressed lately and can't concentrate on my work," the device sends this information to the server. The server analyzes the emotional data and evaluates high stress levels and other emotional states. Based on the analysis results, the server generates an alert if necessary and notifies the administrator's device. The administrator can then take appropriate action based on this alert.

[1737] Specific examples

[1738] For example, if a user says, "I've been feeling very stressed lately and can't concentrate on my work," the device will send this data to the server. The server will analyze it using an emotion engine and confirm the high stress level. Based on the judgment, it will generate an alert saying, "User A is feeling very stressed," and send it to the administrator's device. The administrator will receive this alert and can follow up with User A.

[1739] The above is a detailed description of each function in the embodiment of the present invention. By using this system, users can efficiently manage their goals and monitor their emotions.

[1740] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1741] Step 1:

[1742] The user speaks to the generative AI model about their goals and tasks. For example, they can input a goal like "I'll rehearse my presentation next Thursday." The input voice data is then converted into text data.

[1743] Step 2:

[1744] The device receives the converted text data, formats it, and sends it to the server. Specifically, the voice data is recognized as text and sent to the server as target data, such as "I will rehearse the presentation next Thursday." In this process, a voice recognition algorithm is used to convert the voice to text.

[1745] Step 3:

[1746] The server analyzes the received goal data and checks its contents. After receiving the user's goal data, the server passes it to the analysis engine, which extracts the goal date and content. For example, the server analyzes the date and time information, such as "next Thursday," and the task content, such as "rehearse the presentation."

[1747] Step 4:

[1748] The server sets alarms for goals and tasks based on the analyzed date information. Specifically, it sets the data to set reminder alarms for the day before and the day of the goal, and sets notifications to be sent at the appropriate date and time. The input is the analyzed goal data, and the output is the set alarm information.

[1749] Step 5:

[1750] When the set date and time arrives, the server sends a notification to the user device. For example, notification data such as "There is a presentation rehearsal tomorrow" is generated and sent to the user device. The device receives this notification data and notifies the user with a sound, vibration, or pop-up notification.

[1751] Step 6:

[1752] The data of the goals and tasks set by the user is sent from the terminal to the server and saved in the database. When saving to the database, the input is the goal data set by the user, and the output is save confirmation information.

[1753] Step 7:

[1754] When the server confirms that the data has been saved successfully, it generates a confirmation message and sends it to the device. The device receives this confirmation message and notifies the user that "the goal has been saved." In the confirmation message generation process, the confirmation message is created using the ID of the saved data.

[1755] Step 8:

[1756] The server records a user's activity log for one week and stores it in a database. The activity log records the time and progress of daily tasks. The input is the user's activity data, and the output is the activity log data.

[1757] Step 9:

[1758] At the end of the week, the server analyzes the collected activity logs and generates a weekly activity summary report using a generative AI model. The input is the activity log data, and the output is the generated summary report. A machine learning algorithm is used for the analysis.

[1759] Step 10:

[1760] The generated report is sent from the server to the device, and the device notifies the user of the report contents, such as "This week, three major tasks were completed, and the team's productivity increased by 15%."

[1761] Step 11:

[1762] The user inputs emotional data into the generative AI model, for example, by saying, "I've been feeling very stressed lately and can't concentrate on my work." The input voice data is converted into text data.

[1763] Step 12:

[1764] The device sends this text data to the server, which then analyzes the received emotional data using an emotion engine to evaluate the user's emotional state. The input is the user's emotional data, and the output is the evaluated emotional state.

[1765] Step 13:

[1766] The server generates alerts based on the analysis results if necessary. For example, if the user is judged to be at a high stress level, an alert is generated. The input is the assessed emotional state, and the output is the generated alert.

[1767] Step 14:

[1768] The generated alert is sent from the server to the administrator's terminal, and the administrator takes appropriate action based on the alert. The terminal receives the alert and displays it to the administrator.

[1769] The above processing steps enable efficient management of user goals and monitoring of emotions.

[1770] (Application example 2)

[1771] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1772] Conventional goal management and progress management systems do not monitor or provide feedback that takes into account the user's emotional state, which means they are unable to provide appropriate support even when the user reaches a high stress level. This can lead to long-term declines in productivity and work efficiency. Furthermore, even in factory environments using robots, there is also the issue of overall work efficiency not improving due to the inability to communicate smoothly with workers or manage tasks appropriately.

[1773] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving goals and tasks from the user, means for transmitting the received goals and tasks to the server, means for recognizing the user's emotional state using an emotion engine, means for transmitting the recognized emotional state to the server, means for analyzing the emotion data and generating an alert based on the emotional state, and means for notifying the administrator of the alert. This improves the user's work efficiency and enables appropriate support based on the user's emotional state.

[1774] The "means for receiving goals and tasks from the user" is a mechanism for receiving goals and tasks set by the user through voice input or text input.

[1775] The "means for transmitting received goals and tasks to a server" is a mechanism for transmitting data on goals and tasks received from a user to a server via the Internet or an internal network.

[1776] "Means for setting alarms for goals and tasks on the server" refers to a function for setting alarms for specific dates and times based on goals and tasks received by the server.

[1777] The "means for notifying the user of the set alarm" is a mechanism for sending a notification to the user's terminal at the set alarm date and time, and notifying the user by sound, vibration, or pop-up notification.

[1778] The "means for recognizing the emotional state of the user using an emotion engine" is a function that analyzes the voice or text input by the user and recognizes the emotional state of the user using an emotion engine.

[1779] The "means for transmitting the recognized emotional state to the server" is a mechanism for transmitting data on the user's emotional state recognized by the emotion engine to the server.

[1780] The "means for analyzing emotional data and generating an alert based on the emotional state" is a function that analyzes the emotional data received by the server and generates an alert if a specific emotional state is confirmed.

[1781] The "means for notifying the administrator of the alert" is a mechanism for notifying the administrator of the generated alert on his / her terminal, so that the administrator can take appropriate action.

[1782] The "means for saving user input data on the server" is a function for saving data on goals and tasks entered by the user on the server.

[1783] The "means for generating a confirmation message for saved data" is a function for generating a message for confirming that saving has been successful.

[1784] The "means for notifying the user of a confirmation message" is a mechanism for sending the generated confirmation message to the user terminal and notifying the user.

[1785] The "means for providing feedback to the worker based on the emotional state" is a function for providing appropriate feedback to the worker based on the analyzed emotional state.

[1786] The "means for recording a user's activity log for one week on the server" is a function for recording a user's activity data for one week on the server.

[1787] The "means for analyzing the recorded activity log and generating a weekly review" is a function for analyzing the recorded activity log and generating a weekly review report.

[1788] The "means for notifying the user of the generated weekly review" is a mechanism for sending the generated weekly review report to the user terminal and notifying the user.

[1789] "Means for generating prompt sentences based on one week's activity data and inputting them into the generative AI model" refers to a function that generates prompt sentences for the generative AI model based on one week's activity data and inputs them into the generative AI model.

[1790] This invention is a system for setting user goals, managing progress, and monitoring emotional states. The system consists of a server, a user terminal (a smartphone or personal computer), and a robot. The user interacts with a generative artificial intelligence (generative AI model) through the terminal or robot, and the emotion engine recognizes the user's emotional state and provides appropriate feedback.

[1791] 1. User Interface

[1792] The user sets goals and tasks using a terminal or robot by voice input or text input, and the entered goals and tasks are sent to a server via the Internet.

[1793] 2. Data transmission and storage

[1794] The received goal and task data is sent to the server, which stores the data in a database. If the data is successfully stored, the server generates a confirmation message and sends it to the user's device.

[1795] 3. Alarm settings and notifications

[1796] The server sets an alarm based on the received goals and tasks. The alarm is notified to the user's device or robot at a specific date and time, and the user is notified by sound, vibration, or a pop-up notification.

[1797] 4. Monitoring your emotional state

[1798] When a user interacts with a generative AI model, the emotion engine analyzes the voice and text to recognize the emotional state. The recognized emotional state is sent to the server, which then analyzes the emotional data.

[1799] 5. Alerting and Notification

[1800] Based on the analysis results, the server generates an alert if it determines that support is required. For example, if it determines that a user is at a high stress level, an alert is generated and sent to the administrator's device. The administrator can then take appropriate action based on this alert.

[1801] 6. Activity log and review

[1802] The server records the user's activity log for one week and stores it in a database. At the end of the week, the server analyzes the activity log and generates a weekly review report using a generative AI model. The generated report is sent to the user's device and the user is notified.

[1803] Hardware and software used

[1804] Hardware: Smartphone, personal computer, robot-integrated microphone, speaker, and internet connection

[1805] Software: Python, speech_recognition, pyttsx3, requests, TextBlob

[1806] Specific examples

[1807] For example, if a user says, "I'll rehearse my presentation next Thursday," the speech is converted into text and sent to the server. The server saves the goal data and notifies the user at the specified date and time, saying, "I'll rehearse my presentation tomorrow."

[1808] Furthermore, if a user says, "I've been feeling very stressed lately and can't concentrate on my work," the emotion engine analyzes the situation and confirms the high stress level. The server generates an alert saying, "User A is feeling very stressed," and sends it to the administrator's device. The administrator receives this and follows up with User A.

[1809] Examples of prompts for generative AI models:

[1810] "User set goal: Increase team productivity by 20%, User's emotional state: High stress, Alarm set time: Tomorrow at 2 PM"

[1811] The above is an embodiment of the present invention.

[1812] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1813] Step 1:

[1814] A user sets goals and tasks using a terminal or robot by voice or text input. For example, if a user sets a goal such as "I will rehearse my presentation next Thursday," the terminal receives this voice as text data. In this case, the input is voice data and the output is text data.

[1815] Step 2:

[1816] The device sends the acquired text data to a server via the Internet. Specifically, the device converts the text data into JSON format and sends the data to the server's API endpoint using an HTTP request. Here, the input is the text data and the output is the HTTP request sent to the server.

[1817] Step 3:

[1818] The server analyzes the received goal and task data and saves it in a database. If successful, the server generates a confirmation message and sends it to the terminal. The input is the text data sent to the server, and the output is the saved status in the database and the confirmation message.

[1819] Step 4:

[1820] The server sets an alarm based on the received goals and tasks. For example, it sets a notification for a specific date and time (for example, the day before or the day itself). It analyzes the date and time data of the goals set by the user and determines the alarm setting time. The input is the date and time data of the goals and tasks, and the output is the alarm setting data.

[1821] Step 5:

[1822] The server sends an alarm notification to the device at the set date and time. The device notifies the user of this notification by sound, vibration, or a pop-up notification. The input is the alarm setting data, and the output is the alarm notified to the user.

[1823] Step 6:

[1824] The user interacts with the generative AI model through a device or robot, making statements that express their emotional state. The emotion engine analyzes these statements and recognizes the user's emotional state. For example, if a user says, "I've been feeling very stressed lately and can't concentrate on my work," the emotion engine recognizes this as high stress. The input is the user's utterance data, and the output is the recognized emotion data.

[1825] Step 7:

[1826] The device sends the recognized emotional data to the server. The server analyzes this emotional data and generates an alert if a specific emotional state (e.g., high stress) is confirmed. For example, an alert may be generated stating, "User A is experiencing high stress." The input is the emotional data, and the output is the generated alert.

[1827] Step 8:

[1828] The generated alert is sent from the server to the administrator's terminal. The administrator's terminal displays the alert and supports the administrator in taking appropriate action. The input is the generated alert data, and the output is the alert notified to the administrator's terminal.

[1829] Step 9:

[1830] The server records a week's worth of user activity logs and stores them in a database. The activity logs include the user's goals, task progress, completion time, emotional state, etc. The input is the user activity data, and the output is the stored activity logs.

[1831] Step 10:

[1832] At the end of the week, the server analyzes the activity log and generates a weekly review report using a generative AI model. The report includes a summary of the user's work efficiency and emotional state. The input is the activity log data, and the output is the generated weekly review report.

[1833] Step 11:

[1834] The generated weekly review report is sent to the user terminal. The user terminal notifies the user of this report and displays its contents. The input is the generated report, and the output is the report notified to the user.

[1835] Step 12:

[1836] A prompt sentence is generated based on one week's activity data and input into the generative AI model. The generative AI model uses this prompt sentence to generate improvement suggestions and advice on setting goals for the next week. For example, a prompt sentence such as "User-set goal: Increase team productivity by 20%, User's emotional state: High stress, Alarm setting time: Tomorrow at 2 p.m." is generated. The input is activity data, and the output is the generated prompt sentence and improvement suggestions.

[1837] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1838] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1839] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1840] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1841] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1842] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1843] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1844] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1845] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1846] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1847] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1848] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1849] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1850] 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.

[1851] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1852] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1853] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1854] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1855] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1856] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1857] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1858] The following is further disclosed regarding the above embodiment.

[1859] (Claim 1)

[1860] a means for receiving goals or tasks from a user;

[1861] a means for transmitting the received goals and tasks to a server;

[1862] A way to set alarms for goals and tasks on the server;

[1863] means for notifying a user of a set alarm;

[1864] A system including:

[1865] (Claim 2)

[1866] means for storing user input data on a server;

[1867] means for generating a confirmation message for the stored data;

[1868] means for notifying a user of a confirmation message;

[1869] 10. The system of claim 1, comprising:

[1870] (Claim 3)

[1871] means for recording a weekly log of user activity on the server;

[1872] A means for analyzing the recorded activity log to generate a weekly review;

[1873] a means for notifying a user of the generated weekly review;

[1874] 10. The system of claim 1, comprising:

[1875] (Claim 4)

[1876] a means for using generative AI to analyze the emotional state of a user;

[1877] a means for generating an alert based on the sentiment analysis results;

[1878] a means for transmitting generated alerts to management;

[1879] 10. The system of claim 1, comprising:

[1880] "Example 1"

[1881] (Claim 1)

[1882] a means for receiving goals or tasks from a user;

[1883] a means for transmitting the received goals and tasks to a server;

[1884] A way to set alarms for goals and tasks on the server;

[1885] means for notifying a user of a set alarm;

[1886] means for analyzing the emotional state of a user;

[1887] means for generating an alert based on the result of the user's sentiment analysis;

[1888] a means for notifying an administrator of generated alerts;

[1889] A system including:

[1890] (Claim 2)

[1891] means for storing user input data on a server;

[1892] means for generating a confirmation message for the stored data;

[1893] means for notifying a user of a confirmation message;

[1894] 10. The system of claim 1, comprising:

[1895] (Claim 3)

[1896] means for recording a weekly log of user activity on the server;

[1897] A means for analyzing the recorded activity log to generate a weekly review;

[1898] a means for notifying a user of the generated weekly review;

[1899] 10. The system of claim 1, comprising:

[1900] "Application Example 1"

[1901] (Claim 1)

[1902] a means for receiving goals or tasks from a user;

[1903] a means for transmitting the received goals and tasks to a server;

[1904] A way to set alarms for goals and tasks on the server;

[1905] means for notifying a user of a set alarm;

[1906] means for analyzing an emotional state from input of a factory worker;

[1907] a means for generating an alert based on the sentiment analysis results;

[1908] a means for notifying an administrator of generated alerts;

[1909] A system including:

[1910] (Claim 2)

[1911] means for storing user input data on a server;

[1912] means for generating a confirmation message for the stored data;

[1913] means for notifying a user of a confirmation message;

[1914] 10. The system of claim 1, comprising:

[1915] (Claim 3)

[1916] means for recording a weekly log of user activity on the server;

[1917] A means for analyzing the recorded activity log to generate a weekly review;

[1918] a means for notifying a user of the generated weekly review;

[1919] 10. The system of claim 1, comprising:

[1920] "Example 2: Combining Emotion Engines"

[1921] (Claim 1)

[1922] a means for receiving goals or tasks from a user;

[1923] a means for transmitting the received goals and tasks to a server;

[1924] A way to set alarms for goals and tasks on the server;

[1925] means for notifying a user of a set alarm;

[1926] means for transmitting emotion data input by a user to a server;

[1927] a means for the server to analyze the emotion data using an emotion engine and evaluate the user's emotional state;

[1928] a means for the server to generate alerts when necessary based on the analysis results;

[1929] A means for notifying the generated alert to the administrator's terminal;

[1930] A system including:

[1931] (Claim 2)

[1932] means for storing user input data on a server;

[1933] means for generating a confirmation message for the stored data;

[1934] means for notifying a user of a confirmation message;

[1935] 10. The system of claim 1, comprising:

[1936] (Claim 3)

[1937] means for recording a weekly log of user activity on the server;

[1938] A means for analyzing the recorded activity log to generate a weekly review;

[1939] a means for notifying a user of the generated weekly review;

[1940] 10. The system of claim 1, comprising:

[1941] "Application example 2 when combining emotion engines"

[1942] (Claim 1)

[1943] a means for receiving goals or tasks from a user;

[1944] a means for transmitting the received goals and tasks to a server;

[1945] A way to set alarms for goals and tasks on the server;

[1946] means for notifying a user of a set alarm;

[1947] means for recognizing an emotional state of a user using an emotion engine;

[1948] means for transmitting the recognized emotional state to a server;

[1949] means for analyzing the emotional data and generating an alert based on the emotional state;

[1950] a means of notifying an administrator of the alert;

[1951] A system including:

[1952] (Claim 2)

[1953] means for storing user input data on a server;

[1954] means for generating a confirmation message for the stored data;

[1955] means for notifying a user of a confirmation message;

[1956] means for providing feedback to the worker based on the emotional state;

[1957] 10. The system of claim 1, comprising:

[1958] (Claim 3)

[1959] means for recording a weekly log of user activity on the server;

[1960] A means for analyzing the recorded activity log to generate a weekly review;

[1961] a means for notifying a user of the generated weekly review;

[1962] A means for generating prompt sentences based on one week of activity data and inputting the prompts into a generative AI model;

[1963] 10. The system of claim 1, comprising: [Explanation of symbols]

[1964] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for receiving goals or tasks from a user; a means for transmitting the received goals and tasks to a server; A way to set alarms for goals and tasks on the server; means for notifying a user of a set alarm; A system including:

2. means for storing user input data on a server; means for generating a confirmation message for the stored data; means for notifying a user of a confirmation message; The system of claim 1 , comprising:

3. means for recording a weekly log of user activity on the server; A means for analyzing the recorded activity log to generate a weekly review; a means for notifying a user of the generated weekly review; The system of claim 1 , comprising:

4. a means for using generative AI to analyze the emotional state of a user; a means for generating an alert based on the sentiment analysis results; a means for transmitting generated alerts to management; The system of claim 1 , comprising:

Images