System

Abstract

A system is provided.SOLUTION: A system comprising: means for a user to set a goal; means for providing the user with appropriate advice using a generative AI model; means for recording and managing daily progress; and means for rewarding the user according to the degree of goal achievement.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In today's world, many people face the problem of being unable to set goals or maintain motivation. In particular, people interested in health and dieting face a lack of effective support for achieving their goals. Conventional methods lack sufficient support for users when managing themselves, which can lead to frustration. [Means for solving the problem]

[0005] This system includes a means for users to set goals and have them supported by a generative AI model, a means for recording and managing daily progress, and a means for awarding points and rewards according to the degree of goal achievement. This allows users to efficiently achieve their set goals and makes it easier to maintain motivation. Specifically, the system provides a mechanism where users set goals on a device such as a smartphone, the generative AI model provides appropriate advice, and points and rewards are awarded through daily progress management. In this way, it supports users in continuously maintaining a healthy lifestyle.

[0006] "Means for users to set goals" is a general term for the interfaces and methods by which users can input their own goals and register them in the system.

[0007] The "means of providing appropriate advice to users using a generative AI model" is part of a system that uses a generative AI model based on goal data set by the user to provide appropriate advice on achieving goals.

[0008] "Means for recording and managing daily progress data" refers to means for collecting data on daily activities and efforts entered by users, and storing and managing the data in a database.

[0009] The "means for providing rewards to users according to the degree of goal achievement" is part of a system for evaluating the degree of goal achievement of users and providing rewards or points to users according to the degree of goal achievement. [Brief explanation of the drawings]

[0010] [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

[0011] 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.

[0012] First, the terms used in the following description will be explained.

[0013] 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).

[0014] 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.

[0015] 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.

[0016] 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.

[0017] 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."

[0018] [First embodiment]

[0019] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0020] 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.

[0021] 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).

[0022] 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.

[0023] 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.

[0024] 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.

[0025] 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.

[0026] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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."

[0031] A specific embodiment of the present invention will be described below. This system uses a generative AI model to help users achieve their set goals, manage their progress, and award rewards according to their level of achievement.

[0032] 1. User goal setting

[0033] User: First, the user accesses the application using a device such as a smartphone and enters a specific goal, such as "I want to lose 3 kg in one month."

[0034] Terminal: Acquires user input and organizes this data for transmission to the server. It sends a goal setting request according to the communication protocol to the server.

[0035] Server: Stores the received goal data in a database and associates it with the user's profile, ensuring that the user's goals are recorded.

[0036] 2. Providing advice using generative AI models

[0037] Server: Calls the generative AI model based on the user's goal data and profile data. The AI ​​model generates appropriate advice for achieving the goal. Examples include "walk 30 minutes every day" and "eat a low-sugar diet."

[0038] Device: The generated advice is notified to the user, who can then check the notification and incorporate it into their daily lives.

[0039] 3. Daily progress management

[0040] User: The user enters daily diet and exercise data on the device. For example, "I had a salad for lunch" or "I walked for 30 minutes."

[0041] Terminal: This input data is organized and sent to the server. Progress checks and feedback are also performed on the terminal.

[0042] Server: Stores the received data in a database and manages the user's progress. Based on the new progress data, the generative AI model generates new advice and notifies the device.

[0043] 4. Points Management and Rewards

[0044] Server: Analyzes the user's progress data and calculates points based on the degree of goal achievement. For example, if a user walks for 30 minutes continuously for one week, 50 points will be awarded.

[0045] Terminal: Displays the user a list of available rewards along with the points awarded, allowing the user to select a reward.

[0046] User: Selects the reward he / she desires from a list of rewards and enters his / her selection on the terminal.

[0047] Server: Receives the user's selection, performs processing to deduct points and provide rewards, and then sends a confirmation message to the device.

[0048] Overall, this system helps users achieve their goals efficiently and maintain a healthy lifestyle. The combination of a generative AI model with progress management and rewards is expected to motivate users and encourage continued efforts.

[0049] The processing flow will be explained below.

[0050] Step 1:

[0051] User: Launches the smartphone app and accesses the goal setting screen. Enters a specific goal, such as "I want to lose 3 kg in one month."

[0052] Step 2:

[0053] Terminal: Obtains user input, organizes goal data, and sends a goal setting request to the server.

[0054] Step 3:

[0055] Server: Stores the received goal data in a database and associates it with the user's profile.

[0056] Step 4:

[0057] Server: Using the generative AI model, the server generates advice based on the user's goal data. For example, it creates specific advice such as "walk 30 minutes every day."

[0058] Step 5:

[0059] Terminal: Notifies the user of the generated advice and displays a notification screen so that the user can check the advice.

[0060] Step 6:

[0061] User: Enters daily progress data. For example, enters "today's meal contents" and "exercise contents" into the device.

[0062] Step 7:

[0063] Terminal: Organizes the data entered by the user and sends it to the server as progress data. Displays a screen to provide feedback on the progress status to the user.

[0064] Step 8:

[0065] Server: Stores the received progress data in a database. Based on the stored data, new advice is generated from the generative AI model.

[0066] Step 9:

[0067] Server: Analyzes the progress data, evaluates the user's achievement level, and calculates points based on the evaluation results.

[0068] Step 10:

[0069] Terminal: Displays the user the points awarded and a list of available rewards. Provides a screen for the user to select a reward.

[0070] Step 11:

[0071] User: Selects the desired reward from the displayed list of rewards and enters the selection into the terminal.

[0072] Step 12:

[0073] Server: Receives the user's selection, deducts points, performs processing to provide rewards, and notifies the user when processing is complete.

[0074] In this way, users are supported in achieving their goals, while tracking their progress and receiving rewards to motivate them.

[0075] Example 1

[0076] 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."

[0077] In modern society, individuals are required to easily and efficiently manage their health and achieve their goals. However, existing applications and systems rarely integrate user goal setting, progress management, advice provision, and rewards. Furthermore, advice provision using generative AI models is underutilized, making it difficult to maintain user motivation. Furthermore, there is a lack of functionality to provide new advice in real time based on the user's progress data. The objective of this invention is to solve these problems.

[0078] 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.

[0079] In this invention, the server includes means for the user to call the generative AI model based on goal data and profile data and generate advice, means for receiving the user's progress data and again calling the generative AI model to generate new advice, and means for rewarding the user according to the degree of goal achievement. This allows the user to receive specific and personalized advice for achieving their goal, and to receive real-time feedback and rewards according to their progress.

[0080] "User" refers to an individual who uses the System to set goals, track progress, receive advice, and receive rewards.

[0081] "Goal setting means" refers to a software or hardware component that has the functionality to allow a user to input specific goals and record them within the system.

[0082] "Generative AI model" refers to an artificial intelligence model that generates specific advice for achieving goals based on a user's goals and profile data.

[0083] "Advice Providing Means" refers to a software or hardware component that has the function of notifying the user of appropriate advice from a generative AI model.

[0084] "Progress management means" refers to a software or hardware component that has the function of recording a user's daily progress data and storing and managing it in a database.

[0085] "Reward granting means" refers to a software or hardware component that has the function of calculating and granting points or rewards based on the user's achievement of goals.

[0086] "Profile Data" refers to data that includes personal information about the user, such as age, weight, and height.

[0087] "Advice generation means" refers to a software or hardware component that has the function of invoking a generative AI model based on a user's goal data and profile data to generate appropriate advice.

[0088] The system of the present invention uses a generative AI model to help users achieve their set goals, manage their progress, and provide rewards based on their achievement. A specific embodiment of this system is described below.

[0089] First, a user can access the application using a device such as a smartphone and set a specific goal. For example, they can input a goal such as "I want to lose 3 kg in one month." Once the user inputs their goal, the device retrieves this data and organizes it for transmission to the server. The data is structured using a format such as JSON and sent to the server via the HTTP protocol.

[0090] The server stores the received goal data in a database and associates it with the user's profile. During this process, the data is inserted using a SQL statement, for example, INSERT INTO goals (user_id, goal) VALUES (123, 'Lose 3 kg in 1 month').

[0091] The server calls the generative AI model based on the user's goal data and profile data, and generates specific advice for achieving the goal. An example of a prompt sentence for the generative AI model is "I want to lose 3 kg in one month," {"age": 30, "weight": 70, "height": 170}. The server then provides the resulting advice to the user. For example, specific advice such as "Walk 30 minutes every day" or "Eat a low-sugar diet" is generated.

[0092] These advice messages are sent to the user via the device. The user can then review the messages and incorporate them into their daily lives. Progress is also managed in the same way, with the user entering their daily diet and exercise data via the device. For example, "I ate a salad for lunch" or "I walked for 30 minutes."

[0093] The device organizes the user's input data and sends it to the server, which stores the data in a database and manages the user's progress. The server then generates new advice from the generative AI model based on the new progress data and notifies the device.

[0094] Furthermore, the server analyzes the user's progress data and calculates points according to the degree of goal achievement. For example, if the user walks for 30 minutes continuously for one week, 50 points will be awarded. Along with these points, a list of available rewards will be displayed on the device, and the user can select the reward they want. The server receives the user's selection and processes it to deduct points and provide the reward. It then sends a confirmation message to the device.

[0095] This system allows users to efficiently achieve their goals and receive support to maintain a healthy lifestyle. Furthermore, by combining a progress management and reward system linked to the generative AI model, it is expected that users will be motivated and encouraged to continue their efforts.

[0096] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0097] Step 1: User-defined goals

[0098] The user accesses the application from a device such as a smartphone and enters a specific goal on the goal setting screen. The input data is, for example, a sentence such as "I want to lose 3 kg in one month." This data is provided to the device as input.

[0099] Step 2: Organize and send data using your device

[0100] The device takes the user's input data and organizes it into JSON format for sending to the server, where the data is structured as follows: {"user_id": 123, "goal": "Lose 3 kg in 1 month"}. The organized data is sent to the server via an HTTP POST request.

[0101] Step 3: Data received and stored by the server

[0102] The server receives the data sent from the device. The received data is in the JSON format shown above, and is parsed to extract the data contents. The data is then saved to the database using an SQL statement. For example, it is inserted into the database in the form of INSERT INTO goals (user_id, goal) VALUES (123, 'Lose 3 kg in 1 month'). The successfully saved data is used as input for the next process.

[0103] Step 4: Generative AI model generates advice

[0104] The server obtains the goal data and the user's profile data, and based on that, calls the generative AI model to generate advice. For example, the prompt sentence "I want to lose 3 kg in one month" and {"age": 30, "weight": 70, "height": 170} are input to the AI ​​model. As a result, the generated advice is output to the server. Examples of advice include "Walk 30 minutes every day" and "Try to eat a diet low in sugar."

[0105] Step 5: Notification of advice to device

[0106] The device that receives the advice generated by the server notifies the user of the content via push notifications or in-app messages. The notification is presented to the user as concrete guidelines to be reflected in their daily lives.

[0107] Step 6: User enters progress data

[0108] Users input their daily diet and exercise data through the app. For example, "I had a salad for lunch" or "I walked for 30 minutes." This input data is stored on the device as input for the next process.

[0109] Step 7: Organize and send progress data from your device

[0110] The device organizes the progress data entered by the user and structures it in JSON format or similar to send it to the server. For example, the data is organized as follows: {"user_id": 123, "diary": ["Salad for lunch", "30 minutes walking"]}. This is sent to the server as an HTTP POST request.

[0111] Step 8: Server saves progress data and generates new advice

[0112] The server receives the progress data sent from the device and stores it in a database. Next, it calls the generative AI model again based on the progress data to generate new advice. The newly generated advice is output to the server, and becomes the next notification sent to the device.

[0113] Step 9: Server calculates points and awards rewards

[0114] The server analyzes the user's progress data and calculates points according to the degree of goal achievement. For example, if the user "achieves 30 minutes of walking continuously for one week," 50 points will be awarded. The result of this calculation becomes the input data for reward processing.

[0115] Step 10: Displaying the reward list on the terminal and user selection

[0116] The terminal displays the calculated points and a list of available rewards to the user, who selects the reward he or she desires from the list and transmits the selection information from the terminal to the server.

[0117] Step 11: Server processes reward and sends confirmation message

[0118] The server receives the user's selection, deducts points, and processes the reward, for example updating points using an SQL statement like UPDATE users SET points = points - 50 WHERE user_id = 123, then generates a confirmation message and sends it to the device.

[0119] In this way, users can efficiently aim to achieve their goals through a series of processes from goal setting to progress management, advice provision, and reward allocation.

[0120] (Application example 1)

[0121] 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."

[0122] In modern society, it is important for users to efficiently achieve their self-set health goals and maintain a healthy lifestyle. However, conventional systems have problems such as users being confused about daily food choices and difficulty in accurately tracking progress toward achieving their goals. Furthermore, the reward system is vague and there is a lack of means to motivate users, making it difficult to continue working on the system.

[0123] 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.

[0124] In this invention, the server includes a means for the user to set goals, a means for providing the user with appropriate advice using a generative AI model, a means for recording and managing daily progress data, a means for rewarding the user according to the degree of goal achievement, a means for the generative AI model to recommend appropriate meal menus based on the user's health goals, and a means for awarding points based on the user's healthy choices in their orders. This enables the user to choose appropriate meals in line with their health goals, effectively manage their progress, and maintain motivation through the awarding of rewards, allowing them to continue working on their goals.

[0125] A "user" is an individual who uses the system to set goals, track progress, and receive rewards.

[0126] "Means for setting goals" is a function that allows users to input specific goals they want to achieve and register them in the system.

[0127] A "generative AI model" is an artificial intelligence model that provides appropriate advice to help users achieve their goals.

[0128] "Means for providing advice" is a function that uses a generative AI model to notify users of appropriate advice that is aligned with their goals.

[0129] "Progress data" is information used to record the actions and data entered by the user on a daily basis and to manage their progress.

[0130] "Means for recording and managing progress data" refers to the function of collecting user behavior and input data, recording it in the system, and managing it.

[0131] "Means for providing rewards" refers to a function that calculates rewards based on the user's achievement of goals and provides the user with points or other rewards.

[0132] "Means for recommending meal menus" refers to a function in which the generative AI model suggests appropriate meal menus based on the user's health goals.

[0133] "Ordering with a healthy choice" refers to the act of a user selecting and ordering a healthy meal menu item.

[0134] The "means of awarding points" is a function that awards points as an incentive when a user takes actions or makes choices that are in line with the goals they have set.

[0135] This invention relates to a system that uses a generative AI model to manage progress and reward users according to their level of achievement in order to help them achieve their health goals. The system starts with the user setting their goal using a device such as a smartphone, and supports them throughout the process of achieving their goal.

[0136] 1. User goal setting

[0137] User:

[0138] Users use the device and input specific goals, such as "I want to lose 3 kilograms in one month," through the application.

[0139] Device:

[0140] The device organizes the user's input and sends it to the server, for example, by sending a goal setting request using the HTTP communication protocol, and also includes a function to validate the user's input and check for omissions or errors.

[0141] server:

[0142] The server stores the received goal data in a database and associates it with the user's profile, which includes information such as the user's current weight and activity history.

[0143] 2. Providing advice using generative AI models

[0144] server:

[0145] The server calls a generative AI model based on the user's goal data and profile data to generate appropriate advice for achieving their goals. The generative AI model references past data and statistical information to provide specific and personalized advice.

[0146] Device:

[0147] The device then notifies the user of the generated advice. For example, it might say, "Order a low-calorie salad today." The user can then use this advice to incorporate it into their daily lives.

[0148] 3. Daily progress management

[0149] User:

[0150] Users input their daily diet and exercise data into the device, for example, entering detailed information such as "I had a salad for lunch" or "I walked for 30 minutes."

[0151] Device:

[0152] The device organizes this input data and sends it to the server. Progress checks and feedback are also done on the device, and the interface is designed so that users can see their progress at a glance.

[0153] server:

[0154] The server stores the received data in a database and manages the user's progress. It also generates new advice from the generative AI model based on new progress data and notifies the device.

[0155] 4. Points Management and Rewards

[0156] server:

[0157] The server analyzes the user's progress data and calculates points based on the achievement of the goal. For example, if the user achieves 30 minutes of walking for one week in a row, 50 points will be awarded.

[0158] Device:

[0159] The terminal will display the points awarded to the user along with a list of available rewards, which the user can use to select a reward.

[0160] User:

[0161] Users select from a list of rewards and enter their selection into the terminal, such as a 10% off coupon for their next food delivery order.

[0162] server:

[0163] The server receives the user's selection, performs processing to deduct points and provide rewards, and then sends a confirmation message to the device.

[0164] Program processing overview

[0165] The system's programs are implemented using programming languages ​​such as Python. Each process, including user goal setting, progress data management, advice provision by the generative AI model, and reward allocation, is carried out through communication between the server and the device. The database uses a relational database such as MySQL, and the generative AI model is implemented using machine learning libraries such as TensorFlow and PyTorch.

[0166] Examples of concrete examples and prompts

[0167] Examples:

[0168] 1. User goal setting: "Lose 3 kg in 1 month"

[0169] 2. AI advice: "To help you achieve your weight loss goal, we recommend a low-calorie salad for lunch today."

[0170] 3. Track your progress: "I took a 30-minute walk and ordered a healthy salad."

[0171] 4. Reward: "10% off your next order"

[0172] Example prompt sentence:

[0173] "Generate specific dietary advice to help the user achieve their goal. The user's goal is to lose 3 kg in 1 month."

[0174] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0175] Step 1:

[0176] The user sets a goal. Specifically, the user accesses the application using a smartphone device and inputs a specific goal, such as "I want to lose 3 kg in one month." The device organizes this input data and sends it to the server using the HTTP communication protocol. The input data is sent to the server as a goal setting request. The server receives this data, stores it in a database, and associates it with the user's profile.

[0177] Step 2:

[0178] The server provides advice using a generative AI model. The server sends a prompt to the generative AI model based on the user's goal data and profile data. An example of a prompt is, "Please generate specific dietary advice to help the user achieve their goal. The user's goal is to lose 3 kg in one month." The generative AI model generates advice based on this prompt and returns it to the server. The server notifies the device of the generated advice. The device displays this notification on its screen to inform the user.

[0179] Step 3:

[0180] Enter the user's daily progress. The user enters data about their daily diet and exercise on the device. For example, they enter data such as "I had salad for lunch" or "I walked for 30 minutes." The device organizes the entered data and sends it to the server using the HTTP communication protocol. The server saves the received data in a database and manages it as daily progress data.

[0181] Step 4:

[0182] The server generates new advice based on the progress data. The server retrieves the latest progress data from the database and sends it to the generative AI model. The generative AI model generates new advice and returns it to the server. The server notifies the device of this new advice. The device notifies the user of the advice so that they can use it as reference.

[0183] Step 5:

[0184] The server calculates rewards based on the degree of goal achievement. The server analyzes daily progress data and calculates the user's degree of goal achievement. For example, if there is data showing that the user has walked for 30 minutes continuously for one week, the server will calculate and award 50 points. The calculated point data is stored in a database.

[0185] Step 6:

[0186] The user receives the reward. The terminal displays the point accrual status and a list of available rewards to the user. The user selects the desired reward and enters it on the terminal. The terminal sends this input data to the server. The server receives the user's selection, deducts points, and processes the reward. The server then sends a confirmation message to the terminal, which notifies the user.

[0187] 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.

[0188] This invention combines a generative AI model and an emotion engine to manage progress and provide rewards according to the degree of achievement in order to help users achieve their set goals. This system can maintain user motivation and support goal achievement.

[0189] User goal setting

[0190] User: First, the user accesses the application using a device such as a smartphone and enters a specific goal, such as "I want to lose 3 kg in one month."

[0191] Terminal: Acquires user input and organizes this data for transmission to the server. It sends a goal setting request according to the communication protocol to the server.

[0192] Server: Stores the received goal data in a database and associates it with the user's profile, ensuring that the user's goals are recorded.

[0193] Providing advice through generative AI models

[0194] Server: Calls the generative AI model based on the user's goal data and profile data. The AI ​​model generates appropriate advice for achieving the goal. Examples include "walk 30 minutes every day" and "eat a low-sugar diet."

[0195] Device: The generated advice is notified to the user, who can then check the notification and incorporate it into their daily lives.

[0196] Daily progress management

[0197] User: The user enters daily diet and exercise data on the device. For example, "I had a salad for lunch" or "I walked for 30 minutes."

[0198] Terminal: This input data is organized and sent to the server. Progress checks and feedback are also performed on the terminal.

[0199] Server: Stores the received data in a database and manages the user's progress. Based on the new progress data, the generative AI model generates new advice and notifies the device.

[0200] Use of emotion engine

[0201] Server: Using the emotion engine, it acquires emotional data from the user's progress data and input data. For example, it analyzes the user's text, facial expressions, and voice data to recognize their emotional state, such as "motivation is decreasing" or "stress is increasing."

[0202] Device: Based on the emotional data, it displays advice and encouraging messages that correspond to the user's state. For example, it displays a message such as "You look like you're doing well today. Keep up the great work."

[0203] Points Management and Rewards

[0204] Server: Calculates points based on the user's progress and emotional data, and sets rewards. For example, it awards additional points when the user's goal achievement is high or when motivation is low.

[0205] Terminal: Displays the user the points awarded and a list of available rewards. Provides a screen for the user to select a reward.

[0206] User: Selects the desired reward from the displayed list of rewards and enters the selection into the terminal.

[0207] Server: Receives the user's selection, deducts points, performs processing to provide rewards, and then sends a confirmation message to the device.

[0208] In this way, users receive multi-layered support to achieve their goals, while also managing their progress and receiving rewards to motivate them according to their emotional state.By working together, the generative AI model and emotion engine can more effectively support users' efforts.

[0209] The processing flow will be explained below.

[0210] Step 1:

[0211] User: Launches the smartphone app and accesses the goal setting screen. Enters a specific goal, such as "I want to lose 3 kg in one month."

[0212] Step 2:

[0213] Terminal: Obtains user input, organizes goal data, and sends a goal setting request to the server.

[0214] Step 3:

[0215] Server: Stores the received goal data in a database and associates it with the user's profile.

[0216] Step 4:

[0217] Server: Using the generative AI model, the server generates advice based on the user's goal data. For example, it creates specific advice such as "walk 30 minutes every day."

[0218] Step 5:

[0219] Terminal: Notifies the user of the generated advice and displays a notification screen so that the user can check the advice.

[0220] Step 6:

[0221] User: Enters daily progress data. For example, enters "today's meal contents" and "exercise contents" into the device.

[0222] Step 7:

[0223] Terminal: Organizes the data entered by the user and sends it to the server as progress data. Displays a screen to provide feedback on the progress status to the user.

[0224] Step 8:

[0225] Server: Stores the received progress data in a database. Based on the stored data, new advice is generated from the generative AI model.

[0226] Step 9:

[0227] Server: In addition to the process of collecting progress data, it also runs an emotion engine to recognize the user's emotional state, for example, by analyzing text, voice, and facial expression data to evaluate the user's emotions.

[0228] Step 10:

[0229] Terminal: Receives emotional data from the emotion engine and provides feedback to the user. For example, if motivation is low, a message such as "Why don't you take a break today?" will be displayed.

[0230] Step 11:

[0231] Server: Based on the emotion data, if it is necessary to calculate additional points to increase the user's motivation, the server calculates and awards the points. For example, it awards additional points to a user whose progress is slow despite their efforts.

[0232] Step 12:

[0233] Terminal: Presents the user with the points awarded and a list of available rewards. Provides a screen where the user can select a reward.

[0234] Step 13:

[0235] User: Selects the desired reward from the displayed list of rewards and enters the selection into the terminal.

[0236] Step 14:

[0237] Server: Receives the user's selection, deducts points, performs processing related to the reward to be provided, and sends a confirmation message to the terminal after processing is complete.

[0238] In this way, users receive multi-layered support to achieve their goals, while being able to manage their progress and stay motivated with emotional feedback and additional incentives.The generative AI model and emotion engine work together to enhance the overall user experience.

[0239] Example 2

[0240] 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."

[0241] Conventional progress management systems have a single approach to helping users achieve their set goals, and lack diverse feedback and mechanisms for maintaining motivation. As a result, users tend to give up easily before achieving their goals, making it difficult to maintain long-term motivation. Furthermore, because support and feedback do not take into account the emotional state of each individual user, they are unable to effectively support users' efforts. To solve these issues, there is a need for the development of a system that provides multi-layered, personalized support.

[0242] 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.

[0243] In this invention, the server includes a means for allowing the user to set goals, a means for providing appropriate advice based on the user profile and goal data using a generative AI model, a means for recording and managing daily progress data, a means for calculating points based on the user's progress data and emotional data and awarding rewards according to the degree of goal achievement, and a means for acquiring the user's emotional data using an emotion engine and generating messages according to the user's state. This enables multi-layered and personalized support for each user, effectively helping users maintain their motivation and achieve their goals.

[0244] "User" refers to an individual or organization that uses the system to set goals, track progress, and earn rewards.

[0245] A "generative AI model" refers to an artificial intelligence system that generates natural language and analyzes data based on input data, and provides appropriate advice and feedback to users.

[0246] "User Profile" means a data set in a database that contains personal information, goals, progress data, etc. related to a User.

[0247] "Goal Data" means data containing information about specific goals that a User seeks to achieve.

[0248] "Progress data" refers to data that records the user's daily actions and results as they work toward their goals.

[0249] "Emotional Data" refers to data that indicates the user's emotional state as analyzed by the emotion engine.

[0250] An "emotion engine" refers to a system that analyzes user input data and behavioral data to recognize the user's emotional state.

[0251] "Points" refer to numerical data used to award rewards calculated based on the user's progress and emotional data.

[0252] "Rewards" refers to incentives such as goods or services given to users when they achieve their goals.

[0253] "Messages" refer to text or notifications generated by the emotion engine that contain encouragement or advice based on the user's state.

[0254] "Database" refers to an information system for storing and managing user profile data, goal data, progress data, emotional data, etc.

[0255] "Advice" refers to specific instructions or recommended actions provided to users by a generative AI model to achieve a goal.

[0256] This invention is a system that combines a generative AI model and an emotion engine to manage progress and provide rewards according to the degree of achievement in order to help users achieve their set goals. This system can maintain the user's motivation and support them in achieving their goals.

[0257] goal setting

[0258] First, a user accesses the application using a device such as a smartphone. They input a specific goal into the application, such as "I want to lose 3 kg in one month." The device acquires the user's input and organizes this data for transmission to the server. It then sends a goal-setting request to the server according to a communications protocol. The server stores the received goal data in a database and associates it with the user's profile, ensuring that the user's goals are recorded reliably.

[0259] Providing advice through generative AI models

[0260] The server calls a generative AI model based on the user's goal data and profile data. Examples of such generative AI models include OpenAI's GPT. The AI ​​model generates appropriate advice for achieving the goal. For example, advice such as "walk 30 minutes every day" or "eat a low-sugar diet" may be used. The device notifies the user of the generated advice, which the user can then review and incorporate into their daily life.

[0261] Daily progress management

[0262] Users input their daily diet and exercise data into the device. For example, they input specific data such as "I ate salad for lunch" or "I walked for 30 minutes." The device organizes this input data and sends it to the server. Progress checks and feedback are also performed on the device. The server stores the received data in a database and manages the user's progress. Based on the new progress data, the generative AI model generates new advice and notifies the device.

[0263] Use of emotion engine

[0264] The server uses an emotion engine to obtain emotional data from the user's progress data and input data. An example of this emotion engine is the IBM Watson Tone Analyzer. For example, it analyzes the user's written text, facial expressions, and voice data to recognize emotional states such as "decreasing motivation" or "increasing stress." Based on the emotional data, the device displays advice and encouraging messages appropriate to the user's condition. For example, it may display a message such as "You look like you're doing well today, keep up the good work."

[0265] Points Management and Rewards

[0266] The server calculates points based on the user's progress data and emotional data and sets rewards. For example, it awards additional points when goal achievement is high or motivation is low. The device displays the awarded points and a list of available rewards to the user. It provides a screen for the user to select a reward. The user selects the desired reward from the displayed reward list and inputs the selection into the device. The server receives the user's selection, deducts points, performs processing to provide the reward, and then sends a confirmation message to the device.

[0267] Prompt Sentence Examples

[0268] 1. Goal Setting:

[0269] "Set a new goal. For example, lose 3 kilos in one month."

[0270] 2. Progress Input:

[0271] "Please enter your diet and exercise data for today."

[0272] 3. Providing advice:

[0273] "Shows advice generated by AI models"

[0274] 4. Emotion data input:

[0275] "Please enter your current emotional state."

[0276] 5. Reward Selection:

[0277] "Select your desired reward from the list of available rewards"

[0278] The system allows users to receive planned and specific support to achieve their goals, and by combining a generative AI model with an emotion engine, it is possible to provide advice and feedback that is optimized for each individual user.

[0279] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0280] Step 1:

[0281] The user sets a goal. Specifically, they launch the smartphone application and input a specific goal, such as "I want to lose 3 kg in one month." The input is the user's goal information, and the output is a goal setting request.

[0282] Step 2:

[0283] The device organizes the user's input. For example, it converts a user's input goal, such as "I want to lose 3 kg in one month," into a format to be sent to the server. The input is a goal setting request, and the output is the goal information converted into a data format to be sent to the server.

[0284] Step 3:

[0285] The server receives the target data and stores it in a database, for example, by associating it with a user profile database. The input is the target information sent from the terminal, and the output is the target data stored in the database.

[0286] Step 4:

[0287] The server invokes a generative AI model based on the received goal data and user profile data. For example, it uses OpenAI's GPT to send prompts and generate advice. The input is the goal data and profile data, and the output is the generated advice.

[0288] Step 5:

[0289] The device receives the advice generated by the server and notifies the user. For example, it may notify the user of advice such as "walk 30 minutes every day" or "eat a low-sugar diet." The input is the generated advice, and the output is the notification to the user.

[0290] Step 6:

[0291] The user inputs daily diet and exercise data into the device. For example, they input progress data such as "I ate salad for lunch" or "I walked for 30 minutes." The input is specific diet and exercise data, and the output is progress data.

[0292] Step 7:

[0293] The device organizes the progress data and sends it to the server. For example, it converts information entered by the user, such as "I ate salad for lunch," into a data format for transmission. The input is the progress data, and the output is the data to be sent to the server.

[0294] Step 8:

[0295] The server stores the received progress data in a database and manages the progress. For example, it stores the data in association with the user's profile. The input is the progress data in the transmission data format, and the output is the progress data stored in the database.

[0296] Step 9:

[0297] The server requests the generative AI model to generate new advice based on the new progress data. For example, it generates additional advice such as "walk 30 minutes a day and incorporate stretching into your daily routine." The input is the new progress data, and the output is the new advice.

[0298] Step 10:

[0299] The terminal notifies the user of newly generated advice. The input is the new advice, and the output is the notification to the user.

[0300] Step 11:

[0301] The server uses an emotion engine to obtain emotion data from the progress data and input data. For example, it uses "IBM Watson Tone Analyzer" to analyze the user's writing and recognize that "motivation is declining." The inputs are progress data and input data, and the output is emotion data.

[0302] Step 12:

[0303] The server generates an appropriate message based on the emotion data and sends it to the device. For example, it generates an encouraging message such as, "You look good today, keep up the good work." The input is the emotion data, and the output is the generated message.

[0304] Step 13:

[0305] The terminal notifies the user of the generated message. The input is the generated message, and the output is the notification to the user.

[0306] Step 14:

[0307] The server calculates points based on the progress data and emotion data and sets rewards. For example, it gives additional points when a specific goal is achieved. The input is the progress data and emotion data, and the output is the calculated points and a list of rewards.

[0308] Step 15:

[0309] The terminal displays the awarded points and the list of available rewards to the user. The input is the reward list, and the output is the display to the user.

[0310] Step 16:

[0311] The user selects the desired reward from the displayed reward list and inputs the selection into the terminal. The input is the user's reward selection, and the output is the selection data.

[0312] Step 17:

[0313] The terminal sends the user's selection to the server. The input is the selection data, and the output is the data to be sent to the server.

[0314] Step 18:

[0315] The server receives the user's selection, deducts points, and executes a process to provide a reward. For example, a procedure may be performed to provide the user with a 500 yen Amazon gift card after deducting points. The input is the selection data and current points, and the output is the updated points balance and confirmation of the reward.

[0316] Step 19:

[0317] The server sends the reward provision confirmation data to the terminal. The input is the reward provision confirmation data, and the output is the data sent to the terminal.

[0318] Step 20:

[0319] The terminal notifies the user of a message confirming the provision of the reward. The input is the confirmation data for the provision of the reward, and the output is a notification to the user.

[0320] (Application example 2)

[0321] 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."

[0322] Conventional goal management systems do not take into account the user's emotions or motivation when managing the user's progress or providing advice, which makes it difficult to maintain motivation to achieve goals. Furthermore, the reward system based on the degree of goal achievement is monotonous, leaving room for improvement in user satisfaction.

[0323] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for the user to set a goal, a means for providing the user with appropriate advice using a generative AI model, a means for recording and managing daily progress data, a means for rewarding the user according to the degree of goal achievement, a means for analyzing the user's emotional state using an emotion engine and providing feedback, and a means for providing cashback or points based on the user's progress and emotional state. This makes it possible to effectively support goal achievement while taking into account the user's emotions and motivation, and to improve user satisfaction through the reward system.

[0324] A "user" is an individual or organization that uses the system to set goals and take action to achieve those goals.

[0325] A "goal" is a specific result or state that a user aims to achieve.

[0326] A "generative AI model" is a system or algorithm that uses artificial intelligence to generate appropriate advice and support to help users achieve their goals.

[0327] "Advice" is information that contains specific instructions, suggestions, or recommendations for achieving a user's set goals.

[0328] "Progress Data" means information that records the activities and actions taken by a user toward achieving a goal and the results of those activities and actions.

[0329] "Rewards" refers to incentives and benefits given to users when they achieve their goals, including cashback and points.

[0330] An "emotion engine" is a system or algorithm that analyzes data such as a user's writing, facial expressions, and voice to recognize the user's emotional state.

[0331] "Feedback" refers to information or messages provided to the user by the system, and contains appropriate content depending on the user's emotional state.

[0332] "Cashback" is a form of reward in which a user receives a refund or rebate when they achieve a goal, depending on the degree of achievement.

[0333] "Points" are numerical rewards given to users for achieving goals or other activities, and once a certain number of points have been accumulated, they can be exchanged for rewards or incentives.

[0334] A system for implementing this invention includes a means for a user to set a goal, a means for providing appropriate advice to the user using a generative AI model, a means for recording and managing daily progress data, a means for rewarding the user according to the degree of goal achievement, a means for analyzing the user's emotional state using an emotion engine and providing feedback, and a means for providing cashback or points based on the user's progress and emotional state.

[0335] 1. User goal setting

[0336] Users access the application using a smartphone or other device and input specific goals, such as "keep monthly credit card spending under 50,000 yen."

[0337] The terminal acquires the goal content input by the user and organizes this data for transmission to the server, and sends a goal setting request to the server according to a communication protocol.

[0338] The server stores the received goal data in a database and associates it with the user's profile, ensuring that the user's goals are recorded.

[0339] 2. Providing advice using generative AI models

[0340] The server calls up a generative AI model based on the user's goal and profile data, and generates appropriate advice for achieving the goal. For example, "cook more meals at home to reduce monthly food costs" or "create a wish list to avoid waste."

[0341] The device will notify the user of the generated advice, which the user can then review and incorporate into their daily lives.

[0342] 3. Use of Emotion Engine

[0343] The server uses an emotion engine to extract emotional data from user input data. For example, it analyzes positive comments such as "I've been having fun saving money this month" and negative comments such as "It was difficult to save money today" to recognize the user's emotional state.

[0344] Based on the recognized emotional data, the device displays advice and encouraging messages according to the user's state, such as "You're feeling good today, keep up the good work," or "You seem a little tired, it's important to take a break."

[0345] 4. Daily progress management and reward provision

[0346] Users input their daily spending data on the device, such as "Today's food expenses were 1,200 yen" or "I spent 5,000 yen on home appliances."

[0347] The device organizes this input data and sends it to the server, where progress confirmation and feedback are also provided.

[0348] The server stores the received data in a database and manages the user's progress. Based on the new progress data, the generative AI model generates new advice and notifies the device. In addition, cashback and points are provided depending on the degree of goal achievement.

[0349] Examples of concrete examples and prompts

[0350] For example, if a user sets a goal of "keeping monthly expenses under 50,000 yen," the prompt to the generative AI model would look like this:

[0351] Please advise how a user can reduce their monthly expenses to 50,000 yen. Current expenses: 45,000 yen.

[0352] In this way, users receive comprehensive support that effectively assists them in achieving their goals, while also receiving feedback and rewards based on their emotional state. By working together, the generative AI model and emotion engine can more effectively support users in their efforts.

[0353] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0354] Step 1:

[0355] Users access the application using a device such as a smartphone and set specific goals. For example, they might enter, "Keep monthly credit card spending under 50,000 yen." The device receives this input, organizes the data, and sends it to the server. The server then receives it, stores it in a database, and associates it with the user profile. The input is goal setting data, and the output is a database entry of the goal data.

[0356] Step 2:

[0357] The server obtains the goal data and user profile data, and sends a prompt to the generative AI model to generate advice for achieving the goal. The specific prompt used is, "Please advise how the user can keep their monthly expenses to 50,000 yen. Current expenses: 45,000 yen." The input is the user data and the prompt, and the output is the generated advice.

[0358] Step 3:

[0359] The device receives the advice of the generative AI model sent from the server and notifies the user. The user can check this notification and incorporate it into their daily life. In this step, feedback is provided by the advice being delivered to the user. The input is the advice data from the server, and the output is a notification to the user.

[0360] Step 4:

[0361] The user inputs details of their daily spending into the device. For example, "Today's food expenses were 1,200 yen" or "I spent 5,000 yen on home appliances." The device organizes this detailed data and sends it to the server. The input is daily spending data, and the output is the transmission of progress data to the server.

[0362] Step 5:

[0363] The server receives daily spending data, stores it in a database, and manages the user's progress. Based on this progress data, it invokes a new generative AI model, generates new advice, and notifies the device. It also manages the allocation of cashback and points according to the degree of goal achievement. The input is daily spending data, and the output is the generation of new advice and reward data.

[0364] Step 6:

[0365] The server uses an emotion engine to analyze emotion data from the user's input data. For example, it analyzes positive emotion from the user's input "I'm having fun saving money this month" and generates an encouraging message such as "You're doing well today, keep up the good work." The input is the user's input data, and the output is the analyzed emotion data and an encouraging message.

[0366] Step 7:

[0367] The device notifies the user of messages generated by the emotion engine. The messages are based on the user's emotional state and play an important role in maintaining motivation. The input is emotional data and messages, and the output is notifications to the user.

[0368] In this way, at each step, data is processed and calculated based on the input data, and the output is used in the next step. This realizes a system that helps users achieve their goals and provides appropriate rewards and feedback.

[0369] 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.

[0370] 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.

[0371] 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.

[0372] [Second embodiment]

[0373] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0374] 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.

[0375] 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).

[0376] 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.

[0377] 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.

[0378] 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).

[0379] 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.

[0380] 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.

[0381] 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.

[0382] 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.

[0383] 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.

[0384] 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."

[0385] A specific embodiment of the present invention will be described below. This system uses a generative AI model to help users achieve their set goals, manage their progress, and award rewards according to their level of achievement.

[0386] 1. User goal setting

[0387] User: First, the user accesses the application using a device such as a smartphone and enters a specific goal, such as "I want to lose 3 kg in one month."

[0388] Terminal: Acquires user input and organizes this data for transmission to the server. It sends a goal setting request according to the communication protocol to the server.

[0389] Server: Stores the received goal data in a database and associates it with the user's profile, ensuring that the user's goals are recorded.

[0390] 2. Providing advice using generative AI models

[0391] Server: Calls the generative AI model based on the user's goal data and profile data. The AI ​​model generates appropriate advice for achieving the goal. Examples include "walk 30 minutes every day" and "eat a low-sugar diet."

[0392] Device: The generated advice is notified to the user, who can then check the notification and incorporate it into their daily lives.

[0393] 3. Daily progress management

[0394] User: The user enters daily diet and exercise data on the device. For example, "I had a salad for lunch" or "I walked for 30 minutes."

[0395] Terminal: This input data is organized and sent to the server. Progress checks and feedback are also performed on the terminal.

[0396] Server: Stores the received data in a database and manages the user's progress. Based on the new progress data, the generative AI model generates new advice and notifies the device.

[0397] 4. Points Management and Rewards

[0398] Server: Analyzes the user's progress data and calculates points based on the degree of goal achievement. For example, if a user walks for 30 minutes continuously for one week, 50 points will be awarded.

[0399] Terminal: Displays the user a list of available rewards along with the points awarded, allowing the user to select a reward.

[0400] User: Selects the reward he / she desires from a list of rewards and enters his / her selection on the terminal.

[0401] Server: Receives the user's selection, performs processing to deduct points and provide rewards, and then sends a confirmation message to the device.

[0402] Overall, this system helps users achieve their goals efficiently and maintain a healthy lifestyle. The combination of a generative AI model with progress management and rewards is expected to motivate users and encourage continued efforts.

[0403] The processing flow will be explained below.

[0404] Step 1:

[0405] User: Launches the smartphone app and accesses the goal setting screen. Enters a specific goal, such as "I want to lose 3 kg in one month."

[0406] Step 2:

[0407] Terminal: Obtains user input, organizes goal data, and sends a goal setting request to the server.

[0408] Step 3:

[0409] Server: Stores the received goal data in a database and associates it with the user's profile.

[0410] Step 4:

[0411] Server: Using the generative AI model, the server generates advice based on the user's goal data. For example, it creates specific advice such as "walk 30 minutes every day."

[0412] Step 5:

[0413] Terminal: Notifies the user of the generated advice and displays a notification screen so that the user can check the advice.

[0414] Step 6:

[0415] User: Enters daily progress data. For example, enters "today's meal contents" and "exercise contents" into the device.

[0416] Step 7:

[0417] Terminal: Organizes the data entered by the user and sends it to the server as progress data. Displays a screen to provide feedback on the progress status to the user.

[0418] Step 8:

[0419] Server: Stores the received progress data in a database. Based on the stored data, new advice is generated from the generative AI model.

[0420] Step 9:

[0421] Server: Analyzes the progress data, evaluates the user's achievement level, and calculates points based on the evaluation results.

[0422] Step 10:

[0423] Terminal: Displays the user the points awarded and a list of available rewards. Provides a screen for the user to select a reward.

[0424] Step 11:

[0425] User: Selects the desired reward from the displayed list of rewards and enters the selection into the terminal.

[0426] Step 12:

[0427] Server: Receives the user's selection, deducts points, performs processing to provide rewards, and notifies the user when processing is complete.

[0428] In this way, users are supported in achieving their goals, while tracking their progress and receiving rewards to motivate them.

[0429] Example 1

[0430] 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."

[0431] In modern society, individuals are required to easily and efficiently manage their health and achieve their goals. However, existing applications and systems rarely integrate user goal setting, progress management, advice provision, and rewards. Furthermore, advice provision using generative AI models is underutilized, making it difficult to maintain user motivation. Furthermore, there is a lack of functionality to provide new advice in real time based on the user's progress data. The objective of this invention is to solve these problems.

[0432] 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.

[0433] In this invention, the server includes means for the user to call the generative AI model based on goal data and profile data and generate advice, means for receiving the user's progress data and again calling the generative AI model to generate new advice, and means for rewarding the user according to the degree of goal achievement. This allows the user to receive specific and personalized advice for achieving their goal, and to receive real-time feedback and rewards according to their progress.

[0434] "User" refers to an individual who uses the System to set goals, track progress, receive advice, and receive rewards.

[0435] "Goal setting means" refers to a software or hardware component that has the functionality to allow a user to input specific goals and record them within the system.

[0436] "Generative AI model" refers to an artificial intelligence model that generates specific advice for achieving goals based on a user's goals and profile data.

[0437] "Advice Providing Means" refers to a software or hardware component that has the function of notifying the user of appropriate advice from a generative AI model.

[0438] "Progress management means" refers to a software or hardware component that has the function of recording a user's daily progress data and storing and managing it in a database.

[0439] "Reward granting means" refers to a software or hardware component that has the function of calculating and granting points or rewards based on the user's achievement of goals.

[0440] "Profile Data" refers to data that includes personal information about the user, such as age, weight, and height.

[0441] "Advice generation means" refers to a software or hardware component that has the function of invoking a generative AI model based on a user's goal data and profile data to generate appropriate advice.

[0442] The system of the present invention uses a generative AI model to help users achieve their set goals, manage their progress, and provide rewards based on their achievement. A specific embodiment of this system is described below.

[0443] First, a user can access the application using a device such as a smartphone and set a specific goal. For example, they can input a goal such as "I want to lose 3 kg in one month." Once the user inputs their goal, the device retrieves this data and organizes it for transmission to the server. The data is structured using a format such as JSON and sent to the server via the HTTP protocol.

[0444] The server stores the received goal data in a database and associates it with the user's profile. During this process, the data is inserted using a SQL statement, for example, INSERT INTO goals (user_id, goal) VALUES (123, 'Lose 3 kg in 1 month').

[0445] The server calls the generative AI model based on the user's goal data and profile data, and generates specific advice for achieving the goal. An example of a prompt sentence for the generative AI model is "I want to lose 3 kg in one month," {"age": 30, "weight": 70, "height": 170}. The server then provides the resulting advice to the user. For example, specific advice such as "Walk 30 minutes every day" or "Eat a low-sugar diet" is generated.

[0446] These advice messages are sent to the user via the device. The user can then review the messages and incorporate them into their daily lives. Progress is also managed in the same way, with the user entering their daily diet and exercise data via the device. For example, "I ate a salad for lunch" or "I walked for 30 minutes."

[0447] The device organizes the user's input data and sends it to the server, which stores the data in a database and manages the user's progress. The server then generates new advice from the generative AI model based on the new progress data and notifies the device.

[0448] Furthermore, the server analyzes the user's progress data and calculates points according to the degree of goal achievement. For example, if the user walks for 30 minutes continuously for one week, 50 points will be awarded. Along with these points, a list of available rewards will be displayed on the device, and the user can select the reward they want. The server receives the user's selection and processes it to deduct points and provide the reward. It then sends a confirmation message to the device.

[0449] This system allows users to efficiently achieve their goals and receive support to maintain a healthy lifestyle. Furthermore, by combining a progress management and reward system linked to the generative AI model, it is expected that users will be motivated and encouraged to continue their efforts.

[0450] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0451] Step 1: User-defined goals

[0452] The user accesses the application from a device such as a smartphone and enters a specific goal on the goal setting screen. The input data is, for example, a sentence such as "I want to lose 3 kg in one month." This data is provided to the device as input.

[0453] Step 2: Organize and send data using your device

[0454] The device takes the user's input data and organizes it into JSON format for sending to the server, where the data is structured as follows: {"user_id": 123, "goal": "Lose 3 kg in 1 month"}. The organized data is sent to the server via an HTTP POST request.

[0455] Step 3: Data received and stored by the server

[0456] The server receives the data sent from the device. The received data is in the JSON format shown above, and is parsed to extract the data contents. The data is then saved to the database using an SQL statement. For example, it is inserted into the database in the form of INSERT INTO goals (user_id, goal) VALUES (123, 'Lose 3 kg in 1 month'). The successfully saved data is used as input for the next process.

[0457] Step 4: Generative AI model generates advice

[0458] The server obtains the goal data and the user's profile data, and based on that, calls the generative AI model to generate advice. For example, the prompt sentence "I want to lose 3 kg in one month" and {"age": 30, "weight": 70, "height": 170} are input to the AI ​​model. As a result, the generated advice is output to the server. Examples of advice include "Walk 30 minutes every day" and "Try to eat a diet low in sugar."

[0459] Step 5: Notification of advice to device

[0460] The device that receives the advice generated by the server notifies the user of the content via push notifications or in-app messages. The notification is presented to the user as concrete guidelines to be reflected in their daily lives.

[0461] Step 6: User enters progress data

[0462] Users input their daily diet and exercise data through the app. For example, "I had a salad for lunch" or "I walked for 30 minutes." This input data is stored on the device as input for the next process.

[0463] Step 7: Organize and send progress data from your device

[0464] The device organizes the progress data entered by the user and structures it in JSON format or similar to send it to the server. For example, the data is organized as follows: {"user_id": 123, "diary": ["Salad for lunch", "30 minutes walking"]}. This is sent to the server as an HTTP POST request.

[0465] Step 8: Server saves progress data and generates new advice

[0466] The server receives the progress data sent from the device and stores it in a database. Next, it calls the generative AI model again based on the progress data to generate new advice. The newly generated advice is output to the server, and becomes the next notification sent to the device.

[0467] Step 9: Server calculates points and awards rewards

[0468] The server analyzes the user's progress data and calculates points according to the degree of goal achievement. For example, if the user "achieves 30 minutes of walking continuously for one week," 50 points will be awarded. The result of this calculation becomes the input data for reward processing.

[0469] Step 10: Displaying the reward list on the terminal and user selection

[0470] The terminal displays the calculated points and a list of available rewards to the user, who selects the reward he or she desires from the list and transmits the selection information from the terminal to the server.

[0471] Step 11: Server processes reward and sends confirmation message

[0472] The server receives the user's selection, deducts points, and processes the reward, for example updating points using an SQL statement like UPDATE users SET points = points - 50 WHERE user_id = 123, then generates a confirmation message and sends it to the device.

[0473] In this way, users can efficiently aim to achieve their goals through a series of processes from goal setting to progress management, advice provision, and reward allocation.

[0474] (Application example 1)

[0475] 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."

[0476] In modern society, it is important for users to efficiently achieve their self-set health goals and maintain a healthy lifestyle. However, conventional systems have problems such as users being confused about daily food choices and difficulty in accurately tracking progress toward achieving their goals. Furthermore, the reward system is vague and there is a lack of means to motivate users, making it difficult to continue working on the system.

[0477] 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.

[0478] In this invention, the server includes a means for the user to set goals, a means for providing the user with appropriate advice using a generative AI model, a means for recording and managing daily progress data, a means for rewarding the user according to the degree of goal achievement, a means for the generative AI model to recommend appropriate meal menus based on the user's health goals, and a means for awarding points based on the user's healthy choices in their orders. This enables the user to choose appropriate meals in line with their health goals, effectively manage their progress, and maintain motivation through the awarding of rewards, allowing them to continue working on their goals.

[0479] A "user" is an individual who uses the system to set goals, track progress, and receive rewards.

[0480] "Means for setting goals" is a function that allows users to input specific goals they want to achieve and register them in the system.

[0481] A "generative AI model" is an artificial intelligence model that provides appropriate advice to help users achieve their goals.

[0482] "Means for providing advice" is a function that uses a generative AI model to notify users of appropriate advice that is aligned with their goals.

[0483] "Progress data" is information used to record the actions and data entered by the user on a daily basis and to manage their progress.

[0484] "Means for recording and managing progress data" refers to the function of collecting user behavior and input data, recording it in the system, and managing it.

[0485] "Means for providing rewards" refers to a function that calculates rewards based on the user's achievement of goals and provides the user with points or other rewards.

[0486] "Means for recommending meal menus" refers to a function in which the generative AI model suggests appropriate meal menus based on the user's health goals.

[0487] "Ordering with a healthy choice" refers to the act of a user selecting and ordering a healthy meal menu item.

[0488] The "means of awarding points" is a function that awards points as an incentive when a user takes actions or makes choices that are in line with the goals they have set.

[0489] This invention relates to a system that uses a generative AI model to manage progress and reward users according to their level of achievement in order to help them achieve their health goals. The system starts with the user setting their goal using a device such as a smartphone, and supports them throughout the process of achieving their goal.

[0490] 1. User goal setting

[0491] User:

[0492] Users use the device and input specific goals, such as "I want to lose 3 kilograms in one month," through the application.

[0493] Device:

[0494] The device organizes the user's input and sends it to the server, for example, by sending a goal setting request using the HTTP communication protocol, and also includes a function to validate the user's input and check for omissions or errors.

[0495] server:

[0496] The server stores the received goal data in a database and associates it with the user's profile, which includes information such as the user's current weight and activity history.

[0497] 2. Providing advice using generative AI models

[0498] server:

[0499] The server calls a generative AI model based on the user's goal data and profile data to generate appropriate advice for achieving their goals. The generative AI model references past data and statistical information to provide specific and personalized advice.

[0500] Device:

[0501] The device then notifies the user of the generated advice. For example, it might say, "Order a low-calorie salad today." The user can then use this advice to incorporate it into their daily lives.

[0502] 3. Daily progress management

[0503] User:

[0504] Users input their daily diet and exercise data into the device, for example, entering detailed information such as "I had a salad for lunch" or "I walked for 30 minutes."

[0505] Device:

[0506] The device organizes this input data and sends it to the server. Progress checks and feedback are also done on the device, and the interface is designed so that users can see their progress at a glance.

[0507] server:

[0508] The server stores the received data in a database and manages the user's progress. It also generates new advice from the generative AI model based on new progress data and notifies the device.

[0509] 4. Points Management and Rewards

[0510] server:

[0511] The server analyzes the user's progress data and calculates points based on the achievement of the goal. For example, if the user achieves 30 minutes of walking for one week in a row, 50 points will be awarded.

[0512] Device:

[0513] The terminal will display the points awarded to the user along with a list of available rewards, which the user can use to select a reward.

[0514] User:

[0515] Users select from a list of rewards and enter their selection into the terminal, such as a 10% off coupon for their next food delivery order.

[0516] server:

[0517] The server receives the user's selection, performs processing to deduct points and provide rewards, and then sends a confirmation message to the device.

[0518] Program processing overview

[0519] The system's programs are implemented using programming languages ​​such as Python. Each process, including user goal setting, progress data management, advice provision by the generative AI model, and reward allocation, is carried out through communication between the server and the device. The database uses a relational database such as MySQL, and the generative AI model is implemented using machine learning libraries such as TensorFlow and PyTorch.

[0520] Examples of concrete examples and prompts

[0521] Examples:

[0522] 1. User goal setting: "Lose 3 kg in 1 month"

[0523] 2. AI advice: "To help you achieve your weight loss goal, we recommend a low-calorie salad for lunch today."

[0524] 3. Track your progress: "I took a 30-minute walk and ordered a healthy salad."

[0525] 4. Reward: "10% off your next order"

[0526] Example prompt sentence:

[0527] "Generate specific dietary advice to help the user achieve their goal. The user's goal is to lose 3 kg in 1 month."

[0528] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0529] Step 1:

[0530] The user sets a goal. Specifically, the user accesses the application using a smartphone device and inputs a specific goal, such as "I want to lose 3 kg in one month." The device organizes this input data and sends it to the server using the HTTP communication protocol. The input data is sent to the server as a goal setting request. The server receives this data, stores it in a database, and associates it with the user's profile.

[0531] Step 2:

[0532] The server provides advice using a generative AI model. The server sends a prompt to the generative AI model based on the user's goal data and profile data. An example of a prompt is, "Please generate specific dietary advice to help the user achieve their goal. The user's goal is to lose 3 kg in one month." The generative AI model generates advice based on this prompt and returns it to the server. The server notifies the device of the generated advice. The device displays this notification on its screen to inform the user.

[0533] Step 3:

[0534] Enter the user's daily progress. The user enters data about their daily diet and exercise on the device. For example, they enter data such as "I had salad for lunch" or "I walked for 30 minutes." The device organizes the entered data and sends it to the server using the HTTP communication protocol. The server saves the received data in a database and manages it as daily progress data.

[0535] Step 4:

[0536] The server generates new advice based on the progress data. The server retrieves the latest progress data from the database and sends it to the generative AI model. The generative AI model generates new advice and returns it to the server. The server notifies the device of this new advice. The device notifies the user of the advice so that they can use it as reference.

[0537] Step 5:

[0538] The server calculates rewards based on the degree of goal achievement. The server analyzes daily progress data and calculates the user's degree of goal achievement. For example, if there is data showing that the user has walked for 30 minutes continuously for one week, the server will calculate and award 50 points. The calculated point data is stored in a database.

[0539] Step 6:

[0540] The user receives the reward. The terminal displays the point accrual status and a list of available rewards to the user. The user selects the desired reward and enters it on the terminal. The terminal sends this input data to the server. The server receives the user's selection, deducts points, and processes the reward. The server then sends a confirmation message to the terminal, which notifies the user.

[0541] 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.

[0542] This invention combines a generative AI model and an emotion engine to manage progress and provide rewards according to the degree of achievement in order to help users achieve their set goals. This system can maintain user motivation and support goal achievement.

[0543] User goal setting

[0544] User: First, the user accesses the application using a device such as a smartphone and enters a specific goal, such as "I want to lose 3 kg in one month."

[0545] Terminal: Acquires user input and organizes this data for transmission to the server. It sends a goal setting request according to the communication protocol to the server.

[0546] Server: Stores the received goal data in a database and associates it with the user's profile, ensuring that the user's goals are recorded.

[0547] Providing advice through generative AI models

[0548] Server: Calls the generative AI model based on the user's goal data and profile data. The AI ​​model generates appropriate advice for achieving the goal. Examples include "walk 30 minutes every day" and "eat a low-sugar diet."

[0549] Device: The generated advice is notified to the user, who can then check the notification and incorporate it into their daily lives.

[0550] Daily progress management

[0551] User: The user enters daily diet and exercise data on the device. For example, "I had a salad for lunch" or "I walked for 30 minutes."

[0552] Terminal: This input data is organized and sent to the server. Progress checks and feedback are also performed on the terminal.

[0553] Server: Stores the received data in a database and manages the user's progress. Based on the new progress data, the generative AI model generates new advice and notifies the device.

[0554] Use of emotion engine

[0555] Server: Using the emotion engine, it acquires emotional data from the user's progress data and input data. For example, it analyzes the user's text, facial expressions, and voice data to recognize their emotional state, such as "motivation is decreasing" or "stress is increasing."

[0556] Device: Based on the emotional data, it displays advice and encouraging messages that correspond to the user's state. For example, it displays a message such as "You look like you're doing well today. Keep up the great work."

[0557] Points Management and Rewards

[0558] Server: Calculates points based on the user's progress and emotional data, and sets rewards. For example, it awards additional points when the user's goal achievement is high or when motivation is low.

[0559] Terminal: Displays the user the points awarded and a list of available rewards. Provides a screen for the user to select a reward.

[0560] User: Selects the desired reward from the displayed list of rewards and enters the selection into the terminal.

[0561] Server: Receives the user's selection, deducts points, performs processing to provide rewards, and then sends a confirmation message to the device.

[0562] In this way, users receive multi-layered support to achieve their goals, while also managing their progress and receiving rewards to motivate them according to their emotional state.By working together, the generative AI model and emotion engine can more effectively support users' efforts.

[0563] The processing flow will be explained below.

[0564] Step 1:

[0565] User: Launches the smartphone app and accesses the goal setting screen. Enters a specific goal, such as "I want to lose 3 kg in one month."

[0566] Step 2:

[0567] Terminal: Obtains user input, organizes goal data, and sends a goal setting request to the server.

[0568] Step 3:

[0569] Server: Stores the received goal data in a database and associates it with the user's profile.

[0570] Step 4:

[0571] Server: Using the generative AI model, the server generates advice based on the user's goal data. For example, it creates specific advice such as "walk 30 minutes every day."

[0572] Step 5:

[0573] Terminal: Notifies the user of the generated advice and displays a notification screen so that the user can check the advice.

[0574] Step 6:

[0575] User: Enters daily progress data. For example, enters "today's meal contents" and "exercise contents" into the device.

[0576] Step 7:

[0577] Terminal: Organizes the data entered by the user and sends it to the server as progress data. Displays a screen to provide feedback on the progress status to the user.

[0578] Step 8:

[0579] Server: Stores the received progress data in a database. Based on the stored data, new advice is generated from the generative AI model.

[0580] Step 9:

[0581] Server: In addition to the process of collecting progress data, it also runs an emotion engine to recognize the user's emotional state, for example, by analyzing text, voice, and facial expression data to evaluate the user's emotions.

[0582] Step 10:

[0583] Terminal: Receives emotional data from the emotion engine and provides feedback to the user. For example, if motivation is low, a message such as "Why don't you take a break today?" will be displayed.

[0584] Step 11:

[0585] Server: Based on the emotion data, if it is necessary to calculate additional points to increase the user's motivation, the server calculates and awards the points. For example, it awards additional points to a user whose progress is slow despite their efforts.

[0586] Step 12:

[0587] Terminal: Presents the user with the points awarded and a list of available rewards. Provides a screen where the user can select a reward.

[0588] Step 13:

[0589] User: Selects the desired reward from the displayed list of rewards and enters the selection into the terminal.

[0590] Step 14:

[0591] Server: Receives the user's selection, deducts points, performs processing related to the reward to be provided, and sends a confirmation message to the terminal after processing is complete.

[0592] In this way, users receive multi-layered support to achieve their goals, while being able to manage their progress and stay motivated with emotional feedback and additional incentives.The generative AI model and emotion engine work together to enhance the overall user experience.

[0593] Example 2

[0594] 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."

[0595] Conventional progress management systems have a single approach to helping users achieve their set goals, and lack diverse feedback and mechanisms for maintaining motivation. As a result, users tend to give up easily before achieving their goals, making it difficult to maintain long-term motivation. Furthermore, because support and feedback do not take into account the emotional state of each individual user, they are unable to effectively support users' efforts. To solve these issues, there is a need for the development of a system that provides multi-layered, personalized support.

[0596] 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.

[0597] In this invention, the server includes a means for allowing the user to set goals, a means for providing appropriate advice based on the user profile and goal data using a generative AI model, a means for recording and managing daily progress data, a means for calculating points based on the user's progress data and emotional data and awarding rewards according to the degree of goal achievement, and a means for acquiring the user's emotional data using an emotion engine and generating messages according to the user's state. This enables multi-layered and personalized support for each user, effectively helping users maintain their motivation and achieve their goals.

[0598] "User" refers to an individual or organization that uses the system to set goals, track progress, and earn rewards.

[0599] A "generative AI model" refers to an artificial intelligence system that generates natural language and analyzes data based on input data, and provides appropriate advice and feedback to users.

[0600] "User Profile" means a data set in a database that contains personal information, goals, progress data, etc. related to a User.

[0601] "Goal Data" means data containing information about specific goals that a User seeks to achieve.

[0602] "Progress data" refers to data that records the user's daily actions and results as they work toward their goals.

[0603] "Emotional Data" refers to data that indicates the user's emotional state as analyzed by the emotion engine.

[0604] An "emotion engine" refers to a system that analyzes user input data and behavioral data to recognize the user's emotional state.

[0605] "Points" refer to numerical data used to award rewards calculated based on the user's progress and emotional data.

[0606] "Rewards" refers to incentives such as goods or services given to users when they achieve their goals.

[0607] "Messages" refer to text or notifications generated by the emotion engine that contain encouragement or advice based on the user's state.

[0608] "Database" refers to an information system for storing and managing user profile data, goal data, progress data, emotional data, etc.

[0609] "Advice" refers to specific instructions or recommended actions provided to users by a generative AI model to achieve a goal.

[0610] This invention is a system that combines a generative AI model and an emotion engine to manage progress and provide rewards according to the degree of achievement in order to help users achieve their set goals. This system can maintain the user's motivation and support them in achieving their goals.

[0611] goal setting

[0612] First, a user accesses the application using a device such as a smartphone. They input a specific goal into the application, such as "I want to lose 3 kg in one month." The device acquires the user's input and organizes this data for transmission to the server. It then sends a goal-setting request to the server according to a communications protocol. The server stores the received goal data in a database and associates it with the user's profile, ensuring that the user's goals are recorded reliably.

[0613] Providing advice through generative AI models

[0614] The server calls a generative AI model based on the user's goal data and profile data. Examples of such generative AI models include OpenAI's GPT. The AI ​​model generates appropriate advice for achieving the goal. For example, advice such as "walk 30 minutes every day" or "eat a low-sugar diet" may be used. The device notifies the user of the generated advice, which the user can then review and incorporate into their daily life.

[0615] Daily progress management

[0616] Users input their daily diet and exercise data into the device. For example, they input specific data such as "I ate salad for lunch" or "I walked for 30 minutes." The device organizes this input data and sends it to the server. Progress checks and feedback are also performed on the device. The server stores the received data in a database and manages the user's progress. Based on the new progress data, the generative AI model generates new advice and notifies the device.

[0617] Use of emotion engine

[0618] The server uses an emotion engine to obtain emotional data from the user's progress data and input data. An example of this emotion engine is the IBM Watson Tone Analyzer. For example, it analyzes the user's written text, facial expressions, and voice data to recognize emotional states such as "decreasing motivation" or "increasing stress." Based on the emotional data, the device displays advice and encouraging messages appropriate to the user's condition. For example, it may display a message such as "You look like you're doing well today, keep up the good work."

[0619] Points Management and Rewards

[0620] The server calculates points based on the user's progress data and emotional data and sets rewards. For example, it awards additional points when goal achievement is high or motivation is low. The device displays the awarded points and a list of available rewards to the user. It provides a screen for the user to select a reward. The user selects the desired reward from the displayed reward list and inputs the selection into the device. The server receives the user's selection, deducts points, performs processing to provide the reward, and then sends a confirmation message to the device.

[0621] Prompt Sentence Examples

[0622] 1. Goal Setting:

[0623] "Set a new goal. For example, lose 3 kilos in one month."

[0624] 2. Progress Input:

[0625] "Please enter your diet and exercise data for today."

[0626] 3. Providing advice:

[0627] "Shows advice generated by AI models"

[0628] 4. Emotion data input:

[0629] "Please enter your current emotional state."

[0630] 5. Reward Selection:

[0631] "Select your desired reward from the list of available rewards"

[0632] The system allows users to receive planned and specific support to achieve their goals, and by combining a generative AI model with an emotion engine, it is possible to provide advice and feedback that is optimized for each individual user.

[0633] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0634] Step 1:

[0635] The user sets a goal. Specifically, they launch the smartphone application and input a specific goal, such as "I want to lose 3 kg in one month." The input is the user's goal information, and the output is a goal setting request.

[0636] Step 2:

[0637] The device organizes the user's input. For example, it converts a user's input goal, such as "I want to lose 3 kg in one month," into a format to be sent to the server. The input is a goal setting request, and the output is the goal information converted into a data format to be sent to the server.

[0638] Step 3:

[0639] The server receives the target data and stores it in a database, for example, by associating it with a user profile database. The input is the target information sent from the terminal, and the output is the target data stored in the database.

[0640] Step 4:

[0641] The server invokes a generative AI model based on the received goal data and user profile data. For example, it uses OpenAI's GPT to send prompts and generate advice. The input is the goal data and profile data, and the output is the generated advice.

[0642] Step 5:

[0643] The device receives the advice generated by the server and notifies the user. For example, it may notify the user of advice such as "walk 30 minutes every day" or "eat a low-sugar diet." The input is the generated advice, and the output is the notification to the user.

[0644] Step 6:

[0645] The user inputs daily diet and exercise data into the device. For example, they input progress data such as "I ate salad for lunch" or "I walked for 30 minutes." The input is specific diet and exercise data, and the output is progress data.

[0646] Step 7:

[0647] The device organizes the progress data and sends it to the server. For example, it converts information entered by the user, such as "I ate salad for lunch," into a data format for transmission. The input is the progress data, and the output is the data to be sent to the server.

[0648] Step 8:

[0649] The server stores the received progress data in a database and manages the progress. For example, it stores the data in association with the user's profile. The input is the progress data in the transmission data format, and the output is the progress data stored in the database.

[0650] Step 9:

[0651] The server requests the generative AI model to generate new advice based on the new progress data. For example, it generates additional advice such as "walk 30 minutes a day and incorporate stretching into your daily routine." The input is the new progress data, and the output is the new advice.

[0652] Step 10:

[0653] The terminal notifies the user of newly generated advice. The input is the new advice, and the output is the notification to the user.

[0654] Step 11:

[0655] The server uses an emotion engine to obtain emotion data from the progress data and input data. For example, it uses "IBM Watson Tone Analyzer" to analyze the user's writing and recognize that "motivation is declining." The inputs are progress data and input data, and the output is emotion data.

[0656] Step 12:

[0657] The server generates an appropriate message based on the emotion data and sends it to the device. For example, it generates an encouraging message such as, "You look good today, keep up the good work." The input is the emotion data, and the output is the generated message.

[0658] Step 13:

[0659] The terminal notifies the user of the generated message. The input is the generated message, and the output is the notification to the user.

[0660] Step 14:

[0661] The server calculates points based on the progress data and emotion data and sets rewards. For example, it gives additional points when a specific goal is achieved. The input is the progress data and emotion data, and the output is the calculated points and a list of rewards.

[0662] Step 15:

[0663] The terminal displays the awarded points and the list of available rewards to the user. The input is the reward list, and the output is the display to the user.

[0664] Step 16:

[0665] The user selects the desired reward from the displayed reward list and inputs the selection into the terminal. The input is the user's reward selection, and the output is the selection data.

[0666] Step 17:

[0667] The terminal sends the user's selection to the server. The input is the selection data, and the output is the data to be sent to the server.

[0668] Step 18:

[0669] The server receives the user's selection, deducts points, and executes a process to provide a reward. For example, a procedure may be performed to provide the user with a 500 yen Amazon gift card after deducting points. The input is the selection data and current points, and the output is the updated points balance and confirmation of the reward.

[0670] Step 19:

[0671] The server sends the reward provision confirmation data to the terminal. The input is the reward provision confirmation data, and the output is the data sent to the terminal.

[0672] Step 20:

[0673] The terminal notifies the user of a message confirming the provision of the reward. The input is the confirmation data for the provision of the reward, and the output is a notification to the user.

[0674] (Application example 2)

[0675] 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."

[0676] Conventional goal management systems do not take into account the user's emotions or motivation when managing the user's progress or providing advice, which makes it difficult to maintain motivation to achieve goals. Furthermore, the reward system based on the degree of goal achievement is monotonous, leaving room for improvement in user satisfaction.

[0677] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for the user to set a goal, a means for providing the user with appropriate advice using a generative AI model, a means for recording and managing daily progress data, a means for rewarding the user according to the degree of goal achievement, a means for analyzing the user's emotional state using an emotion engine and providing feedback, and a means for providing cashback or points based on the user's progress and emotional state. This makes it possible to effectively support goal achievement while taking into account the user's emotions and motivation, and to improve user satisfaction through the reward system.

[0678] A "user" is an individual or organization that uses the system to set goals and take action to achieve those goals.

[0679] A "goal" is a specific result or state that a user aims to achieve.

[0680] A "generative AI model" is a system or algorithm that uses artificial intelligence to generate appropriate advice and support to help users achieve their goals.

[0681] "Advice" is information that contains specific instructions, suggestions, or recommendations for achieving a user's set goals.

[0682] "Progress Data" means information that records the activities and actions taken by a user toward achieving a goal and the results of those activities and actions.

[0683] "Rewards" refers to incentives and benefits given to users when they achieve their goals, including cashback and points.

[0684] An "emotion engine" is a system or algorithm that analyzes data such as a user's writing, facial expressions, and voice to recognize the user's emotional state.

[0685] "Feedback" refers to information or messages provided to the user by the system, and contains appropriate content depending on the user's emotional state.

[0686] "Cashback" is a form of reward in which a user receives a refund or rebate when they achieve a goal, depending on the degree of achievement.

[0687] "Points" are numerical rewards given to users for achieving goals or other activities, and once a certain number of points have been accumulated, they can be exchanged for rewards or incentives.

[0688] A system for implementing this invention includes a means for a user to set a goal, a means for providing appropriate advice to the user using a generative AI model, a means for recording and managing daily progress data, a means for rewarding the user according to the degree of goal achievement, a means for analyzing the user's emotional state using an emotion engine and providing feedback, and a means for providing cashback or points based on the user's progress and emotional state.

[0689] 1. User goal setting

[0690] Users access the application using a smartphone or other device and input specific goals, such as "keep monthly credit card spending under 50,000 yen."

[0691] The terminal acquires the goal content input by the user and organizes this data for transmission to the server, and sends a goal setting request to the server according to a communication protocol.

[0692] The server stores the received goal data in a database and associates it with the user's profile, ensuring that the user's goals are recorded.

[0693] 2. Providing advice using generative AI models

[0694] The server calls up a generative AI model based on the user's goal and profile data, and generates appropriate advice for achieving the goal. For example, "cook more meals at home to reduce monthly food costs" or "create a wish list to avoid waste."

[0695] The device will notify the user of the generated advice, which the user can then review and incorporate into their daily lives.

[0696] 3. Use of Emotion Engine

[0697] The server uses an emotion engine to extract emotional data from user input data. For example, it analyzes positive comments such as "I've been having fun saving money this month" and negative comments such as "It was difficult to save money today" to recognize the user's emotional state.

[0698] Based on the recognized emotional data, the device displays advice and encouraging messages according to the user's state, such as "You're feeling good today, keep up the good work," or "You seem a little tired, it's important to take a break."

[0699] 4. Daily progress management and reward provision

[0700] Users input their daily spending data on the device, such as "Today's food expenses were 1,200 yen" or "I spent 5,000 yen on home appliances."

[0701] The device organizes this input data and sends it to the server, where progress confirmation and feedback are also provided.

[0702] The server stores the received data in a database and manages the user's progress. Based on the new progress data, the generative AI model generates new advice and notifies the device. In addition, cashback and points are provided depending on the degree of goal achievement.

[0703] Examples of concrete examples and prompts

[0704] For example, if a user sets a goal of "keeping monthly expenses under 50,000 yen," the prompt to the generative AI model would look like this:

[0705] Please advise how a user can reduce their monthly expenses to 50,000 yen. Current expenses: 45,000 yen.

[0706] In this way, users receive comprehensive support that effectively assists them in achieving their goals, while also receiving feedback and rewards based on their emotional state. By working together, the generative AI model and emotion engine can more effectively support users in their efforts.

[0707] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0708] Step 1:

[0709] Users access the application using a device such as a smartphone and set specific goals. For example, they might enter, "Keep monthly credit card spending under 50,000 yen." The device receives this input, organizes the data, and sends it to the server. The server then receives it, stores it in a database, and associates it with the user profile. The input is goal setting data, and the output is a database entry of the goal data.

[0710] Step 2:

[0711] The server obtains the goal data and user profile data, and sends a prompt to the generative AI model to generate advice for achieving the goal. The specific prompt used is, "Please advise how the user can keep their monthly expenses to 50,000 yen. Current expenses: 45,000 yen." The input is the user data and the prompt, and the output is the generated advice.

[0712] Step 3:

[0713] The device receives the advice of the generative AI model sent from the server and notifies the user. The user can check this notification and incorporate it into their daily life. In this step, feedback is provided by the advice being delivered to the user. The input is the advice data from the server, and the output is a notification to the user.

[0714] Step 4:

[0715] The user inputs details of their daily spending into the device. For example, "Today's food expenses were 1,200 yen" or "I spent 5,000 yen on home appliances." The device organizes this detailed data and sends it to the server. The input is daily spending data, and the output is the transmission of progress data to the server.

[0716] Step 5:

[0717] The server receives daily spending data, stores it in a database, and manages the user's progress. Based on this progress data, it invokes a new generative AI model, generates new advice, and notifies the device. It also manages the allocation of cashback and points according to the degree of goal achievement. The input is daily spending data, and the output is the generation of new advice and reward data.

[0718] Step 6:

[0719] The server uses an emotion engine to analyze emotion data from the user's input data. For example, it analyzes positive emotion from the user's input "I'm having fun saving money this month" and generates an encouraging message such as "You're doing well today, keep up the good work." The input is the user's input data, and the output is the analyzed emotion data and an encouraging message.

[0720] Step 7:

[0721] The device notifies the user of messages generated by the emotion engine. The messages are based on the user's emotional state and play an important role in maintaining motivation. The input is emotional data and messages, and the output is notifications to the user.

[0722] In this way, at each step, data is processed and calculated based on the input data, and the output is used in the next step. This realizes a system that helps users achieve their goals and provides appropriate rewards and feedback.

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

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

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

[0726] [Third embodiment]

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

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

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

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

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

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

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

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

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

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

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

[0738] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0739] A specific embodiment of the present invention will be described below. This system uses a generative AI model to help users achieve their set goals, manage their progress, and award rewards according to their level of achievement.

[0740] 1. User goal setting

[0741] User: First, the user accesses the application using a device such as a smartphone and enters a specific goal, such as "I want to lose 3 kg in one month."

[0742] Terminal: Acquires user input and organizes this data for transmission to the server. It sends a goal setting request according to the communication protocol to the server.

[0743] Server: Stores the received goal data in a database and associates it with the user's profile, ensuring that the user's goals are recorded.

[0744] 2. Providing advice using generative AI models

[0745] Server: Calls the generative AI model based on the user's goal data and profile data. The AI ​​model generates appropriate advice for achieving the goal. Examples include "walk 30 minutes every day" and "eat a low-sugar diet."

[0746] Device: The generated advice is notified to the user, who can then check the notification and incorporate it into their daily lives.

[0747] 3. Daily progress management

[0748] User: The user enters daily diet and exercise data on the device. For example, "I had a salad for lunch" or "I walked for 30 minutes."

[0749] Terminal: This input data is organized and sent to the server. Progress checks and feedback are also performed on the terminal.

[0750] Server: Stores the received data in a database and manages the user's progress. Based on the new progress data, the generative AI model generates new advice and notifies the device.

[0751] 4. Points Management and Rewards

[0752] Server: Analyzes the user's progress data and calculates points based on the degree of goal achievement. For example, if a user walks for 30 minutes continuously for one week, 50 points will be awarded.

[0753] Terminal: Displays the user a list of available rewards along with the points awarded, allowing the user to select a reward.

[0754] User: Selects the reward he / she desires from a list of rewards and enters his / her selection on the terminal.

[0755] Server: Receives the user's selection, performs processing to deduct points and provide rewards, and then sends a confirmation message to the device.

[0756] Overall, this system helps users achieve their goals efficiently and maintain a healthy lifestyle. The combination of a generative AI model with progress management and rewards is expected to motivate users and encourage continued efforts.

[0757] The processing flow will be explained below.

[0758] Step 1:

[0759] User: Launches the smartphone app and accesses the goal setting screen. Enters a specific goal, such as "I want to lose 3 kg in one month."

[0760] Step 2:

[0761] Terminal: Obtains user input, organizes goal data, and sends a goal setting request to the server.

[0762] Step 3:

[0763] Server: Stores the received goal data in a database and associates it with the user's profile.

[0764] Step 4:

[0765] Server: Using the generative AI model, the server generates advice based on the user's goal data. For example, it creates specific advice such as "walk 30 minutes every day."

[0766] Step 5:

[0767] Terminal: Notifies the user of the generated advice and displays a notification screen so that the user can check the advice.

[0768] Step 6:

[0769] User: Enters daily progress data. For example, enters "today's meal contents" and "exercise contents" into the device.

[0770] Step 7:

[0771] Terminal: Organizes the data entered by the user and sends it to the server as progress data. Displays a screen to provide feedback on the progress status to the user.

[0772] Step 8:

[0773] Server: Stores the received progress data in a database. Based on the stored data, new advice is generated from the generative AI model.

[0774] Step 9:

[0775] Server: Analyzes the progress data, evaluates the user's achievement level, and calculates points based on the evaluation results.

[0776] Step 10:

[0777] Terminal: Displays the user the points awarded and a list of available rewards. Provides a screen for the user to select a reward.

[0778] Step 11:

[0779] User: Selects the desired reward from the displayed list of rewards and enters the selection into the terminal.

[0780] Step 12:

[0781] Server: Receives the user's selection, deducts points, performs processing to provide rewards, and notifies the user when processing is complete.

[0782] In this way, users are supported in achieving their goals, while tracking their progress and receiving rewards to motivate them.

[0783] Example 1

[0784] 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."

[0785] In modern society, individuals are required to easily and efficiently manage their health and achieve their goals. However, existing applications and systems rarely integrate user goal setting, progress management, advice provision, and rewards. Furthermore, advice provision using generative AI models is underutilized, making it difficult to maintain user motivation. Furthermore, there is a lack of functionality to provide new advice in real time based on the user's progress data. The objective of this invention is to solve these problems.

[0786] 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.

[0787] In this invention, the server includes means for the user to call the generative AI model based on goal data and profile data and generate advice, means for receiving the user's progress data and again calling the generative AI model to generate new advice, and means for rewarding the user according to the degree of goal achievement. This allows the user to receive specific and personalized advice for achieving their goal, and to receive real-time feedback and rewards according to their progress.

[0788] "User" refers to an individual who uses the System to set goals, track progress, receive advice, and receive rewards.

[0789] "Goal setting means" refers to a software or hardware component that has the functionality to allow a user to input specific goals and record them within the system.

[0790] "Generative AI model" refers to an artificial intelligence model that generates specific advice for achieving goals based on a user's goals and profile data.

[0791] "Advice Providing Means" refers to a software or hardware component that has the function of notifying the user of appropriate advice from a generative AI model.

[0792] "Progress management means" refers to a software or hardware component that has the function of recording a user's daily progress data and storing and managing it in a database.

[0793] "Reward granting means" refers to a software or hardware component that has the function of calculating and granting points or rewards based on the user's achievement of goals.

[0794] "Profile Data" refers to data that includes personal information about the user, such as age, weight, and height.

[0795] "Advice generation means" refers to a software or hardware component that has the function of invoking a generative AI model based on a user's goal data and profile data to generate appropriate advice.

[0796] The system of the present invention uses a generative AI model to help users achieve their set goals, manage their progress, and provide rewards based on their achievement. A specific embodiment of this system is described below.

[0797] First, a user can access the application using a device such as a smartphone and set a specific goal. For example, they can input a goal such as "I want to lose 3 kg in one month." Once the user inputs their goal, the device retrieves this data and organizes it for transmission to the server. The data is structured using a format such as JSON and sent to the server via the HTTP protocol.

[0798] The server stores the received goal data in a database and associates it with the user's profile. During this process, the data is inserted using a SQL statement, for example, INSERT INTO goals (user_id, goal) VALUES (123, 'Lose 3 kg in 1 month').

[0799] The server calls the generative AI model based on the user's goal data and profile data, and generates specific advice for achieving the goal. An example of a prompt sentence for the generative AI model is "I want to lose 3 kg in one month," {"age": 30, "weight": 70, "height": 170}. The server then provides the resulting advice to the user. For example, specific advice such as "Walk 30 minutes every day" or "Eat a low-sugar diet" is generated.

[0800] These advice messages are sent to the user via the device. The user can then review the messages and incorporate them into their daily lives. Progress is also managed in the same way, with the user entering their daily diet and exercise data via the device. For example, "I ate a salad for lunch" or "I walked for 30 minutes."

[0801] The device organizes the user's input data and sends it to the server, which stores the data in a database and manages the user's progress. The server then generates new advice from the generative AI model based on the new progress data and notifies the device.

[0802] Furthermore, the server analyzes the user's progress data and calculates points according to the degree of goal achievement. For example, if the user walks for 30 minutes continuously for one week, 50 points will be awarded. Along with these points, a list of available rewards will be displayed on the device, and the user can select the reward they want. The server receives the user's selection and processes it to deduct points and provide the reward. It then sends a confirmation message to the device.

[0803] This system allows users to efficiently achieve their goals and receive support to maintain a healthy lifestyle. Furthermore, by combining a progress management and reward system linked to the generative AI model, it is expected that users will be motivated and encouraged to continue their efforts.

[0804] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0805] Step 1: User-defined goals

[0806] The user accesses the application from a device such as a smartphone and enters a specific goal on the goal setting screen. The input data is, for example, a sentence such as "I want to lose 3 kg in one month." This data is provided to the device as input.

[0807] Step 2: Organize and send data using your device

[0808] The device takes the user's input data and organizes it into JSON format for sending to the server, where the data is structured as follows: {"user_id": 123, "goal": "Lose 3 kg in 1 month"}. The organized data is sent to the server via an HTTP POST request.

[0809] Step 3: Data received and stored by the server

[0810] The server receives the data sent from the device. The received data is in the JSON format shown above, and is parsed to extract the data contents. The data is then saved to the database using an SQL statement. For example, it is inserted into the database in the form of INSERT INTO goals (user_id, goal) VALUES (123, 'Lose 3 kg in 1 month'). The successfully saved data is used as input for the next process.

[0811] Step 4: Generative AI model generates advice

[0812] The server obtains the goal data and the user's profile data, and based on that, calls the generative AI model to generate advice. For example, the prompt sentence "I want to lose 3 kg in one month" and {"age": 30, "weight": 70, "height": 170} are input to the AI ​​model. As a result, the generated advice is output to the server. Examples of advice include "Walk 30 minutes every day" and "Try to eat a diet low in sugar."

[0813] Step 5: Notification of advice to device

[0814] The device that receives the advice generated by the server notifies the user of the content via push notifications or in-app messages. The notification is presented to the user as concrete guidelines to be reflected in their daily lives.

[0815] Step 6: User enters progress data

[0816] Users input their daily diet and exercise data through the app. For example, "I had a salad for lunch" or "I walked for 30 minutes." This input data is stored on the device as input for the next process.

[0817] Step 7: Organize and send progress data from your device

[0818] The device organizes the progress data entered by the user and structures it in JSON format or similar to send it to the server. For example, the data is organized as follows: {"user_id": 123, "diary": ["Salad for lunch", "30 minutes walking"]}. This is sent to the server as an HTTP POST request.

[0819] Step 8: Server saves progress data and generates new advice

[0820] The server receives the progress data sent from the device and stores it in a database. Next, it calls the generative AI model again based on the progress data to generate new advice. The newly generated advice is output to the server, and becomes the next notification sent to the device.

[0821] Step 9: Server calculates points and awards rewards

[0822] The server analyzes the user's progress data and calculates points according to the degree of goal achievement. For example, if the user "achieves 30 minutes of walking continuously for one week," 50 points will be awarded. The result of this calculation becomes the input data for reward processing.

[0823] Step 10: Displaying the reward list on the terminal and user selection

[0824] The terminal displays the calculated points and a list of available rewards to the user, who selects the reward he or she desires from the list and transmits the selection information from the terminal to the server.

[0825] Step 11: Server processes reward and sends confirmation message

[0826] The server receives the user's selection, deducts points, and processes the reward, for example updating points using an SQL statement like UPDATE users SET points = points - 50 WHERE user_id = 123, then generates a confirmation message and sends it to the device.

[0827] In this way, users can efficiently aim to achieve their goals through a series of processes from goal setting to progress management, advice provision, and reward allocation.

[0828] (Application example 1)

[0829] 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."

[0830] In modern society, it is important for users to efficiently achieve their self-set health goals and maintain a healthy lifestyle. However, conventional systems have problems such as users being confused about daily food choices and difficulty in accurately tracking progress toward achieving their goals. Furthermore, the reward system is vague and there is a lack of means to motivate users, making it difficult to continue working on the system.

[0831] 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.

[0832] In this invention, the server includes a means for the user to set goals, a means for providing the user with appropriate advice using a generative AI model, a means for recording and managing daily progress data, a means for rewarding the user according to the degree of goal achievement, a means for the generative AI model to recommend appropriate meal menus based on the user's health goals, and a means for awarding points based on the user's healthy choices in their orders. This enables the user to choose appropriate meals in line with their health goals, effectively manage their progress, and maintain motivation through the awarding of rewards, allowing them to continue working on their goals.

[0833] A "user" is an individual who uses the system to set goals, track progress, and receive rewards.

[0834] "Means for setting goals" is a function that allows users to input specific goals they want to achieve and register them in the system.

[0835] A "generative AI model" is an artificial intelligence model that provides appropriate advice to help users achieve their goals.

[0836] "Means for providing advice" is a function that uses a generative AI model to notify users of appropriate advice that is aligned with their goals.

[0837] "Progress data" is information used to record the actions and data entered by the user on a daily basis and to manage their progress.

[0838] "Means for recording and managing progress data" refers to the function of collecting user behavior and input data, recording it in the system, and managing it.

[0839] "Means for providing rewards" refers to a function that calculates rewards based on the user's achievement of goals and provides the user with points or other rewards.

[0840] "Means for recommending meal menus" refers to a function in which the generative AI model suggests appropriate meal menus based on the user's health goals.

[0841] "Ordering with a healthy choice" refers to the act of a user selecting and ordering a healthy meal menu item.

[0842] The "means of awarding points" is a function that awards points as an incentive when a user takes actions or makes choices that are in line with the goals they have set.

[0843] This invention relates to a system that uses a generative AI model to manage progress and reward users according to their level of achievement in order to help them achieve their health goals. The system starts with the user setting their goal using a device such as a smartphone, and supports them throughout the process of achieving their goal.

[0844] 1. User goal setting

[0845] User:

[0846] Users use the device and input specific goals, such as "I want to lose 3 kilograms in one month," through the application.

[0847] Device:

[0848] The device organizes the user's input and sends it to the server, for example, by sending a goal setting request using the HTTP communication protocol, and also includes a function to validate the user's input and check for omissions or errors.

[0849] server:

[0850] The server stores the received goal data in a database and associates it with the user's profile, which includes information such as the user's current weight and activity history.

[0851] 2. Providing advice using generative AI models

[0852] server:

[0853] The server calls a generative AI model based on the user's goal data and profile data to generate appropriate advice for achieving their goals. The generative AI model references past data and statistical information to provide specific and personalized advice.

[0854] Device:

[0855] The device then notifies the user of the generated advice. For example, it might say, "Order a low-calorie salad today." The user can then use this advice to incorporate it into their daily lives.

[0856] 3. Daily progress management

[0857] User:

[0858] Users input their daily diet and exercise data into the device, for example, entering detailed information such as "I had a salad for lunch" or "I walked for 30 minutes."

[0859] Device:

[0860] The device organizes this input data and sends it to the server. Progress checks and feedback are also done on the device, and the interface is designed so that users can see their progress at a glance.

[0861] server:

[0862] The server stores the received data in a database and manages the user's progress. It also generates new advice from the generative AI model based on new progress data and notifies the device.

[0863] 4. Points Management and Rewards

[0864] server:

[0865] The server analyzes the user's progress data and calculates points based on the achievement of the goal. For example, if the user achieves 30 minutes of walking for one week in a row, 50 points will be awarded.

[0866] Device:

[0867] The terminal will display the points awarded to the user along with a list of available rewards, which the user can use to select a reward.

[0868] User:

[0869] Users select from a list of rewards and enter their selection into the terminal, such as a 10% off coupon for their next food delivery order.

[0870] server:

[0871] The server receives the user's selection, performs processing to deduct points and provide rewards, and then sends a confirmation message to the device.

[0872] Program processing overview

[0873] The system's programs are implemented using programming languages ​​such as Python. Each process, including user goal setting, progress data management, advice provision by the generative AI model, and reward allocation, is carried out through communication between the server and the device. The database uses a relational database such as MySQL, and the generative AI model is implemented using machine learning libraries such as TensorFlow and PyTorch.

[0874] Examples of concrete examples and prompts

[0875] Examples:

[0876] 1. User goal setting: "Lose 3 kg in 1 month"

[0877] 2. AI advice: "To help you achieve your weight loss goal, we recommend a low-calorie salad for lunch today."

[0878] 3. Track your progress: "I took a 30-minute walk and ordered a healthy salad."

[0879] 4. Reward: "10% off your next order"

[0880] Example prompt sentence:

[0881] "Generate specific dietary advice to help the user achieve their goal. The user's goal is to lose 3 kg in 1 month."

[0882] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0883] Step 1:

[0884] The user sets a goal. Specifically, the user accesses the application using a smartphone device and inputs a specific goal, such as "I want to lose 3 kg in one month." The device organizes this input data and sends it to the server using the HTTP communication protocol. The input data is sent to the server as a goal setting request. The server receives this data, stores it in a database, and associates it with the user's profile.

[0885] Step 2:

[0886] The server provides advice using a generative AI model. The server sends a prompt to the generative AI model based on the user's goal data and profile data. An example of a prompt is, "Please generate specific dietary advice to help the user achieve their goal. The user's goal is to lose 3 kg in one month." The generative AI model generates advice based on this prompt and returns it to the server. The server notifies the device of the generated advice. The device displays this notification on its screen to inform the user.

[0887] Step 3:

[0888] Enter the user's daily progress. The user enters data about their daily diet and exercise on the device. For example, they enter data such as "I had salad for lunch" or "I walked for 30 minutes." The device organizes the entered data and sends it to the server using the HTTP communication protocol. The server saves the received data in a database and manages it as daily progress data.

[0889] Step 4:

[0890] The server generates new advice based on the progress data. The server retrieves the latest progress data from the database and sends it to the generative AI model. The generative AI model generates new advice and returns it to the server. The server notifies the device of this new advice. The device notifies the user of the advice so that they can use it as reference.

[0891] Step 5:

[0892] The server calculates rewards based on the degree of goal achievement. The server analyzes daily progress data and calculates the user's degree of goal achievement. For example, if there is data showing that the user has walked for 30 minutes continuously for one week, the server will calculate and award 50 points. The calculated point data is stored in a database.

[0893] Step 6:

[0894] The user receives the reward. The terminal displays the point accrual status and a list of available rewards to the user. The user selects the desired reward and enters it on the terminal. The terminal sends this input data to the server. The server receives the user's selection, deducts points, and processes the reward. The server then sends a confirmation message to the terminal, which notifies the user.

[0895] 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.

[0896] This invention combines a generative AI model and an emotion engine to manage progress and provide rewards according to the degree of achievement in order to help users achieve their set goals. This system can maintain user motivation and support goal achievement.

[0897] User goal setting

[0898] User: First, the user accesses the application using a device such as a smartphone and enters a specific goal, such as "I want to lose 3 kg in one month."

[0899] Terminal: Acquires user input and organizes this data for transmission to the server. It sends a goal setting request according to the communication protocol to the server.

[0900] Server: Stores the received goal data in a database and associates it with the user's profile, ensuring that the user's goals are recorded.

[0901] Providing advice through generative AI models

[0902] Server: Calls the generative AI model based on the user's goal data and profile data. The AI ​​model generates appropriate advice for achieving the goal. Examples include "walk 30 minutes every day" and "eat a low-sugar diet."

[0903] Device: The generated advice is notified to the user, who can then check the notification and incorporate it into their daily lives.

[0904] Daily progress management

[0905] User: The user enters daily diet and exercise data on the device. For example, "I had a salad for lunch" or "I walked for 30 minutes."

[0906] Terminal: This input data is organized and sent to the server. Progress checks and feedback are also performed on the terminal.

[0907] Server: Stores the received data in a database and manages the user's progress. Based on the new progress data, the generative AI model generates new advice and notifies the device.

[0908] Use of emotion engine

[0909] Server: Using the emotion engine, it acquires emotional data from the user's progress data and input data. For example, it analyzes the user's text, facial expressions, and voice data to recognize their emotional state, such as "motivation is decreasing" or "stress is increasing."

[0910] Device: Based on the emotional data, it displays advice and encouraging messages that correspond to the user's state. For example, it displays a message such as "You look like you're doing well today. Keep up the great work."

[0911] Points Management and Rewards

[0912] Server: Calculates points based on the user's progress and emotional data, and sets rewards. For example, it awards additional points when the user's goal achievement is high or when motivation is low.

[0913] Terminal: Displays the user the points awarded and a list of available rewards. Provides a screen for the user to select a reward.

[0914] User: Selects the desired reward from the displayed list of rewards and enters the selection into the terminal.

[0915] Server: Receives the user's selection, deducts points, performs processing to provide rewards, and then sends a confirmation message to the device.

[0916] In this way, users receive multi-layered support to achieve their goals, while also managing their progress and receiving rewards to motivate them according to their emotional state.By working together, the generative AI model and emotion engine can more effectively support users' efforts.

[0917] The processing flow will be explained below.

[0918] Step 1:

[0919] User: Launches the smartphone app and accesses the goal setting screen. Enters a specific goal, such as "I want to lose 3 kg in one month."

[0920] Step 2:

[0921] Terminal: Obtains user input, organizes goal data, and sends a goal setting request to the server.

[0922] Step 3:

[0923] Server: Stores the received goal data in a database and associates it with the user's profile.

[0924] Step 4:

[0925] Server: Using the generative AI model, the server generates advice based on the user's goal data. For example, it creates specific advice such as "walk 30 minutes every day."

[0926] Step 5:

[0927] Terminal: Notifies the user of the generated advice and displays a notification screen so that the user can check the advice.

[0928] Step 6:

[0929] User: Enters daily progress data. For example, enters "today's meal contents" and "exercise contents" into the device.

[0930] Step 7:

[0931] Terminal: Organizes the data entered by the user and sends it to the server as progress data. Displays a screen to provide feedback on the progress status to the user.

[0932] Step 8:

[0933] Server: Stores the received progress data in a database. Based on the stored data, new advice is generated from the generative AI model.

[0934] Step 9:

[0935] Server: In addition to the process of collecting progress data, it also runs an emotion engine to recognize the user's emotional state, for example, by analyzing text, voice, and facial expression data to evaluate the user's emotions.

[0936] Step 10:

[0937] Terminal: Receives emotional data from the emotion engine and provides feedback to the user. For example, if motivation is low, a message such as "Why don't you take a break today?" will be displayed.

[0938] Step 11:

[0939] Server: Based on the emotion data, if it is necessary to calculate additional points to increase the user's motivation, the server calculates and awards the points. For example, it awards additional points to a user whose progress is slow despite their efforts.

[0940] Step 12:

[0941] Terminal: Presents the user with the points awarded and a list of available rewards. Provides a screen where the user can select a reward.

[0942] Step 13:

[0943] User: Selects the desired reward from the displayed list of rewards and enters the selection into the terminal.

[0944] Step 14:

[0945] Server: Receives the user's selection, deducts points, performs processing related to the reward to be provided, and sends a confirmation message to the terminal after processing is complete.

[0946] In this way, users receive multi-layered support to achieve their goals, while being able to manage their progress and stay motivated with emotional feedback and additional incentives.The generative AI model and emotion engine work together to enhance the overall user experience.

[0947] Example 2

[0948] 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."

[0949] Conventional progress management systems have a single approach to helping users achieve their set goals, and lack diverse feedback and mechanisms for maintaining motivation. As a result, users tend to give up easily before achieving their goals, making it difficult to maintain long-term motivation. Furthermore, because support and feedback do not take into account the emotional state of each individual user, they are unable to effectively support users' efforts. To solve these issues, there is a need for the development of a system that provides multi-layered, personalized support.

[0950] 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.

[0951] In this invention, the server includes a means for allowing the user to set goals, a means for providing appropriate advice based on the user profile and goal data using a generative AI model, a means for recording and managing daily progress data, a means for calculating points based on the user's progress data and emotional data and awarding rewards according to the degree of goal achievement, and a means for acquiring the user's emotional data using an emotion engine and generating messages according to the user's state. This enables multi-layered and personalized support for each user, effectively helping users maintain their motivation and achieve their goals.

[0952] "User" refers to an individual or organization that uses the system to set goals, track progress, and earn rewards.

[0953] A "generative AI model" refers to an artificial intelligence system that generates natural language and analyzes data based on input data, and provides appropriate advice and feedback to users.

[0954] "User Profile" means a data set in a database that contains personal information, goals, progress data, etc. related to a User.

[0955] "Goal Data" means data containing information about specific goals that a User seeks to achieve.

[0956] "Progress data" refers to data that records the user's daily actions and results as they work toward their goals.

[0957] "Emotional Data" refers to data that indicates the user's emotional state as analyzed by the emotion engine.

[0958] An "emotion engine" refers to a system that analyzes user input data and behavioral data to recognize the user's emotional state.

[0959] "Points" refer to numerical data used to award rewards calculated based on the user's progress and emotional data.

[0960] "Rewards" refers to incentives such as goods or services given to users when they achieve their goals.

[0961] "Messages" refer to text or notifications generated by the emotion engine that contain encouragement or advice based on the user's state.

[0962] "Database" refers to an information system for storing and managing user profile data, goal data, progress data, emotional data, etc.

[0963] "Advice" refers to specific instructions or recommended actions provided to users by a generative AI model to achieve a goal.

[0964] This invention is a system that combines a generative AI model and an emotion engine to manage progress and provide rewards according to the degree of achievement in order to help users achieve their set goals. This system can maintain the user's motivation and support them in achieving their goals.

[0965] goal setting

[0966] First, a user accesses the application using a device such as a smartphone. They input a specific goal into the application, such as "I want to lose 3 kg in one month." The device acquires the user's input and organizes this data for transmission to the server. It then sends a goal-setting request to the server according to a communications protocol. The server stores the received goal data in a database and associates it with the user's profile, ensuring that the user's goals are recorded reliably.

[0967] Providing advice through generative AI models

[0968] The server calls a generative AI model based on the user's goal data and profile data. Examples of such generative AI models include OpenAI's GPT. The AI ​​model generates appropriate advice for achieving the goal. For example, advice such as "walk 30 minutes every day" or "eat a low-sugar diet" may be used. The device notifies the user of the generated advice, which the user can then review and incorporate into their daily life.

[0969] Daily progress management

[0970] Users input their daily diet and exercise data into the device. For example, they input specific data such as "I ate salad for lunch" or "I walked for 30 minutes." The device organizes this input data and sends it to the server. Progress checks and feedback are also performed on the device. The server stores the received data in a database and manages the user's progress. Based on the new progress data, the generative AI model generates new advice and notifies the device.

[0971] Use of emotion engine

[0972] The server uses an emotion engine to obtain emotional data from the user's progress data and input data. An example of this emotion engine is the IBM Watson Tone Analyzer. For example, it analyzes the user's written text, facial expressions, and voice data to recognize emotional states such as "decreasing motivation" or "increasing stress." Based on the emotional data, the device displays advice and encouraging messages appropriate to the user's condition. For example, it may display a message such as "You look like you're doing well today, keep up the good work."

[0973] Points Management and Rewards

[0974] The server calculates points based on the user's progress data and emotional data and sets rewards. For example, it awards additional points when goal achievement is high or motivation is low. The device displays the awarded points and a list of available rewards to the user. It provides a screen for the user to select a reward. The user selects the desired reward from the displayed reward list and inputs the selection into the device. The server receives the user's selection, deducts points, performs processing to provide the reward, and then sends a confirmation message to the device.

[0975] Prompt Sentence Examples

[0976] 1. Goal Setting:

[0977] "Set a new goal. For example, lose 3 kilos in one month."

[0978] 2. Progress Input:

[0979] "Please enter your diet and exercise data for today."

[0980] 3. Providing advice:

[0981] "Shows advice generated by AI models"

[0982] 4. Emotion data input:

[0983] "Please enter your current emotional state."

[0984] 5. Reward Selection:

[0985] "Select your desired reward from the list of available rewards"

[0986] The system allows users to receive planned and specific support to achieve their goals, and by combining a generative AI model with an emotion engine, it is possible to provide advice and feedback that is optimized for each individual user.

[0987] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0988] Step 1:

[0989] The user sets a goal. Specifically, they launch the smartphone application and input a specific goal, such as "I want to lose 3 kg in one month." The input is the user's goal information, and the output is a goal setting request.

[0990] Step 2:

[0991] The device organizes the user's input. For example, it converts a user's input goal, such as "I want to lose 3 kg in one month," into a format to be sent to the server. The input is a goal setting request, and the output is the goal information converted into a data format to be sent to the server.

[0992] Step 3:

[0993] The server receives the target data and stores it in a database, for example, by associating it with a user profile database. The input is the target information sent from the terminal, and the output is the target data stored in the database.

[0994] Step 4:

[0995] The server invokes a generative AI model based on the received goal data and user profile data. For example, it uses OpenAI's GPT to send prompts and generate advice. The input is the goal data and profile data, and the output is the generated advice.

[0996] Step 5:

[0997] The device receives the advice generated by the server and notifies the user. For example, it may notify the user of advice such as "walk 30 minutes every day" or "eat a low-sugar diet." The input is the generated advice, and the output is the notification to the user.

[0998] Step 6:

[0999] The user inputs daily diet and exercise data into the device. For example, they input progress data such as "I ate salad for lunch" or "I walked for 30 minutes." The input is specific diet and exercise data, and the output is progress data.

[1000] Step 7:

[1001] The device organizes the progress data and sends it to the server. For example, it converts information entered by the user, such as "I ate salad for lunch," into a data format for transmission. The input is the progress data, and the output is the data to be sent to the server.

[1002] Step 8:

[1003] The server stores the received progress data in a database and manages the progress. For example, it stores the data in association with the user's profile. The input is the progress data in the transmission data format, and the output is the progress data stored in the database.

[1004] Step 9:

[1005] The server requests the generative AI model to generate new advice based on the new progress data. For example, it generates additional advice such as "walk 30 minutes a day and incorporate stretching into your daily routine." The input is the new progress data, and the output is the new advice.

[1006] Step 10:

[1007] The terminal notifies the user of newly generated advice. The input is the new advice, and the output is the notification to the user.

[1008] Step 11:

[1009] The server uses an emotion engine to obtain emotion data from the progress data and input data. For example, it uses "IBM Watson Tone Analyzer" to analyze the user's writing and recognize that "motivation is declining." The inputs are progress data and input data, and the output is emotion data.

[1010] Step 12:

[1011] The server generates an appropriate message based on the emotion data and sends it to the device. For example, it generates an encouraging message such as, "You look good today, keep up the good work." The input is the emotion data, and the output is the generated message.

[1012] Step 13:

[1013] The terminal notifies the user of the generated message. The input is the generated message, and the output is the notification to the user.

[1014] Step 14:

[1015] The server calculates points based on the progress data and emotion data and sets rewards. For example, it gives additional points when a specific goal is achieved. The input is the progress data and emotion data, and the output is the calculated points and a list of rewards.

[1016] Step 15:

[1017] The terminal displays the awarded points and the list of available rewards to the user. The input is the reward list, and the output is the display to the user.

[1018] Step 16:

[1019] The user selects the desired reward from the displayed reward list and inputs the selection into the terminal. The input is the user's reward selection, and the output is the selection data.

[1020] Step 17:

[1021] The terminal sends the user's selection to the server. The input is the selection data, and the output is the data to be sent to the server.

[1022] Step 18:

[1023] The server receives the user's selection, deducts points, and executes a process to provide a reward. For example, a procedure may be performed to provide the user with a 500 yen Amazon gift card after deducting points. The input is the selection data and current points, and the output is the updated points balance and confirmation of the reward.

[1024] Step 19:

[1025] The server sends the reward provision confirmation data to the terminal. The input is the reward provision confirmation data, and the output is the data sent to the terminal.

[1026] Step 20:

[1027] The terminal notifies the user of a message confirming the provision of the reward. The input is the confirmation data for the provision of the reward, and the output is a notification to the user.

[1028] (Application example 2)

[1029] 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."

[1030] Conventional goal management systems do not take into account the user's emotions or motivation when managing the user's progress or providing advice, which makes it difficult to maintain motivation to achieve goals. Furthermore, the reward system based on the degree of goal achievement is monotonous, leaving room for improvement in user satisfaction.

[1031] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for the user to set a goal, a means for providing the user with appropriate advice using a generative AI model, a means for recording and managing daily progress data, a means for rewarding the user according to the degree of goal achievement, a means for analyzing the user's emotional state using an emotion engine and providing feedback, and a means for providing cashback or points based on the user's progress and emotional state. This makes it possible to effectively support goal achievement while taking into account the user's emotions and motivation, and to improve user satisfaction through the reward system.

[1032] A "user" is an individual or organization that uses the system to set goals and take action to achieve those goals.

[1033] A "goal" is a specific result or state that a user aims to achieve.

[1034] A "generative AI model" is a system or algorithm that uses artificial intelligence to generate appropriate advice and support to help users achieve their goals.

[1035] "Advice" is information that contains specific instructions, suggestions, or recommendations for achieving a user's set goals.

[1036] "Progress Data" means information that records the activities and actions taken by a user toward achieving a goal and the results of those activities and actions.

[1037] "Rewards" refers to incentives and benefits given to users when they achieve their goals, including cashback and points.

[1038] An "emotion engine" is a system or algorithm that analyzes data such as a user's writing, facial expressions, and voice to recognize the user's emotional state.

[1039] "Feedback" refers to information or messages provided to the user by the system, and contains appropriate content depending on the user's emotional state.

[1040] "Cashback" is a form of reward in which a user receives a refund or rebate when they achieve a goal, depending on the degree of achievement.

[1041] "Points" are numerical rewards given to users for achieving goals or other activities, and once a certain number of points have been accumulated, they can be exchanged for rewards or incentives.

[1042] A system for implementing this invention includes a means for a user to set a goal, a means for providing appropriate advice to the user using a generative AI model, a means for recording and managing daily progress data, a means for rewarding the user according to the degree of goal achievement, a means for analyzing the user's emotional state using an emotion engine and providing feedback, and a means for providing cashback or points based on the user's progress and emotional state.

[1043] 1. User goal setting

[1044] Users access the application using a smartphone or other device and input specific goals, such as "keep monthly credit card spending under 50,000 yen."

[1045] The terminal acquires the goal content input by the user and organizes this data for transmission to the server, and sends a goal setting request to the server according to a communication protocol.

[1046] The server stores the received goal data in a database and associates it with the user's profile, ensuring that the user's goals are recorded.

[1047] 2. Providing advice using generative AI models

[1048] The server calls up a generative AI model based on the user's goal and profile data, and generates appropriate advice for achieving the goal. For example, "cook more meals at home to reduce monthly food costs" or "create a wish list to avoid waste."

[1049] The device will notify the user of the generated advice, which the user can then review and incorporate into their daily lives.

[1050] 3. Use of Emotion Engine

[1051] The server uses an emotion engine to extract emotional data from user input data. For example, it analyzes positive comments such as "I've been having fun saving money this month" and negative comments such as "It was difficult to save money today" to recognize the user's emotional state.

[1052] Based on the recognized emotional data, the device displays advice and encouraging messages according to the user's state, such as "You're feeling good today, keep up the good work," or "You seem a little tired, it's important to take a break."

[1053] 4. Daily progress management and reward provision

[1054] Users input their daily spending data on the device, such as "Today's food expenses were 1,200 yen" or "I spent 5,000 yen on home appliances."

[1055] The device organizes this input data and sends it to the server, where progress confirmation and feedback are also provided.

[1056] The server stores the received data in a database and manages the user's progress. Based on the new progress data, the generative AI model generates new advice and notifies the device. In addition, cashback and points are provided depending on the degree of goal achievement.

[1057] Examples of concrete examples and prompts

[1058] For example, if a user sets a goal of "keeping monthly expenses under 50,000 yen," the prompt to the generative AI model would look like this:

[1059] Please advise how a user can reduce their monthly expenses to 50,000 yen. Current expenses: 45,000 yen.

[1060] In this way, users receive comprehensive support that effectively assists them in achieving their goals, while also receiving feedback and rewards based on their emotional state. By working together, the generative AI model and emotion engine can more effectively support users in their efforts.

[1061] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1062] Step 1:

[1063] Users access the application using a device such as a smartphone and set specific goals. For example, they might enter, "Keep monthly credit card spending under 50,000 yen." The device receives this input, organizes the data, and sends it to the server. The server then receives it, stores it in a database, and associates it with the user profile. The input is goal setting data, and the output is a database entry of the goal data.

[1064] Step 2:

[1065] The server obtains the goal data and user profile data, and sends a prompt to the generative AI model to generate advice for achieving the goal. The specific prompt used is, "Please advise how the user can keep their monthly expenses to 50,000 yen. Current expenses: 45,000 yen." The input is the user data and the prompt, and the output is the generated advice.

[1066] Step 3:

[1067] The device receives the advice of the generative AI model sent from the server and notifies the user. The user can check this notification and incorporate it into their daily life. In this step, feedback is provided by the advice being delivered to the user. The input is the advice data from the server, and the output is a notification to the user.

[1068] Step 4:

[1069] The user inputs details of their daily spending into the device. For example, "Today's food expenses were 1,200 yen" or "I spent 5,000 yen on home appliances." The device organizes this detailed data and sends it to the server. The input is daily spending data, and the output is the transmission of progress data to the server.

[1070] Step 5:

[1071] The server receives daily spending data, stores it in a database, and manages the user's progress. Based on this progress data, it invokes a new generative AI model, generates new advice, and notifies the device. It also manages the allocation of cashback and points according to the degree of goal achievement. The input is daily spending data, and the output is the generation of new advice and reward data.

[1072] Step 6:

[1073] The server uses an emotion engine to analyze emotion data from the user's input data. For example, it analyzes positive emotion from the user's input "I'm having fun saving money this month" and generates an encouraging message such as "You're doing well today, keep up the good work." The input is the user's input data, and the output is the analyzed emotion data and an encouraging message.

[1074] Step 7:

[1075] The device notifies the user of messages generated by the emotion engine. The messages are based on the user's emotional state and play an important role in maintaining motivation. The input is emotional data and messages, and the output is notifications to the user.

[1076] In this way, at each step, data is processed and calculated based on the input data, and the output is used in the next step. This realizes a system that helps users achieve their goals and provides appropriate rewards and feedback.

[1077] 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.

[1078] 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.

[1079] 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.

[1080] [Fourth embodiment]

[1081] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1082] 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.

[1083] 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).

[1084] 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.

[1085] 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.

[1086] 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).

[1087] 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.

[1088] 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.

[1089] 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.

[1090] 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.

[1091] 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.

[1092] 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.

[1093] 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."

[1094] A specific embodiment of the present invention will be described below. This system uses a generative AI model to help users achieve their set goals, manage their progress, and award rewards according to their level of achievement.

[1095] 1. User goal setting

[1096] User: First, the user accesses the application using a device such as a smartphone and enters a specific goal, such as "I want to lose 3 kg in one month."

[1097] Terminal: Acquires user input and organizes this data for transmission to the server. It sends a goal setting request according to the communication protocol to the server.

[1098] Server: Stores the received goal data in a database and associates it with the user's profile, ensuring that the user's goals are recorded.

[1099] 2. Providing advice using generative AI models

[1100] Server: Calls the generative AI model based on the user's goal data and profile data. The AI ​​model generates appropriate advice for achieving the goal. Examples include "walk 30 minutes every day" and "eat a low-sugar diet."

[1101] Device: The generated advice is notified to the user, who can then check the notification and incorporate it into their daily lives.

[1102] 3. Daily progress management

[1103] User: The user enters daily diet and exercise data on the device. For example, "I had a salad for lunch" or "I walked for 30 minutes."

[1104] Terminal: This input data is organized and sent to the server. Progress checks and feedback are also performed on the terminal.

[1105] Server: Stores the received data in a database and manages the user's progress. Based on the new progress data, the generative AI model generates new advice and notifies the device.

[1106] 4. Points Management and Rewards

[1107] Server: Analyzes the user's progress data and calculates points based on the degree of goal achievement. For example, if a user walks for 30 minutes continuously for one week, 50 points will be awarded.

[1108] Terminal: Displays the user a list of available rewards along with the points awarded, allowing the user to select a reward.

[1109] User: Selects the reward he / she desires from a list of rewards and enters his / her selection on the terminal.

[1110] Server: Receives the user's selection, performs processing to deduct points and provide rewards, and then sends a confirmation message to the device.

[1111] Overall, this system helps users achieve their goals efficiently and maintain a healthy lifestyle. The combination of a generative AI model with progress management and rewards is expected to motivate users and encourage continued efforts.

[1112] The processing flow will be explained below.

[1113] Step 1:

[1114] User: Launches the smartphone app and accesses the goal setting screen. Enters a specific goal, such as "I want to lose 3 kg in one month."

[1115] Step 2:

[1116] Terminal: Obtains user input, organizes goal data, and sends a goal setting request to the server.

[1117] Step 3:

[1118] Server: Stores the received goal data in a database and associates it with the user's profile.

[1119] Step 4:

[1120] Server: Using the generative AI model, the server generates advice based on the user's goal data. For example, it creates specific advice such as "walk 30 minutes every day."

[1121] Step 5:

[1122] Terminal: Notifies the user of the generated advice and displays a notification screen so that the user can check the advice.

[1123] Step 6:

[1124] User: Enters daily progress data. For example, enters "today's meal contents" and "exercise contents" into the device.

[1125] Step 7:

[1126] Terminal: Organizes the data entered by the user and sends it to the server as progress data. Displays a screen to provide feedback on the progress status to the user.

[1127] Step 8:

[1128] Server: Stores the received progress data in a database. Based on the stored data, new advice is generated from the generative AI model.

[1129] Step 9:

[1130] Server: Analyzes the progress data, evaluates the user's achievement level, and calculates points based on the evaluation results.

[1131] Step 10:

[1132] Terminal: Displays the user the points awarded and a list of available rewards. Provides a screen for the user to select a reward.

[1133] Step 11:

[1134] User: Selects the desired reward from the displayed list of rewards and enters the selection into the terminal.

[1135] Step 12:

[1136] Server: Receives the user's selection, deducts points, performs processing to provide rewards, and notifies the user when processing is complete.

[1137] In this way, users are supported in achieving their goals, while tracking their progress and receiving rewards to motivate them.

[1138] Example 1

[1139] 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."

[1140] In modern society, individuals are required to easily and efficiently manage their health and achieve their goals. However, existing applications and systems rarely integrate user goal setting, progress management, advice provision, and rewards. Furthermore, advice provision using generative AI models is underutilized, making it difficult to maintain user motivation. Furthermore, there is a lack of functionality to provide new advice in real time based on the user's progress data. The objective of this invention is to solve these problems.

[1141] 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.

[1142] In this invention, the server includes means for the user to call the generative AI model based on goal data and profile data and generate advice, means for receiving the user's progress data and again calling the generative AI model to generate new advice, and means for rewarding the user according to the degree of goal achievement. This allows the user to receive specific and personalized advice for achieving their goal, and to receive real-time feedback and rewards according to their progress.

[1143] "User" refers to an individual who uses the System to set goals, track progress, receive advice, and receive rewards.

[1144] "Goal setting means" refers to a software or hardware component that has the functionality to allow a user to input specific goals and record them within the system.

[1145] "Generative AI model" refers to an artificial intelligence model that generates specific advice for achieving goals based on a user's goals and profile data.

[1146] "Advice Providing Means" refers to a software or hardware component that has the function of notifying the user of appropriate advice from a generative AI model.

[1147] "Progress management means" refers to a software or hardware component that has the function of recording a user's daily progress data and storing and managing it in a database.

[1148] "Reward granting means" refers to a software or hardware component that has the function of calculating and granting points or rewards based on the user's achievement of goals.

[1149] "Profile Data" refers to data that includes personal information about the user, such as age, weight, and height.

[1150] "Advice generation means" refers to a software or hardware component that has the function of invoking a generative AI model based on a user's goal data and profile data to generate appropriate advice.

[1151] The system of the present invention uses a generative AI model to help users achieve their set goals, manage their progress, and provide rewards based on their achievement. A specific embodiment of this system is described below.

[1152] First, a user can access the application using a device such as a smartphone and set a specific goal. For example, they can input a goal such as "I want to lose 3 kg in one month." Once the user inputs their goal, the device retrieves this data and organizes it for transmission to the server. The data is structured using a format such as JSON and sent to the server via the HTTP protocol.

[1153] The server stores the received goal data in a database and associates it with the user's profile. During this process, the data is inserted using a SQL statement, for example, INSERT INTO goals (user_id, goal) VALUES (123, 'Lose 3 kg in 1 month').

[1154] The server calls the generative AI model based on the user's goal data and profile data, and generates specific advice for achieving the goal. An example of a prompt sentence for the generative AI model is "I want to lose 3 kg in one month," {"age": 30, "weight": 70, "height": 170}. The server then provides the resulting advice to the user. For example, specific advice such as "Walk 30 minutes every day" or "Eat a low-sugar diet" is generated.

[1155] These advice messages are sent to the user via the device. The user can then review the messages and incorporate them into their daily lives. Progress is also managed in the same way, with the user entering their daily diet and exercise data via the device. For example, "I ate a salad for lunch" or "I walked for 30 minutes."

[1156] The device organizes the user's input data and sends it to the server, which stores the data in a database and manages the user's progress. The server then generates new advice from the generative AI model based on the new progress data and notifies the device.

[1157] Furthermore, the server analyzes the user's progress data and calculates points according to the degree of goal achievement. For example, if the user walks for 30 minutes continuously for one week, 50 points will be awarded. Along with these points, a list of available rewards will be displayed on the device, and the user can select the reward they want. The server receives the user's selection and processes it to deduct points and provide the reward. It then sends a confirmation message to the device.

[1158] This system allows users to efficiently achieve their goals and receive support to maintain a healthy lifestyle. Furthermore, by combining a progress management and reward system linked to the generative AI model, it is expected that users will be motivated and encouraged to continue their efforts.

[1159] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1160] Step 1: User-defined goals

[1161] The user accesses the application from a device such as a smartphone and enters a specific goal on the goal setting screen. The input data is, for example, a sentence such as "I want to lose 3 kg in one month." This data is provided to the device as input.

[1162] Step 2: Organize and send data using your device

[1163] The device takes the user's input data and organizes it into JSON format for sending to the server, where the data is structured as follows: {"user_id": 123, "goal": "Lose 3 kg in 1 month"}. The organized data is sent to the server via an HTTP POST request.

[1164] Step 3: Data received and stored by the server

[1165] The server receives the data sent from the device. The received data is in the JSON format shown above, and is parsed to extract the data contents. The data is then saved to the database using an SQL statement. For example, it is inserted into the database in the form of INSERT INTO goals (user_id, goal) VALUES (123, 'Lose 3 kg in 1 month'). The successfully saved data is used as input for the next process.

[1166] Step 4: Generative AI model generates advice

[1167] The server obtains the goal data and the user's profile data, and based on that, calls the generative AI model to generate advice. For example, the prompt sentence "I want to lose 3 kg in one month" and {"age": 30, "weight": 70, "height": 170} are input to the AI ​​model. As a result, the generated advice is output to the server. Examples of advice include "Walk 30 minutes every day" and "Try to eat a diet low in sugar."

[1168] Step 5: Notification of advice to device

[1169] The device that receives the advice generated by the server notifies the user of the content via push notifications or in-app messages. The notification is presented to the user as concrete guidelines to be reflected in their daily lives.

[1170] Step 6: User enters progress data

[1171] Users input their daily diet and exercise data through the app. For example, "I had a salad for lunch" or "I walked for 30 minutes." This input data is stored on the device as input for the next process.

[1172] Step 7: Organize and send progress data from your device

[1173] The device organizes the progress data entered by the user and structures it in JSON format or similar to send it to the server. For example, the data is organized as follows: {"user_id": 123, "diary": ["Salad for lunch", "30 minutes walking"]}. This is sent to the server as an HTTP POST request.

[1174] Step 8: Server saves progress data and generates new advice

[1175] The server receives the progress data sent from the device and stores it in a database. Next, it calls the generative AI model again based on the progress data to generate new advice. The newly generated advice is output to the server, and becomes the next notification sent to the device.

[1176] Step 9: Server calculates points and awards rewards

[1177] The server analyzes the user's progress data and calculates points according to the degree of goal achievement. For example, if the user "achieves 30 minutes of walking continuously for one week," 50 points will be awarded. The result of this calculation becomes the input data for reward processing.

[1178] Step 10: Displaying the reward list on the terminal and user selection

[1179] The terminal displays the calculated points and a list of available rewards to the user, who selects the reward he or she desires from the list and transmits the selection information from the terminal to the server.

[1180] Step 11: Server processes reward and sends confirmation message

[1181] The server receives the user's selection, deducts points, and processes the reward, for example updating points using an SQL statement like UPDATE users SET points = points - 50 WHERE user_id = 123, then generates a confirmation message and sends it to the device.

[1182] In this way, users can efficiently aim to achieve their goals through a series of processes from goal setting to progress management, advice provision, and reward allocation.

[1183] (Application example 1)

[1184] 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."

[1185] In modern society, it is important for users to efficiently achieve their self-set health goals and maintain a healthy lifestyle. However, conventional systems have problems such as users being confused about daily food choices and difficulty in accurately tracking progress toward achieving their goals. Furthermore, the reward system is vague and there is a lack of means to motivate users, making it difficult to continue working on the system.

[1186] 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.

[1187] In this invention, the server includes a means for the user to set goals, a means for providing the user with appropriate advice using a generative AI model, a means for recording and managing daily progress data, a means for rewarding the user according to the degree of goal achievement, a means for the generative AI model to recommend appropriate meal menus based on the user's health goals, and a means for awarding points based on the user's healthy choices in their orders. This enables the user to choose appropriate meals in line with their health goals, effectively manage their progress, and maintain motivation through the awarding of rewards, allowing them to continue working on their goals.

[1188] A "user" is an individual who uses the system to set goals, track progress, and receive rewards.

[1189] "Means for setting goals" is a function that allows users to input specific goals they want to achieve and register them in the system.

[1190] A "generative AI model" is an artificial intelligence model that provides appropriate advice to help users achieve their goals.

[1191] "Means for providing advice" is a function that uses a generative AI model to notify users of appropriate advice that is aligned with their goals.

[1192] "Progress data" is information used to record the actions and data entered by the user on a daily basis and to manage their progress.

[1193] "Means for recording and managing progress data" refers to the function of collecting user behavior and input data, recording it in the system, and managing it.

[1194] "Means for providing rewards" refers to a function that calculates rewards based on the user's achievement of goals and provides the user with points or other rewards.

[1195] "Means for recommending meal menus" refers to a function in which the generative AI model suggests appropriate meal menus based on the user's health goals.

[1196] "Ordering with a healthy choice" refers to the act of a user selecting and ordering a healthy meal menu item.

[1197] The "means of awarding points" is a function that awards points as an incentive when a user takes actions or makes choices that are in line with the goals they have set.

[1198] This invention relates to a system that uses a generative AI model to manage progress and reward users according to their level of achievement in order to help them achieve their health goals. The system starts with the user setting their goal using a device such as a smartphone, and supports them throughout the process of achieving their goal.

[1199] 1. User goal setting

[1200] User:

[1201] Users use the device and input specific goals, such as "I want to lose 3 kilograms in one month," through the application.

[1202] Device:

[1203] The device organizes the user's input and sends it to the server, for example, by sending a goal setting request using the HTTP communication protocol, and also includes a function to validate the user's input and check for omissions or errors.

[1204] server:

[1205] The server stores the received goal data in a database and associates it with the user's profile, which includes information such as the user's current weight and activity history.

[1206] 2. Providing advice using generative AI models

[1207] server:

[1208] The server calls a generative AI model based on the user's goal data and profile data to generate appropriate advice for achieving their goals. The generative AI model references past data and statistical information to provide specific and personalized advice.

[1209] Device:

[1210] The device then notifies the user of the generated advice. For example, it might say, "Order a low-calorie salad today." The user can then use this advice to incorporate it into their daily lives.

[1211] 3. Daily progress management

[1212] User:

[1213] Users input their daily diet and exercise data into the device, for example, entering detailed information such as "I had a salad for lunch" or "I walked for 30 minutes."

[1214] Device:

[1215] The device organizes this input data and sends it to the server. Progress checks and feedback are also done on the device, and the interface is designed so that users can see their progress at a glance.

[1216] server:

[1217] The server stores the received data in a database and manages the user's progress. It also generates new advice from the generative AI model based on new progress data and notifies the device.

[1218] 4. Points Management and Rewards

[1219] server:

[1220] The server analyzes the user's progress data and calculates points based on the achievement of the goal. For example, if the user achieves 30 minutes of walking for one week in a row, 50 points will be awarded.

[1221] Device:

[1222] The terminal will display the points awarded to the user along with a list of available rewards, which the user can use to select a reward.

[1223] User:

[1224] Users select from a list of rewards and enter their selection into the terminal, such as a 10% off coupon for their next food delivery order.

[1225] server:

[1226] The server receives the user's selection, performs processing to deduct points and provide rewards, and then sends a confirmation message to the device.

[1227] Program processing overview

[1228] The system's programs are implemented using programming languages ​​such as Python. Each process, including user goal setting, progress data management, advice provision by the generative AI model, and reward allocation, is carried out through communication between the server and the device. The database uses a relational database such as MySQL, and the generative AI model is implemented using machine learning libraries such as TensorFlow and PyTorch.

[1229] Examples of concrete examples and prompts

[1230] Examples:

[1231] 1. User goal setting: "Lose 3 kg in 1 month"

[1232] 2. AI advice: "To help you achieve your weight loss goal, we recommend a low-calorie salad for lunch today."

[1233] 3. Track your progress: "I took a 30-minute walk and ordered a healthy salad."

[1234] 4. Reward: "10% off your next order"

[1235] Example prompt sentence:

[1236] "Generate specific dietary advice to help the user achieve their goal. The user's goal is to lose 3 kg in 1 month."

[1237] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1238] Step 1:

[1239] The user sets a goal. Specifically, the user accesses the application using a smartphone device and inputs a specific goal, such as "I want to lose 3 kg in one month." The device organizes this input data and sends it to the server using the HTTP communication protocol. The input data is sent to the server as a goal setting request. The server receives this data, stores it in a database, and associates it with the user's profile.

[1240] Step 2:

[1241] The server provides advice using a generative AI model. The server sends a prompt to the generative AI model based on the user's goal data and profile data. An example of a prompt is, "Please generate specific dietary advice to help the user achieve their goal. The user's goal is to lose 3 kg in one month." The generative AI model generates advice based on this prompt and returns it to the server. The server notifies the device of the generated advice. The device displays this notification on its screen to inform the user.

[1242] Step 3:

[1243] Enter the user's daily progress. The user enters data about their daily diet and exercise on the device. For example, they enter data such as "I had salad for lunch" or "I walked for 30 minutes." The device organizes the entered data and sends it to the server using the HTTP communication protocol. The server saves the received data in a database and manages it as daily progress data.

[1244] Step 4:

[1245] The server generates new advice based on the progress data. The server retrieves the latest progress data from the database and sends it to the generative AI model. The generative AI model generates new advice and returns it to the server. The server notifies the device of this new advice. The device notifies the user of the advice so that they can use it as reference.

[1246] Step 5:

[1247] The server calculates rewards based on the degree of goal achievement. The server analyzes daily progress data and calculates the user's degree of goal achievement. For example, if there is data showing that the user has walked for 30 minutes continuously for one week, the server will calculate and award 50 points. The calculated point data is stored in a database.

[1248] Step 6:

[1249] The user receives the reward. The terminal displays the point accrual status and a list of available rewards to the user. The user selects the desired reward and enters it on the terminal. The terminal sends this input data to the server. The server receives the user's selection, deducts points, and processes the reward. The server then sends a confirmation message to the terminal, which notifies the user.

[1250] 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.

[1251] This invention combines a generative AI model and an emotion engine to manage progress and provide rewards according to the degree of achievement in order to help users achieve their set goals. This system can maintain user motivation and support goal achievement.

[1252] User goal setting

[1253] User: First, the user accesses the application using a device such as a smartphone and enters a specific goal, such as "I want to lose 3 kg in one month."

[1254] Terminal: Acquires user input and organizes this data for transmission to the server. It sends a goal setting request according to the communication protocol to the server.

[1255] Server: Stores the received goal data in a database and associates it with the user's profile, ensuring that the user's goals are recorded.

[1256] Providing advice through generative AI models

[1257] Server: Calls the generative AI model based on the user's goal data and profile data. The AI ​​model generates appropriate advice for achieving the goal. Examples include "walk 30 minutes every day" and "eat a low-sugar diet."

[1258] Device: The generated advice is notified to the user, who can then check the notification and incorporate it into their daily lives.

[1259] Daily progress management

[1260] User: The user enters daily diet and exercise data on the device. For example, "I had a salad for lunch" or "I walked for 30 minutes."

[1261] Terminal: This input data is organized and sent to the server. Progress checks and feedback are also performed on the terminal.

[1262] Server: Stores the received data in a database and manages the user's progress. Based on the new progress data, the generative AI model generates new advice and notifies the device.

[1263] Use of emotion engine

[1264] Server: Using the emotion engine, it acquires emotional data from the user's progress data and input data. For example, it analyzes the user's text, facial expressions, and voice data to recognize their emotional state, such as "motivation is decreasing" or "stress is increasing."

[1265] Device: Based on the emotional data, it displays advice and encouraging messages that correspond to the user's state. For example, it displays a message such as "You look like you're doing well today. Keep up the great work."

[1266] Points Management and Rewards

[1267] Server: Calculates points based on the user's progress and emotional data, and sets rewards. For example, it awards additional points when the user's goal achievement is high or when motivation is low.

[1268] Terminal: Displays the user the points awarded and a list of available rewards. Provides a screen for the user to select a reward.

[1269] User: Selects the desired reward from the displayed list of rewards and enters the selection into the terminal.

[1270] Server: Receives the user's selection, deducts points, performs processing to provide rewards, and then sends a confirmation message to the device.

[1271] In this way, users receive multi-layered support to achieve their goals, while also managing their progress and receiving rewards to motivate them according to their emotional state.By working together, the generative AI model and emotion engine can more effectively support users' efforts.

[1272] The processing flow will be explained below.

[1273] Step 1:

[1274] User: Launches the smartphone app and accesses the goal setting screen. Enters a specific goal, such as "I want to lose 3 kg in one month."

[1275] Step 2:

[1276] Terminal: Obtains user input, organizes goal data, and sends a goal setting request to the server.

[1277] Step 3:

[1278] Server: Stores the received goal data in a database and associates it with the user's profile.

[1279] Step 4:

[1280] Server: Using the generative AI model, the server generates advice based on the user's goal data. For example, it creates specific advice such as "walk 30 minutes every day."

[1281] Step 5:

[1282] Terminal: Notifies the user of the generated advice and displays a notification screen so that the user can check the advice.

[1283] Step 6:

[1284] User: Enters daily progress data. For example, enters "today's meal contents" and "exercise contents" into the device.

[1285] Step 7:

[1286] Terminal: Organizes the data entered by the user and sends it to the server as progress data. Displays a screen to provide feedback on the progress status to the user.

[1287] Step 8:

[1288] Server: Stores the received progress data in a database. Based on the stored data, new advice is generated from the generative AI model.

[1289] Step 9:

[1290] Server: In addition to the process of collecting progress data, it also runs an emotion engine to recognize the user's emotional state, for example, by analyzing text, voice, and facial expression data to evaluate the user's emotions.

[1291] Step 10:

[1292] Terminal: Receives emotional data from the emotion engine and provides feedback to the user. For example, if motivation is low, a message such as "Why don't you take a break today?" will be displayed.

[1293] Step 11:

[1294] Server: Based on the emotion data, if it is necessary to calculate additional points to increase the user's motivation, the server calculates and awards the points. For example, it awards additional points to a user whose progress is slow despite their efforts.

[1295] Step 12:

[1296] Terminal: Presents the user with the points awarded and a list of available rewards. Provides a screen where the user can select a reward.

[1297] Step 13:

[1298] User: Selects the desired reward from the displayed list of rewards and enters the selection into the terminal.

[1299] Step 14:

[1300] Server: Receives the user's selection, deducts points, performs processing related to the reward to be provided, and sends a confirmation message to the terminal after processing is complete.

[1301] In this way, users receive multi-layered support to achieve their goals, while being able to manage their progress and stay motivated with emotional feedback and additional incentives.The generative AI model and emotion engine work together to enhance the overall user experience.

[1302] Example 2

[1303] 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."

[1304] Conventional progress management systems have a single approach to helping users achieve their set goals, and lack diverse feedback and mechanisms for maintaining motivation. As a result, users tend to give up easily before achieving their goals, making it difficult to maintain long-term motivation. Furthermore, because support and feedback do not take into account the emotional state of each individual user, they are unable to effectively support users' efforts. To solve these issues, there is a need for the development of a system that provides multi-layered, personalized support.

[1305] 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.

[1306] In this invention, the server includes a means for allowing the user to set goals, a means for providing appropriate advice based on the user profile and goal data using a generative AI model, a means for recording and managing daily progress data, a means for calculating points based on the user's progress data and emotional data and awarding rewards according to the degree of goal achievement, and a means for acquiring the user's emotional data using an emotion engine and generating messages according to the user's state. This enables multi-layered and personalized support for each user, effectively helping users maintain their motivation and achieve their goals.

[1307] "User" refers to an individual or organization that uses the system to set goals, track progress, and earn rewards.

[1308] A "generative AI model" refers to an artificial intelligence system that generates natural language and analyzes data based on input data, and provides appropriate advice and feedback to users.

[1309] "User Profile" means a data set in a database that contains personal information, goals, progress data, etc. related to a User.

[1310] "Goal Data" means data containing information about specific goals that a User seeks to achieve.

[1311] "Progress data" refers to data that records the user's daily actions and results as they work toward their goals.

[1312] "Emotional Data" refers to data that indicates the user's emotional state as analyzed by the emotion engine.

[1313] An "emotion engine" refers to a system that analyzes user input data and behavioral data to recognize the user's emotional state.

[1314] "Points" refer to numerical data used to award rewards calculated based on the user's progress and emotional data.

[1315] "Rewards" refers to incentives such as goods or services given to users when they achieve their goals.

[1316] "Messages" refer to text or notifications generated by the emotion engine that contain encouragement or advice based on the user's state.

[1317] "Database" refers to an information system for storing and managing user profile data, goal data, progress data, emotional data, etc.

[1318] "Advice" refers to specific instructions or recommended actions provided to users by a generative AI model to achieve a goal.

[1319] This invention is a system that combines a generative AI model and an emotion engine to manage progress and provide rewards according to the degree of achievement in order to help users achieve their set goals. This system can maintain the user's motivation and support them in achieving their goals.

[1320] goal setting

[1321] First, a user accesses the application using a device such as a smartphone. They input a specific goal into the application, such as "I want to lose 3 kg in one month." The device acquires the user's input and organizes this data for transmission to the server. It then sends a goal-setting request to the server according to a communications protocol. The server stores the received goal data in a database and associates it with the user's profile, ensuring that the user's goals are recorded reliably.

[1322] Providing advice through generative AI models

[1323] The server calls a generative AI model based on the user's goal data and profile data. Examples of such generative AI models include OpenAI's GPT. The AI ​​model generates appropriate advice for achieving the goal. For example, advice such as "walk 30 minutes every day" or "eat a low-sugar diet" may be used. The device notifies the user of the generated advice, which the user can then review and incorporate into their daily life.

[1324] Daily progress management

[1325] Users input their daily diet and exercise data into the device. For example, they input specific data such as "I ate salad for lunch" or "I walked for 30 minutes." The device organizes this input data and sends it to the server. Progress checks and feedback are also performed on the device. The server stores the received data in a database and manages the user's progress. Based on the new progress data, the generative AI model generates new advice and notifies the device.

[1326] Use of emotion engine

[1327] The server uses an emotion engine to obtain emotional data from the user's progress data and input data. An example of this emotion engine is the IBM Watson Tone Analyzer. For example, it analyzes the user's written text, facial expressions, and voice data to recognize emotional states such as "decreasing motivation" or "increasing stress." Based on the emotional data, the device displays advice and encouraging messages appropriate to the user's condition. For example, it may display a message such as "You look like you're doing well today, keep up the good work."

[1328] Points Management and Rewards

[1329] The server calculates points based on the user's progress data and emotional data and sets rewards. For example, it awards additional points when goal achievement is high or motivation is low. The device displays the awarded points and a list of available rewards to the user. It provides a screen for the user to select a reward. The user selects the desired reward from the displayed reward list and inputs the selection into the device. The server receives the user's selection, deducts points, performs processing to provide the reward, and then sends a confirmation message to the device.

[1330] Prompt Sentence Examples

[1331] 1. Goal Setting:

[1332] "Set a new goal. For example, lose 3 kilos in one month."

[1333] 2. Progress Input:

[1334] "Please enter your diet and exercise data for today."

[1335] 3. Providing advice:

[1336] "Shows advice generated by AI models"

[1337] 4. Emotion data input:

[1338] "Please enter your current emotional state."

[1339] 5. Reward Selection:

[1340] "Select your desired reward from the list of available rewards"

[1341] The system allows users to receive planned and specific support to achieve their goals, and by combining a generative AI model with an emotion engine, it is possible to provide advice and feedback that is optimized for each individual user.

[1342] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1343] Step 1:

[1344] The user sets a goal. Specifically, they launch the smartphone application and input a specific goal, such as "I want to lose 3 kg in one month." The input is the user's goal information, and the output is a goal setting request.

[1345] Step 2:

[1346] The device organizes the user's input. For example, it converts a user's input goal, such as "I want to lose 3 kg in one month," into a format to be sent to the server. The input is a goal setting request, and the output is the goal information converted into a data format to be sent to the server.

[1347] Step 3:

[1348] The server receives the target data and stores it in a database, for example, by associating it with a user profile database. The input is the target information sent from the terminal, and the output is the target data stored in the database.

[1349] Step 4:

[1350] The server invokes a generative AI model based on the received goal data and user profile data. For example, it uses OpenAI's GPT to send prompts and generate advice. The input is the goal data and profile data, and the output is the generated advice.

[1351] Step 5:

[1352] The device receives the advice generated by the server and notifies the user. For example, it may notify the user of advice such as "walk 30 minutes every day" or "eat a low-sugar diet." The input is the generated advice, and the output is the notification to the user.

[1353] Step 6:

[1354] The user inputs daily diet and exercise data into the device. For example, they input progress data such as "I ate salad for lunch" or "I walked for 30 minutes." The input is specific diet and exercise data, and the output is progress data.

[1355] Step 7:

[1356] The device organizes the progress data and sends it to the server. For example, it converts information entered by the user, such as "I ate salad for lunch," into a data format for transmission. The input is the progress data, and the output is the data to be sent to the server.

[1357] Step 8:

[1358] The server stores the received progress data in a database and manages the progress. For example, it stores the data in association with the user's profile. The input is the progress data in the transmission data format, and the output is the progress data stored in the database.

[1359] Step 9:

[1360] The server requests the generative AI model to generate new advice based on the new progress data. For example, it generates additional advice such as "walk 30 minutes a day and incorporate stretching into your daily routine." The input is the new progress data, and the output is the new advice.

[1361] Step 10:

[1362] The terminal notifies the user of newly generated advice. The input is the new advice, and the output is the notification to the user.

[1363] Step 11:

[1364] The server uses an emotion engine to obtain emotion data from the progress data and input data. For example, it uses "IBM Watson Tone Analyzer" to analyze the user's writing and recognize that "motivation is declining." The inputs are progress data and input data, and the output is emotion data.

[1365] Step 12:

[1366] The server generates an appropriate message based on the emotion data and sends it to the device. For example, it generates an encouraging message such as, "You look good today, keep up the good work." The input is the emotion data, and the output is the generated message.

[1367] Step 13:

[1368] The terminal notifies the user of the generated message. The input is the generated message, and the output is the notification to the user.

[1369] Step 14:

[1370] The server calculates points based on the progress data and emotion data and sets rewards. For example, it gives additional points when a specific goal is achieved. The input is the progress data and emotion data, and the output is the calculated points and a list of rewards.

[1371] Step 15:

[1372] The terminal displays the awarded points and the list of available rewards to the user. The input is the reward list, and the output is the display to the user.

[1373] Step 16:

[1374] The user selects the desired reward from the displayed reward list and inputs the selection into the terminal. The input is the user's reward selection, and the output is the selection data.

[1375] Step 17:

[1376] The terminal sends the user's selection to the server. The input is the selection data, and the output is the data to be sent to the server.

[1377] Step 18:

[1378] The server receives the user's selection, deducts points, and executes a process to provide a reward. For example, a procedure may be performed to provide the user with a 500 yen Amazon gift card after deducting points. The input is the selection data and current points, and the output is the updated points balance and confirmation of the reward.

[1379] Step 19:

[1380] The server sends the reward provision confirmation data to the terminal. The input is the reward provision confirmation data, and the output is the data sent to the terminal.

[1381] Step 20:

[1382] The terminal notifies the user of a message confirming the provision of the reward. The input is the confirmation data for the provision of the reward, and the output is a notification to the user.

[1383] (Application example 2)

[1384] 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."

[1385] Conventional goal management systems do not take into account the user's emotions or motivation when managing the user's progress or providing advice, which makes it difficult to maintain motivation to achieve goals. Furthermore, the reward system based on the degree of goal achievement is monotonous, leaving room for improvement in user satisfaction.

[1386] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for the user to set a goal, a means for providing the user with appropriate advice using a generative AI model, a means for recording and managing daily progress data, a means for rewarding the user according to the degree of goal achievement, a means for analyzing the user's emotional state using an emotion engine and providing feedback, and a means for providing cashback or points based on the user's progress and emotional state. This makes it possible to effectively support goal achievement while taking into account the user's emotions and motivation, and to improve user satisfaction through the reward system.

[1387] A "user" is an individual or organization that uses the system to set goals and take action to achieve those goals.

[1388] A "goal" is a specific result or state that a user aims to achieve.

[1389] A "generative AI model" is a system or algorithm that uses artificial intelligence to generate appropriate advice and support to help users achieve their goals.

[1390] "Advice" is information that contains specific instructions, suggestions, or recommendations for achieving a user's set goals.

[1391] "Progress Data" means information that records the activities and actions taken by a user toward achieving a goal and the results of those activities and actions.

[1392] "Rewards" refers to incentives and benefits given to users when they achieve their goals, including cashback and points.

[1393] An "emotion engine" is a system or algorithm that analyzes data such as a user's writing, facial expressions, and voice to recognize the user's emotional state.

[1394] "Feedback" refers to information or messages provided to the user by the system, and contains appropriate content depending on the user's emotional state.

[1395] "Cashback" is a form of reward in which a user receives a refund or rebate when they achieve a goal, depending on the degree of achievement.

[1396] "Points" are numerical rewards given to users for achieving goals or other activities, and once a certain number of points have been accumulated, they can be exchanged for rewards or incentives.

[1397] A system for implementing this invention includes a means for a user to set a goal, a means for providing appropriate advice to the user using a generative AI model, a means for recording and managing daily progress data, a means for rewarding the user according to the degree of goal achievement, a means for analyzing the user's emotional state using an emotion engine and providing feedback, and a means for providing cashback or points based on the user's progress and emotional state.

[1398] 1. User goal setting

[1399] Users access the application using a smartphone or other device and input specific goals, such as "keep monthly credit card spending under 50,000 yen."

[1400] The terminal acquires the goal content input by the user and organizes this data for transmission to the server, and sends a goal setting request to the server according to a communication protocol.

[1401] The server stores the received goal data in a database and associates it with the user's profile, ensuring that the user's goals are recorded.

[1402] 2. Providing advice using generative AI models

[1403] The server calls up a generative AI model based on the user's goal and profile data, and generates appropriate advice for achieving the goal. For example, "cook more meals at home to reduce monthly food costs" or "create a wish list to avoid waste."

[1404] The device will notify the user of the generated advice, which the user can then review and incorporate into their daily lives.

[1405] 3. Use of Emotion Engine

[1406] The server uses an emotion engine to extract emotional data from user input data. For example, it analyzes positive comments such as "I've been having fun saving money this month" and negative comments such as "It was difficult to save money today" to recognize the user's emotional state.

[1407] Based on the recognized emotional data, the device displays advice and encouraging messages according to the user's state, such as "You're feeling good today, keep up the good work," or "You seem a little tired, it's important to take a break."

[1408] 4. Daily progress management and reward provision

[1409] Users input their daily spending data on the device, such as "Today's food expenses were 1,200 yen" or "I spent 5,000 yen on home appliances."

[1410] The device organizes this input data and sends it to the server, where progress confirmation and feedback are also provided.

[1411] The server stores the received data in a database and manages the user's progress. Based on the new progress data, the generative AI model generates new advice and notifies the device. In addition, cashback and points are provided depending on the degree of goal achievement.

[1412] Examples of concrete examples and prompts

[1413] For example, if a user sets a goal of "keeping monthly expenses under 50,000 yen," the prompt to the generative AI model would look like this:

[1414] Please advise how a user can reduce their monthly expenses to 50,000 yen. Current expenses: 45,000 yen.

[1415] In this way, users receive comprehensive support that effectively assists them in achieving their goals, while also receiving feedback and rewards based on their emotional state. By working together, the generative AI model and emotion engine can more effectively support users in their efforts.

[1416] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1417] Step 1:

[1418] Users access the application using a device such as a smartphone and set specific goals. For example, they might enter, "Keep monthly credit card spending under 50,000 yen." The device receives this input, organizes the data, and sends it to the server. The server then receives it, stores it in a database, and associates it with the user profile. The input is goal setting data, and the output is a database entry of the goal data.

[1419] Step 2:

[1420] The server obtains the goal data and user profile data, and sends a prompt to the generative AI model to generate advice for achieving the goal. The specific prompt used is, "Please advise how the user can keep their monthly expenses to 50,000 yen. Current expenses: 45,000 yen." The input is the user data and the prompt, and the output is the generated advice.

[1421] Step 3:

[1422] The device receives the advice of the generative AI model sent from the server and notifies the user. The user can check this notification and incorporate it into their daily life. In this step, feedback is provided by the advice being delivered to the user. The input is the advice data from the server, and the output is a notification to the user.

[1423] Step 4:

[1424] The user inputs details of their daily spending into the device. For example, "Today's food expenses were 1,200 yen" or "I spent 5,000 yen on home appliances." The device organizes this detailed data and sends it to the server. The input is daily spending data, and the output is the transmission of progress data to the server.

[1425] Step 5:

[1426] The server receives daily spending data, stores it in a database, and manages the user's progress. Based on this progress data, it invokes a new generative AI model, generates new advice, and notifies the device. It also manages the allocation of cashback and points according to the degree of goal achievement. The input is daily spending data, and the output is the generation of new advice and reward data.

[1427] Step 6:

[1428] The server uses an emotion engine to analyze emotion data from the user's input data. For example, it analyzes positive emotion from the user's input "I'm having fun saving money this month" and generates an encouraging message such as "You're doing well today, keep up the good work." The input is the user's input data, and the output is the analyzed emotion data and an encouraging message.

[1429] Step 7:

[1430] The device notifies the user of messages generated by the emotion engine. The messages are based on the user's emotional state and play an important role in maintaining motivation. The input is emotional data and messages, and the output is notifications to the user.

[1431] In this way, at each step, data is processed and calculated based on the input data, and the output is used in the next step. This realizes a system that helps users achieve their goals and provides appropriate rewards and feedback.

[1432] 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.

[1433] 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.

[1434] 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 robot 414.

[1435] 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.

[1436] 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.

[1437] 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.

[1438] 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).

[1439] 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.

[1440] 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."

[1441] 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.

[1442] 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).

[1443] 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.

[1444] 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.

[1445] 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.

[1446] 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.

[1447] 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.

[1448] 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.

[1449] 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.

[1450] 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.

[1451] 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.

[1452] 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.

[1453] The following is further disclosed regarding the above embodiment.

[1454] (Claim 1)

[1455] a means for users to set goals;

[1456] A means of providing appropriate advice to users using generative AI models; and

[1457] A means of recording and managing daily progress data;

[1458] a means for rewarding users based on goal achievement;

[1459] A system including:

[1460] (Claim 2)

[1461] 10. The system of claim 1, further comprising means for organizing user input and transmitting it to the server.

[1462] (Claim 3)

[1463] 10. The system of claim 1 further comprising means for storing the goal setting data in a database and associating it with the user's profile.

[1464] "Example 1"

[1465] (Claim 1)

[1466] a means for users to set goals;

[1467] A means of providing appropriate advice to users using generative AI models; and

[1468] A means of recording and managing daily progress data;

[1469] a means for rewarding users based on goal achievement;

[1470] A means for invoking a generative AI model based on the user's goal data and profile data to generate advice;

[1471] A means for receiving the user's progress data and calling the generative AI model again to generate new advice;

[1472] A system including:

[1473] (Claim 2)

[1474] 10. The system of claim 1, wherein the system organizes and transmits user input to a server.

[1475] (Claim 3)

[1476] 10. The system of claim 1, wherein the goal setting data is stored in a database and associated with the user's profile.

[1477] "Application Example 1"

[1478] (Claim 1)

[1479] a means for users to set goals;

[1480] A means of providing appropriate advice to users using generative AI models; and

[1481] A means of recording and managing daily progress data;

[1482] a means for rewarding users based on goal achievement;

[1483] A means for the generative AI model to recommend appropriate meal plans based on the user's health goals; and

[1484] a means of awarding points based on healthy choices made by users in their orders;

[1485] A system including:

[1486] (Claim 2)

[1487] 10. The system of claim 1 further comprising means for organizing user input and transmitting it to the server.

[1488] (Claim 3)

[1489] 10. The system of claim 1, further comprising means for storing the goal setting data in a database and associating it with the user's profile.

[1490] "Example 2: Combining Emotion Engines"

[1491] (Claim 1)

[1492] a means for users to set goals;

[1493] a means for providing appropriate advice based on user profile and goal data using a generative AI model;

[1494] A means of recording and managing daily progress data;

[1495] A method to calculate points based on the user's progress and emotional data and award rewards according to the degree of goal achievement.

[1496] A means for acquiring user emotion data using an emotion engine and generating a message according to the user's state;

[1497] A system including:

[1498] (Claim 2)

[1499] a means for organizing user input and sending it to the server;

[1500] 10. The system of claim 1.

[1501] (Claim 3)

[1502] a means for storing goal setting data in a database and associating it with the user's profile;

[1503] 10. The system of claim 1.

[1504] "Application example 2 when combining emotion engines"

[1505] (Claim 1)

[1506] a means for users to set goals;

[1507] A means of providing appropriate advice to users using generative AI models; and

[1508] A means of recording and managing daily progress data;

[1509] a means for rewarding users based on goal achievement;

[1510] a means for analyzing the user's emotional state using an emotion engine and providing feedback;

[1511] A means to offer cashback or points based on the user's progress and emotional state;

[1512] A system including:

[1513] (Claim 2)

[1514] a means for organizing user input and sending it to the server;

[1515] a means for sending prompts to the generative AI model to generate advice;

[1516] 2. The system of claim 1.

[1517] (Claim 3)

[1518] a means for storing goal setting data in a database and associating it with the user's profile;

[1519] a means for recording and managing the user's emotional state;

[1520] 2. The system of claim 1. [Explanation of symbols]

[1521] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for users to set goals; A means of providing appropriate advice to users using generative AI models; and A means of recording and managing daily progress data; a means for rewarding users based on goal achievement; A system including:

2. 10. The system of claim 1, further comprising means for organizing and transmitting user input to a server.

3. 10. The system of claim 1, further comprising means for storing goal setting data in a database and associating it with a user profile.

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