System

Abstract

A system is provided.SOLUTION: The system includes a data input means to be used for inputting data of a new user, a generation means for generating a training plan on the basis of past training data and basic information of the user, a proposal means for proposing the generated training plan to the user, a detection means for detecting abnormality, and a response means for performing emergency response when the abnormality is detected.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] While the recent spread of 24-hour fitness gyms has provided great convenience to users, it has also created problems that users must solve themselves, such as formulating training menus and responding to emergencies due to the lack of staff. This has resulted in issues such as a lack of satisfaction among users of unmanned gyms and an inability to respond quickly to emergencies. Beginners and those using the gym for short periods of time may find it difficult to easily and effectively train. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides the following means. Specifically, the present invention provides a system including a data input means used to input data of a new user, a generation means for generating a training plan based on past training data and basic information of the user, a proposal means for proposing the generated training plan to the user, a detection means for detecting abnormalities, and a response means for taking emergency measures when an abnormality is detected. This system eliminates the need for users to create complex training plans themselves and allows for rapid response in emergencies.

[0006] "Data Entry Means" means a device or system used to enter data such as a user's basic information and fitness goals.

[0007] "Generation means" refers to an algorithm or system that generates appropriate training plans and advice based on collected user data and past training data.

[0008] The "suggestion means" is a device or system for presenting the training plan and advice generated by the generation means to the user.

[0009] "Detection means" refers to sensors or monitoring devices used to detect abnormal conditions or situations involving users.

[0010] The "response means" is a device or system for carrying out an appropriate emergency response when an abnormality is detected by the detection means. [Brief explanation of the drawings]

[0011] [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

[0012] 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.

[0013] First, the terms used in the following description will be explained.

[0014] 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).

[0015] 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.

[0016] 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.

[0017] 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.

[0018] 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."

[0019] [First embodiment]

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

[0021] 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.

[0022] 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).

[0023] 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.

[0024] 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.

[0025] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0026] 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.

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

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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."

[0032] This invention is a system that allows users to train efficiently and safely at a 24-hour fitness gym. This system includes a data input means, a generation means, a proposal means, a detection means, and a response means. The function of each means is explained below with specific examples.

[0033] Data Entry Method

[0034] Server: Collects data from cameras and sensors installed at the entrance to detect when a user arrives at the gym.

[0035] Device: When the user scans the QR code, a screen will appear prompting them to enter basic information (fitness experience, goals, etc.).

[0036] User: Enter a self-introduction and fitness goals into the input screen displayed on the device.

[0037] Example: When a user scans a QR code at the entrance, a screen appears on the device asking them to introduce themselves and enter their fitness goals. The user enters their goal as "I want to do strength training three times a week."

[0038] generation means

[0039] Server: Runs the generation AI to generate training plans based on the collected basic information and past training data.

[0040] Terminal: Proposes the training plan generated by the generation AI to the user.

[0041] Example: When a user enters basic information, the server uses a generative AI to generate a "strength training plan for one hour, three times a week" based on past data and the entered information. The device displays a specific plan such as "Squats and planks on the first day, deadlifts and side lunges on the second day, and bench presses and hip thrusts on the third day."

[0042] Proposal means

[0043] Server: Sends instructions to PepperGPT to suggest the training plan generated by the generator to the user.

[0044] Device: PepperGPT will propose the generated training plan to the user via voice and display.

[0045] User: Review the proposed training plans and select the plan they wish to implement.

[0046] Example: PepperGPT will say, "Hello, Mr. / Ms. X. Today's training plan is 30 minutes of strength training. Let's start with squats." The user will confirm the proposed plan and proceed to the next step.

[0047] Detection Method

[0048] Server: Collects data in real time from various sensors installed within the fitness gym and processes it to detect abnormalities.

[0049] Device: Prepare to display an emergency alert if an anomaly is detected.

[0050] Example: If a user falls during training, the heart rate monitor and fall detection sensor will detect the abnormality and the server will immediately send an alert to the device.

[0051] Countermeasures

[0052] Server: When an abnormality is detected, it immediately sends an instruction to PepperGPT to switch to emergency response mode.

[0053] Terminal: The terminal displays the emergency situation and provides specific instructions to the user. It also automatically notifies emergency contacts as needed.

[0054] User: Follow the emergency response instructions displayed on the device.

[0055] Example: If a user collapses, PepperGPT will provide a voice prompt saying, "This is an emergency. Please rest immediately. We will call an ambulance," and the device will simultaneously display, "An emergency has occurred. We will notify emergency contacts."

[0056] The above is a specific embodiment for carrying out the present invention. This system allows users to easily obtain an efficient training plan and also enables quick response in emergencies.

[0057] The processing flow will be explained below.

[0058] New User Guide

[0059] Step 1:

[0060] Server: Collects data from cameras and sensors installed at the entrance to confirm the user's entry and identifies whether the user is a new user.

[0061] Step 2:

[0062] Device: If a new user is identified, a screen for scanning a QR code will be displayed on the device.

[0063] Step 3:

[0064] User: Scan the QR code displayed on the device to start using the service.

[0065] Step 4:

[0066] Terminal: Displays a screen where users can enter basic information such as their fitness experience and goals.

[0067] Step 5:

[0068] User: Enter a profile and fitness goals into the device.

[0069] Step 6:

[0070] Server: Processes the basic information entered and sends a command to PepperGPT to start facility guidance.

[0071] Step 7:

[0072] Terminal: PepperGPT begins to provide voice guidance to the user, saying, "Hello, you are a new user. We will show you how to use the facility."

[0073] Short workout suggestions

[0074] Step 1:

[0075] User: Enter a time limit into the terminal, such as "Only 30 minutes available today."

[0076] Step 2:

[0077] Terminal: Sends the entered time limit to the server.

[0078] Step 3:

[0079] Server: Runs the generative AI to generate effective workout plans in a short amount of time based on past training data and basic user information.

[0080] Step 4:

[0081] Terminal: Displays the generated workout plan to the user.

[0082] Step 5:

[0083] User: Check the training plan displayed on the device and decide whether to carry it out.

[0084] Step 6:

[0085] Server: Optimizes training plans based on user feedback.

[0086] Goal setting support

[0087] Step 1:

[0088] User: Enter a specific goal into the device, such as "lose 5 kg in 3 months."

[0089] Step 2:

[0090] Terminal: Sends the entered goal to the server.

[0091] Step 3:

[0092] Server: Based on the input goal, the generation AI proposes a feasible method and timeframe for achieving the goal.

[0093] Step 4:

[0094] Device: The generated advice is displayed to the user and read aloud by PepperGPT.

[0095] Step 5:

[0096] User: Review the proposed goals and methods, make adjustments as needed, and finalize the goal setting.

[0097] Step 6:

[0098] Server: Stores the adjusted goals and methods and periodically tracks the user's progress.

[0099] Emergency Response Support

[0100] Step 1:

[0101] Server: Collects data in real time from heart rate monitors and fall detection sensors installed within the facility and detects abnormalities.

[0102] Step 2:

[0103] Terminal: Prepare to display an emergency situation if an abnormality is detected.

[0104] Step 3:

[0105] Server: When an abnormality is detected, it immediately sends an instruction to PepperGPT to switch to emergency response mode.

[0106] Step 4:

[0107] Device: An emergency message will be displayed on the device, along with specific steps to take. Emergency contacts will also be notified automatically.

[0108] Step 5:

[0109] User: Follow the emergency response instructions displayed on the device and, if necessary, seek assistance until the situation improves.

[0110] The above are the specific processing steps of this system. At each processing step, the server, terminal, and user work together to provide efficient training support.

[0111] Example 1

[0112] 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."

[0113] At current fitness gyms, users need a lot of time and effort to find an appropriate training plan that suits their individual fitness experience and goals. Real-time monitoring and rapid response to abnormalities to ensure user safety are also difficult. Therefore, there is a need for a system that allows users to train efficiently and safely.

[0114] 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.

[0115] In this invention, the server includes a data input means for inputting user data, a generation means for generating a training plan based on past training data and basic information about the user, a proposal means for proposing the generated training plan to the user, a detection means for detecting abnormalities, a response means for taking emergency action when an abnormality is detected, a means for collecting data from cameras and sensors to detect the arrival of the user, and a means for providing audio and visual guidance on the proposed training plan. This allows users to efficiently obtain training plans, monitors safety in real time, and enables rapid response to abnormalities.

[0116] "Data input means" refers to a device or method by which a user inputs basic information such as training information and goals.

[0117] "Generation means" refers to a device or method for creating an appropriate training plan based on collected data.

[0118] The "suggestion means" is a device or method for proposing the generated training plan to the user.

[0119] "Detection means" refers to a device or method for detecting abnormalities in users using sensors or cameras within the fitness gym.

[0120] "Response means" refers to a device or method for taking emergency action when an abnormality is detected.

[0121] "Means for collecting data from cameras and sensors" refers to devices or methods that detect the arrival or movement of users and collect data based on that.

[0122] "Means for providing audio or visual guidance on a training plan" refers to a device or method for providing audio guidance or displaying a generated training plan on a terminal screen to a user.

[0123] MODE FOR CARRYING OUT THE INVENTION

[0124] This invention is a system that allows users to train efficiently and safely at a 24-hour fitness gym. This system includes a data input means, a generation means, a proposal means, a detection means, and a response means. The functions of each means and specific operation examples are shown below.

[0125] Data Entry Method

[0126] Server: To detect when a user arrives at the gym, the server collects data from cameras and sensors installed at the entrance. The server analyzes this data and confirms that the user has arrived at the gym.

[0127] Terminal: When a user scans the QR code installed at the gym entrance, a screen will appear prompting them to enter basic information (fitness experience, goals, etc.), making it easy for users to enter the required information.

[0128] User: Enters a self-introduction and fitness goals into the input screen displayed on the device. Specifically, the user enters a goal such as "I want to do strength training three times a week."

[0129] generation means

[0130] Server: Based on the collected basic information and past training data, a training plan is generated using a "generative AI model." This generative AI model can be, for example, "ChatGPT Turbo."

[0131] Example: When a user enters basic information, the server uses training AI to generate a "strength training plan for one hour, three times a week" based on past data and the entered information. The generated plan contains specific content, and the device displays a specific plan such as "Squats and planks on the first day, deadlifts and side lunges on the second day, and bench presses and hip thrusts on the third day."

[0132] Proposal means

[0133] Server: Sends instructions to PepperGPT to suggest the generated training plan to the user.

[0134] On the device, PepperGPT will propose the generated training plan to the user via voice and display. For example, it might say, "Hello, Mr. / Ms. X. Today's training plan is 30 minutes of strength training. Let's start with squats."

[0135] Detection Method

[0136] Server: Collects data in real time from various sensors installed in the fitness gym and processes it to detect abnormalities. For example, heart rate monitors and fall detection sensors are used.

[0137] Terminal: Prepare to display an emergency alert if an abnormality is detected. When the server detects an abnormality, it immediately sends an alert to the terminal.

[0138] Example: If a user falls during training, the heart rate monitor and fall detection sensor will detect the abnormality and the server will immediately send an alert to the device.

[0139] Countermeasures

[0140] Server: When an abnormality is detected, PepperGPT is immediately instructed to switch to emergency response mode, enabling a rapid response.

[0141] Terminal: The terminal displays the emergency situation and provides specific instructions to the user. It also automatically notifies emergency contacts as needed.

[0142] User: Follow the emergency response instructions displayed on the device. For example, PepperGPT will say, "This is an emergency. Please rest immediately. We will call an ambulance," and the device will simultaneously display, "Emergency situation has occurred. We will notify emergency contacts."

[0143] Prompt Sentence Examples

[0144] A user arrives at the gym. They scan a QR code to enter their basic information and fitness goals. For example, "I want to do one hour of strength training three times a week." Once they've completed the input, they can begin generating a training plan.

[0145] This system allows users to easily obtain efficient training plans and also enables quick response in emergencies.

[0146] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0147] Step 1:

[0148] User arrival detection

[0149] Server: Operates the camera and sensor system installed at the gym entrance.

[0150] Input: Images and data captured from cameras and sensors.

[0151] Data processing: Image analysis is used to recognize people's movements and faces.

[0152] Output: A flag confirming the user's arrival.

[0153] How it works: The camera captures the user's image data, the sensor detects their presence, and the server analyzes this data to recognize the user's arrival.

[0154] Step 2:

[0155] Prompt for QR code scanning and basic information entry

[0156] Terminal: When the user scans the QR code installed at the entrance, a screen for entering basic information is displayed.

[0157] Input: User ID via QR code scan.

[0158] Data processing: Decode the contents of the QR code and extract the user ID.

[0159] Output: Basic information input screen.

[0160] Specific operation: The QR code is scanned with the device's camera. The device then displays an input screen prompting the user to "Enter your name, age, fitness experience, and goals."

[0161] Step 3:

[0162] Enter your basic information and fitness goals

[0163] User: Enter basic information and fitness goals.

[0164] Input: Basic information entered by the user into the input screen (name, age, fitness experience, goals).

[0165] Data Calculation: Validation and storage of input data.

[0166] Output: User's basic information and goals.

[0167] Specific Action: A user inputs a fitness goal: "I want to do strength training three times a week."

[0168] Step 4:

[0169] Generate a training plan

[0170] Server: Runs the generative AI model based on collected basic information and past training data.

[0171] Input: User's basic information and past training data.

[0172] Data processing: Inputting and analyzing data into generative AI models.

[0173] Output: The generated training plan.

[0174] Specific operation: The server uses training AI to generate a "strength training plan for one hour, three times a week" based on past data and input information. The generated plan contains specific content.

[0175] Step 5:

[0176] Training plan suggestions

[0177] Server: Sends the generated training plan to PepperGPT.

[0178] Input: The generated training plan.

[0179] Data processing: Instructions for sending training plan.

[0180] Output: Suggested instructions to PepperGPT.

[0181] Specific operation: Details of the generated training plan are sent to PepperGPT via API.

[0182] Device: PepperGPT will suggest training plans to the user via voice and display.

[0183] Input: Proposal data from PepperGPT.

[0184] Data processing: speech synthesis and display on the screen.

[0185] Output: Suggestions to the user.

[0186] Specific actions: PepperGPT will guide you by saying, "Hello, Mr. / Ms. XX. Today's training plan is 30 minutes of strength training. Let's start with squats."

[0187] Step 6:

[0188] Monitoring during training

[0189] Server: Collects data in real time from various sensors within the fitness gym and processes it to detect abnormalities.

[0190] Input: Data from heart rate monitors and fall detection sensors.

[0191] Data processing: Real-time analysis for anomaly detection.

[0192] Output: Anomaly detection flag.

[0193] Specific operation: The server receives data from the heart rate monitor and fall detection sensor in real time and analyzes it to detect abnormalities.

[0194] Step 7:

[0195] Emergency response

[0196] Server: When an abnormality is detected, it immediately sends an instruction to PepperGPT to switch to emergency response mode.

[0197] Input: Anomaly detection flag.

[0198] Data processing: Generation of emergency response instructions.

[0199] Output: Emergency response instructions to PepperGPT.

[0200] Specific operation: The server sends emergency response instructions to PepperGPT through the API, causing it to immediately begin emergency response.

[0201] Terminal: Provides emergency response instructions to the user via voice and display, and also notifies emergency contacts as necessary.

[0202] Input: Emergency response instructions from the server.

[0203] Data processing: Voice synthesis and on-screen display of emergency instructions.

[0204] Output: Instructs the user on emergency measures and makes an emergency call.

[0205] Specific operation: The device displays "Emergency! Please stay still until an ambulance arrives" and automatically calls emergency contacts.

[0206] Users: Follow emergency plan instructions.

[0207] Input: Emergency instructions from terminal.

[0208] Data calculation: Deciding on actions based on instructions.

[0209] Output: Safety action.

[0210] Specific actions: The user follows the instructions to stay calm and wait for the ambulance to arrive.

[0211] (Application example 1)

[0212] 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."

[0213] To ensure that new users can train efficiently and safely at fitness facilities, it is necessary to provide individually tailored training plans and monitor safety in real time. However, traditional fitness facilities face challenges such as users having to make their own decisions when training, which increases the risk of users training incorrectly and makes it difficult to respond quickly to emergencies. Furthermore, providing users with training plans tailored to their individual fitness goals requires processing large amounts of data, making it difficult to perform complex calculations in real time.

[0214] 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.

[0215] In this invention, the server includes a generating means for generating a training plan based on past training data and basic information of the user, a means for generating and inputting prompts to the generating AI model to generate a training plan suited to the user's fitness goals using the generating AI model, a suggesting means for suggesting and notifying the user of the generated training plan and emergency alerts, a detecting means for acquiring data in real time from sensors installed in the fitness facility and detecting abnormalities, and a responding means for taking emergency action when an abnormality is detected. This makes it possible to provide users with efficient and individually tailored training plans, while simultaneously enabling rapid response to emergencies and ensuring safety.

[0216] A "new user" is someone using a fitness facility for the first time, or an existing user who needs a new training plan.

[0217] "Data entry means" refers to the tools and methods used to enter basic information about the user, fitness goals, past training data, etc.

[0218] "Generation means" refers to tools and methods for generating an appropriate training plan based on input data and past training information.

[0219] A "generative AI model" refers to an algorithm or system that uses artificial intelligence to process data and generate an appropriate training plan.

[0220] A "prompt" refers to a specific form of sentence used to give specific instructions or questions to a generative AI model.

[0221] "Proposal means" refers to the tools and methods used to propose and notify users of generated training plans and emergency alerts.

[0222] "Detection Methods" means tools or methods for detecting abnormal conditions or emergencies based on data from sensors installed within a fitness facility.

[0223] "Response measures" refer to tools and methods for quickly taking appropriate action when an abnormality or emergency is detected.

[0224] The present invention provides a system for enabling users to train efficiently and safely in a fitness facility, the system including a data input means, a generating means, a suggesting means, a detecting means, and a responding means.

[0225] Data Entry Method

[0226] The server collects data from cameras and sensors installed at the entrances of fitness facilities and detects the arrival of users. When the user scans a QR code, the device displays a screen prompting them to enter basic information (fitness experience, goals, etc.). Through this screen, the user enters their self-introduction and fitness goals. For example, when a user scans a QR code at the entrance, a screen prompting them to enter their self-introduction and fitness goals appears on the device, and the user enters their goal, such as "I want to do strength training three times a week."

[0227] generation means

[0228] The server runs a generative AI model to generate a training plan based on the collected basic information and past training data. A means for generating and inputting prompts for the generative AI model is included. For example, when a user inputs basic information, the server uses the generative AI model to generate a "strength training plan for one hour, three times a week" based on the past data and the input information, using the following prompt:

[0229] Username: "User A"

[0230] Fitness Experience: "Intermediate"

[0231] Fitness goal: "Strength training three times a week"

[0232] Past training data: "Squat", "Deadlift"

[0233] The device displays a specific plan, such as "Day 1: Squats and planks, Day 2: Deadlifts and side lunges, Day 3: Bench presses and hip thrusts."

[0234] Proposal means

[0235] The server sends instructions to the terminal to propose the training plan generated by the generation means to the user. After this, the terminal proposes the generated training plan to the user by voice or display. The user checks the proposed training plan and selects the plan to implement. For example, the terminal may say, "Today's training plan is 30 minutes of strength training. Let's start with squats," and the user may confirm the proposed plan.

[0236] Detection Method

[0237] The server collects data in real time from various sensors installed in the fitness facility and processes it to detect abnormalities. For example, if a user falls during training, the heart rate monitor or fall detection sensor will detect the abnormality and the server will immediately send an alert to the device.

[0238] Countermeasures

[0239] When an abnormality is detected, the server immediately sends an instruction to switch to emergency response mode. The device displays the emergency situation and provides the user with specific instructions on what to do. It also automatically notifies emergency contacts if necessary. For example, if the user collapses, the device will announce in voice, "This is an emergency. Please rest immediately. We will call an ambulance," and at the same time display, "An emergency has occurred. We will notify emergency contacts."

[0240] The above is a specific embodiment for carrying out the present invention. This system allows users to easily obtain an efficient training plan and also enables quick response in emergencies.

[0241] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0242] Step 1:

[0243] When a user arrives at a fitness facility, they scan a QR code at the entrance. The device then displays a screen where the user can enter their basic information and fitness goals. Once the user has finished entering their details, the data is sent to the server.

[0244] Input: User basic information, fitness goals

[0245] Data processing / data calculation: Collection and storage of input data

[0246] Output: Send user information to the server

[0247] Step 2:

[0248] The server runs a generative AI model to generate a training plan based on the collected basic information and past training data. The server provides the specified prompt sentence to the generative AI model to create an appropriate training plan.

[0249] Input: User's basic information, past training data

[0250] Data processing / data calculation: Prompt generation for generative AI models and training plan generation

[0251] Output: Generated training plan

[0252] Step 3:

[0253] The server sends the generated training plan to the device, which then presents it to the user via voice guidance and on-screen display. The user can then review the proposed training plans and select the one they wish to implement.

[0254] Input: Generated training plan

[0255] Data processing / data calculation: Display of training plan and voice guidance

[0256] Output: User confirms and selects training plan

[0257] Step 4:

[0258] The server collects data in real time from various sensors installed in the fitness facility and processes it to detect abnormalities. Based on the data collected from the sensors, it determines whether there are any abnormalities.

[0259] Input: Real-time data from sensors

[0260] Data processing / data calculation: Real-time data analysis and anomaly detection

[0261] Output: Anomaly detection results

[0262] Step 5:

[0263] When an abnormality is detected, the server immediately sends an instruction to switch to emergency response mode. The device notifies the user of the emergency through voice guidance and on-screen display, and automatically notifies emergency contacts if necessary. The user follows the instructions on the device and takes appropriate action.

[0264] Input: Anomaly detection results, user location, contact information

[0265] Data processing / data calculation: generation and notification of emergency response instructions

[0266] Output: Emergency response and automatic notification

[0267] By following these steps, a system is realized that provides effective training plans while ensuring the safety of users within a fitness facility.

[0268] 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.

[0269] This invention is a system that enables users to train efficiently and safely at a 24-hour fitness gym. This system is provided by combining a data input means, a generation means, a proposal means, a detection means, a response means, and an emotion engine. The function of each means is explained below with specific examples.

[0270] Data Entry Method

[0271] Server: Collects data from cameras and sensors installed at the entrance to confirm the user's entry and identifies whether the user is a new user.

[0272] Device: If a new user is identified, a screen for scanning a QR code will be displayed on the device.

[0273] User: Scan the QR code displayed on the device to start using the service.

[0274] Terminal: Displays a screen where users can enter basic information such as their fitness experience and goals.

[0275] User: Enter a profile and fitness goals into the device.

[0276] Example: When a user scans a QR code at the entrance, a screen appears on the device asking them to introduce themselves and enter their fitness goals. The user enters their goal as "I want to do strength training three times a week."

[0277] generation means

[0278] Server: Runs the generation AI to generate training plans based on the collected basic information and past training data.

[0279] Terminal: Proposes the training plan generated by the generation AI to the user.

[0280] Example: When a user enters basic information, the server uses a generative AI to generate a "strength training plan for one hour, three times a week" based on past data and the entered information. The device displays a specific plan such as "Squats and planks on the first day, deadlifts and side lunges on the second day, and bench presses and hip thrusts on the third day."

[0281] Proposal means

[0282] Server: Sends instructions to PepperGPT to suggest the training plan generated by the generator to the user.

[0283] Device: PepperGPT will propose the generated training plan to the user via voice and display.

[0284] User: Review the proposed training plans and select the plan they wish to implement.

[0285] Example: PepperGPT will say, "Hello, Mr. / Ms. X. Today's training plan is 30 minutes of strength training. Let's start with squats." The user will confirm the proposed plan and proceed to the next step.

[0286] Emotion Engine

[0287] Server: The emotion engine collects data to analyze the user's voice and facial expressions and recognize emotions.

[0288] Terminal: The emotion engine receives feedback on the user's emotional state based on the analysis results.

[0289] User: Review the suggestions tailored through emotion recognition and select a plan to implement.

[0290] Example: If a user says to their device, "I'm not feeling very well today," the emotion engine will analyze this and PepperGPT will adjust its suggestions, saying, "It seems like you're not feeling well. I recommend some light stretching and breathing exercises today."

[0291] Detection Method

[0292] Server: Collects data in real time from various sensors installed within the fitness gym and processes it to detect abnormalities.

[0293] Device: Prepare to display an emergency alert if an anomaly is detected.

[0294] Example: If a user falls during training, the heart rate monitor and fall detection sensor will detect the abnormality and the server will immediately send an alert to the device.

[0295] Countermeasures

[0296] Server: When an abnormality is detected, it immediately sends an instruction to PepperGPT to switch to emergency response mode.

[0297] Terminal: The terminal displays the emergency situation and provides specific instructions to the user. It also automatically notifies emergency contacts as needed.

[0298] User: Follow the emergency response instructions displayed on the device.

[0299] Example: If a user collapses, PepperGPT will provide a voice prompt saying, "This is an emergency. Please rest immediately. We will call an ambulance," and the device will simultaneously display, "An emergency has occurred. We will notify emergency contacts."

[0300] The above is a specific embodiment for carrying out the present invention. By combining it with an emotion engine, it becomes possible to propose flexible training plans that take into account the user's emotional state, which is expected to improve user satisfaction to a greater extent.

[0301] The processing flow will be explained below.

[0302] New User Guide

[0303] Step 1:

[0304] Server: Collects data from cameras and sensors installed at the entrance to confirm the user's entry and identifies whether the user is a new user.

[0305] Step 2:

[0306] Device: If a new user is identified, a screen for scanning a QR code will be displayed on the device.

[0307] Step 3:

[0308] User: Scan the QR code displayed on the device to start using the service.

[0309] Step 4:

[0310] Terminal: Displays a screen where users can enter basic information such as their fitness experience and goals.

[0311] Step 5:

[0312] User: Enter a profile and fitness goals into the device.

[0313] Step 6:

[0314] Server: Processes the basic information entered and sends a command to PepperGPT to start facility guidance.

[0315] Step 7:

[0316] Terminal: PepperGPT begins to provide voice guidance to the user, saying, "Hello, you are a new user. We will show you how to use the facility."

[0317] Short workout suggestions

[0318] Step 1:

[0319] User: Enter a time limit into the terminal, such as "Only 30 minutes available today."

[0320] Step 2:

[0321] Terminal: Sends the entered time limit to the server.

[0322] Step 3:

[0323] Server: Runs the generative AI to generate effective workout plans in a short amount of time based on past training data and basic user information.

[0324] Step 4:

[0325] Terminal: Displays the generated workout plan to the user.

[0326] Step 5:

[0327] User: Check the training plan displayed on the device and decide whether to carry it out.

[0328] Step 6:

[0329] Server: Optimizes training plans based on user feedback.

[0330] Goal setting support

[0331] Step 1:

[0332] User: Enter a specific goal into the device, such as "lose 5 kg in 3 months."

[0333] Step 2:

[0334] Terminal: Sends the entered goal to the server.

[0335] Step 3:

[0336] Server: Based on the input goal, the generation AI proposes a feasible method and timeframe for achieving the goal.

[0337] Step 4:

[0338] Device: The generated advice is displayed to the user and read aloud by PepperGPT.

[0339] Step 5:

[0340] User: Review the proposed goals and methods, make adjustments as needed, and finalize the goal setting.

[0341] Step 6:

[0342] Server: Stores the adjusted goals and methods and periodically tracks the user's progress.

[0343] Emotion Engine

[0344] Step 1:

[0345] Server: Collects data for the emotion engine to analyze the user's voice and facial expressions to recognize emotions.

[0346] Step 2:

[0347] Terminal: The emotion engine receives feedback on the user's emotional state based on the analysis results.

[0348] Step 3:

[0349] User: Review the suggestions tailored through emotion recognition and select a plan to implement.

[0350] Step 4:

[0351] Server: Based on the user's emotional data, the server adjusts the training plan and suggestions accordingly.

[0352] Step 5:

[0353] On the device: The adjustment results are displayed to the user, and PepperGPT provides voice guidance.

[0354] Example: If a user says to their device, "I'm not feeling very well today," the emotion engine will analyze this and PepperGPT will adjust its suggestions, saying, "It seems like you're not feeling well. I recommend some light stretching and breathing exercises today."

[0355] Detection Method

[0356] Step 1:

[0357] Server: Collects data in real time from various sensors installed within the fitness gym and processes it to detect abnormalities.

[0358] Step 2:

[0359] Device: Prepare to display an emergency alert if an anomaly is detected.

[0360] Example: If a user falls during training, the heart rate monitor and fall detection sensor will detect the abnormality and the server will immediately send an alert to the device.

[0361] Countermeasures

[0362] Step 1:

[0363] Server: When an abnormality is detected, it immediately sends an instruction to PepperGPT to switch to emergency response mode.

[0364] Step 2:

[0365] Terminal: The terminal displays the emergency situation and provides specific instructions to the user. It also automatically notifies emergency contacts as needed.

[0366] Step 3:

[0367] User: Follow the emergency response instructions displayed on the device.

[0368] Example: If a user collapses, PepperGPT will provide a voice prompt saying, "This is an emergency. Please rest immediately. We will call an ambulance," and the device will simultaneously display, "An emergency has occurred. We will notify emergency contacts."

[0369] The above is a specific embodiment for carrying out the present invention. By combining it with an emotion engine, it becomes possible to propose flexible training plans that take into account the user's emotional state, which is expected to improve user satisfaction to a greater extent.

[0370] Example 2

[0371] 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."

[0372] In conventional fitness gyms, it is difficult for users to independently adjust their training plans to suit their own physical condition and emotional state, and quick response is required when abnormalities occur. Furthermore, there is a lack of systems that utilize individual user data to provide optimal exercise plans. To solve this problem, there is a need for an integrated fitness support system that includes flexible proposals that take users' emotional state into account and quick response when abnormalities occur.

[0373] 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.

[0374] In this invention, the server

[0375] a data capture means used to input new user data;

[0376] A plan generation means for generating an exercise plan based on past exercise data and basic information of the user;

[0377] a suggestion means for suggesting the generated exercise plan to a user;

[0378] an anomaly detection means for detecting an anomaly;

[0379] an emergency response means for taking emergency action when an abnormality is detected;

[0380] emotion analysis means for analyzing the user's voice and facial expression to recognize emotions;

[0381] a voice suggestion means for suggesting an exercise plan to a user by voice;

[0382] Includes:

[0383] This will enable the system to propose flexible training plans that take into account the user's emotional state, as well as to respond quickly and appropriately in the event of an emergency.

[0384] "Data acquisition means" refers to the devices or systems used to input user data, such as cameras or sensors installed at entrances or the QR code scanning function displayed on terminals.

[0385] The "plan generation means" is a function that generates an optimal exercise plan based on collected past exercise data and basic information of the user. This includes a generative AI model.

[0386] The "suggestion means" refers to a means for presenting the generated exercise plan to the user, including a display on the device and audio guidance.

[0387] "Anomaly detection means" refers to sensors or monitoring systems that detect abnormalities within the fitness gym. Examples include heart rate monitors and fall detection sensors.

[0388] "Emergency response measures" are measures for taking prompt and appropriate action when an abnormality is detected, including displaying an emergency alert and automatically notifying emergency contacts.

[0389] "Emotion analysis means" refers to a system that analyzes a user's voice and facial expressions to recognize their emotional state. This includes voice analysis software and facial expression recognition technology.

[0390] The "audio suggestion means" refers to a means for suggesting the generated exercise plan to the user by voice, including a voice assistant function and a speaker.

[0391] This invention is a system that allows users to train efficiently and safely at a 24-hour fitness gym. This system is provided by combining a data acquisition means, a plan generation means, a proposal means, an anomaly detection means, an emergency response means, and an emotion analysis means. The specific functions and operations of each means are described below.

[0392] Data Acquisition Method

[0393] The server collects data from cameras and sensors installed at the entrance to confirm the user's entry and, based on this data, distinguishes between new and existing users.

[0394] If the device recognizes the user as a new user, it displays a screen for scanning a QR code and prompts the user to enter basic information.

[0395] Users scan a QR code displayed on their device and enter a profile picture and fitness goals.

[0396] Examples:

[0397] When users scan the QR code at the entrance, a screen appears on the device where they can introduce themselves and enter their fitness goals. The user enters their goal, such as "I want to do strength training three times a week."

[0398] Plan Generation Method

[0399] The server runs a generative AI model based on the collected basic information and past training data to generate an optimal training plan.

[0400] The device proposes a training plan generated by the generation AI to the user.

[0401] Examples:

[0402] Once the user enters their basic information, the server uses a generative AI to generate a "strength training plan for one hour, three times a week" based on past data and the information entered. The device displays a specific plan such as "Squats and planks on the first day, deadlifts and side lunges on the second day, and bench presses and hip thrusts on the third day."

[0403] Proposal means

[0404] The server sends instructions to propose the training plan generated by the generating means.

[0405] The device will suggest a training plan to the user by voice or display.

[0406] The user reviews the proposed training plans and selects the plan to implement.

[0407] Examples:

[0408] The device will say, "Hello, Mr. / Ms. X. Today's training plan is 30 minutes of strength training." The user will confirm the proposed plan and proceed to the next step.

[0409] Emotion analysis means

[0410] The server uses an emotion engine to analyze the user's voice and facial expressions and collect data to recognize emotions.

[0411] The terminal receives the user's emotional state as feedback based on the analysis results of the emotion engine.

[0412] The user checks the proposals adjusted by emotion recognition and selects a plan to implement.

[0413] Examples:

[0414] If a user tells the device, "I'm not feeling very well today," the emotion engine analyzes this and the device adjusts its suggestions, saying, "You seem to be feeling unwell. I recommend some light stretching and breathing exercises today."

[0415] Anomaly detection means

[0416] The server collects data in real time from various sensors installed within the fitness gym and performs processing to detect abnormalities.

[0417] The device will display an emergency alert if an abnormality is detected.

[0418] Examples:

[0419] If a user falls during training, the heart rate monitor and fall detection sensor will detect the abnormality, and the server will immediately send an alert to the device.

[0420] Emergency response measures

[0421] When an abnormality is detected, the server immediately sends an instruction to switch to emergency response mode.

[0422] The terminal displays the emergency situation, provides specific instructions to the user, and automatically notifies emergency contacts as necessary.

[0423] The user follows the emergency response instructions displayed on the terminal.

[0424] Examples:

[0425] If the user collapses, the device will provide a voice message saying, "This is an emergency. Please rest immediately. We will call an ambulance," and at the same time display the message, "An emergency has occurred. We will notify emergency contact points."

[0426] Prompt Sentence Examples

[0427] 1. Example prompt

[0428] Describe a scenario where a new user enters a fitness gym and scans a QR code to begin their session. The user then introduces themselves and their fitness goals, and the generative AI uses that information to suggest training plans. Include using sentiment analysis to adjust suggestions based on the user's mood.

[0429] In this way, by linking the server, terminal, and user, we have created a system that offers a safe and effective fitness experience by proposing the optimal exercise plan based on the user's emotions and condition and responding quickly in the event of an abnormality.

[0430] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0431] Step 1:

[0432] The server collects data from cameras and sensors installed at the entrances to confirm the user's entry, and processes this data in real time to identify whether the user is a new or existing user.

[0433] Input: Image data and sensor data obtained from cameras and sensors

[0434] Output: User identification information

[0435] How it works: The camera captures the user's image, and sensors collect data such as movement and body temperature. The server analyzes this information to determine whether the user is a new or existing user.

[0436] Step 2:

[0437] If the device recognizes the user as a new user, it displays a screen for scanning a QR code and prompts the user to enter basic information.

[0438] Input: New user identification information received from the server

[0439] Output: QR code scanning screen and basic information input screen

[0440] What it does: The device prepares to scan the QR code and displays the necessary screen. Once the user scans the QR code, the device displays a screen for entering basic information.

[0441] Step 3:

[0442] Users scan a QR code displayed on their device and enter a profile picture and fitness goals.

[0443] Input: QR code, bio information, and fitness goals

[0444] Output: User information entered

[0445] Specific operation: The user scans the QR code using a smartphone or other device, and then enters their fitness goals on the input screen that appears.

[0446] Step 4:

[0447] The server collects basic information and past training data entered by the user and runs a generative AI model to generate an optimal training plan.

[0448] Input: Basic information, past training data, generative AI model

[0449] Power: Optimal training plan

[0450] How it works: The server stores the information received from the user and runs a generative AI model that compares it with past training data. The generative AI model performs calculations and analysis to generate a personalized training plan.

[0451] Step 5:

[0452] The terminal displays the generated training plan to the user and also provides audio guidance.

[0453] Input: Training plan sent from the server

[0454] Output: On-screen training plan and audio guidance

[0455] Specific operation: The device displays the training plan information on the screen, and at the same time, an audio guide guides the user through the plan.

[0456] Step 6:

[0457] The user reviews the proposed training plans and selects the plan to implement.

[0458] Input: Training plan displayed on device

[0459] Output: Selected training plan

[0460] Specific operation: The user checks the screen display and selects the plan they want to implement from the options.

[0461] Step 7:

[0462] The server uses emotion analysis to analyze the user's voice and facial expressions to recognize their emotions, and provides feedback on the content of the suggestions based on this.

[0463] Input: User's voice data, facial expression data

[0464] Output: Parsed emotion information

[0465] Specific operation: The server captures the user's voice and facial expressions, processes the data using emotion analysis, and adjusts the training plan based on the analysis results.

[0466] Step 8:

[0467] The device adjusts suggestions to the user based on the emotion analysis results.

[0468] Input: Sentiment analysis results

[0469] Output: Tailored training plan

[0470] Specific operation: The device receives the emotion analysis results and presents the adjusted training plan to the user again.

[0471] Step 9:

[0472] The server collects data in real time from sensors inside the fitness gym and detects any abnormalities.

[0473] Input: Sensor data

[0474] Output: Abnormal warning

[0475] Specific operation: The server continuously reads data from the sensors and immediately issues an alert if it detects an abnormality.

[0476] Step 10:

[0477] If an abnormality is detected, the device will display an emergency alert and provide specific instructions to the user. It will also automatically notify emergency contacts if necessary.

[0478] Input: Abnormal warning from the server

[0479] Output: Emergency alert display, emergency call

[0480] Specific operation: The device displays an emergency alert and provides instructions to the user, while automatically notifying emergency contacts.

[0481] Step 11:

[0482] The user follows the emergency response instructions displayed on the device and acts safely.

[0483] Input: Emergency response instructions displayed on the terminal

[0484] Output: User's response action

[0485] Specific actions: The user follows the instructions on the device and takes emergency measures, such as taking a rest immediately or providing first aid.

[0486] (Application example 2)

[0487] 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."

[0488] To improve the work efficiency and safety of robots in modern factories, it is essential to propose efficient and flexible work plans, detect abnormalities, and respond to emergencies. However, conventional systems lack sufficient automation to meet these requirements, and many tasks must be performed manually by managers, hindering efficiency. Furthermore, it is difficult to analyze the robot's work status and performance in real time and propose optimal work plans based on that analysis. Furthermore, rapid response is also required in the event of an emergency.

[0489] The identification process by the identification 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 a data input means used to input data of a new user, a generation means for generating a work plan based on past work data and basic information about the user, a proposal means for proposing the generated work plan to the user, a detection means for detecting anomalies, a response means for taking emergency action when an anomaly is detected, and an emotion analysis means for monitoring and adjusting the efficiency state of the user. This enables flexible and rapid response while improving the work efficiency of the robot and ensuring safety.

[0490] A "new user" is an individual or device that begins using the system for the first time.

[0491] "Data input means" refers to a device or program for collecting basic information about users and past work data.

[0492] "Task data" refers to information about the history and performance of tasks performed by a robot in the past.

[0493] "Basic information" refers to information about the attributes, goals, and initial settings of a user or robot.

[0494] A "task plan" is a specific plan created to allow a robot to efficiently perform a task.

[0495] The "generation means" is a program or device for generating an optimal work plan based on collected data.

[0496] The "proposing means" is a device or program that notifies the user of the generated work plan and encourages execution.

[0497] "Detection means" refers to sensors or programs used to detect abnormalities.

[0498] "Response means" refers to a device or program for carrying out an emergency response when an abnormality is detected.

[0499] "Emotion analysis means" refers to a program or device for monitoring and analyzing the efficiency and performance of a user or robot.

[0500] The present invention is a system that collects data on new users and robots, generates and proposes appropriate work plans, and detects and responds to anomalies. This system is realized by combining programs, hardware, and software. Each component and its processing are described in detail below.

[0501] Data Entry Method

[0502] The server monitors the robot's location and working status using cameras and sensors installed in the factory, and collects identification data when a new robot is introduced. When a new robot is introduced, the terminal displays a screen for scanning a QR code and provides a screen for entering basic information such as training goals. The user scans the QR code of the new robot and enters basic information and work goals.

[0503] generation means

[0504] The server runs a generative AI model based on the collected basic information and past work data to generate an appropriate work plan. This data is combined with previously collected historical data and analyzed. The generative AI model used is OpenAI's GPT-4, and the generated work plan is presented to the administrator's device.

[0505] Proposal means

[0506] The server sends instructions to the robot's AI to propose the generated work plan to the robot. The proposed work plan is presented to the terminal by voice and display. The administrator checks it and adjusts it as necessary.

[0507] Emotion analysis means

[0508] The server analyzes the robot's work performance data and managerial feedback to provide efficient work plans as feedback. TensorFlow is used as the emotion analysis engine.

[0509] Detection Method

[0510] The server collects data in real time from various sensors installed in the factory and detects any abnormalities, which are immediately notified to the administrator.

[0511] Countermeasures

[0512] When an abnormality is detected, the server sends an instruction to the robot's AI to switch to emergency response mode. The emergency situation is displayed on the terminal, and specific instructions for countermeasures are shown to the administrator.

[0513] Specific examples

[0514] When a new robot is introduced, the manager scans a QR code on the terminal and inputs basic information and work goals. For example, a work plan is generated based on basic information such as "New robot, Type X, goal is to improve picking efficiency" and past data such as "Processed 1,000 pieces in the past month."

[0515] Here is an example prompt:

[0516] Robot Basics: Type A, the goal is to improve picking efficiency

[0517] Historical data: 1000 pieces processed for the past month

[0518] Generate efficient work plans for this robot.

[0519] The program uses OpenAI GPT-4 to generate optimal work plans for the robots and TensorFlow to perform emotion analysis of the robots, improving work efficiency and ensuring safety.

[0520] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0521] Step 1: Data entry method

[0522] The server monitors the robot's location and working status in real time using cameras and sensors installed in the factory. When a new robot is introduced, the server collects and stores its identification data. The terminal displays a QR code scanning screen dedicated to the new robot, which the manager scans to enter basic information and work goals. The entered basic information (e.g., robot type, purpose) and work goals (e.g., improving the efficiency of picking work) are then transferred to the server.

[0523] Step 2: Generator

[0524] The server runs a generative AI model using the collected basic information and past work data. Specifically, it uses OpenAI GPT-4 to generate a work plan. Based on this prompt (e.g., "Robot basic information: Type A, goal is to improve picking efficiency. Past data: processed 1,000 pieces in the past month. Please generate an efficient work plan for this robot."), the generative AI model generates an optimal work plan. The generated work plan is sent from the server to the device.

[0525] Step 3: Proposal method

[0526] The server sends the generated work plan to the AI ​​inside the robot. The proposed work plan is displayed on the terminal and reviewed by the manager. For example, a specific work plan may be proposed, such as "focus on picking work on the first day, and maintenance work on the next day." The manager can adjust the work plan as necessary and finalize it.

[0527] Step 4: Sentiment Analysis Methods

[0528] The server analyzes work performance data collected from the factory robots and feedback from managers in real time. The sentiment analysis engine uses TensorFlow to analyze the robot's efficiency and whether there are any abnormalities. For example, if the robot's movements are slow, this may indicate a decrease in efficiency or an abnormality. The analysis results are notified to the terminal as feedback from the server.

[0529] Step 5: Detection Methods

[0530] The server collects data in real time from various sensors installed in the factory and detects abnormalities. For example, if a robot is not performing its scheduled operation or is overloaded, the server will immediately detect the abnormality based on the data from the sensor. The detected data is analyzed by the server, and if an abnormality is confirmed, the administrator is notified.

[0531] Step 6: Response measures

[0532] When an abnormality is detected, the server immediately sends an instruction to the AI ​​in the robot to switch to emergency response mode. The terminal displays the emergency situation and provides the administrator with specific response instructions (e.g., stop the robot and instruct a human to inspect it). In addition, if necessary, an automatic notification is sent to emergency contacts (e.g., technical support or emergency contacts). The administrator follows the emergency response instructions displayed on the terminal and takes appropriate action.

[0533] 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.

[0534] 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.

[0535] 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.

[0536] [Second embodiment]

[0537] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0538] 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.

[0539] 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).

[0540] 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.

[0541] 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.

[0542] 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).

[0543] 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.

[0544] 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.

[0545] 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.

[0546] 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.

[0547] 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.

[0548] 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."

[0549] This invention is a system that allows users to train efficiently and safely at a 24-hour fitness gym. This system includes a data input means, a generation means, a proposal means, a detection means, and a response means. The function of each means is explained below with specific examples.

[0550] Data Entry Method

[0551] Server: Collects data from cameras and sensors installed at the entrance to detect when a user arrives at the gym.

[0552] Device: When the user scans the QR code, a screen will appear prompting them to enter basic information (fitness experience, goals, etc.).

[0553] User: Enter a self-introduction and fitness goals into the input screen displayed on the device.

[0554] Example: When a user scans a QR code at the entrance, a screen appears on the device asking them to introduce themselves and enter their fitness goals. The user enters their goal as "I want to do strength training three times a week."

[0555] generation means

[0556] Server: Runs the generation AI to generate training plans based on the collected basic information and past training data.

[0557] Terminal: Proposes the training plan generated by the generation AI to the user.

[0558] Example: When a user enters basic information, the server uses a generative AI to generate a "strength training plan for one hour, three times a week" based on past data and the entered information. The device displays a specific plan such as "Squats and planks on the first day, deadlifts and side lunges on the second day, and bench presses and hip thrusts on the third day."

[0559] Proposal means

[0560] Server: Sends instructions to PepperGPT to suggest the training plan generated by the generator to the user.

[0561] Device: PepperGPT will propose the generated training plan to the user via voice and display.

[0562] User: Review the proposed training plans and select the plan they wish to implement.

[0563] Example: PepperGPT will say, "Hello, Mr. / Ms. X. Today's training plan is 30 minutes of strength training. Let's start with squats." The user will confirm the proposed plan and proceed to the next step.

[0564] Detection Method

[0565] Server: Collects data in real time from various sensors installed within the fitness gym and processes it to detect abnormalities.

[0566] Device: Prepare to display an emergency alert if an anomaly is detected.

[0567] Example: If a user falls during training, the heart rate monitor and fall detection sensor will detect the abnormality and the server will immediately send an alert to the device.

[0568] Countermeasures

[0569] Server: When an abnormality is detected, it immediately sends an instruction to PepperGPT to switch to emergency response mode.

[0570] Terminal: The terminal displays the emergency situation and provides specific instructions to the user. It also automatically notifies emergency contacts as needed.

[0571] User: Follow the emergency response instructions displayed on the device.

[0572] Example: If a user collapses, PepperGPT will provide a voice prompt saying, "This is an emergency. Please rest immediately. We will call an ambulance," and the device will simultaneously display, "An emergency has occurred. We will notify emergency contacts."

[0573] The above is a specific embodiment for carrying out the present invention. This system allows users to easily obtain an efficient training plan and also enables quick response in emergencies.

[0574] The processing flow will be explained below.

[0575] New User Guide

[0576] Step 1:

[0577] Server: Collects data from cameras and sensors installed at the entrance to confirm the user's entry and identifies whether the user is a new user.

[0578] Step 2:

[0579] Device: If a new user is identified, a screen for scanning a QR code will be displayed on the device.

[0580] Step 3:

[0581] User: Scan the QR code displayed on the device to start using the service.

[0582] Step 4:

[0583] Terminal: Displays a screen where users can enter basic information such as their fitness experience and goals.

[0584] Step 5:

[0585] User: Enter a profile and fitness goals into the device.

[0586] Step 6:

[0587] Server: Processes the basic information entered and sends a command to PepperGPT to start facility guidance.

[0588] Step 7:

[0589] Terminal: PepperGPT begins to provide voice guidance to the user, saying, "Hello, you are a new user. We will show you how to use the facility."

[0590] Short workout suggestions

[0591] Step 1:

[0592] User: Enter a time limit into the terminal, such as "Only 30 minutes available today."

[0593] Step 2:

[0594] Terminal: Sends the entered time limit to the server.

[0595] Step 3:

[0596] Server: Runs the generative AI to generate effective workout plans in a short amount of time based on past training data and basic user information.

[0597] Step 4:

[0598] Terminal: Displays the generated workout plan to the user.

[0599] Step 5:

[0600] User: Check the training plan displayed on the device and decide whether to carry it out.

[0601] Step 6:

[0602] Server: Optimizes training plans based on user feedback.

[0603] Goal setting support

[0604] Step 1:

[0605] User: Enter a specific goal into the device, such as "lose 5 kg in 3 months."

[0606] Step 2:

[0607] Terminal: Sends the entered goal to the server.

[0608] Step 3:

[0609] Server: Based on the input goal, the generation AI proposes a feasible method and timeframe for achieving the goal.

[0610] Step 4:

[0611] Device: The generated advice is displayed to the user and read aloud by PepperGPT.

[0612] Step 5:

[0613] User: Review the proposed goals and methods, make adjustments as needed, and finalize the goal setting.

[0614] Step 6:

[0615] Server: Stores the adjusted goals and methods and periodically tracks the user's progress.

[0616] Emergency Response Support

[0617] Step 1:

[0618] Server: Collects data in real time from heart rate monitors and fall detection sensors installed within the facility and detects abnormalities.

[0619] Step 2:

[0620] Terminal: Prepare to display an emergency situation if an abnormality is detected.

[0621] Step 3:

[0622] Server: When an abnormality is detected, it immediately sends an instruction to PepperGPT to switch to emergency response mode.

[0623] Step 4:

[0624] Device: An emergency message will be displayed on the device, along with specific steps to take. Emergency contacts will also be notified automatically.

[0625] Step 5:

[0626] User: Follow the emergency response instructions displayed on the device and, if necessary, seek assistance until the situation improves.

[0627] The above are the specific processing steps of this system. At each processing step, the server, terminal, and user work together to provide efficient training support.

[0628] Example 1

[0629] 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."

[0630] At current fitness gyms, users need a lot of time and effort to find an appropriate training plan that suits their individual fitness experience and goals. Real-time monitoring and rapid response to abnormalities to ensure user safety are also difficult. Therefore, there is a need for a system that allows users to train efficiently and safely.

[0631] 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.

[0632] In this invention, the server includes a data input means for inputting user data, a generation means for generating a training plan based on past training data and basic information about the user, a proposal means for proposing the generated training plan to the user, a detection means for detecting abnormalities, a response means for taking emergency action when an abnormality is detected, a means for collecting data from cameras and sensors to detect the arrival of the user, and a means for providing audio and visual guidance on the proposed training plan. This allows users to efficiently obtain training plans, monitors safety in real time, and enables rapid response to abnormalities.

[0633] "Data input means" refers to a device or method by which a user inputs basic information such as training information and goals.

[0634] "Generation means" refers to a device or method for creating an appropriate training plan based on collected data.

[0635] The "suggestion means" is a device or method for proposing the generated training plan to the user.

[0636] "Detection means" refers to a device or method for detecting abnormalities in users using sensors or cameras within the fitness gym.

[0637] "Response means" refers to a device or method for taking emergency action when an abnormality is detected.

[0638] "Means for collecting data from cameras and sensors" refers to devices or methods that detect the arrival or movement of users and collect data based on that.

[0639] "Means for providing audio or visual guidance on a training plan" refers to a device or method for providing audio guidance or displaying a generated training plan on a terminal screen to a user.

[0640] MODE FOR CARRYING OUT THE INVENTION

[0641] This invention is a system that allows users to train efficiently and safely at a 24-hour fitness gym. This system includes a data input means, a generation means, a proposal means, a detection means, and a response means. The functions of each means and specific operation examples are shown below.

[0642] Data Entry Method

[0643] Server: To detect when a user arrives at the gym, the server collects data from cameras and sensors installed at the entrance. The server analyzes this data and confirms that the user has arrived at the gym.

[0644] Terminal: When a user scans the QR code installed at the gym entrance, a screen will appear prompting them to enter basic information (fitness experience, goals, etc.), making it easy for users to enter the required information.

[0645] User: Enters a self-introduction and fitness goals into the input screen displayed on the device. Specifically, the user enters a goal such as "I want to do strength training three times a week."

[0646] generation means

[0647] Server: Based on the collected basic information and past training data, a training plan is generated using a "generative AI model." This generative AI model can be, for example, "ChatGPT Turbo."

[0648] Example: When a user enters basic information, the server uses training AI to generate a "strength training plan for one hour, three times a week" based on past data and the entered information. The generated plan contains specific content, and the device displays a specific plan such as "Squats and planks on the first day, deadlifts and side lunges on the second day, and bench presses and hip thrusts on the third day."

[0649] Proposal means

[0650] Server: Sends instructions to PepperGPT to suggest the generated training plan to the user.

[0651] On the device, PepperGPT will propose the generated training plan to the user via voice and display. For example, it might say, "Hello, Mr. / Ms. X. Today's training plan is 30 minutes of strength training. Let's start with squats."

[0652] Detection Method

[0653] Server: Collects data in real time from various sensors installed in the fitness gym and processes it to detect abnormalities. For example, heart rate monitors and fall detection sensors are used.

[0654] Terminal: Prepare to display an emergency alert if an abnormality is detected. When the server detects an abnormality, it immediately sends an alert to the terminal.

[0655] Example: If a user falls during training, the heart rate monitor and fall detection sensor will detect the abnormality and the server will immediately send an alert to the device.

[0656] Countermeasures

[0657] Server: When an abnormality is detected, PepperGPT is immediately instructed to switch to emergency response mode, enabling a rapid response.

[0658] Terminal: The terminal displays the emergency situation and provides specific instructions to the user. It also automatically notifies emergency contacts as needed.

[0659] User: Follow the emergency response instructions displayed on the device. For example, PepperGPT will say, "This is an emergency. Please rest immediately. We will call an ambulance," and the device will simultaneously display, "Emergency situation has occurred. We will notify emergency contacts."

[0660] Prompt Sentence Examples

[0661] A user arrives at the gym. They scan a QR code to enter their basic information and fitness goals. For example, "I want to do one hour of strength training three times a week." Once they've completed the input, they can begin generating a training plan.

[0662] This system allows users to easily obtain efficient training plans and also enables quick response in emergencies.

[0663] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0664] Step 1:

[0665] User arrival detection

[0666] Server: Operates the camera and sensor system installed at the gym entrance.

[0667] Input: Images and data captured from cameras and sensors.

[0668] Data processing: Image analysis is used to recognize people's movements and faces.

[0669] Output: A flag confirming the user's arrival.

[0670] How it works: The camera captures the user's image data, the sensor detects their presence, and the server analyzes this data to recognize the user's arrival.

[0671] Step 2:

[0672] Prompt for QR code scanning and basic information entry

[0673] Terminal: When the user scans the QR code installed at the entrance, a screen for entering basic information is displayed.

[0674] Input: User ID via QR code scan.

[0675] Data processing: Decode the contents of the QR code and extract the user ID.

[0676] Output: Basic information input screen.

[0677] Specific operation: The QR code is scanned with the device's camera. The device then displays an input screen prompting the user to "Enter your name, age, fitness experience, and goals."

[0678] Step 3:

[0679] Enter your basic information and fitness goals

[0680] User: Enter basic information and fitness goals.

[0681] Input: Basic information entered by the user into the input screen (name, age, fitness experience, goals).

[0682] Data Calculation: Validation and storage of input data.

[0683] Output: User's basic information and goals.

[0684] Specific Action: A user inputs a fitness goal: "I want to do strength training three times a week."

[0685] Step 4:

[0686] Generate a training plan

[0687] Server: Runs the generative AI model based on collected basic information and past training data.

[0688] Input: User's basic information and past training data.

[0689] Data processing: Inputting and analyzing data into generative AI models.

[0690] Output: The generated training plan.

[0691] Specific operation: The server uses training AI to generate a "strength training plan for one hour, three times a week" based on past data and input information. The generated plan contains specific content.

[0692] Step 5:

[0693] Training plan suggestions

[0694] Server: Sends the generated training plan to PepperGPT.

[0695] Input: The generated training plan.

[0696] Data processing: Instructions for sending training plan.

[0697] Output: Suggested instructions to PepperGPT.

[0698] Specific operation: Details of the generated training plan are sent to PepperGPT via API.

[0699] Device: PepperGPT will suggest training plans to the user via voice and display.

[0700] Input: Proposal data from PepperGPT.

[0701] Data processing: speech synthesis and display on the screen.

[0702] Output: Suggestions to the user.

[0703] Specific actions: PepperGPT will guide you by saying, "Hello, Mr. / Ms. XX. Today's training plan is 30 minutes of strength training. Let's start with squats."

[0704] Step 6:

[0705] Monitoring during training

[0706] Server: Collects data in real time from various sensors within the fitness gym and processes it to detect abnormalities.

[0707] Input: Data from heart rate monitors and fall detection sensors.

[0708] Data processing: Real-time analysis for anomaly detection.

[0709] Output: Anomaly detection flag.

[0710] Specific operation: The server receives data from the heart rate monitor and fall detection sensor in real time and analyzes it to detect abnormalities.

[0711] Step 7:

[0712] Emergency response

[0713] Server: When an abnormality is detected, it immediately sends an instruction to PepperGPT to switch to emergency response mode.

[0714] Input: Anomaly detection flag.

[0715] Data processing: Generation of emergency response instructions.

[0716] Output: Emergency response instructions to PepperGPT.

[0717] Specific operation: The server sends emergency response instructions to PepperGPT through the API, causing it to immediately begin emergency response.

[0718] Terminal: Provides emergency response instructions to the user via voice and display, and also notifies emergency contacts as necessary.

[0719] Input: Emergency response instructions from the server.

[0720] Data processing: Voice synthesis and on-screen display of emergency instructions.

[0721] Output: Instructs the user on emergency measures and makes an emergency call.

[0722] Specific operation: The device displays "Emergency! Please stay still until an ambulance arrives" and automatically calls emergency contacts.

[0723] Users: Follow emergency plan instructions.

[0724] Input: Emergency instructions from terminal.

[0725] Data calculation: Deciding on actions based on instructions.

[0726] Output: Safety action.

[0727] Specific actions: The user follows the instructions to stay calm and wait for the ambulance to arrive.

[0728] (Application example 1)

[0729] 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."

[0730] To ensure that new users can train efficiently and safely at fitness facilities, it is necessary to provide individually tailored training plans and monitor safety in real time. However, traditional fitness facilities face challenges such as users having to make their own decisions when training, which increases the risk of users training incorrectly and makes it difficult to respond quickly to emergencies. Furthermore, providing users with training plans tailored to their individual fitness goals requires processing large amounts of data, making it difficult to perform complex calculations in real time.

[0731] 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.

[0732] In this invention, the server includes a generating means for generating a training plan based on past training data and basic information of the user, a means for generating and inputting prompts to the generating AI model to generate a training plan suited to the user's fitness goals using the generating AI model, a suggesting means for suggesting and notifying the user of the generated training plan and emergency alerts, a detecting means for acquiring data in real time from sensors installed in the fitness facility and detecting abnormalities, and a responding means for taking emergency action when an abnormality is detected. This makes it possible to provide users with efficient and individually tailored training plans, while simultaneously enabling rapid response to emergencies and ensuring safety.

[0733] A "new user" is someone using a fitness facility for the first time, or an existing user who needs a new training plan.

[0734] "Data entry means" refers to the tools and methods used to enter basic information about the user, fitness goals, past training data, etc.

[0735] "Generation means" refers to tools and methods for generating an appropriate training plan based on input data and past training information.

[0736] A "generative AI model" refers to an algorithm or system that uses artificial intelligence to process data and generate an appropriate training plan.

[0737] A "prompt" refers to a specific form of sentence used to give specific instructions or questions to a generative AI model.

[0738] "Proposal means" refers to the tools and methods used to propose and notify users of generated training plans and emergency alerts.

[0739] "Detection Methods" means tools or methods for detecting abnormal conditions or emergencies based on data from sensors installed within a fitness facility.

[0740] "Response measures" refer to tools and methods for quickly taking appropriate action when an abnormality or emergency is detected.

[0741] The present invention provides a system for enabling users to train efficiently and safely in a fitness facility, the system including a data input means, a generating means, a suggesting means, a detecting means, and a responding means.

[0742] Data Entry Method

[0743] The server collects data from cameras and sensors installed at the entrances of fitness facilities and detects the arrival of users. When the user scans a QR code, the device displays a screen prompting them to enter basic information (fitness experience, goals, etc.). Through this screen, the user enters their self-introduction and fitness goals. For example, when a user scans a QR code at the entrance, a screen prompting them to enter their self-introduction and fitness goals appears on the device, and the user enters their goal, such as "I want to do strength training three times a week."

[0744] generation means

[0745] The server runs a generative AI model to generate a training plan based on the collected basic information and past training data. A means for generating and inputting prompts for the generative AI model is included. For example, when a user inputs basic information, the server uses the generative AI model to generate a "strength training plan for one hour, three times a week" based on the past data and the input information, using the following prompt:

[0746] Username: "User A"

[0747] Fitness Experience: "Intermediate"

[0748] Fitness goal: "Strength training three times a week"

[0749] Past training data: "Squat", "Deadlift"

[0750] The device displays a specific plan, such as "Day 1: Squats and planks, Day 2: Deadlifts and side lunges, Day 3: Bench presses and hip thrusts."

[0751] Proposal means

[0752] The server sends instructions to the terminal to propose the training plan generated by the generation means to the user. After this, the terminal proposes the generated training plan to the user by voice or display. The user checks the proposed training plan and selects the plan to implement. For example, the terminal may say, "Today's training plan is 30 minutes of strength training. Let's start with squats," and the user may confirm the proposed plan.

[0753] Detection Method

[0754] The server collects data from various sensors installed in the fitness facility in real time and processes it to detect abnormalities. For example, if a user falls during training, the heart rate monitor or fall detection sensor will detect the abnormality and the server will immediately send an alert to the device.

[0755] Countermeasures

[0756] When an abnormality is detected, the server immediately sends an instruction to switch to emergency response mode. The device displays the emergency situation and provides the user with specific instructions on what to do. It also automatically notifies emergency contacts if necessary. For example, if the user collapses, the device will announce in voice, "This is an emergency. Please rest immediately. We will call an ambulance," and at the same time display, "An emergency has occurred. We will notify emergency contacts."

[0757] The above is a specific embodiment for carrying out the present invention. This system allows users to easily obtain an efficient training plan and also enables quick response in emergencies.

[0758] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0759] Step 1:

[0760] When a user arrives at a fitness facility, they scan a QR code at the entrance. The device then displays a screen where the user can enter their basic information and fitness goals. Once the user has finished entering their information, the data is sent to the server.

[0761] Input: User basic information, fitness goals

[0762] Data processing / data calculation: Collection and storage of input data

[0763] Output: Send user information to the server

[0764] Step 2:

[0765] The server runs a generative AI model to generate a training plan based on the collected basic information and past training data. The server provides the specified prompt sentences to the generative AI model to create an appropriate training plan.

[0766] Input: User's basic information, past training data

[0767] Data processing / data calculation: Prompt generation for generative AI models and training plan generation

[0768] Output: Generated training plan

[0769] Step 3:

[0770] The server sends the generated training plan to the device, which then presents it to the user via voice guidance and on-screen display. The user can then review the proposed training plans and select the one they wish to implement.

[0771] Input: Generated training plan

[0772] Data processing / data calculation: Display of training plan and voice guidance

[0773] Output: User confirms and selects training plan

[0774] Step 4:

[0775] The server collects data in real time from various sensors installed in the fitness center and processes it to detect abnormalities. Based on the data collected from the sensors, it determines whether there are any abnormalities.

[0776] Input: Real-time data from sensors

[0777] Data processing / data calculation: Real-time data analysis and anomaly detection

[0778] Output: Anomaly detection results

[0779] Step 5:

[0780] When an abnormality is detected, the server immediately sends an instruction to switch to emergency response mode. The device notifies the user of the emergency through voice guidance and on-screen display, and automatically notifies emergency contacts if necessary. The user follows the instructions on the device and takes appropriate action.

[0781] Input: Anomaly detection results, user location, contact information

[0782] Data processing / data calculation: generation and notification of emergency response instructions

[0783] Output: Emergency response and automatic notification

[0784] By following these steps, a system is realized that provides effective training plans while ensuring the safety of users within a fitness facility.

[0785] 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.

[0786] This invention is a system that enables users to train efficiently and safely at a 24-hour fitness gym. This system is provided by combining a data input means, a generation means, a proposal means, a detection means, a response means, and an emotion engine. The function of each means is explained below with specific examples.

[0787] Data Entry Method

[0788] Server: Collects data from cameras and sensors installed at the entrance to confirm the user's entry and identifies whether the user is a new user.

[0789] Device: If a new user is identified, a screen for scanning a QR code will be displayed on the device.

[0790] User: Scan the QR code displayed on the device to start using the service.

[0791] Terminal: Displays a screen where users can enter basic information such as their fitness experience and goals.

[0792] User: Enter a profile and fitness goals into the device.

[0793] Example: When a user scans a QR code at the entrance, a screen appears on the device asking them to introduce themselves and enter their fitness goals. The user enters their goal as "I want to do strength training three times a week."

[0794] generation means

[0795] Server: Runs the generation AI to generate training plans based on the collected basic information and past training data.

[0796] Terminal: Proposes the training plan generated by the generation AI to the user.

[0797] Example: When a user enters basic information, the server uses a generative AI to generate a "strength training plan for one hour, three times a week" based on past data and the entered information. The device displays a specific plan such as "Squats and planks on the first day, deadlifts and side lunges on the second day, and bench presses and hip thrusts on the third day."

[0798] Proposal means

[0799] Server: Sends instructions to PepperGPT to suggest the training plan generated by the generator to the user.

[0800] Device: PepperGPT will propose the generated training plan to the user via voice and display.

[0801] User: Review the proposed training plans and select the plan they wish to implement.

[0802] Example: PepperGPT will say, "Hello, Mr. / Ms. X. Today's training plan is 30 minutes of strength training. Let's start with squats." The user will confirm the proposed plan and proceed to the next step.

[0803] Emotion Engine

[0804] Server: The emotion engine collects data to analyze the user's voice and facial expressions and recognize emotions.

[0805] Terminal: The emotion engine receives feedback on the user's emotional state based on the analysis results.

[0806] User: Review the suggestions tailored through emotion recognition and select a plan to implement.

[0807] Example: If a user says to their device, "I'm not feeling very well today," the emotion engine will analyze this and PepperGPT will adjust its suggestions, saying, "It seems like you're not feeling well. I recommend some light stretching and breathing exercises today."

[0808] Detection Method

[0809] Server: Collects data in real time from various sensors installed within the fitness gym and processes it to detect abnormalities.

[0810] Device: Prepare to display an emergency alert if an anomaly is detected.

[0811] Example: If a user falls during training, the heart rate monitor and fall detection sensor will detect the abnormality and the server will immediately send an alert to the device.

[0812] Countermeasures

[0813] Server: When an abnormality is detected, it immediately sends an instruction to PepperGPT to switch to emergency response mode.

[0814] Terminal: The terminal displays the emergency situation and provides specific instructions to the user. It also automatically notifies emergency contacts as needed.

[0815] User: Follow the emergency response instructions displayed on the device.

[0816] Example: If a user collapses, PepperGPT will provide a voice prompt saying, "This is an emergency. Please rest immediately. We will call an ambulance," and the device will simultaneously display, "An emergency has occurred. We will notify emergency contacts."

[0817] The above is a specific embodiment for carrying out the present invention. By combining it with an emotion engine, it becomes possible to propose flexible training plans that take into account the user's emotional state, which is expected to improve user satisfaction to a greater extent.

[0818] The processing flow will be explained below.

[0819] New User Guide

[0820] Step 1:

[0821] Server: Collects data from cameras and sensors installed at the entrance to confirm the user's entry and identifies whether the user is a new user.

[0822] Step 2:

[0823] Device: If a new user is identified, a screen for scanning a QR code will be displayed on the device.

[0824] Step 3:

[0825] User: Scan the QR code displayed on the device to start using the service.

[0826] Step 4:

[0827] Terminal: Displays a screen where users can enter basic information such as their fitness experience and goals.

[0828] Step 5:

[0829] User: Enter a profile and fitness goals into the device.

[0830] Step 6:

[0831] Server: Processes the basic information entered and sends a command to PepperGPT to start facility guidance.

[0832] Step 7:

[0833] Terminal: PepperGPT begins to provide voice guidance to the user, saying, "Hello, you are a new user. We will show you how to use the facility."

[0834] Short workout suggestions

[0835] Step 1:

[0836] User: Enter a time limit into the terminal, such as "Only 30 minutes available today."

[0837] Step 2:

[0838] Terminal: Sends the entered time limit to the server.

[0839] Step 3:

[0840] Server: Runs the generative AI to generate effective workout plans in a short amount of time based on past training data and basic user information.

[0841] Step 4:

[0842] Terminal: Displays the generated workout plan to the user.

[0843] Step 5:

[0844] User: Check the training plan displayed on the device and decide whether to carry it out.

[0845] Step 6:

[0846] Server: Optimizes training plans based on user feedback.

[0847] Goal setting support

[0848] Step 1:

[0849] User: Enter a specific goal into the device, such as "lose 5 kg in 3 months."

[0850] Step 2:

[0851] Terminal: Sends the entered goal to the server.

[0852] Step 3:

[0853] Server: Based on the input goal, the generation AI proposes a feasible method and timeframe for achieving the goal.

[0854] Step 4:

[0855] Device: The generated advice is displayed to the user and read aloud by PepperGPT.

[0856] Step 5:

[0857] User: Review the proposed goals and methods, make adjustments as needed, and finalize the goal setting.

[0858] Step 6:

[0859] Server: Stores the adjusted goals and methods and periodically tracks the user's progress.

[0860] Emotion Engine

[0861] Step 1:

[0862] Server: Collects data for the emotion engine to analyze the user's voice and facial expressions to recognize emotions.

[0863] Step 2:

[0864] Terminal: The emotion engine receives feedback on the user's emotional state based on the analysis results.

[0865] Step 3:

[0866] User: Review the suggestions tailored through emotion recognition and select a plan to implement.

[0867] Step 4:

[0868] Server: Based on the user's emotional data, the server adjusts the training plan and suggestions accordingly.

[0869] Step 5:

[0870] On the device: The adjustment results are displayed to the user, and PepperGPT provides voice guidance.

[0871] Example: If a user says to their device, "I'm not feeling very well today," the emotion engine will analyze this and PepperGPT will adjust its suggestions, saying, "It seems like you're not feeling well. I recommend some light stretching and breathing exercises today."

[0872] Detection Method

[0873] Step 1:

[0874] Server: Collects data in real time from various sensors installed within the fitness gym and processes it to detect abnormalities.

[0875] Step 2:

[0876] Device: Prepare to display an emergency alert if an anomaly is detected.

[0877] Example: If a user falls during training, the heart rate monitor and fall detection sensor will detect the abnormality and the server will immediately send an alert to the device.

[0878] Countermeasures

[0879] Step 1:

[0880] Server: When an abnormality is detected, it immediately sends an instruction to PepperGPT to switch to emergency response mode.

[0881] Step 2:

[0882] Terminal: The terminal displays the emergency situation and provides specific instructions to the user. It also automatically notifies emergency contacts as needed.

[0883] Step 3:

[0884] User: Follow the emergency response instructions displayed on the device.

[0885] Example: If a user collapses, PepperGPT will provide a voice prompt saying, "This is an emergency. Please rest immediately. We will call an ambulance," and the device will simultaneously display, "An emergency has occurred. We will notify emergency contacts."

[0886] The above is a specific embodiment for carrying out the present invention. By combining it with an emotion engine, it becomes possible to propose flexible training plans that take into account the user's emotional state, which is expected to improve user satisfaction to a greater extent.

[0887] Example 2

[0888] 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."

[0889] In conventional fitness gyms, it is difficult for users to independently adjust their training plans to suit their own physical condition and emotional state, and quick response is required when abnormalities occur. Furthermore, there is a lack of systems that utilize individual user data to provide optimal exercise plans. To solve this problem, there is a need for an integrated fitness support system that includes flexible proposals that take users' emotional state into account and quick response when abnormalities occur.

[0890] 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.

[0891] In this invention, the server

[0892] a data capture means used to input new user data;

[0893] A plan generation means for generating an exercise plan based on past exercise data and basic information of the user;

[0894] a suggestion means for suggesting the generated exercise plan to a user;

[0895] an anomaly detection means for detecting an anomaly;

[0896] an emergency response means for taking emergency action when an abnormality is detected;

[0897] emotion analysis means for analyzing the user's voice and facial expression to recognize emotions;

[0898] a voice suggestion means for suggesting an exercise plan to a user by voice;

[0899] Includes:

[0900] This will enable the system to propose flexible training plans that take into account the user's emotional state, as well as to respond quickly and appropriately in the event of an emergency.

[0901] "Data acquisition means" refers to the devices or systems used to input user data, such as cameras or sensors installed at entrances or the QR code scanning function displayed on terminals.

[0902] The "plan generation means" is a function that generates an optimal exercise plan based on collected past exercise data and basic information of the user. This includes a generative AI model.

[0903] The "suggestion means" refers to a means for presenting the generated exercise plan to the user, including a display on the device and audio guidance.

[0904] "Anomaly detection means" refers to sensors or monitoring systems that detect abnormalities within the fitness gym. Examples include heart rate monitors and fall detection sensors.

[0905] "Emergency response measures" are measures for taking prompt and appropriate action when an abnormality is detected, including displaying an emergency alert and automatically notifying emergency contacts.

[0906] "Emotion analysis means" refers to a system that analyzes a user's voice and facial expressions to recognize their emotional state. This includes voice analysis software and facial expression recognition technology.

[0907] The "audio suggestion means" refers to a means for suggesting the generated exercise plan to the user by voice, including a voice assistant function and a speaker.

[0908] This invention is a system that allows users to train efficiently and safely at a 24-hour fitness gym. This system is provided by combining a data acquisition means, a plan generation means, a proposal means, an anomaly detection means, an emergency response means, and an emotion analysis means. The specific functions and operations of each means are described below.

[0909] Data Acquisition Method

[0910] The server collects data from cameras and sensors installed at the entrance to confirm the user's entry and, based on this data, distinguishes between new and existing users.

[0911] If the device recognizes the user as a new user, it displays a screen for scanning a QR code and prompts the user to enter basic information.

[0912] Users scan a QR code displayed on their device and enter a profile picture and fitness goals.

[0913] Examples:

[0914] When users scan the QR code at the entrance, a screen appears on the device where they can introduce themselves and enter their fitness goals. The user enters their goal, such as "I want to do strength training three times a week."

[0915] Plan Generation Method

[0916] The server runs a generative AI model based on the collected basic information and past training data to generate an optimal training plan.

[0917] The device proposes a training plan generated by the generation AI to the user.

[0918] Examples:

[0919] Once the user enters their basic information, the server uses a generative AI to generate a "strength training plan for one hour, three times a week" based on past data and the information entered. The device displays a specific plan such as "Squats and planks on the first day, deadlifts and side lunges on the second day, and bench presses and hip thrusts on the third day."

[0920] Proposal means

[0921] The server sends instructions to propose the training plan generated by the generating means.

[0922] The device will suggest a training plan to the user by voice or display.

[0923] The user reviews the proposed training plans and selects the plan to implement.

[0924] Examples:

[0925] The device will say, "Hello, Mr. / Ms. X. Today's training plan is 30 minutes of strength training." The user will confirm the proposed plan and proceed to the next step.

[0926] Emotion analysis means

[0927] The server uses an emotion engine to analyze the user's voice and facial expressions and collect data to recognize emotions.

[0928] The terminal receives the user's emotional state as feedback based on the analysis results of the emotion engine.

[0929] The user checks the proposals adjusted by emotion recognition and selects a plan to implement.

[0930] Examples:

[0931] If a user tells the device, "I'm not feeling very well today," the emotion engine analyzes this and the device adjusts its suggestions, saying, "You seem to be feeling unwell. I recommend some light stretching and breathing exercises today."

[0932] Anomaly detection means

[0933] The server collects data in real time from various sensors installed within the fitness gym and performs processing to detect abnormalities.

[0934] The device will display an emergency alert if an abnormality is detected.

[0935] Examples:

[0936] If a user falls during training, the heart rate monitor and fall detection sensor will detect the abnormality, and the server will immediately send an alert to the device.

[0937] Emergency response measures

[0938] When an abnormality is detected, the server immediately sends an instruction to switch to emergency response mode.

[0939] The terminal displays the emergency situation, provides specific instructions to the user, and automatically notifies emergency contacts as necessary.

[0940] The user follows the emergency response instructions displayed on the terminal.

[0941] Examples:

[0942] If the user collapses, the device will provide a voice message saying, "This is an emergency. Please rest immediately. We will call an ambulance," and at the same time display the message, "An emergency has occurred. We will notify emergency contact points."

[0943] Prompt Sentence Examples

[0944] 1. Example prompt

[0945] Describe a scenario where a new user enters a fitness gym and scans a QR code to begin their session. The user then introduces themselves and their fitness goals, and the generative AI uses that information to suggest training plans. Include using sentiment analysis to adjust suggestions based on the user's mood.

[0946] In this way, by linking the server, terminal, and user, we have created a system that offers a safe and effective fitness experience by proposing the optimal exercise plan based on the user's emotions and condition and responding quickly in the event of an abnormality.

[0947] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0948] Step 1:

[0949] The server collects data from cameras and sensors installed at the entrances to confirm the user's entry, and processes this data in real time to identify whether the user is a new or existing user.

[0950] Input: Image data and sensor data obtained from cameras and sensors

[0951] Output: User identification information

[0952] How it works: The camera captures the user's image, and sensors collect data such as movement and body temperature. The server analyzes this information to determine whether the user is a new or existing user.

[0953] Step 2:

[0954] If the device recognizes the user as a new user, it displays a screen for scanning a QR code and prompts the user to enter basic information.

[0955] Input: New user identification information received from the server

[0956] Output: QR code scanning screen and basic information input screen

[0957] What it does: The device prepares to scan the QR code and displays the necessary screen. Once the user scans the QR code, the device displays a screen for entering basic information.

[0958] Step 3:

[0959] Users scan a QR code displayed on their device and enter a profile picture and fitness goals.

[0960] Input: QR code, bio information, and fitness goals

[0961] Output: User information entered

[0962] Specific operation: The user scans the QR code using a smartphone or other device, and then enters their fitness goals on the input screen that appears.

[0963] Step 4:

[0964] The server collects basic information and past training data entered by the user and runs a generative AI model to generate an optimal training plan.

[0965] Input: Basic information, past training data, generative AI model

[0966] Power: Optimal training plan

[0967] How it works: The server stores the information received from the user and runs a generative AI model that compares it with past training data. The generative AI model performs calculations and analysis to generate a personalized training plan.

[0968] Step 5:

[0969] The terminal displays the generated training plan to the user and also provides audio guidance.

[0970] Input: Training plan sent from the server

[0971] Output: On-screen training plan and audio guidance

[0972] Specific operation: The device displays the training plan information on the screen, and at the same time, an audio guide guides the user through the plan.

[0973] Step 6:

[0974] The user reviews the proposed training plans and selects the plan to implement.

[0975] Input: Training plan displayed on device

[0976] Output: Selected training plan

[0977] Specific operation: The user checks the screen display and selects the plan they want to implement from the options.

[0978] Step 7:

[0979] The server uses emotion analysis to analyze the user's voice and facial expressions to recognize their emotions, and provides feedback on the content of the suggestions based on this.

[0980] Input: User's voice data, facial expression data

[0981] Output: Parsed emotion information

[0982] Specific operation: The server captures the user's voice and facial expressions, processes the data using emotion analysis, and adjusts the training plan based on the analysis results.

[0983] Step 8:

[0984] The device adjusts suggestions to the user based on the emotion analysis results.

[0985] Input: Sentiment analysis results

[0986] Output: Tailored training plan

[0987] Specific operation: The device receives the emotion analysis results and presents the adjusted training plan to the user again.

[0988] Step 9:

[0989] The server collects data in real time from sensors inside the fitness gym and detects any abnormalities.

[0990] Input: Sensor data

[0991] Output: Abnormal warning

[0992] Specific operation: The server continuously reads data from the sensors and immediately issues an alert if it detects an abnormality.

[0993] Step 10:

[0994] If an abnormality is detected, the device will display an emergency alert and provide specific instructions to the user. It will also automatically notify emergency contacts if necessary.

[0995] Input: Abnormal warning from the server

[0996] Output: Emergency alert display, emergency call

[0997] Specific operation: The device displays an emergency alert and provides instructions to the user, while automatically notifying emergency contacts.

[0998] Step 11:

[0999] The user follows the emergency response instructions displayed on the device and acts safely.

[1000] Input: Emergency response instructions displayed on the terminal

[1001] Output: User's response action

[1002] Specific actions: The user follows the instructions on the device and takes emergency measures, such as taking a rest immediately or providing first aid.

[1003] (Application example 2)

[1004] 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."

[1005] To improve the work efficiency and safety of robots in modern factories, it is essential to propose efficient and flexible work plans, detect abnormalities, and respond to emergencies. However, conventional systems lack sufficient automation to meet these requirements, and many tasks must be performed manually by managers, hindering efficiency. Furthermore, it is difficult to analyze the robot's work status and performance in real time and propose optimal work plans based on that analysis. Furthermore, rapid response is also required in the event of an emergency.

[1006] The identification process by the identification 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 a data input means used to input data of a new user, a generation means for generating a work plan based on past work data and basic information about the user, a proposal means for proposing the generated work plan to the user, a detection means for detecting anomalies, a response means for taking emergency action when an anomaly is detected, and an emotion analysis means for monitoring and adjusting the efficiency state of the user. This enables flexible and rapid response while improving the work efficiency of the robot and ensuring safety.

[1007] A "new user" is an individual or device that begins using the system for the first time.

[1008] "Data input means" refers to a device or program for collecting basic information about users and past work data.

[1009] "Task data" refers to information about the history and performance of tasks performed by a robot in the past.

[1010] "Basic information" refers to information about the attributes, goals, and initial settings of a user or robot.

[1011] A "task plan" is a specific plan created to allow a robot to efficiently perform a task.

[1012] The "generation means" is a program or device for generating an optimal work plan based on collected data.

[1013] The "proposing means" is a device or program that notifies the user of the generated work plan and encourages execution.

[1014] "Detection means" refers to sensors or programs used to detect abnormalities.

[1015] "Response means" refers to a device or program for carrying out an emergency response when an abnormality is detected.

[1016] "Emotion analysis means" refers to a program or device for monitoring and analyzing the efficiency and performance of a user or robot.

[1017] The present invention is a system that collects data on new users and robots, generates and proposes appropriate work plans, and detects and responds to anomalies. This system is realized by combining programs, hardware, and software. Each component and its processing are described in detail below.

[1018] Data Entry Method

[1019] The server monitors the robot's location and working status using cameras and sensors installed in the factory, and collects identification data when a new robot is introduced. When a new robot is introduced, the terminal displays a screen for scanning a QR code and provides a screen for entering basic information such as training goals. The user scans the QR code of the new robot and enters basic information and work goals.

[1020] generation means

[1021] The server runs a generative AI model based on the collected basic information and past work data to generate an appropriate work plan. This data is combined with previously collected historical data and analyzed. The generative AI model used is OpenAI's GPT-4, and the generated work plan is presented to the administrator's device.

[1022] Proposal means

[1023] The server sends instructions to the robot's AI to propose the generated work plan to the robot. The proposed work plan is presented to the terminal by voice and display. The administrator checks it and adjusts it as necessary.

[1024] Emotion analysis means

[1025] The server analyzes the robot's work performance data and managerial feedback to provide efficient work plans as feedback. TensorFlow is used as the emotion analysis engine.

[1026] Detection Method

[1027] The server collects data in real time from various sensors installed in the factory and detects any abnormalities, which are immediately notified to the administrator.

[1028] Countermeasures

[1029] When an abnormality is detected, the server sends an instruction to the robot's AI to switch to emergency response mode. The emergency situation is displayed on the terminal, and specific instructions for countermeasures are shown to the administrator.

[1030] Specific examples

[1031] When a new robot is introduced, the manager scans a QR code on the terminal and inputs basic information and work goals. For example, a work plan is generated based on basic information such as "New robot, Type X, goal is to improve picking efficiency" and past data such as "Processed 1,000 pieces in the past month."

[1032] Here is an example prompt:

[1033] Robot Basics: Type A, the goal is to improve picking efficiency

[1034] Historical data: 1000 pieces processed for the past month

[1035] Generate efficient work plans for this robot.

[1036] The program uses OpenAI GPT-4 to generate optimal work plans for the robots and TensorFlow to perform emotion analysis of the robots, improving work efficiency and ensuring safety.

[1037] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1038] Step 1: Data entry method

[1039] The server monitors the robot's location and working status in real time using cameras and sensors installed in the factory. When a new robot is introduced, the server collects and stores its identification data. The terminal displays a QR code scanning screen dedicated to the new robot, which the manager scans to enter basic information and work goals. The entered basic information (e.g., robot type, purpose) and work goals (e.g., improving the efficiency of picking work) are then transferred to the server.

[1040] Step 2: Generator

[1041] The server runs a generative AI model using the collected basic information and past work data. Specifically, it uses OpenAI GPT-4 to generate a work plan. Based on this prompt (e.g., "Robot basic information: Type A, goal is to improve picking efficiency. Past data: processed 1,000 pieces in the past month. Please generate an efficient work plan for this robot."), the generative AI model generates an optimal work plan. The generated work plan is sent from the server to the device.

[1042] Step 3: Proposal method

[1043] The server sends the generated work plan to the AI ​​inside the robot. The proposed work plan is displayed on the terminal and reviewed by the manager. For example, a specific work plan may be proposed, such as "focus on picking work on the first day, and maintenance work on the next day." The manager can adjust the work plan as necessary and finalize it.

[1044] Step 4: Sentiment Analysis Methods

[1045] The server analyzes work performance data collected from the factory robots and feedback from managers in real time. The sentiment analysis engine uses TensorFlow to analyze the robot's efficiency and whether there are any abnormalities. For example, if the robot's movements are slow, this may indicate a decrease in efficiency or an abnormality. The analysis results are notified to the terminal as feedback from the server.

[1046] Step 5: Detection Methods

[1047] The server collects data in real time from various sensors installed in the factory and detects abnormalities. For example, if a robot is not performing its scheduled operation or is overloaded, the server will immediately detect the abnormality based on the data from the sensor. The detected data is analyzed by the server, and if an abnormality is confirmed, the administrator is notified.

[1048] Step 6: Response measures

[1049] When an abnormality is detected, the server immediately sends an instruction to the AI ​​in the robot to switch to emergency response mode. The terminal displays the emergency situation and provides the administrator with specific response instructions (e.g., stop the robot and instruct a human to inspect it). In addition, if necessary, an automatic notification is sent to emergency contacts (e.g., technical support or emergency contacts). The administrator follows the emergency response instructions displayed on the terminal and takes appropriate action.

[1050] 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.

[1051] 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.

[1052] 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.

[1053] [Third embodiment]

[1054] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1055] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1056] 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).

[1057] 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.

[1058] 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.

[1059] 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).

[1060] 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.

[1061] 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.

[1062] 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.

[1063] 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.

[1064] 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.

[1065] 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."

[1066] The present invention is a system that allows users to train efficiently and safely at a 24-hour fitness gym. The system includes a data input means, a generation means, a proposal means, a detection means, and a response means. The functions of each means are explained below with specific examples.

[1067] Data Entry Method

[1068] Server: Collects data from cameras and sensors installed at the entrance to detect when a user arrives at the gym.

[1069] Device: When the user scans the QR code, a screen will appear prompting them to enter basic information (fitness experience, goals, etc.).

[1070] User: Enter a self-introduction and fitness goals into the input screen displayed on the device.

[1071] Example: When a user scans a QR code at the entrance, a screen appears on the device asking them to introduce themselves and enter their fitness goals. The user enters their goal as "I want to do strength training three times a week."

[1072] generation means

[1073] Server: Runs the generation AI to generate training plans based on the collected basic information and past training data.

[1074] Terminal: Proposes the training plan generated by the generation AI to the user.

[1075] Example: When a user enters basic information, the server uses a generative AI to generate a "strength training plan for one hour, three times a week" based on past data and the entered information. The device displays a specific plan such as "Squats and planks on the first day, deadlifts and side lunges on the second day, and bench presses and hip thrusts on the third day."

[1076] Proposal means

[1077] Server: Sends instructions to PepperGPT to suggest the training plan generated by the generator to the user.

[1078] Device: PepperGPT will propose the generated training plan to the user via voice and display.

[1079] User: Review the proposed training plans and select the plan they wish to implement.

[1080] Example: PepperGPT will say, "Hello, Mr. / Ms. X. Today's training plan is 30 minutes of strength training. Let's start with squats." The user will confirm the proposed plan and proceed to the next step.

[1081] Detection Method

[1082] Server: Collects data in real time from various sensors installed within the fitness gym and processes it to detect abnormalities.

[1083] Device: Prepare to display an emergency alert if an anomaly is detected.

[1084] Example: If a user falls during training, the heart rate monitor and fall detection sensor will detect the abnormality and the server will immediately send an alert to the device.

[1085] Countermeasures

[1086] Server: When an abnormality is detected, it immediately sends an instruction to PepperGPT to switch to emergency response mode.

[1087] Terminal: The terminal displays the emergency situation and provides specific instructions to the user. It also automatically notifies emergency contacts as needed.

[1088] User: Follow the emergency response instructions displayed on the device.

[1089] Example: If a user collapses, PepperGPT will provide a voice prompt saying, "This is an emergency. Please rest immediately. We will call an ambulance," and the device will simultaneously display, "An emergency has occurred. We will notify emergency contacts."

[1090] The above is a specific embodiment for carrying out the present invention. This system allows users to easily obtain an efficient training plan and also enables quick response in emergencies.

[1091] The processing flow will be explained below.

[1092] New User Guide

[1093] Step 1:

[1094] Server: Collects data from cameras and sensors installed at the entrance to confirm the user's entry and identifies whether the user is a new user.

[1095] Step 2:

[1096] Device: If a new user is identified, a screen for scanning a QR code will be displayed on the device.

[1097] Step 3:

[1098] User: Scan the QR code displayed on the device to start using the service.

[1099] Step 4:

[1100] Terminal: Displays a screen where users can enter basic information such as their fitness experience and goals.

[1101] Step 5:

[1102] User: Enter a profile and fitness goals into the device.

[1103] Step 6:

[1104] Server: Processes the basic information entered and sends a command to PepperGPT to start facility guidance.

[1105] Step 7:

[1106] Terminal: PepperGPT begins to provide voice guidance to the user, saying, "Hello, you are a new user. We will show you how to use the facility."

[1107] Short workout suggestions

[1108] Step 1:

[1109] User: Enter a time limit into the terminal, such as "Only 30 minutes available today."

[1110] Step 2:

[1111] Terminal: Sends the entered time limit to the server.

[1112] Step 3:

[1113] Server: Runs the generative AI to generate effective workout plans in a short amount of time based on past training data and basic user information.

[1114] Step 4:

[1115] Terminal: Displays the generated workout plan to the user.

[1116] Step 5:

[1117] User: Check the training plan displayed on the device and decide whether to carry it out.

[1118] Step 6:

[1119] Server: Optimizes training plans based on user feedback.

[1120] Goal setting support

[1121] Step 1:

[1122] User: Enter a specific goal into the device, such as "lose 5 kg in 3 months."

[1123] Step 2:

[1124] Terminal: Sends the entered goal to the server.

[1125] Step 3:

[1126] Server: Based on the input goal, the generation AI proposes a feasible method and timeframe for achieving the goal.

[1127] Step 4:

[1128] Device: The generated advice is displayed to the user and read aloud by PepperGPT.

[1129] Step 5:

[1130] User: Review the proposed goals and methods, make adjustments as needed, and finalize the goal setting.

[1131] Step 6:

[1132] Server: Stores the adjusted goals and methods and periodically tracks the user's progress.

[1133] Emergency Response Support

[1134] Step 1:

[1135] Server: Collects data in real time from heart rate monitors and fall detection sensors installed within the facility and detects abnormalities.

[1136] Step 2:

[1137] Terminal: Prepare to display an emergency situation if an abnormality is detected.

[1138] Step 3:

[1139] Server: When an abnormality is detected, it immediately sends an instruction to PepperGPT to switch to emergency response mode.

[1140] Step 4:

[1141] Device: An emergency message will be displayed on the device, along with specific steps to take. Emergency contacts will also be notified automatically.

[1142] Step 5:

[1143] User: Follow the emergency response instructions displayed on the device and, if necessary, seek assistance until the situation improves.

[1144] The above are the specific processing steps of this system. At each processing step, the server, terminal, and user work together to provide efficient training support.

[1145] Example 1

[1146] 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."

[1147] At current fitness gyms, users need a lot of time and effort to find an appropriate training plan that suits their individual fitness experience and goals. Real-time monitoring and rapid response to abnormalities to ensure user safety are also difficult. Therefore, there is a need for a system that allows users to train efficiently and safely.

[1148] 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.

[1149] In this invention, the server includes a data input means for inputting user data, a generation means for generating a training plan based on past training data and basic information about the user, a proposal means for proposing the generated training plan to the user, a detection means for detecting abnormalities, a response means for taking emergency action when an abnormality is detected, a means for collecting data from cameras and sensors to detect the arrival of the user, and a means for providing audio and visual guidance on the proposed training plan. This allows users to efficiently obtain training plans, monitors safety in real time, and enables rapid response to abnormalities.

[1150] "Data input means" refers to a device or method by which a user inputs basic information such as training information and goals.

[1151] "Generation means" refers to a device or method for creating an appropriate training plan based on collected data.

[1152] The "suggestion means" is a device or method for proposing the generated training plan to the user.

[1153] "Detection means" refers to a device or method for detecting abnormalities in users using sensors or cameras within the fitness gym.

[1154] "Response means" refers to a device or method for taking emergency action when an abnormality is detected.

[1155] "Means for collecting data from cameras and sensors" refers to devices or methods that detect the arrival or movement of users and collect data based on that.

[1156] "Means for providing audio or visual guidance on a training plan" refers to a device or method for providing audio guidance or displaying a generated training plan on a terminal screen to a user.

[1157] MODE FOR CARRYING OUT THE INVENTION

[1158] This invention is a system that allows users to train efficiently and safely at a 24-hour fitness gym. This system includes a data input means, a generation means, a proposal means, a detection means, and a response means. The functions of each means and specific operation examples are shown below.

[1159] Data Entry Method

[1160] Server: To detect when a user arrives at the gym, the server collects data from cameras and sensors installed at the entrance. The server analyzes this data and confirms that the user has arrived at the gym.

[1161] Terminal: When a user scans the QR code installed at the gym entrance, a screen will appear prompting them to enter basic information (fitness experience, goals, etc.), making it easy for users to enter the required information.

[1162] User: Enters a self-introduction and fitness goals into the input screen displayed on the device. Specifically, the user enters a goal such as "I want to do strength training three times a week."

[1163] generation means

[1164] Server: Based on the collected basic information and past training data, a training plan is generated using a "generative AI model." This generative AI model can be, for example, "ChatGPT Turbo."

[1165] Example: When a user enters basic information, the server uses training AI to generate a "strength training plan for one hour, three times a week" based on past data and the entered information. The generated plan contains specific content, and the device displays a specific plan such as "Squats and planks on the first day, deadlifts and side lunges on the second day, and bench presses and hip thrusts on the third day."

[1166] Proposal means

[1167] Server: Sends instructions to PepperGPT to suggest the generated training plan to the user.

[1168] On the device, PepperGPT will propose the generated training plan to the user via voice and display. For example, it might say, "Hello, Mr. / Ms. X. Today's training plan is 30 minutes of strength training. Let's start with squats."

[1169] Detection Method

[1170] Server: Collects data in real time from various sensors installed in the fitness gym and processes it to detect abnormalities. For example, heart rate monitors and fall detection sensors are used.

[1171] Terminal: Prepare to display an emergency alert if an abnormality is detected. When the server detects an abnormality, it immediately sends an alert to the terminal.

[1172] Example: If a user falls during training, the heart rate monitor and fall detection sensor will detect the abnormality and the server will immediately send an alert to the device.

[1173] Countermeasures

[1174] Server: When an abnormality is detected, PepperGPT is immediately instructed to switch to emergency response mode, enabling a rapid response.

[1175] Terminal: The terminal displays the emergency situation and provides specific instructions to the user. It also automatically notifies emergency contacts as needed.

[1176] User: Follow the emergency response instructions displayed on the device. For example, PepperGPT will say, "This is an emergency. Please rest immediately. We will call an ambulance," and the device will simultaneously display, "Emergency situation has occurred. We will notify emergency contacts."

[1177] Prompt Sentence Examples

[1178] A user arrives at the gym. They scan a QR code to enter their basic information and fitness goals. For example, "I want to do one hour of strength training three times a week." Once they've completed the input, they can begin generating a training plan.

[1179] This system allows users to easily obtain efficient training plans and also enables quick response in emergencies.

[1180] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1181] Step 1:

[1182] User arrival detection

[1183] Server: Operates the camera and sensor system installed at the gym entrance.

[1184] Input: Images and data captured from cameras and sensors.

[1185] Data processing: Image analysis is used to recognize people's movements and faces.

[1186] Output: A flag confirming the user's arrival.

[1187] How it works: The camera captures the user's image data, the sensor detects their presence, and the server analyzes this data to recognize the user's arrival.

[1188] Step 2:

[1189] Prompt for QR code scanning and basic information entry

[1190] Terminal: When the user scans the QR code installed at the entrance, a screen for entering basic information is displayed.

[1191] Input: User ID via QR code scan.

[1192] Data processing: Decode the contents of the QR code and extract the user ID.

[1193] Output: Basic information input screen.

[1194] Specific operation: The QR code is scanned with the device's camera. The device then displays an input screen prompting the user to "Enter your name, age, fitness experience, and goals."

[1195] Step 3:

[1196] Enter your basic information and fitness goals

[1197] User: Enter basic information and fitness goals.

[1198] Input: Basic information entered by the user into the input screen (name, age, fitness experience, goals).

[1199] Data Calculation: Validation and storage of input data.

[1200] Output: User's basic information and goals.

[1201] Specific Action: A user inputs a fitness goal: "I want to do strength training three times a week."

[1202] Step 4:

[1203] Generate a training plan

[1204] Server: Runs the generative AI model based on collected basic information and past training data.

[1205] Input: User's basic information and past training data.

[1206] Data processing: Inputting and analyzing data into generative AI models.

[1207] Output: The generated training plan.

[1208] Specific operation: The server uses training AI to generate a "strength training plan for one hour, three times a week" based on past data and input information. The generated plan contains specific content.

[1209] Step 5:

[1210] Training plan suggestions

[1211] Server: Sends the generated training plan to PepperGPT.

[1212] Input: The generated training plan.

[1213] Data processing: Instructions for sending training plan.

[1214] Output: Suggested instructions to PepperGPT.

[1215] Specific operation: Details of the generated training plan are sent to PepperGPT via API.

[1216] Device: PepperGPT will suggest training plans to the user via voice and display.

[1217] Input: Proposal data from PepperGPT.

[1218] Data processing: speech synthesis and display on the screen.

[1219] Output: Suggestions to the user.

[1220] Specific actions: PepperGPT will guide you by saying, "Hello, Mr. / Ms. XX. Today's training plan is 30 minutes of strength training. Let's start with squats."

[1221] Step 6:

[1222] Monitoring during training

[1223] Server: Collects data in real time from various sensors within the fitness gym and processes it to detect abnormalities.

[1224] Input: Data from heart rate monitors and fall detection sensors.

[1225] Data processing: Real-time analysis for anomaly detection.

[1226] Output: Anomaly detection flag.

[1227] Specific operation: The server receives data from the heart rate monitor and fall detection sensor in real time and analyzes it to detect abnormalities.

[1228] Step 7:

[1229] Emergency response

[1230] Server: When an abnormality is detected, it immediately sends an instruction to PepperGPT to switch to emergency response mode.

[1231] Input: Anomaly detection flag.

[1232] Data processing: Generation of emergency response instructions.

[1233] Output: Emergency response instructions to PepperGPT.

[1234] Specific operation: The server sends emergency response instructions to PepperGPT through the API, causing it to immediately begin emergency response.

[1235] Terminal: Provides emergency response instructions to the user via voice and display, and also notifies emergency contacts as necessary.

[1236] Input: Emergency response instructions from the server.

[1237] Data processing: Voice synthesis and on-screen display of emergency instructions.

[1238] Output: Instructs the user on emergency measures and makes an emergency call.

[1239] Specific operation: The device displays "Emergency! Please stay still until an ambulance arrives" and automatically calls emergency contacts.

[1240] Users: Follow emergency plan instructions.

[1241] Input: Emergency instructions from terminal.

[1242] Data calculation: Deciding on actions based on instructions.

[1243] Output: Safety action.

[1244] Specific actions: The user follows the instructions to stay calm and wait for the ambulance to arrive.

[1245] (Application example 1)

[1246] 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."

[1247] To ensure that new users can train efficiently and safely at fitness facilities, it is necessary to provide individually tailored training plans and monitor safety in real time. However, traditional fitness facilities face challenges such as users having to make their own decisions when training, which increases the risk of users training incorrectly and makes it difficult to respond quickly to emergencies. Furthermore, providing users with training plans tailored to their individual fitness goals requires processing large amounts of data, making it difficult to perform complex calculations in real time.

[1248] 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.

[1249] In this invention, the server includes a generating means for generating a training plan based on past training data and basic information of the user, a means for generating and inputting prompts to the generating AI model to generate a training plan suited to the user's fitness goals using the generating AI model, a suggesting means for suggesting and notifying the user of the generated training plan and emergency alerts, a detecting means for acquiring data in real time from sensors installed in the fitness facility and detecting abnormalities, and a responding means for taking emergency action when an abnormality is detected. This makes it possible to provide users with efficient and individually tailored training plans, while simultaneously enabling rapid response to emergencies and ensuring safety.

[1250] A "new user" is someone using a fitness facility for the first time, or an existing user who needs a new training plan.

[1251] "Data entry means" refers to the tools and methods used to enter basic information about the user, fitness goals, past training data, etc.

[1252] "Generation means" refers to tools and methods for generating an appropriate training plan based on input data and past training information.

[1253] A "generative AI model" refers to an algorithm or system that uses artificial intelligence to process data and generate an appropriate training plan.

[1254] A "prompt" refers to a specific form of sentence used to give specific instructions or questions to a generative AI model.

[1255] "Proposal means" refers to the tools and methods used to propose and notify users of generated training plans and emergency alerts.

[1256] "Detection Methods" means tools or methods for detecting abnormal conditions or emergencies based on data from sensors installed within a fitness facility.

[1257] "Response measures" refer to tools and methods for quickly taking appropriate action when an abnormality or emergency is detected.

[1258] The present invention provides a system for enabling users to train efficiently and safely in a fitness facility, the system including a data input means, a generating means, a suggesting means, a detecting means, and a responding means.

[1259] Data Entry Method

[1260] The server collects data from cameras and sensors installed at the entrances of fitness facilities and detects the arrival of users. When the user scans a QR code, the device displays a screen prompting them to enter basic information (fitness experience, goals, etc.). Through this screen, the user enters their self-introduction and fitness goals. For example, when a user scans a QR code at the entrance, a screen prompting them to enter their self-introduction and fitness goals appears on the device, and the user enters their goal, such as "I want to do strength training three times a week."

[1261] generation means

[1262] The server runs a generative AI model to generate a training plan based on the collected basic information and past training data. A means for generating and inputting prompts for the generative AI model is included. For example, when a user inputs basic information, the server uses the generative AI model to generate a "strength training plan for one hour, three times a week" based on the past data and the input information, using the following prompt:

[1263] Username: "User A"

[1264] Fitness Experience: "Intermediate"

[1265] Fitness goal: "Strength training three times a week"

[1266] Past training data: "Squat", "Deadlift"

[1267] The device displays a specific plan, such as "Day 1: Squats and planks, Day 2: Deadlifts and side lunges, Day 3: Bench presses and hip thrusts."

[1268] Proposal means

[1269] The server sends instructions to the terminal to propose the training plan generated by the generation means to the user. After this, the terminal proposes the generated training plan to the user by voice or display. The user checks the proposed training plan and selects the plan to implement. For example, the terminal may say, "Today's training plan is 30 minutes of strength training. Let's start with squats," and the user may confirm the proposed plan.

[1270] Detection Method

[1271] The server collects data from various sensors installed in the fitness facility in real time and processes it to detect abnormalities. For example, if a user falls during training, the heart rate monitor or fall detection sensor will detect the abnormality and the server will immediately send an alert to the device.

[1272] Countermeasures

[1273] When an abnormality is detected, the server immediately sends an instruction to switch to emergency response mode. The device displays the emergency situation and provides the user with specific instructions on what to do. It also automatically notifies emergency contacts if necessary. For example, if the user collapses, the device will announce in voice, "This is an emergency. Please rest immediately. We will call an ambulance," and at the same time display, "An emergency has occurred. We will notify emergency contacts."

[1274] The above is a specific embodiment for carrying out the present invention. This system allows users to easily obtain an efficient training plan and also enables quick response in emergencies.

[1275] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1276] Step 1:

[1277] When a user arrives at a fitness facility, they scan a QR code at the entrance. The device then displays a screen where the user can enter their basic information and fitness goals. Once the user has finished entering their information, the data is sent to the server.

[1278] Input: User basic information, fitness goals

[1279] Data processing / data calculation: Collection and storage of input data

[1280] Output: Send user information to the server

[1281] Step 2:

[1282] The server runs a generative AI model to generate a training plan based on the collected basic information and past training data. The server provides the specified prompt sentences to the generative AI model to create an appropriate training plan.

[1283] Input: User's basic information, past training data

[1284] Data processing / data calculation: Prompt generation for generative AI models and training plan generation

[1285] Output: Generated training plan

[1286] Step 3:

[1287] The server sends the generated training plan to the device, which then presents it to the user via voice guidance and on-screen display. The user can then review the proposed training plans and select the one they wish to implement.

[1288] Input: Generated training plan

[1289] Data processing / data calculation: Display of training plan and voice guidance

[1290] Output: User confirms and selects training plan

[1291] Step 4:

[1292] The server collects data in real time from various sensors installed in the fitness center and processes it to detect abnormalities. Based on the data collected from the sensors, it determines whether there are any abnormalities.

[1293] Input: Real-time data from sensors

[1294] Data processing / data calculation: Real-time data analysis and anomaly detection

[1295] Output: Anomaly detection results

[1296] Step 5:

[1297] When an abnormality is detected, the server immediately sends an instruction to switch to emergency response mode. The device notifies the user of the emergency through voice guidance and on-screen display, and automatically notifies emergency contacts if necessary. The user follows the instructions on the device and takes appropriate action.

[1298] Input: Anomaly detection results, user location, contact information

[1299] Data processing / data calculation: generation and notification of emergency response instructions

[1300] Output: Emergency response and automatic notification

[1301] By following these steps, a system is realized that provides effective training plans while ensuring the safety of users within a fitness facility.

[1302] 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.

[1303] This invention is a system that enables users to train efficiently and safely at a 24-hour fitness gym. This system is provided by combining a data input means, a generation means, a proposal means, a detection means, a response means, and an emotion engine. The function of each means is explained below with specific examples.

[1304] Data Entry Method

[1305] Server: Collects data from cameras and sensors installed at the entrance to confirm the user's entry and identifies whether the user is a new user.

[1306] Device: If a new user is identified, a screen for scanning a QR code will be displayed on the device.

[1307] User: Scan the QR code displayed on the device to start using the service.

[1308] Terminal: Displays a screen where users can enter basic information such as their fitness experience and goals.

[1309] User: Enter a profile and fitness goals into the device.

[1310] Example: When a user scans a QR code at the entrance, a screen appears on the device asking them to introduce themselves and enter their fitness goals. The user enters their goal as "I want to do strength training three times a week."

[1311] generation means

[1312] Server: Runs the generation AI to generate training plans based on the collected basic information and past training data.

[1313] Terminal: Proposes the training plan generated by the generation AI to the user.

[1314] Example: When a user enters basic information, the server uses a generative AI to generate a "strength training plan for one hour, three times a week" based on past data and the entered information. The device displays a specific plan such as "Squats and planks on the first day, deadlifts and side lunges on the second day, and bench presses and hip thrusts on the third day."

[1315] Proposal means

[1316] Server: Sends instructions to PepperGPT to suggest the training plan generated by the generator to the user.

[1317] Device: PepperGPT will propose the generated training plan to the user via voice and display.

[1318] User: Review the proposed training plans and select the plan they wish to implement.

[1319] Example: PepperGPT will say, "Hello, Mr. / Ms. X. Today's training plan is 30 minutes of strength training. Let's start with squats." The user will confirm the proposed plan and proceed to the next step.

[1320] Emotion Engine

[1321] Server: The emotion engine collects data to analyze the user's voice and facial expressions and recognize emotions.

[1322] Terminal: The emotion engine receives feedback on the user's emotional state based on the analysis results.

[1323] User: Review the suggestions tailored through emotion recognition and select a plan to implement.

[1324] Example: If a user says to their device, "I'm not feeling very well today," the emotion engine will analyze this and PepperGPT will adjust its suggestions, saying, "It seems like you're not feeling well. I recommend some light stretching and breathing exercises today."

[1325] Detection Method

[1326] Server: Collects data in real time from various sensors installed within the fitness gym and processes it to detect abnormalities.

[1327] Device: Prepare to display an emergency alert if an anomaly is detected.

[1328] Example: If a user falls during training, the heart rate monitor and fall detection sensor will detect the abnormality and the server will immediately send an alert to the device.

[1329] Countermeasures

[1330] Server: When an abnormality is detected, it immediately sends an instruction to PepperGPT to switch to emergency response mode.

[1331] Terminal: The terminal displays the emergency situation and provides specific instructions to the user. It also automatically notifies emergency contacts as needed.

[1332] User: Follow the emergency response instructions displayed on the device.

[1333] Example: If a user collapses, PepperGPT will provide a voice prompt saying, "This is an emergency. Please rest immediately. We will call an ambulance," and the device will simultaneously display, "An emergency has occurred. We will notify emergency contacts."

[1334] The above is a specific embodiment for carrying out the present invention. By combining it with an emotion engine, it becomes possible to propose flexible training plans that take into account the user's emotional state, which is expected to improve user satisfaction to a greater extent.

[1335] The processing flow will be explained below.

[1336] New User Guide

[1337] Step 1:

[1338] Server: Collects data from cameras and sensors installed at the entrance to confirm the user's entry and identifies whether the user is a new user.

[1339] Step 2:

[1340] Device: If a new user is identified, a screen for scanning a QR code will be displayed on the device.

[1341] Step 3:

[1342] User: Scan the QR code displayed on the device to start using the service.

[1343] Step 4:

[1344] Terminal: Displays a screen where users can enter basic information such as their fitness experience and goals.

[1345] Step 5:

[1346] User: Enter a profile and fitness goals into the device.

[1347] Step 6:

[1348] Server: Processes the basic information entered and sends a command to PepperGPT to start facility guidance.

[1349] Step 7:

[1350] Terminal: PepperGPT begins to provide voice guidance to the user, saying, "Hello, you are a new user. We will show you how to use the facility."

[1351] Short workout suggestions

[1352] Step 1:

[1353] User: Enter a time limit into the terminal, such as "Only 30 minutes available today."

[1354] Step 2:

[1355] Terminal: Sends the entered time limit to the server.

[1356] Step 3:

[1357] Server: Runs the generative AI to generate effective workout plans in a short amount of time based on past training data and basic user information.

[1358] Step 4:

[1359] Terminal: Displays the generated workout plan to the user.

[1360] Step 5:

[1361] User: Check the training plan displayed on the device and decide whether to carry it out.

[1362] Step 6:

[1363] Server: Optimizes training plans based on user feedback.

[1364] Goal setting support

[1365] Step 1:

[1366] User: Enter a specific goal into the device, such as "lose 5 kg in 3 months."

[1367] Step 2:

[1368] Terminal: Sends the entered goal to the server.

[1369] Step 3:

[1370] Server: Based on the input goal, the generation AI proposes a feasible method and timeframe for achieving the goal.

[1371] Step 4:

[1372] Device: The generated advice is displayed to the user and read aloud by PepperGPT.

[1373] Step 5:

[1374] User: Review the proposed goals and methods, make adjustments as needed, and finalize the goal setting.

[1375] Step 6:

[1376] Server: Stores the adjusted goals and methods and periodically tracks the user's progress.

[1377] Emotion Engine

[1378] Step 1:

[1379] Server: Collects data for the emotion engine to analyze the user's voice and facial expressions to recognize emotions.

[1380] Step 2:

[1381] Terminal: The emotion engine receives feedback on the user's emotional state based on the analysis results.

[1382] Step 3:

[1383] User: Review the suggestions tailored through emotion recognition and select a plan to implement.

[1384] Step 4:

[1385] Server: Based on the user's emotional data, the server adjusts the training plan and suggestions accordingly.

[1386] Step 5:

[1387] On the device: The adjustment results are displayed to the user, and PepperGPT provides voice guidance.

[1388] Example: If a user says to their device, "I'm not feeling very well today," the emotion engine will analyze this and PepperGPT will adjust its suggestions, saying, "It seems like you're not feeling well. I recommend some light stretching and breathing exercises today."

[1389] Detection Method

[1390] Step 1:

[1391] Server: Collects data in real time from various sensors installed within the fitness gym and processes it to detect abnormalities.

[1392] Step 2:

[1393] Device: Prepare to display an emergency alert if an anomaly is detected.

[1394] Example: If a user falls during training, the heart rate monitor and fall detection sensor will detect the abnormality and the server will immediately send an alert to the device.

[1395] Countermeasures

[1396] Step 1:

[1397] Server: When an abnormality is detected, it immediately sends an instruction to PepperGPT to switch to emergency response mode.

[1398] Step 2:

[1399] Terminal: The terminal displays the emergency situation and provides specific instructions to the user. It also automatically notifies emergency contacts as needed.

[1400] Step 3:

[1401] User: Follow the emergency response instructions displayed on the device.

[1402] Example: If a user collapses, PepperGPT will provide a voice prompt saying, "This is an emergency. Please rest immediately. We will call an ambulance," and the device will simultaneously display, "An emergency has occurred. We will notify emergency contacts."

[1403] The above is a specific embodiment for carrying out the present invention. By combining it with an emotion engine, it becomes possible to propose flexible training plans that take into account the user's emotional state, which is expected to improve user satisfaction to a greater extent.

[1404] Example 2

[1405] 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."

[1406] In conventional fitness gyms, it is difficult for users to independently adjust their training plans to suit their own physical condition and emotional state, and quick response is required when abnormalities occur. Furthermore, there is a lack of systems that utilize individual user data to provide optimal exercise plans. To solve this problem, there is a need for an integrated fitness support system that includes flexible proposals that take users' emotional state into account and quick response when abnormalities occur.

[1407] 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.

[1408] In this invention, the server

[1409] a data capture means used to input new user data;

[1410] A plan generation means for generating an exercise plan based on past exercise data and basic information of the user;

[1411] a suggestion means for suggesting the generated exercise plan to a user;

[1412] an anomaly detection means for detecting an anomaly;

[1413] an emergency response means for taking emergency action when an abnormality is detected;

[1414] emotion analysis means for analyzing the user's voice and facial expression to recognize emotions;

[1415] a voice suggestion means for suggesting an exercise plan to a user by voice;

[1416] Includes:

[1417] This will enable the system to propose flexible training plans that take into account the user's emotional state, as well as to respond quickly and appropriately in the event of an emergency.

[1418] "Data acquisition means" refers to the devices or systems used to input user data, such as cameras or sensors installed at entrances or the QR code scanning function displayed on terminals.

[1419] The "plan generation means" is a function that generates an optimal exercise plan based on collected past exercise data and basic information of the user. This includes a generative AI model.

[1420] The "suggestion means" refers to a means for presenting the generated exercise plan to the user, including a display on the device and audio guidance.

[1421] "Anomaly detection means" refers to sensors or monitoring systems that detect abnormalities within the fitness gym. Examples include heart rate monitors and fall detection sensors.

[1422] "Emergency response measures" are measures for taking prompt and appropriate action when an abnormality is detected, including displaying an emergency alert and automatically notifying emergency contacts.

[1423] "Emotion analysis means" refers to a system that analyzes a user's voice and facial expressions to recognize their emotional state. This includes voice analysis software and facial expression recognition technology.

[1424] The "audio suggestion means" refers to a means for suggesting the generated exercise plan to the user by voice, including a voice assistant function and a speaker.

[1425] This invention is a system that allows users to train efficiently and safely at a 24-hour fitness gym. This system is provided by combining a data acquisition means, a plan generation means, a proposal means, an anomaly detection means, an emergency response means, and an emotion analysis means. The specific functions and operations of each means are described below.

[1426] Data Acquisition Method

[1427] The server collects data from cameras and sensors installed at the entrance to confirm the user's entry and, based on this data, distinguishes between new and existing users.

[1428] If the device recognizes the user as a new user, it displays a screen for scanning a QR code and prompts the user to enter basic information.

[1429] Users scan a QR code displayed on their device and enter a profile picture and fitness goals.

[1430] Examples:

[1431] When users scan the QR code at the entrance, a screen appears on the device where they can introduce themselves and enter their fitness goals. The user enters their goal, such as "I want to do strength training three times a week."

[1432] Plan Generation Method

[1433] The server runs a generative AI model based on the collected basic information and past training data to generate an optimal training plan.

[1434] The device proposes a training plan generated by the generation AI to the user.

[1435] Examples:

[1436] Once the user enters their basic information, the server uses a generative AI to generate a "strength training plan for one hour, three times a week" based on past data and the information entered. The device displays a specific plan such as "Squats and planks on the first day, deadlifts and side lunges on the second day, and bench presses and hip thrusts on the third day."

[1437] Proposal means

[1438] The server sends instructions to propose the training plan generated by the generating means.

[1439] The device will suggest a training plan to the user by voice or display.

[1440] The user reviews the proposed training plans and selects the plan to implement.

[1441] Examples:

[1442] The device will say, "Hello, Mr. / Ms. X. Today's training plan is 30 minutes of strength training." The user will confirm the proposed plan and proceed to the next step.

[1443] Emotion analysis means

[1444] The server uses an emotion engine to analyze the user's voice and facial expressions and collect data to recognize emotions.

[1445] The terminal receives the user's emotional state as feedback based on the analysis results of the emotion engine.

[1446] The user checks the proposals adjusted by emotion recognition and selects a plan to implement.

[1447] Examples:

[1448] If a user tells the device, "I'm not feeling very well today," the emotion engine analyzes this and the device adjusts its suggestions, saying, "You seem to be feeling unwell. I recommend some light stretching and breathing exercises today."

[1449] Anomaly detection means

[1450] The server collects data in real time from various sensors installed within the fitness gym and performs processing to detect abnormalities.

[1451] The device will display an emergency alert if an abnormality is detected.

[1452] Examples:

[1453] If a user falls during training, the heart rate monitor and fall detection sensor will detect the abnormality, and the server will immediately send an alert to the device.

[1454] Emergency response measures

[1455] When an abnormality is detected, the server immediately sends an instruction to switch to emergency response mode.

[1456] The terminal displays the emergency situation, provides specific instructions to the user, and automatically notifies emergency contacts as necessary.

[1457] The user follows the emergency response instructions displayed on the terminal.

[1458] Examples:

[1459] If the user collapses, the device will provide a voice message saying, "This is an emergency. Please rest immediately. We will call an ambulance," and at the same time display the message, "An emergency has occurred. We will notify emergency contact points."

[1460] Prompt Sentence Examples

[1461] 1. Example prompt

[1462] Describe a scenario where a new user enters a fitness gym and scans a QR code to begin their session. The user then introduces themselves and their fitness goals, and the generative AI uses that information to suggest training plans. Include using sentiment analysis to adjust suggestions based on the user's mood.

[1463] In this way, by linking the server, terminal, and user, we have created a system that offers a safe and effective fitness experience by proposing the optimal exercise plan based on the user's emotions and condition and responding quickly in the event of an abnormality.

[1464] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1465] Step 1:

[1466] The server collects data from cameras and sensors installed at the entrances to confirm the user's entry, and processes this data in real time to identify whether the user is a new or existing user.

[1467] Input: Image data and sensor data obtained from cameras and sensors

[1468] Output: User identification information

[1469] How it works: The camera captures the user's image, and sensors collect data such as movement and body temperature. The server analyzes this information to determine whether the user is a new or existing user.

[1470] Step 2:

[1471] If the device recognizes the user as a new user, it displays a screen for scanning a QR code and prompts the user to enter basic information.

[1472] Input: New user identification information received from the server

[1473] Output: QR code scanning screen and basic information input screen

[1474] What it does: The device prepares to scan the QR code and displays the necessary screen. Once the user scans the QR code, the device displays a screen for entering basic information.

[1475] Step 3:

[1476] Users scan a QR code displayed on their device and enter a profile picture and fitness goals.

[1477] Input: QR code, bio information, and fitness goals

[1478] Output: User information entered

[1479] Specific operation: The user scans the QR code using a smartphone or other device, and then enters their fitness goals on the input screen that appears.

[1480] Step 4:

[1481] The server collects basic information and past training data entered by the user and runs a generative AI model to generate an optimal training plan.

[1482] Input: Basic information, past training data, generative AI model

[1483] Power: Optimal training plan

[1484] How it works: The server stores the information received from the user and runs a generative AI model that compares it with past training data. The generative AI model performs calculations and analysis to generate a personalized training plan.

[1485] Step 5:

[1486] The terminal displays the generated training plan to the user and also provides audio guidance.

[1487] Input: Training plan sent from the server

[1488] Output: On-screen training plan and audio guidance

[1489] Specific operation: The device displays the training plan information on the screen, and at the same time, an audio guide guides the user through the plan.

[1490] Step 6:

[1491] The user reviews the proposed training plans and selects the plan to implement.

[1492] Input: Training plan displayed on device

[1493] Output: Selected training plan

[1494] Specific operation: The user checks the screen display and selects the plan they want to implement from the options.

[1495] Step 7:

[1496] The server uses emotion analysis to analyze the user's voice and facial expressions to recognize their emotions, and provides feedback on the content of the suggestions based on this.

[1497] Input: User's voice data, facial expression data

[1498] Output: Parsed emotion information

[1499] Specific operation: The server captures the user's voice and facial expressions, processes the data using emotion analysis, and adjusts the training plan based on the analysis results.

[1500] Step 8:

[1501] The device adjusts suggestions to the user based on the emotion analysis results.

[1502] Input: Sentiment analysis results

[1503] Output: Tailored training plan

[1504] Specific operation: The device receives the emotion analysis results and presents the adjusted training plan to the user again.

[1505] Step 9:

[1506] The server collects data in real time from sensors inside the fitness gym and detects any abnormalities.

[1507] Input: Sensor data

[1508] Output: Abnormal warning

[1509] Specific operation: The server continuously reads data from the sensors and immediately issues an alert if it detects an abnormality.

[1510] Step 10:

[1511] If an abnormality is detected, the device will display an emergency alert and provide specific instructions to the user. It will also automatically notify emergency contacts if necessary.

[1512] Input: Abnormal warning from the server

[1513] Output: Emergency alert display, emergency call

[1514] Specific operation: The device displays an emergency alert and provides instructions to the user, while automatically notifying emergency contacts.

[1515] Step 11:

[1516] The user follows the emergency response instructions displayed on the device and acts safely.

[1517] Input: Emergency response instructions displayed on the terminal

[1518] Output: User's response action

[1519] Specific actions: The user follows the instructions on the device and takes emergency measures, such as taking a rest immediately or providing first aid.

[1520] (Application example 2)

[1521] 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."

[1522] To improve the work efficiency and safety of robots in modern factories, it is essential to propose efficient and flexible work plans, detect abnormalities, and respond to emergencies. However, conventional systems lack sufficient automation to meet these requirements, and many tasks must be performed manually by managers, hindering efficiency. Furthermore, it is difficult to analyze the robot's work status and performance in real time and propose optimal work plans based on that analysis. Furthermore, rapid response is also required in the event of an emergency.

[1523] The identification process by the identification 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 a data input means used to input data of a new user, a generation means for generating a work plan based on past work data and basic information about the user, a proposal means for proposing the generated work plan to the user, a detection means for detecting anomalies, a response means for taking emergency action when an anomaly is detected, and an emotion analysis means for monitoring and adjusting the efficiency state of the user. This enables flexible and rapid response while improving the work efficiency of the robot and ensuring safety.

[1524] A "new user" is an individual or device that begins using the system for the first time.

[1525] "Data input means" refers to a device or program for collecting basic information about users and past work data.

[1526] "Task data" refers to information about the history and performance of tasks performed by a robot in the past.

[1527] "Basic information" refers to information about the attributes, goals, and initial settings of a user or robot.

[1528] A "task plan" is a specific plan created to allow a robot to efficiently perform a task.

[1529] The "generation means" is a program or device for generating an optimal work plan based on collected data.

[1530] The "proposing means" is a device or program that notifies the user of the generated work plan and encourages execution.

[1531] "Detection means" refers to sensors or programs used to detect abnormalities.

[1532] "Response means" refers to a device or program for carrying out an emergency response when an abnormality is detected.

[1533] "Emotion analysis means" refers to a program or device for monitoring and analyzing the efficiency and performance of a user or robot.

[1534] The present invention is a system that collects data on new users and robots, generates and proposes appropriate work plans, and detects and responds to anomalies. This system is realized by combining programs, hardware, and software. Each component and its processing are described in detail below.

[1535] Data Entry Method

[1536] The server monitors the robot's location and working status using cameras and sensors installed in the factory, and collects identification data when a new robot is introduced. When a new robot is introduced, the terminal displays a screen for scanning a QR code and provides a screen for entering basic information such as training goals. The user scans the QR code of the new robot and enters basic information and work goals.

[1537] generation means

[1538] The server runs a generative AI model based on the collected basic information and past work data to generate an appropriate work plan. This data is combined with previously collected historical data and analyzed. The generative AI model used is OpenAI's GPT-4, and the generated work plan is presented to the administrator's device.

[1539] Proposal means

[1540] The server sends instructions to the robot's AI to propose the generated work plan to the robot. The proposed work plan is presented to the terminal by voice and display. The administrator checks it and adjusts it as necessary.

[1541] Emotion analysis means

[1542] The server analyzes the robot's work performance data and managerial feedback to provide efficient work plans as feedback. TensorFlow is used as the emotion analysis engine.

[1543] Detection Method

[1544] The server collects data in real time from various sensors installed in the factory and detects any abnormalities, which are immediately notified to the administrator.

[1545] Countermeasures

[1546] When an abnormality is detected, the server sends an instruction to the robot's AI to switch to emergency response mode. The emergency situation is displayed on the terminal, and specific instructions for countermeasures are shown to the administrator.

[1547] Specific examples

[1548] When a new robot is introduced, the manager scans a QR code on the terminal and inputs basic information and work goals. For example, a work plan is generated based on basic information such as "New robot, Type X, goal is to improve picking efficiency" and past data such as "Processed 1,000 pieces in the past month."

[1549] Here is an example prompt:

[1550] Robot Basics: Type A, the goal is to improve picking efficiency

[1551] Historical data: 1000 pieces processed for the past month

[1552] Generate efficient work plans for this robot.

[1553] The program uses OpenAI GPT-4 to generate optimal work plans for the robots and TensorFlow to perform emotion analysis of the robots, improving work efficiency and ensuring safety.

[1554] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1555] Step 1: Data entry method

[1556] The server monitors the robot's location and working status in real time using cameras and sensors installed in the factory. When a new robot is introduced, the server collects and stores its identification data. The terminal displays a QR code scanning screen dedicated to the new robot, which the manager scans to enter basic information and work goals. The entered basic information (e.g., robot type, purpose) and work goals (e.g., improving the efficiency of picking work) are then transferred to the server.

[1557] Step 2: Generator

[1558] The server runs a generative AI model using the collected basic information and past work data. Specifically, it uses OpenAI GPT-4 to generate a work plan. Based on this prompt (e.g., "Robot basic information: Type A, goal is to improve picking efficiency. Past data: processed 1,000 pieces in the past month. Please generate an efficient work plan for this robot."), the generative AI model generates an optimal work plan. The generated work plan is sent from the server to the device.

[1559] Step 3: Proposal method

[1560] The server sends the generated work plan to the AI ​​inside the robot. The proposed work plan is displayed on the terminal and reviewed by the manager. For example, a specific work plan may be proposed, such as "focus on picking work on the first day, and maintenance work on the next day." The manager can adjust the work plan as necessary and finalize it.

[1561] Step 4: Sentiment Analysis Methods

[1562] The server analyzes work performance data collected from the factory robots and feedback from managers in real time. The sentiment analysis engine uses TensorFlow to analyze the robot's efficiency and whether there are any abnormalities. For example, if the robot's movements are slow, this may indicate a decrease in efficiency or an abnormality. The analysis results are notified to the terminal as feedback from the server.

[1563] Step 5: Detection Methods

[1564] The server collects data in real time from various sensors installed in the factory and detects abnormalities. For example, if a robot is not performing its scheduled operation or is overloaded, the server will immediately detect the abnormality based on the data from the sensor. The detected data is analyzed by the server, and if an abnormality is confirmed, the administrator is notified.

[1565] Step 6: Response measures

[1566] When an abnormality is detected, the server immediately sends an instruction to the AI ​​in the robot to switch to emergency response mode. The terminal displays the emergency situation and provides the administrator with specific response instructions (e.g., stop the robot and instruct a human to inspect it). In addition, if necessary, an automatic notification is sent to emergency contacts (e.g., technical support or emergency contacts). The administrator follows the emergency response instructions displayed on the terminal and takes appropriate action.

[1567] 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.

[1568] 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.

[1569] 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.

[1570] [Fourth embodiment]

[1571] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1572] 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.

[1573] 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).

[1574] 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.

[1575] 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.

[1576] 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).

[1577] 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.

[1578] 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.

[1579] 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.

[1580] 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.

[1581] 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.

[1582] 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.

[1583] 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."

[1584] The present invention is a system that allows users to train efficiently and safely at a 24-hour fitness gym. The system includes a data input means, a generation means, a proposal means, a detection means, and a response means. The functions of each means are explained below with specific examples.

[1585] Data Entry Method

[1586] Server: Collects data from cameras and sensors installed at the entrance to detect when a user arrives at the gym.

[1587] Device: When the user scans the QR code, a screen will appear prompting them to enter basic information (fitness experience, goals, etc.).

[1588] User: Enter a self-introduction and fitness goals into the input screen displayed on the device.

[1589] Example: When a user scans a QR code at the entrance, a screen appears on the device asking them to introduce themselves and enter their fitness goals. The user enters their goal as "I want to do strength training three times a week."

[1590] generation means

[1591] Server: Runs the generation AI to generate training plans based on the collected basic information and past training data.

[1592] Terminal: Proposes the training plan generated by the generation AI to the user.

[1593] Example: When a user enters basic information, the server uses a generative AI to generate a "strength training plan for one hour, three times a week" based on past data and the entered information. The device displays a specific plan such as "Squats and planks on the first day, deadlifts and side lunges on the second day, and bench presses and hip thrusts on the third day."

[1594] Proposal means

[1595] Server: Sends instructions to PepperGPT to suggest the training plan generated by the generator to the user.

[1596] Device: PepperGPT will propose the generated training plan to the user via voice and display.

[1597] User: Review the proposed training plans and select the plan they wish to implement.

[1598] Example: PepperGPT will say, "Hello, Mr. / Ms. X. Today's training plan is 30 minutes of strength training. Let's start with squats." The user will confirm the proposed plan and proceed to the next step.

[1599] Detection Method

[1600] Server: Collects data in real time from various sensors installed within the fitness gym and processes it to detect abnormalities.

[1601] Device: Prepare to display an emergency alert if an anomaly is detected.

[1602] Example: If a user falls during training, the heart rate monitor and fall detection sensor will detect the abnormality and the server will immediately send an alert to the device.

[1603] Countermeasures

[1604] Server: When an abnormality is detected, it immediately sends an instruction to PepperGPT to switch to emergency response mode.

[1605] Terminal: The terminal displays the emergency situation and provides specific instructions to the user. It also automatically notifies emergency contacts as needed.

[1606] User: Follow the emergency response instructions displayed on the device.

[1607] Example: If a user collapses, PepperGPT will provide a voice prompt saying, "This is an emergency. Please rest immediately. We will call an ambulance," and the device will simultaneously display, "An emergency has occurred. We will notify emergency contacts."

[1608] The above is a specific embodiment for carrying out the present invention. This system allows users to easily obtain an efficient training plan and also enables quick response in emergencies.

[1609] The processing flow will be explained below.

[1610] New User Guide

[1611] Step 1:

[1612] Server: Collects data from cameras and sensors installed at the entrance to confirm the user's entry and identifies whether the user is a new user.

[1613] Step 2:

[1614] Device: If a new user is identified, a screen for scanning a QR code will be displayed on the device.

[1615] Step 3:

[1616] User: Scan the QR code displayed on the device to start using the service.

[1617] Step 4:

[1618] Terminal: Displays a screen where users can enter basic information such as their fitness experience and goals.

[1619] Step 5:

[1620] User: Enter a profile and fitness goals into the device.

[1621] Step 6:

[1622] Server: Processes the basic information entered and sends a command to PepperGPT to start facility guidance.

[1623] Step 7:

[1624] Terminal: PepperGPT begins to provide voice guidance to the user, saying, "Hello, you are a new user. We will show you how to use the facility."

[1625] Short workout suggestions

[1626] Step 1:

[1627] User: Enter a time limit into the terminal, such as "Only 30 minutes available today."

[1628] Step 2:

[1629] Terminal: Sends the entered time limit to the server.

[1630] Step 3:

[1631] Server: Runs the generative AI to generate effective workout plans in a short amount of time based on past training data and basic user information.

[1632] Step 4:

[1633] Terminal: Displays the generated workout plan to the user.

[1634] Step 5:

[1635] User: Check the training plan displayed on the device and decide whether to carry it out.

[1636] Step 6:

[1637] Server: Optimizes training plans based on user feedback.

[1638] Goal setting support

[1639] Step 1:

[1640] User: Enter a specific goal into the device, such as "lose 5 kg in 3 months."

[1641] Step 2:

[1642] Terminal: Sends the entered goal to the server.

[1643] Step 3:

[1644] Server: Based on the input goal, the generation AI proposes a feasible method and timeframe for achieving the goal.

[1645] Step 4:

[1646] Device: The generated advice is displayed to the user and read aloud by PepperGPT.

[1647] Step 5:

[1648] User: Review the proposed goals and methods, make adjustments as needed, and finalize the goal setting.

[1649] Step 6:

[1650] Server: Stores the adjusted goals and methods and periodically tracks the user's progress.

[1651] Emergency Response Support

[1652] Step 1:

[1653] Server: Collects data in real time from heart rate monitors and fall detection sensors installed within the facility and detects abnormalities.

[1654] Step 2:

[1655] Terminal: Prepare to display an emergency situation if an abnormality is detected.

[1656] Step 3:

[1657] Server: When an abnormality is detected, it immediately sends an instruction to PepperGPT to switch to emergency response mode.

[1658] Step 4:

[1659] Device: An emergency message will be displayed on the device, along with specific steps to take. Emergency contacts will also be notified automatically.

[1660] Step 5:

[1661] User: Follow the emergency response instructions displayed on the device and, if necessary, seek assistance until the situation improves.

[1662] The above are the specific processing steps of this system. At each processing step, the server, terminal, and user work together to provide efficient training support.

[1663] Example 1

[1664] 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."

[1665] At current fitness gyms, users need a lot of time and effort to find an appropriate training plan that suits their individual fitness experience and goals. Real-time monitoring and rapid response to abnormalities to ensure user safety are also difficult. Therefore, there is a need for a system that allows users to train efficiently and safely.

[1666] 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.

[1667] In this invention, the server includes a data input means for inputting user data, a generation means for generating a training plan based on past training data and basic information about the user, a proposal means for proposing the generated training plan to the user, a detection means for detecting abnormalities, a response means for taking emergency action when an abnormality is detected, a means for collecting data from cameras and sensors to detect the arrival of the user, and a means for providing audio and visual guidance on the proposed training plan. This allows users to efficiently obtain training plans, monitors safety in real time, and enables rapid response to abnormalities.

[1668] "Data input means" refers to a device or method by which a user inputs basic information such as training information and goals.

[1669] "Generation means" refers to a device or method for creating an appropriate training plan based on collected data.

[1670] The "suggestion means" is a device or method for proposing the generated training plan to the user.

[1671] "Detection means" refers to a device or method for detecting abnormalities in users using sensors or cameras within the fitness gym.

[1672] "Response means" refers to a device or method for taking emergency action when an abnormality is detected.

[1673] "Means for collecting data from cameras and sensors" refers to devices or methods that detect the arrival or movement of users and collect data based on that.

[1674] "Means for providing audio or visual guidance on a training plan" refers to a device or method for providing audio guidance or displaying a generated training plan on a terminal screen to a user.

[1675] MODE FOR CARRYING OUT THE INVENTION

[1676] This invention is a system that allows users to train efficiently and safely at a 24-hour fitness gym. This system includes a data input means, a generation means, a proposal means, a detection means, and a response means. The functions of each means and specific operation examples are shown below.

[1677] Data Entry Method

[1678] Server: To detect when a user arrives at the gym, the server collects data from cameras and sensors installed at the entrance. The server analyzes this data and confirms that the user has arrived at the gym.

[1679] Terminal: When a user scans the QR code installed at the gym entrance, a screen will appear prompting them to enter basic information (fitness experience, goals, etc.), making it easy for users to enter the required information.

[1680] User: Enters a self-introduction and fitness goals into the input screen displayed on the device. Specifically, the user enters a goal such as "I want to do strength training three times a week."

[1681] generation means

[1682] Server: Based on the collected basic information and past training data, a training plan is generated using a "generative AI model." This generative AI model can be, for example, "ChatGPT Turbo."

[1683] Example: When a user enters basic information, the server uses training AI to generate a "strength training plan for one hour, three times a week" based on past data and the entered information. The generated plan contains specific content, and the device displays a specific plan such as "Squats and planks on the first day, deadlifts and side lunges on the second day, and bench presses and hip thrusts on the third day."

[1684] Proposal means

[1685] Server: Sends instructions to PepperGPT to suggest the generated training plan to the user.

[1686] On the device, PepperGPT will propose the generated training plan to the user via voice and display. For example, it might say, "Hello, Mr. / Ms. X. Today's training plan is 30 minutes of strength training. Let's start with squats."

[1687] Detection Method

[1688] Server: Collects data in real time from various sensors installed in the fitness gym and processes it to detect abnormalities. For example, heart rate monitors and fall detection sensors are used.

[1689] Terminal: Prepare to display an emergency alert if an abnormality is detected. When the server detects an abnormality, it immediately sends an alert to the terminal.

[1690] Example: If a user falls during training, the heart rate monitor and fall detection sensor will detect the abnormality and the server will immediately send an alert to the device.

[1691] Countermeasures

[1692] Server: When an abnormality is detected, PepperGPT is immediately instructed to switch to emergency response mode, enabling a rapid response.

[1693] Terminal: The terminal displays the emergency situation and provides specific instructions to the user. It also automatically notifies emergency contacts as needed.

[1694] User: Follow the emergency response instructions displayed on the device. For example, PepperGPT will say, "This is an emergency. Please rest immediately. We will call an ambulance," and the device will simultaneously display, "Emergency situation has occurred. We will notify emergency contacts."

[1695] Prompt Sentence Examples

[1696] A user arrives at the gym. They scan a QR code to enter their basic information and fitness goals. For example, "I want to do one hour of strength training three times a week." Once they've completed the input, they can begin generating a training plan.

[1697] This system allows users to easily obtain efficient training plans and also enables quick response in emergencies.

[1698] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1699] Step 1:

[1700] User arrival detection

[1701] Server: Operates the camera and sensor system installed at the gym entrance.

[1702] Input: Images and data captured from cameras and sensors.

[1703] Data processing: Image analysis is used to recognize people's movements and faces.

[1704] Output: A flag confirming the user's arrival.

[1705] How it works: The camera captures the user's image data, the sensor detects their presence, and the server analyzes this data to recognize the user's arrival.

[1706] Step 2:

[1707] Prompt for QR code scanning and basic information entry

[1708] Terminal: When the user scans the QR code installed at the entrance, a screen for entering basic information is displayed.

[1709] Input: User ID via QR code scan.

[1710] Data processing: Decode the contents of the QR code and extract the user ID.

[1711] Output: Basic information input screen.

[1712] Specific operation: The QR code is scanned with the device's camera. The device then displays an input screen prompting the user to "Enter your name, age, fitness experience, and goals."

[1713] Step 3:

[1714] Enter your basic information and fitness goals

[1715] User: Enter basic information and fitness goals.

[1716] Input: Basic information entered by the user into the input screen (name, age, fitness experience, goals).

[1717] Data Calculation: Validation and storage of input data.

[1718] Output: User's basic information and goals.

[1719] Specific Action: A user inputs a fitness goal: "I want to do strength training three times a week."

[1720] Step 4:

[1721] Generate a training plan

[1722] Server: Runs the generative AI model based on collected basic information and past training data.

[1723] Input: User's basic information and past training data.

[1724] Data processing: Inputting and analyzing data into generative AI models.

[1725] Output: The generated training plan.

[1726] Specific operation: The server uses training AI to generate a "strength training plan for one hour, three times a week" based on past data and input information. The generated plan contains specific content.

[1727] Step 5:

[1728] Training plan suggestions

[1729] Server: Sends the generated training plan to PepperGPT.

[1730] Input: The generated training plan.

[1731] Data processing: Instructions for sending training plan.

[1732] Output: Suggested instructions to PepperGPT.

[1733] Specific operation: Details of the generated training plan are sent to PepperGPT via API.

[1734] Device: PepperGPT will suggest training plans to the user via voice and display.

[1735] Input: Proposal data from PepperGPT.

[1736] Data processing: speech synthesis and display on the screen.

[1737] Output: Suggestions to the user.

[1738] Specific actions: PepperGPT will guide you by saying, "Hello, Mr. / Ms. XX. Today's training plan is 30 minutes of strength training. Let's start with squats."

[1739] Step 6:

[1740] Monitoring during training

[1741] Server: Collects data in real time from various sensors within the fitness gym and processes it to detect abnormalities.

[1742] Input: Data from heart rate monitors and fall detection sensors.

[1743] Data processing: Real-time analysis for anomaly detection.

[1744] Output: Anomaly detection flag.

[1745] Specific operation: The server receives data from the heart rate monitor and fall detection sensor in real time and analyzes it to detect abnormalities.

[1746] Step 7:

[1747] Emergency response

[1748] Server: When an abnormality is detected, it immediately sends an instruction to PepperGPT to switch to emergency response mode.

[1749] Input: Anomaly detection flag.

[1750] Data processing: Generation of emergency response instructions.

[1751] Output: Emergency response instructions to PepperGPT.

[1752] Specific operation: The server sends emergency response instructions to PepperGPT through the API, causing it to immediately begin emergency response.

[1753] Terminal: Provides emergency response instructions to the user via voice and display, and also notifies emergency contacts as necessary.

[1754] Input: Emergency response instructions from the server.

[1755] Data processing: Voice synthesis and on-screen display of emergency instructions.

[1756] Output: Instructs the user on emergency measures and makes an emergency call.

[1757] Specific operation: The device displays "Emergency! Please stay still until an ambulance arrives" and automatically calls emergency contacts.

[1758] Users: Follow emergency plan instructions.

[1759] Input: Emergency instructions from terminal.

[1760] Data calculation: Deciding on actions based on instructions.

[1761] Output: Safety action.

[1762] Specific actions: The user follows the instructions to stay calm and wait for the ambulance to arrive.

[1763] (Application example 1)

[1764] 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."

[1765] To ensure that new users can train efficiently and safely at fitness facilities, it is necessary to provide individually tailored training plans and monitor safety in real time. However, traditional fitness facilities face challenges such as users having to make their own decisions when training, which increases the risk of users training incorrectly and makes it difficult to respond quickly to emergencies. Furthermore, providing users with training plans tailored to their individual fitness goals requires processing large amounts of data, making it difficult to perform complex calculations in real time.

[1766] 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.

[1767] In this invention, the server includes a generating means for generating a training plan based on past training data and basic information of the user, a means for generating and inputting prompts to the generating AI model to generate a training plan suited to the user's fitness goals using the generating AI model, a suggesting means for suggesting and notifying the user of the generated training plan and emergency alerts, a detecting means for acquiring data in real time from sensors installed in the fitness facility and detecting abnormalities, and a responding means for taking emergency action when an abnormality is detected. This makes it possible to provide users with efficient and individually tailored training plans, while simultaneously enabling rapid response to emergencies and ensuring safety.

[1768] A "new user" is someone using a fitness facility for the first time, or an existing user who needs a new training plan.

[1769] "Data input means" refers to the tools and methods used to input basic information about the user, fitness goals, past training data, etc.

[1770] "Generation means" refers to tools and methods for generating an appropriate training plan based on input data and past training information.

[1771] A "generative AI model" refers to an algorithm or system that uses artificial intelligence to process data and generate an appropriate training plan.

[1772] A "prompt" refers to a specific form of sentence used to give specific instructions or questions to a generative AI model.

[1773] "Proposal means" refers to the tools and methods used to propose and notify users of generated training plans and emergency alerts.

[1774] "Detection Methods" means tools or methods for detecting abnormal conditions or emergencies based on data from sensors installed within a fitness facility.

[1775] "Response measures" refer to tools and methods for quickly taking appropriate action when an abnormality or emergency is detected.

[1776] The present invention provides a system for enabling users to train efficiently and safely in a fitness facility, the system including a data input means, a generating means, a suggesting means, a detecting means, and a responding means.

[1777] Data Entry Method

[1778] The server collects data from cameras and sensors installed at the entrances of fitness facilities and detects the arrival of users. When the user scans a QR code, the device displays a screen prompting them to enter basic information (fitness experience, goals, etc.). Through this screen, the user enters their self-introduction and fitness goals. For example, when a user scans a QR code at the entrance, a screen prompting them to enter their self-introduction and fitness goals appears on the device, and the user enters their goal, such as "I want to do strength training three times a week."

[1779] generation means

[1780] The server runs a generative AI model to generate a training plan based on the collected basic information and past training data. A means for generating and inputting prompts for the generative AI model is included. For example, when a user inputs basic information, the server uses the generative AI model to generate a "strength training plan for one hour, three times a week" based on the past data and the input information, using the following prompt:

[1781] Username: "User A"

[1782] Fitness Experience: "Intermediate"

[1783] Fitness goal: "Strength training three times a week"

[1784] Past training data: "Squat", "Deadlift"

[1785] The device displays a specific plan, such as "Day 1: Squats and planks, Day 2: Deadlifts and side lunges, Day 3: Bench presses and hip thrusts."

[1786] Proposal means

[1787] The server sends instructions to the terminal to propose the training plan generated by the generation means to the user. After this, the terminal proposes the generated training plan to the user by voice or display. The user checks the proposed training plan and selects the plan to implement. For example, the terminal may say, "Today's training plan is 30 minutes of strength training. Let's start with squats," and the user may confirm the proposed plan.

[1788] Detection Method

[1789] The server collects data in real time from various sensors installed in the fitness facility and processes it to detect abnormalities. For example, if a user falls during training, the heart rate monitor or fall detection sensor will detect the abnormality and the server will immediately send an alert to the device.

[1790] Countermeasures

[1791] When an abnormality is detected, the server immediately sends an instruction to switch to emergency response mode. The device displays the emergency situation and provides the user with specific instructions on what to do. It also automatically notifies emergency contacts if necessary. For example, if the user collapses, the device will announce in voice, "This is an emergency. Please rest immediately. We will call an ambulance," and at the same time display, "An emergency has occurred. We will notify emergency contacts."

[1792] The above is a specific embodiment for carrying out the present invention. This system allows users to easily obtain an efficient training plan and also enables quick response in emergencies.

[1793] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1794] Step 1:

[1795] When a user arrives at a fitness facility, they scan a QR code at the entrance. The device then displays a screen where the user can enter their basic information and fitness goals. Once the user has finished entering their details, the data is sent to the server.

[1796] Input: User basic information, fitness goals

[1797] Data processing / data calculation: Collection and storage of input data

[1798] Output: Send user information to the server

[1799] Step 2:

[1800] The server runs a generative AI model to generate a training plan based on the collected basic information and past training data. The server provides the specified prompt sentences to the generative AI model to create an appropriate training plan.

[1801] Input: User's basic information, past training data

[1802] Data processing / data calculation: Prompt generation for generative AI models and training plan generation

[1803] Output: Generated training plan

[1804] Step 3:

[1805] The server sends the generated training plan to the device, which then presents it to the user via voice guidance and on-screen display. The user can then review the proposed training plans and select the one they wish to implement.

[1806] Input: Generated training plan

[1807] Data processing / data calculation: Display of training plan and voice guidance

[1808] Output: User confirms and selects training plan

[1809] Step 4:

[1810] The server collects data in real time from various sensors installed in the fitness center and processes it to detect abnormalities. Based on the data collected from the sensors, it determines whether there are any abnormalities.

[1811] Input: Real-time data from sensors

[1812] Data processing / data calculation: Real-time data analysis and anomaly detection

[1813] Output: Anomaly detection results

[1814] Step 5:

[1815] When an abnormality is detected, the server immediately sends an instruction to switch to emergency response mode. The device notifies the user of the emergency through voice guidance and on-screen display, and automatically notifies emergency contacts if necessary. The user follows the instructions on the device and takes appropriate action.

[1816] Input: Anomaly detection results, user location, contact information

[1817] Data processing / data calculation: generation and notification of emergency response instructions

[1818] Output: Emergency response and automatic notification

[1819] By following these steps, a system is realized that provides effective training plans while ensuring the safety of users within a fitness facility.

[1820] 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.

[1821] This invention is a system that enables users to train efficiently and safely at a 24-hour fitness gym. This system is provided by combining a data input means, a generation means, a proposal means, a detection means, a response means, and an emotion engine. The function of each means is explained below with specific examples.

[1822] Data Entry Method

[1823] Server: Collects data from cameras and sensors installed at the entrance to confirm the user's entry and identifies whether the user is a new user.

[1824] Device: If a new user is identified, a screen for scanning a QR code will be displayed on the device.

[1825] User: Scan the QR code displayed on the device to start using the service.

[1826] Terminal: Displays a screen where users can enter basic information such as their fitness experience and goals.

[1827] User: Enter a profile and fitness goals into the device.

[1828] Example: When a user scans a QR code at the entrance, a screen appears on the device asking them to introduce themselves and enter their fitness goals. The user enters their goal as "I want to do strength training three times a week."

[1829] generation means

[1830] Server: Runs the generation AI to generate training plans based on the collected basic information and past training data.

[1831] Terminal: Proposes the training plan generated by the generation AI to the user.

[1832] Example: When a user enters basic information, the server uses a generative AI to generate a "strength training plan for one hour, three times a week" based on past data and the entered information. The device displays a specific plan such as "Squats and planks on the first day, deadlifts and side lunges on the second day, and bench presses and hip thrusts on the third day."

[1833] Proposal means

[1834] Server: Sends instructions to PepperGPT to suggest the training plan generated by the generator to the user.

[1835] Device: PepperGPT will propose the generated training plan to the user via voice and display.

[1836] User: Review the proposed training plans and select the plan they wish to implement.

[1837] Example: PepperGPT will say, "Hello, Mr. / Ms. X. Today's training plan is 30 minutes of strength training. Let's start with squats." The user will confirm the proposed plan and proceed to the next step.

[1838] Emotion Engine

[1839] Server: The emotion engine collects data to analyze the user's voice and facial expressions and recognize emotions.

[1840] Terminal: The emotion engine receives feedback on the user's emotional state based on the analysis results.

[1841] User: Review the suggestions tailored through emotion recognition and select a plan to implement.

[1842] Example: If a user says to their device, "I'm not feeling very well today," the emotion engine will analyze this and PepperGPT will adjust its suggestions, saying, "It seems like you're not feeling well. I recommend some light stretching and breathing exercises today."

[1843] Detection Method

[1844] Server: Collects data in real time from various sensors installed within the fitness gym and processes it to detect abnormalities.

[1845] Device: Prepare to display an emergency alert if an anomaly is detected.

[1846] Example: If a user falls during training, the heart rate monitor and fall detection sensor will detect the abnormality and the server will immediately send an alert to the device.

[1847] Countermeasures

[1848] Server: When an abnormality is detected, it immediately sends an instruction to PepperGPT to switch to emergency response mode.

[1849] Terminal: The terminal displays the emergency situation and provides specific instructions to the user. It also automatically notifies emergency contacts as needed.

[1850] User: Follow the emergency response instructions displayed on the device.

[1851] Example: If a user collapses, PepperGPT will provide a voice prompt saying, "This is an emergency. Please rest immediately. We will call an ambulance," and the device will simultaneously display, "An emergency has occurred. We will notify emergency contacts."

[1852] The above is a specific embodiment for carrying out the present invention. By combining it with an emotion engine, it becomes possible to propose flexible training plans that take into account the user's emotional state, which is expected to improve user satisfaction to a greater extent.

[1853] The processing flow will be explained below.

[1854] New User Guide

[1855] Step 1:

[1856] Server: Collects data from cameras and sensors installed at the entrance to confirm the user's entry and identifies whether the user is a new user.

[1857] Step 2:

[1858] Device: If a new user is identified, a screen for scanning a QR code will be displayed on the device.

[1859] Step 3:

[1860] User: Scan the QR code displayed on the device to start using the service.

[1861] Step 4:

[1862] Terminal: Displays a screen where users can enter basic information such as their fitness experience and goals.

[1863] Step 5:

[1864] User: Enter a profile and fitness goals into the device.

[1865] Step 6:

[1866] Server: Processes the basic information entered and sends a command to PepperGPT to start facility guidance.

[1867] Step 7:

[1868] Terminal: PepperGPT begins to provide voice guidance to the user, saying, "Hello, you are a new user. We will show you how to use the facility."

[1869] Short workout suggestions

[1870] Step 1:

[1871] User: Enter a time limit into the terminal, such as "Only 30 minutes available today."

[1872] Step 2:

[1873] Terminal: Sends the entered time limit to the server.

[1874] Step 3:

[1875] Server: Runs the generative AI to generate effective workout plans in a short amount of time based on past training data and basic user information.

[1876] Step 4:

[1877] Terminal: Displays the generated workout plan to the user.

[1878] Step 5:

[1879] User: Check the training plan displayed on the device and decide whether to carry it out.

[1880] Step 6:

[1881] Server: Optimizes training plans based on user feedback.

[1882] Goal setting support

[1883] Step 1:

[1884] User: Enter a specific goal into the device, such as "lose 5 kg in 3 months."

[1885] Step 2:

[1886] Terminal: Sends the entered goal to the server.

[1887] Step 3:

[1888] Server: Based on the input goal, the generation AI proposes a feasible method and timeframe for achieving the goal.

[1889] Step 4:

[1890] Device: The generated advice is displayed to the user and read aloud by PepperGPT.

[1891] Step 5:

[1892] User: Review the proposed goals and methods, make adjustments as needed, and finalize the goal setting.

[1893] Step 6:

[1894] Server: Stores the adjusted goals and methods and periodically tracks the user's progress.

[1895] Emotion Engine

[1896] Step 1:

[1897] Server: Collects data for the emotion engine to analyze the user's voice and facial expressions to recognize emotions.

[1898] Step 2:

[1899] Terminal: The emotion engine receives feedback on the user's emotional state based on the analysis results.

[1900] Step 3:

[1901] User: Review the suggestions tailored through emotion recognition and select a plan to implement.

[1902] Step 4:

[1903] Server: Based on the user's emotional data, the server adjusts the training plan and suggestions accordingly.

[1904] Step 5:

[1905] On the device: The adjustment results are displayed to the user, and PepperGPT provides voice guidance.

[1906] Example: If a user says to their device, "I'm not feeling very well today," the emotion engine will analyze this and PepperGPT will adjust its suggestions, saying, "It seems like you're not feeling well. I recommend some light stretching and breathing exercises today."

[1907] Detection Method

[1908] Step 1:

[1909] Server: Collects data in real time from various sensors installed within the fitness gym and processes it to detect abnormalities.

[1910] Step 2:

[1911] Device: Prepare to display an emergency alert if an anomaly is detected.

[1912] Example: If a user falls during training, the heart rate monitor and fall detection sensor will detect the abnormality and the server will immediately send an alert to the device.

[1913] Countermeasures

[1914] Step 1:

[1915] Server: When an abnormality is detected, it immediately sends an instruction to PepperGPT to switch to emergency response mode.

[1916] Step 2:

[1917] Terminal: The terminal displays the emergency situation and provides specific instructions to the user. It also automatically notifies emergency contacts as needed.

[1918] Step 3:

[1919] User: Follow the emergency response instructions displayed on the device.

[1920] Example: If a user collapses, PepperGPT will provide a voice prompt saying, "This is an emergency. Please rest immediately. We will call an ambulance," and the device will simultaneously display, "An emergency has occurred. We will notify emergency contacts."

[1921] The above is a specific embodiment for carrying out the present invention. By combining it with an emotion engine, it becomes possible to propose flexible training plans that take into account the user's emotional state, which is expected to improve user satisfaction to a greater extent.

[1922] Example 2

[1923] 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."

[1924] In conventional fitness gyms, it is difficult for users to independently adjust their training plans to suit their own physical condition and emotional state, and quick response is required when abnormalities occur. Furthermore, there is a lack of systems that utilize individual user data to provide optimal exercise plans. To solve this problem, there is a need for an integrated fitness support system that includes flexible proposals that take users' emotional state into account and quick response when abnormalities occur.

[1925] 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.

[1926] In this invention, the server

[1927] a data capture means used to input new user data;

[1928] A plan generation means for generating an exercise plan based on past exercise data and basic information of the user;

[1929] a suggestion means for suggesting the generated exercise plan to a user;

[1930] an anomaly detection means for detecting an anomaly;

[1931] an emergency response means for taking emergency action when an abnormality is detected;

[1932] emotion analysis means for analyzing the user's voice and facial expression to recognize emotions;

[1933] a voice suggestion means for suggesting an exercise plan to a user by voice;

[1934] Includes:

[1935] This will enable the system to propose flexible training plans that take into account the user's emotional state, as well as to respond quickly and appropriately in the event of an emergency.

[1936] "Data acquisition means" refers to the devices or systems used to input user data, such as cameras or sensors installed at entrances or the QR code scanning function displayed on terminals.

[1937] The "plan generation means" is a function that generates an optimal exercise plan based on collected past exercise data and basic information of the user. This includes a generative AI model.

[1938] The "suggestion means" refers to a means for presenting the generated exercise plan to the user, including a display on the device and audio guidance.

[1939] "Anomaly detection means" refers to sensors or monitoring systems that detect abnormalities within the fitness gym. Examples include heart rate monitors and fall detection sensors.

[1940] "Emergency response measures" are measures for taking prompt and appropriate action when an abnormality is detected, including displaying an emergency alert and automatically notifying emergency contacts.

[1941] "Emotion analysis means" refers to a system that analyzes a user's voice and facial expressions to recognize their emotional state. This includes voice analysis software and facial expression recognition technology.

[1942] The "audio suggestion means" refers to a means for suggesting the generated exercise plan to the user by voice, including a voice assistant function and a speaker.

[1943] This invention is a system that allows users to train efficiently and safely at a 24-hour fitness gym. This system is provided by combining a data acquisition means, a plan generation means, a proposal means, an anomaly detection means, an emergency response means, and an emotion analysis means. The specific functions and operations of each means are described below.

[1944] Data Acquisition Method

[1945] The server collects data from cameras and sensors installed at the entrance to confirm the user's entry and, based on this data, distinguishes between new and existing users.

[1946] If the device recognizes the user as a new user, it displays a screen for scanning a QR code and prompts the user to enter basic information.

[1947] Users scan a QR code displayed on their device and enter a profile picture and fitness goals.

[1948] Examples:

[1949] When users scan the QR code at the entrance, a screen appears on the device where they can introduce themselves and enter their fitness goals. The user enters their goal, such as "I want to do strength training three times a week."

[1950] Plan Generation Method

[1951] The server runs a generative AI model based on the collected basic information and past training data to generate an optimal training plan.

[1952] The device proposes a training plan generated by the generation AI to the user.

[1953] Examples:

[1954] Once the user enters their basic information, the server uses a generative AI to generate a "strength training plan for one hour, three times a week" based on past data and the information entered. The device displays a specific plan such as "Squats and planks on the first day, deadlifts and side lunges on the second day, and bench presses and hip thrusts on the third day."

[1955] Proposal means

[1956] The server sends instructions to propose the training plan generated by the generating means.

[1957] The device will suggest a training plan to the user by voice or display.

[1958] The user reviews the proposed training plans and selects the plan to implement.

[1959] Examples:

[1960] The device will say, "Hello, Mr. / Ms. X. Today's training plan is 30 minutes of strength training." The user will confirm the proposed plan and proceed to the next step.

[1961] Emotion analysis means

[1962] The server uses an emotion engine to analyze the user's voice and facial expressions and collect data to recognize emotions.

[1963] The terminal receives the user's emotional state as feedback based on the analysis results of the emotion engine.

[1964] The user checks the proposals adjusted by emotion recognition and selects a plan to implement.

[1965] Examples:

[1966] If a user tells the device, "I'm not feeling very well today," the emotion engine analyzes this and the device adjusts its suggestions, saying, "You seem to be feeling unwell. I recommend some light stretching and breathing exercises today."

[1967] Anomaly detection means

[1968] The server collects data in real time from various sensors installed within the fitness gym and performs processing to detect abnormalities.

[1969] The device will display an emergency alert if an abnormality is detected.

[1970] Examples:

[1971] If a user falls during training, the heart rate monitor and fall detection sensor will detect the abnormality, and the server will immediately send an alert to the device.

[1972] Emergency response measures

[1973] When an abnormality is detected, the server immediately sends an instruction to switch to emergency response mode.

[1974] The terminal displays the emergency situation, provides specific instructions to the user, and automatically notifies emergency contacts as necessary.

[1975] The user follows the emergency response instructions displayed on the terminal.

[1976] Examples:

[1977] If the user collapses, the device will provide a voice message saying, "This is an emergency. Please rest immediately. We will call an ambulance," and at the same time display the message, "An emergency has occurred. We will notify emergency contact points."

[1978] Prompt Sentence Examples

[1979] 1. Example prompt

[1980] Describe a scenario where a new user enters a fitness gym and scans a QR code to begin their session. The user then introduces themselves and their fitness goals, and the generative AI uses that information to suggest training plans. Include using sentiment analysis to adjust suggestions based on the user's mood.

[1981] In this way, by linking the server, terminal, and user, we have created a system that offers a safe and effective fitness experience by proposing the optimal exercise plan based on the user's emotions and condition and responding quickly in the event of an abnormality.

[1982] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1983] Step 1:

[1984] The server collects data from cameras and sensors installed at the entrances to confirm the user's entry, and processes this data in real time to identify whether the user is a new or existing user.

[1985] Input: Image data and sensor data obtained from cameras and sensors

[1986] Output: User identification information

[1987] How it works: The camera captures the user's image, and sensors collect data such as movement and body temperature. The server analyzes this information to determine whether the user is a new or existing user.

[1988] Step 2:

[1989] If the device recognizes the user as a new user, it displays a screen for scanning a QR code and prompts the user to enter basic information.

[1990] Input: New user identification information received from the server

[1991] Output: QR code scanning screen and basic information input screen

[1992] Specific behavior: The device prepares to scan the QR code and displays the necessary screen. After the user scans the QR code, the device displays a screen for entering basic information.

[1993] Step 3:

[1994] Users scan a QR code displayed on their device and enter a profile picture and fitness goals.

[1995] Input: QR code, bio information, and fitness goals

[1996] Output: User information entered

[1997] Specific operation: The user scans the QR code using a smartphone or other device, and then enters their fitness goals on the input screen that appears.

[1998] Step 4:

[1999] The server collects basic information and past training data entered by the user and runs a generative AI model to generate an optimal training plan.

[2000] Input: Basic information, past training data, generative AI model

[2001] Power: Optimal training plan

[2002] How it works: The server stores the information received from the user and runs a generative AI model that compares it with past training data. The generative AI model performs calculations and analysis to generate a personalized training plan.

[2003] Step 5:

[2004] The terminal displays the generated training plan to the user and also provides audio guidance.

[2005] Input: Training plan sent from the server

[2006] Output: On-screen training plan and audio guidance

[2007] Specific operation: The device displays the training plan information on the screen, and at the same time, an audio guide guides the user through the plan.

[2008] Step 6:

[2009] The user reviews the proposed training plans and selects the plan to implement.

[2010] Input: Training plan displayed on device

[2011] Output: Selected training plan

[2012] Specific operation: The user checks the screen display and selects the plan they want to implement from the options.

[2013] Step 7:

[2014] The server uses emotion analysis to analyze the user's voice and facial expressions to recognize their emotions, and provides feedback on the content of the suggestions based on this.

[2015] Input: User's voice data, facial expression data

[2016] Output: Parsed emotion information

[2017] Specific operation: The server captures the user's voice and facial expressions, processes the data using emotion analysis, and adjusts the training plan based on the analysis results.

[2018] Step 8:

[2019] The device adjusts suggestions to the user based on the emotion analysis results.

[2020] Input: Sentiment analysis results

[2021] Output: Tailored training plan

[2022] Specific operation: The device receives the emotion analysis results and presents the adjusted training plan to the user again.

[2023] Step 9:

[2024] The server collects data in real time from sensors inside the fitness gym and detects any abnormalities.

[2025] Input: Sensor data

[2026] Output: Abnormal warning

[2027] Specific operation: The server continuously reads data from the sensors and immediately issues an alert if it detects an abnormality.

[2028] Step 10:

[2029] If an abnormality is detected, the device will display an emergency alert and provide specific instructions to the user. It will also automatically notify emergency contacts if necessary.

[2030] Input: Abnormal warning from the server

[2031] Output: Emergency alert display, emergency call

[2032] Specific operation: The device displays an emergency alert and provides instructions to the user, while automatically notifying emergency contacts.

[2033] Step 11:

[2034] The user follows the emergency response instructions displayed on the device and acts safely.

[2035] Input: Emergency response instructions displayed on the terminal

[2036] Output: User's response action

[2037] Specific actions: The user follows the instructions on the device and takes emergency measures, such as taking a rest immediately or providing first aid.

[2038] (Application example 2)

[2039] 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."

[2040] To improve the work efficiency and safety of robots in modern factories, it is essential to propose efficient and flexible work plans, detect abnormalities, and respond to emergencies. However, conventional systems lack sufficient automation to meet these requirements, and many tasks must be performed manually by managers, hindering efficiency. Furthermore, it is difficult to analyze the robot's work status and performance in real time and propose optimal work plans based on that analysis. Furthermore, rapid response is also required in the event of an emergency.

[2041] The identification process by the identification 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 a data input means used to input data of a new user, a generation means for generating a work plan based on past work data and basic information about the user, a proposal means for proposing the generated work plan to the user, a detection means for detecting anomalies, a response means for taking emergency action when an anomaly is detected, and an emotion analysis means for monitoring and adjusting the efficiency state of the user. This enables flexible and rapid response while improving the work efficiency of the robot and ensuring safety.

[2042] A "new user" is an individual or device that begins using the system for the first time.

[2043] "Data input means" refers to a device or program for collecting basic information about users and past work data.

[2044] "Task data" refers to information about the history and performance of tasks performed by a robot in the past.

[2045] "Basic information" refers to information about the attributes, goals, and initial settings of a user or robot.

[2046] A "task plan" is a specific plan created to allow a robot to efficiently perform a task.

[2047] The "generation means" is a program or device for generating an optimal work plan based on collected data.

[2048] The "proposing means" is a device or program that notifies the user of the generated work plan and encourages execution.

[2049] "Detection means" refers to sensors or programs used to detect abnormalities.

[2050] "Response means" refers to a device or program for carrying out an emergency response when an abnormality is detected.

[2051] "Emotion analysis means" refers to a program or device for monitoring and analyzing the efficiency and performance of a user or robot.

[2052] The present invention is a system that collects data on new users and robots, generates and proposes appropriate work plans, and detects and responds to anomalies. This system is realized by combining programs, hardware, and software. Each component and its processing are described in detail below.

[2053] Data Entry Method

[2054] The server monitors the robot's location and working status using cameras and sensors installed in the factory, and collects identification data when a new robot is introduced. When a new robot is introduced, the terminal displays a screen for scanning a QR code and provides a screen for entering basic information such as training goals. The user scans the QR code of the new robot and enters basic information and work goals.

[2055] generation means

[2056] The server runs a generative AI model based on the collected basic information and past work data to generate an appropriate work plan. This data is combined with previously collected historical data and analyzed. The generative AI model used is OpenAI's GPT-4, and the generated work plan is presented to the administrator's device.

[2057] Proposal means

[2058] The server sends instructions to the robot's AI to propose the generated work plan to the robot. The proposed work plan is presented to the terminal by voice and display. The administrator checks it and adjusts it as necessary.

[2059] Emotion analysis means

[2060] The server analyzes the robot's work performance data and managerial feedback to provide efficient work plans as feedback. TensorFlow is used as the emotion analysis engine.

[2061] Detection Method

[2062] The server collects data in real time from various sensors installed in the factory and detects any abnormalities, which are immediately notified to the administrator.

[2063] Countermeasures

[2064] When an abnormality is detected, the server sends an instruction to the robot's AI to switch to emergency response mode. The emergency situation is displayed on the terminal, and specific instructions for countermeasures are shown to the administrator.

[2065] Specific examples

[2066] When a new robot is introduced, the manager scans a QR code on the terminal and inputs basic information and work goals. For example, a work plan is generated based on basic information such as "New robot, Type X, goal is to improve picking efficiency" and past data such as "Processed 1,000 pieces in the past month."

[2067] Here is an example prompt:

[2068] Robot Basics: Type A, the goal is to improve picking efficiency

[2069] Historical data: 1000 pieces processed for the past month

[2070] Generate efficient work plans for this robot.

[2071] The program uses OpenAI GPT-4 to generate optimal work plans for the robots and TensorFlow to perform emotion analysis of the robots, improving work efficiency and ensuring safety.

[2072] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2073] Step 1: Data entry method

[2074] The server monitors the robot's location and working status in real time using cameras and sensors installed in the factory. When a new robot is introduced, the server collects and stores its identification data. The terminal displays a QR code scanning screen dedicated to the new robot, which the manager scans to enter basic information and work goals. The entered basic information (e.g., robot type, purpose) and work goals (e.g., improving the efficiency of picking work) are then transferred to the server.

[2075] Step 2: Generator

[2076] The server runs a generative AI model using the collected basic information and past work data. Specifically, it uses OpenAI GPT-4 to generate a work plan. Based on this prompt (e.g., "Robot basic information: Type A, goal is to improve picking efficiency. Past data: processed 1,000 pieces in the past month. Please generate an efficient work plan for this robot."), the generative AI model generates an optimal work plan. The generated work plan is sent from the server to the device.

[2077] Step 3: Proposal method

[2078] The server sends the generated work plan to the AI ​​inside the robot. The proposed work plan is displayed on the terminal and reviewed by the manager. For example, a specific work plan may be proposed, such as "focus on picking work on the first day, and maintenance work on the next day." The manager can adjust the work plan as necessary and finalize it.

[2079] Step 4: Sentiment Analysis Methods

[2080] The server analyzes work performance data collected from the factory robots and feedback from managers in real time. The sentiment analysis engine uses TensorFlow to analyze the robot's efficiency and whether there are any abnormalities. For example, if the robot's movements are slow, this may indicate a decrease in efficiency or an abnormality. The analysis results are notified to the terminal as feedback from the server.

[2081] Step 5: Detection Methods

[2082] The server collects data in real time from various sensors installed in the factory and detects abnormalities. For example, if a robot is not performing its scheduled operation or is overloaded, the server will immediately detect the abnormality based on the data from the sensor. The detected data is analyzed by the server, and if an abnormality is confirmed, the administrator is notified.

[2083] Step 6: Response measures

[2084] When an abnormality is detected, the server immediately sends an instruction to the AI ​​in the robot to switch to emergency response mode. The terminal displays the emergency situation and provides the administrator with specific response instructions (e.g., stop the robot and instruct a human to inspect it). In addition, if necessary, an automatic notification is sent to emergency contacts (e.g., technical support or emergency contacts). The administrator follows the emergency response instructions displayed on the terminal and takes appropriate action.

[2085] 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.

[2086] 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.

[2087] 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.

[2088] 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.

[2089] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2090] 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.

[2091] 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).

[2092] 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.

[2093] 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."

[2094] 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.

[2095] 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).

[2096] 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.

[2097] 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.

[2098] 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.

[2099] 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.

[2100] 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.

[2101] 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.

[2102] 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.

[2103] 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.

[2104] 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.

[2105] 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.

[2106] The following is further disclosed regarding the above embodiment.

[2107] (Claim 1)

[2108] data entry means used to enter new user data;

[2109] A generation means for generating a training plan based on past training data and basic information of the user;

[2110] a suggestion means for suggesting the generated training plan to a user;

[2111] detection means for detecting an abnormality;

[2112] A response method for taking emergency action when an abnormality is detected;

[2113] A system including:

[2114] (Claim 2)

[2115] 2. The system of claim 1, wherein the data input means includes scanning means for scanning a QR code.

[2116] (Claim 3)

[2117] 10. The system of claim 1, wherein the generating means includes means for generating a recommendation based on a user's fitness goals.

[2118] "Example 1"

[2119] (Claim 1)

[2120] data entry means used to enter new user data;

[2121] A generation means for generating a training plan based on past training data and basic information of the user;

[2122] a suggestion means for suggesting the generated training plan to a user;

[2123] detection means for detecting an abnormality;

[2124] A response method for taking emergency action when an abnormality is detected;

[2125] A means of collecting data from cameras and sensors to detect the arrival of users;

[2126] A means of providing audio and visual guidance on suggested training plans,

[2127] A system including:

[2128] (Claim 2)

[2129] 2. The system of claim 1, wherein the data input means includes scanning means for scanning a QR code.

[2130] (Claim 3)

[2131] 10. The system of claim 1, wherein the generating means includes means for generating a recommendation based on a user's fitness goals.

[2132] "Application Example 1"

[2133] (Claim 1)

[2134] data entry means used to enter new user data;

[2135] A generating means for generating a training plan based on past training data and basic information of the user, and a means for generating and inputting prompt sentences to the generating AI model to generate a training plan suitable for the user's fitness goals using the generating AI model;

[2136] A suggestion means for suggesting and notifying the generated training plan and emergency alert to the user;

[2137] a detection means for acquiring data in real time from sensors installed within the fitness facility and detecting abnormalities;

[2138] A response method for taking emergency action when an abnormality is detected;

[2139] A system including:

[2140] (Claim 2)

[2141] 2. The system of claim 1, wherein the data input means includes scanning means for scanning a QR code.

[2142] (Claim 3)

[2143] 2. The system of claim 1, wherein the generating means includes means for generating advice based on the user's fitness goals and means for generating prompt sentences using a generative AI model.

[2144] "Example 2: Combining Emotion Engines"

[2145] (Claim 1)

[2146] a data capture means used to input new user data;

[2147] A plan generation means for generating an exercise plan based on past exercise data and basic information of the user;

[2148] a suggestion means for suggesting the generated exercise plan to a user;

[2149] an anomaly detection means for detecting an anomaly;

[2150] an emergency response means for taking emergency action when an abnormality is detected;

[2151] emotion analysis means for analyzing the user's voice and facial expression to recognize emotions;

[2152] a voice suggestion means for suggesting an exercise plan to a user by voice;

[2153] A system including:

[2154] (Claim 2)

[2155] 2. The system of claim 1, wherein the data acquisition means includes scanning means for scanning a two-dimensional code.

[2156] (Claim 3)

[2157] 2. The system according to claim 1, wherein the plan generating means includes means for generating advice based on the user's exercise goals.

[2158] "Application example 2 when combining emotion engines"

[2159] (Claim 1)

[2160] data entry means used to enter new user data;

[2161] A generation means for generating a work plan based on past work data and basic information of a user;

[2162] a proposal means for proposing the generated work plan to a user;

[2163] detection means for detecting an abnormality;

[2164] A response method for taking emergency action when an abnormality is detected;

[2165] A sentiment analysis means for monitoring and adjusting the user's efficiency state;

[2166] A system including:

[2167] (Claim 2)

[2168] 2. The system of claim 1, wherein the data input means includes scanning means for scanning a QR code.

[2169] (Claim 3)

[2170] 2. The system according to claim 1, wherein the generating means includes means for generating advice based on a task goal of the user. [Explanation of symbols]

[2171] 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. data entry means used to enter new user data; A generation means for generating a training plan based on past training data and basic information of the user; a suggestion means for suggesting the generated training plan to a user; detection means for detecting an abnormality; A response method for taking emergency action when an abnormality is detected; A system including:

2. 2. The system of claim 1, wherein the data input means includes scanning means for scanning a QR code.

3. 2. The system of claim 1, wherein the generating means includes means for generating recommendations based on a user's fitness goals.

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