System

Abstract

A system is provided.SOLUTION: A system comprising input means for a user to set new habits and make deposits, means for storing data received by a server in a database, means for tracking habits progress of a user, means for AI analyzing progress data and evaluating a degree of achievement of habits, means for calculating a reward amount based on an evaluation result, and means for executing cash back to a bank account of a user.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] Many people want to develop new habits, but struggle to maintain the motivation to continue. Habit formation often fails, especially when there is no immediate, attractive reward. This invention aims to support the habit formation process by providing users with financial incentives to make it fun and easy to continue a new habit. [Means for solving the problem]

[0005] The present invention provides a system that includes an input means for users to set new habits and make deposits, a server means for storing the received data in a database, a means for tracking the user's habit progress, an AI means for analyzing the progress data and evaluating the degree of habit achievement, a means for calculating a reward amount based on the evaluation results, and a means for providing cashback to the user's bank account. This system allows users to earn rewards while continuing their new habits in an enjoyable way. The system also includes a means for the AI ​​to adjust the optimal reward amount based on the user's behavioral patterns and a means for providing an interface for users to input their progress.

[0006] "User" refers to an individual who uses the System to set new habits and track their progress.

[0007] A "habit" is a behavior or activity that a user sets up to continue.

[0008] A "deposit" is money that users deposit in advance to receive rewards based on completing habits.

[0009] "Input method" refers to the interface through which the user sets up a new habit or enters the amount of the deposit.

[0010] A "server" is a computer system that receives, stores, and processes data submitted by users.

[0011] "Database" means a repository of information managed by a server that stores user habits and progress information.

[0012] "Tracking Facility" means a facility that provides functionality for monitoring and recording a user's habit progress.

[0013] "AI" stands for artificial intelligence, a program or system that analyzes tracking data and evaluates habit completion.

[0014] "Evaluation means" refers to a means that provides a function for determining a user's level of achievement based on data analyzed by AI.

[0015] "Reward amount" refers to the amount of monetary incentive provided based on the user's habit completion.

[0016] "Cashback" refers to the amount of money that is refunded from the deposit when the user completes the habits they have set.

[0017] "Bank Account" means the account at a User's financial institution to which Cash Back will be transferred.

[0018] An "interface" is an operating screen or mechanism that allows a user to input information into or receive information from a system. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

[0027] [First embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0040] This invention is a system that provides financial incentives to help users enjoyably continue new habits and supports the habit-forming process. This system tracks the habits set by the user and their progress in achieving them, and provides monetary rewards according to the degree of progress. The program and specific processing of this system are described in detail below.

[0041] Program processing explanation

[0042] User registration and login

[0043] On the device: The user installs and launches the app, clicks the "Sign Up" button on the screen, and enters their email address and password.

[0044] Server: The server receives the input data, stores it in the database, and returns a success message to the terminal if the registration is successful.

[0045] Device: The user enters the registered email address and password on the login screen and clicks the login button. The server authenticates the entered information, and if authentication is successful, generates a token and sends it to the device.

[0046] Terminal: Receives the token, moves to the dashboard screen, and the user can use the system.

[0047] Habit Setting and Deposits

[0048] On the device: The user opens the "Set up a new habit" screen and enters the habit. For example, they might enter "30 minutes of exercise every day." Then they enter the amount they want to deposit. For example, they enter "10,000 yen."

[0049] Server: The server receives the entered habits and deposit information, stores it in the database, and returns a success message to the terminal.

[0050] Terminal: Prompts the user that their habits and deposits have been set up.

[0051] Habit Tracking

[0052] On the device: To record their daily progress, users open the "Progress Input" screen in the app. For example, they enter "30 minutes of exercise today" and submit.

[0053] Server: The server receives the progress data and sends it to the AI ​​model.

[0054] AI model: The AI ​​model analyzes the progress data and evaluates the habit achievement, for example, rating it as "progressing as expected."

[0055] Server: The server stores the evaluation results in a database and sends the results to the device.

[0056] On your device: Notify users that their habit has been assessed and display their progress.

[0057] Reward System

[0058] AI model: The AI ​​model calculates the reward amount based on the habit achievement level. For example, it determines "50% achievement means 100 yen per day."

[0059] Server: The server receives the reward calculation results and executes cashback to the user's bank account.

[0060] On the device: Display a cashback notification to the user. For example, display a notification such as "You've received a cashback of 100 yen for achieving your exercise goal today."

[0061] Specific examples

[0062] Case 1: When you set a new habit "exercise 30 minutes a day" and set a deposit of 10,000 yen

[0063] 1. User Registration and Login

[0064] Device: David launches the app and enters the required information to create a new account.

[0065] Server: The server receives the input information, stores it in a database, and returns a success message.

[0066] Device: Yamada enters her email address and password on the login screen and obtains an authentication token.

[0067] 2. Habit setting and deposits

[0068] Device: Yamada sets "30 minutes of exercise every day" and deposits 10,000 yen.

[0069] Server: The server receives and stores this information and returns a completion message.

[0070] 3. Habit Tracking

[0071] Device: Yamada enters today's exercise time as "30 minutes" and submits.

[0072] Server: The server receives the progress data and has the AI ​​model evaluate it.

[0073] AI model: The AI ​​model evaluates the results as "Progressing as expected" and saves them.

[0074] Server: The server notifies Yamada's device of the evaluation results.

[0075] 4. Reward System

[0076] AI model: The AI ​​model decides to give a cashback of 100 yen as a reward for one day.

[0077] Server: The server calls the cashback API and transfers 100 yen to Yamada's bank account.

[0078] Device: Notify "You've received a cashback of 100 yen for achieving your exercise goal today."

[0079] Through this specific process, users can develop new habits in a fun and efficient way.

[0080] The processing flow will be explained below.

[0081] Program processing details

[0082] User registration and login

[0083] Step 1:

[0084] On the device: The user installs and launches the app. They click the "Sign up" button.

[0085] Step 2:

[0086] Device: The user enters their email address and password and clicks the "Register" button.

[0087] Step 3:

[0088] Server: Receives input data and saves it in the database. If registration is successful, returns a success message to the device.

[0089] Step 4:

[0090] On the device: The user enters their email address and password on the login screen and clicks the "Login" button.

[0091] Step 5:

[0092] Server: Authenticates the input information, and if successful, generates an authentication token and sends it to the device.

[0093] Step 6:

[0094] Terminal: Receive the token and proceed to the dashboard screen.

[0095] Habit Setting and Deposits

[0096] Step 1:

[0097] On the device: The user opens the "Set up a new habit" screen and enters "30 minutes of exercise daily." They then click the Next button.

[0098] Step 2:

[0099] Terminal: The user enters the amount to deposit (10,000 yen). Then clicks the Complete button.

[0100] Step 3:

[0101] Server: Receives the habit and deposit information, stores it in the database, and returns a success message to the terminal.

[0102] Step 4:

[0103] Terminal: Prompts the user that their habits and deposit setup is complete.

[0104] Habit Tracking

[0105] Step 1:

[0106] Device: The user opens the "Enter Progress" screen, enters today's exercise time as "30 minutes," and clicks the submit button.

[0107] Step 2:

[0108] Server: Receives progress data and stores it in a database.

[0109] Step 3:

[0110] Server: Sends saved progress data to the AI ​​model.

[0111] Step 4:

[0112] AI model: Analyzes the received data and evaluates it as "progressing as expected."

[0113] Step 5:

[0114] AI model: Sends the evaluation results to the server.

[0115] Step 6:

[0116] Server: Saves the evaluation results in a database and notifies the terminal of the evaluation results.

[0117] Step 7:

[0118] Device: Shows the user today's progress and assessment results.

[0119] Reward System

[0120] Step 1:

[0121] AI model: Calculates reward amount based on habit achievement. For example, "For 50% achievement, a cashback of 100 yen will be given."

[0122] Step 2:

[0123] AI model: Sends the calculation results to the server.

[0124] Step 3:

[0125] Server: Stores the reward amount in the database.

[0126] Step 4:

[0127] Server: Calls the API to execute the cashback and transfers the money to the user's bank account.

[0128] Step 5:

[0129] On the device: Display a cashback notification to the user, for example, "You've received a cashback of 100 yen for achieving your exercise goal today."

[0130] Specific examples

[0131] Case 1: When you set a new habit "exercise 30 minutes a day" and set a deposit of 10,000 yen

[0132] 1. User Registration and Login

[0133] Step 1: Yamada launches the app and clicks "New Registration."

[0134] Step 2: Sam enters her email address and password and clicks "Register."

[0135] Step 3: The server saves the data and returns a success message.

[0136] Step 4: On the login screen, Yamada enters her email address and password and clicks "Login."

[0137] Step 5: The server generates an authentication token and sends it to the device.

[0138] Step 6: Yamada's device receives the token and is redirected to the dashboard.

[0139] 2. Habit setting and deposits

[0140] Step 1: Yamada enters "30 minutes of exercise every day" in "Set a new habit" and clicks "Next."

[0141] Step 2: Enter the deposit amount "10,000 yen" and click "Complete".

[0142] Step 3: The server saves the information and returns a completion message.

[0143] Step 4: Yamada's device will display a message that the setup is complete.

[0144] 3. Habit Tracking

[0145] Step 1: Yamada enters "30 minutes of exercise" in "Enter progress" and submits it.

[0146] Step 2: The server stores the data and sends it to the AI ​​model.

[0147] Step 3: The AI ​​model analyzes the progress and sends the evaluation results to the server.

[0148] Step 4: The server notifies Yamada's device of the evaluation results.

[0149] Step 5: Yamada's device displays the progress and evaluation results.

[0150] 4. Reward System

[0151] Step 1: The AI ​​model determines the cashback of 100 yen based on the achievement level.

[0152] Step 2: The server stores the reward amount in the database.

[0153] Step 3: Call the cashback API and transfer 100 yen to Yamada's bank account.

[0154] Step 4: Yamada's device will notify him that the cashback has been completed.

[0155] This specific processing step allows users to enjoyably pursue new habits while earning financial rewards.

[0156] Example 1

[0157] 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."

[0158] In modern society, it is difficult for users to form and maintain new habits. Effective methods for maintaining sustained motivation are scarce, and methods for utilizing economic incentives are limited. Furthermore, current systems lack mechanisms for tracking user progress and providing rewards based on that progress, making it difficult to maintain motivation for habit formation.

[0159] 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.

[0160] In this invention, the server includes an input means for a user to set a new habit and make a deposit, a means for the server to store the received data in a database, a means for tracking the user's habit progress, a means for an AI to analyze the progress data and evaluate the degree of habit achievement, a means for calculating a reward amount based on the evaluation result, a means for executing cashback to the user's financial institution account, and an authentication means for enabling the user to log in and use the system using a token. This allows the user to continue a new habit in a fun way and form a habit while receiving economic incentives.

[0161] "Input" is the interface on the system through which users can set new habits and make deposits.

[0162] A "database" is an information management system that stores and manages data received by a server.

[0163] "Tracking Tools" are features that allow users to monitor and record their habit progress.

[0164] The "AI model" is an artificial intelligence model that analyzes progress data and evaluates the user's level of habit achievement.

[0165] The "evaluation method" is a function for determining the degree of habit achievement based on the results of analysis by the AI ​​model.

[0166] The "remuneration calculation means" is a function for calculating the amount of remuneration to be provided to the user based on the evaluation results.

[0167] "Cashback method" is a system function that actually transfers rewards to the user's financial institution account.

[0168] "Authentication means" is a security feature that allows users to log in using a token and access the system.

[0169] The present invention is a system that provides economic incentives to users to help them continue new habits in a fun way and supports the habit formation process. The system receives user input, manages and analyzes data using a server and an AI model, evaluates the user's habit achievement, and provides rewards. Details of the system's program and the specific form of its processing are described below.

[0170] Handling user registration and login

[0171] Terminal: The user installs and launches the application. They click the "New Registration" button on the screen and enter their email address and password. This input method allows the user to create a new account within the system. For example, they enter the email address "example@example.com" and the password "password123."

[0172] Server: The server receives the entered data and stores it in the database. It executes the query "INSERT INTO users (email, password) VALUES ('example@example.com', 'password123');" and returns a success message to the terminal if registration is successful.

[0173] Terminal: The user enters the registered email address and password on the login screen and clicks the login button. The server authenticates the entered information, and if authentication is successful, generates a token and sends it to the terminal. The terminal receives this token, transitions to the dashboard screen, and the user can use the system.

[0174] Setting habits and processing deposits

[0175] On the device: The user opens the "Set up a new habit" screen and enters the habit. For example, they might enter "30 minutes of exercise every day," then enter the amount they want to deposit. For the deposit amount, they enter "10,000 yen."

[0176] Server: The server receives the entered habit and deposit information and stores it in the database. It executes the query "INSERT INTO habits (user_id, habit_detail, deposit_amount) VALUES (1, '30 minutes of exercise daily', 10000);" and returns a success message.

[0177] Terminal: Prompts the user that their habits and deposits have been set up.

[0178] Handling habit completion tracking

[0179] On the device: To record their daily progress, users open the "Progress Input" screen in the app. For example, they enter "30 minutes of exercise today" and submit.

[0180] Server: The server receives the progress data and sends it to the AI ​​model through the endpoint " / api / v1 / progress / evaluate".

[0181] AI model: The AI ​​model analyzes the progress data and evaluates the habit achievement level. For example, it evaluates the habit achievement level as "80%" based on the progress data.

[0182] Server: Save the evaluation results in the database and use the query "UPDATE progress SET evaluation = 'Habit achievement level 80%' WHERE user_id = 1;". The evaluation results are notified to the device.

[0183] On your device: Notify users that their habit has been assessed and display their progress.

[0184] Reward system processing

[0185] AI model: The AI ​​model calculates the reward amount based on the habit completion rate. For example, it determines "80 yen as the daily reward."

[0186] Server: Receives the reward calculation result and executes cashback to the user's financial institution account using the endpoint " / api / v1 / banking / cashback".

[0187] On the device: Notify the user that the cashback has been applied. For example, display a notification such as "You've received a cashback of 80 yen for achieving your exercise goal today."

[0188] Examples of concrete examples and prompts

[0189] To generate a prompt, enter the following:

[0190] Set a new habit of "30 minutes of exercise every day" and set a deposit of 10,000 yen. Then, record "30 minutes of exercise today" on the progress entry screen in the app, and explain how your habit achievement will be evaluated and how you will be rewarded.

[0191] Based on these prompts, the AI ​​model generates concrete examples to help users maintain their new habits in a fun and efficient way. The system is designed to encourage users to proactively establish new habits and achieve their goals while enjoying financial incentives.

[0192] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0193] Step 1: User Registration and Login

[0194] user:

[0195] Input: The user installs and launches the app, clicks the Sign Up button, and enters the email address "example@example.com" and the password "password123."

[0196] Specific operations: Enter the required information on the new registration screen and click the "Register" button.

[0197] Output: A success message is displayed.

[0198] server:

[0199] Input: The server receives the email address and password entered by the user.

[0200] Data processing: Execute the query "INSERT INTO users (email, password) VALUES ('example@example.com', 'password123');".

[0201] Output: The user information is saved to the database and a success message is returned.

[0202] user:

[0203] Input: On the login screen, enter the email address "example@example.com" and the password "password123".

[0204] Specific actions: Enter information on the login screen and click the Login button.

[0205] Output: Get the token.

[0206] server:

[0207] Input: The server receives the user's email address and password and performs authentication.

[0208] Data operation: Execute the query "SELECT FROM users WHERE email = 'example@example.com' AND password = 'password123';" and generate a token if authentication is successful.

[0209] Output: A token is generated and sent to the device.

[0210] Device:

[0211] Input: Receives a token.

[0212] Specific operation: Save the token and move to the dashboard screen.

[0213] Output: User can access the dashboard.

[0214] Step 2: Setting habits and depositing

[0215] user:

[0216] Input: On the "Set up a new habit" screen, enter the habit "30 minutes of exercise every day" and the deposit amount "10,000 yen."

[0217] Specific actions: Enter your habit and deposit information and click the "Save" button.

[0218] Output: A message will be displayed indicating that the setup is complete.

[0219] server:

[0220] Input: Receives the habits and deposit amount entered by the user.

[0221] Data processing: Run the query "INSERT INTO habits (user_id, habit_detail, deposit_amount) VALUES (1, '30 minutes of exercise daily', 10000);".

[0222] Output: Saves the information to the database and returns a success message.

[0223] Device:

[0224] Input: Receives a success message.

[0225] What it does: Prompts the user that their habits and deposits have been set up.

[0226] Output: A completion message is displayed on the screen.

[0227] Step 3: Track your habit completion

[0228] user:

[0229] Input: Open the progress input screen in the app, enter "Today's exercise time: 30 minutes" and submit.

[0230] Specific actions: Enter information on the progress input screen and click the submit button.

[0231] Output: Progress data is sent.

[0232] server:

[0233] Input: Receives the user's progress data.

[0234] Data processing: Call the endpoint " / api / v1 / progress / evaluate" to send progress data to the AI ​​model.

[0235] Output: Progress data sent to the AI ​​model.

[0236] AI model:

[0237] Input: Receives progress data.

[0238] Data calculation: Analyzes progress data and evaluates "Habit achievement rate 80%."

[0239] Output: Returns the evaluation result to the server.

[0240] server:

[0241] Input: Receives the evaluation results from the AI ​​model.

[0242] Data processing: Execute the query "UPDATE progress SET evaluation = 'Habit achievement level 80%' WHERE user_id = 1;" and save the evaluation results to the database.

[0243] Output: The evaluation results are saved and sent to the device.

[0244] Device:

[0245] Input: Receives notifications from the server.

[0246] What it does: Show the user a notification that says "Habit completion is 80%."

[0247] Output: Progress is displayed on the screen.

[0248] Step 4: Reward System

[0249] AI model:

[0250] Input: Receives the user's habit completion rate.

[0251] Data calculation: Calculate "daily reward of 80 yen" based on the achievement level.

[0252] Output: Returns the reward result to the server.

[0253] server:

[0254] Input: Receives the reward calculation results from the AI ​​model.

[0255] Data processing: Use the endpoint " / api / v1 / banking / cashback" to transfer 80 yen to the user's financial institution account.

[0256] Output: Notifies the terminal of the cashback execution result.

[0257] Device:

[0258] Enter: Receive cashback notifications.

[0259] Specific behavior: Notify the user that "You have received a cashback of 80 yen for achieving your exercise goal today."

[0260] Output: A cashback notification will appear on the screen.

[0261] (Application example 1)

[0262] 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."

[0263] Previous habit-forming systems lacked sufficient motivation to encourage users to continue newly established habits, making long-term habit formation particularly difficult. Furthermore, there was no system that accurately tracked users' progress or provided appropriate rewards. This made it difficult for users to continue the habit, often leading to abandonment. Furthermore, online education platforms and content distribution services lacked methods to encourage users to continue using the habit.

[0264] 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.

[0265] In this invention, the server includes an input means for a user to set a new habit and make a deposit, a means for the server to store the received data in a database, a means for tracking the user's habit progress, a means for an AI to analyze the progress data and evaluate the degree of habit achievement, a means for calculating a reward amount based on the evaluation result, a means for providing cashback to the user's financial account, an input means for setting a learning routine or a viewing routine as a habit set by the user, a means for the user to input or automatically track progress, and a means for notifying the user of progress and rewards. This allows users to form enjoyable and sustainable habits and encourages continued use of online education platforms and content distribution services.

[0266] A "user" is an individual who uses the system to set up new habits and track their progress.

[0267] A "habit" is an ongoing activity, such as a learning routine or viewing routine, that a user engages in regularly.

[0268] A "deposit" is an amount set by the user as an incentive to continue the habit.

[0269] "Progress" is data that shows the degree of achievement of the user's set habits.

[0270] "Tracking" refers to the system recording and monitoring the user's progress in achieving their habits.

[0271] A "server" is a computer system that receives and stores data sent by users and performs any necessary calculations or analyses.

[0272] "Database" means a digital storage system for storing user registration information, progress data, deposit information, reward information, etc.

[0273] "AI" refers to artificial intelligence that analyzes progress data, evaluates the degree of habit achievement, and calculates reward amounts.

[0274] "Rewards" are monetary incentives that users receive for completing their set habits.

[0275] "Cashback" refers to the actual amount of money transferred to a user's financial account based on the habits they achieve.

[0276] "Financial account" refers to a bank account, electronic money account, etc. that a user uses to receive cashback.

[0277] A "learning routine" refers to the regular execution of specific learning activities set by the user.

[0278] A "viewing routine" refers to the regular viewing of specific content set by a user.

[0279] The "input method" is the interface through which the user inputs new habits, deposit amounts, and progress.

[0280] "Notification" refers to the system sending messages to the user to inform them of progress, achievement of rewards, etc.

[0281] The present invention is a system involving three parties: a server, a terminal, and a user, and provides support for users to form new habits.

[0282] 1. Program Generation

[0283] The system consists of the following main components:

[0284] User device: a mobile device such as a smartphone or tablet.

[0285] Server: A computer system for processing and storing data.

[0286] AI model: An artificial intelligence program to assess habit completion.

[0287] 2. Natural language explanation

[0288] User registration and login

[0289] The terminal provides an interface where users can create a new account. The user enters their email address and password, which the server receives and stores in a database. Upon login, authenticated users are issued a token and taken to the dashboard screen.

[0290] Habit Setting and Deposits

[0291] The terminal presents a screen where the user can set up a new habit (e.g., 30 minutes of study per day or watching movies three times a week) and enter a deposit amount. The server stores this information in a database and returns a success message.

[0292] Habit Tracking

[0293] Users record their daily progress and send it from their device to the server. In some cases, progress data is tracked automatically. The server receives the progress data and sends it to the AI ​​model. The AI ​​model analyzes this data and evaluates the degree of habit achievement. The evaluation results are stored in a database and notified to the user.

[0294] Reward System

[0295] The AI ​​model calculates the reward amount based on the habit completion rate. The server receives the calculation result and issues a cashback to the user's financial account. The user can check their progress and reward achievement on their device.

[0296] 3. Hardware and Software Used

[0297] Smartphone app: Implemented using React Native and Flutter.

[0298] Server: Use Node.js or Django.

[0299] Database: Data is stored using PostgreSQL or MongoDB.

[0300] AI model: Use TensorFlow or PyTorch to assess habit completion.

[0301] Cashback API: Use Stripe or PayPal API to execute cashback.

[0302] Specific examples

[0303] Case 1: When you set a new habit of "studying English for 30 minutes every day" and set a deposit of 10,000 yen

[0304] 1. User Registration and Login

[0305] The device provides an interface for creating a new account, and the user enters the required information.

[0306] The server saves the input information in a database and returns a success message.

[0307] The terminal issues a token to the user and takes them to the dashboard screen.

[0308] 2. Habit setting and deposits

[0309] The device provides the user with a habit setting screen, where they input "30 minutes of English study every day" and "a deposit of 10,000 yen."

[0310] The server stores this information in a database and returns a success message.

[0311] 3. Habit Tracking

[0312] The terminal provides an interface for inputting the user's progress.

[0313] The server sends the received progress data to the AI ​​model and stores the evaluation results in a database.

[0314] The device notifies the user of the evaluation results.

[0315] 4. Reward System

[0316] The AI ​​model decides to set the daily reward at 100 yen.

[0317] The server calls the cashback API and transfers 100 yen to the user's financial account.

[0318] The device will notify you, "You have received a cash back of 100 yen for achieving today's learning goal."

[0319] Prompt Sentence Examples

[0320] Write a program that rewards users with 100 yen if they complete 30 minutes of English study every day.

[0321] This system allows users to form new habits in a fun and sustainable way, encouraging continued use of online education platforms and content delivery services.

[0322] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0323] Step 1:

[0324] User registration and login

[0325] Terminal: To create a new account, the user clicks the "Sign up" button on the screen and enters their email address and password. The entered data is sent to the server.

[0326] Server: Receives the input data, stores it in a database, verifies that the information entered is correct, and returns a success message if successful.

[0327] Output: A success message is printed to the terminal.

[0328] On the device: The user enters their email address and password on the login screen and sends them to the server, which authenticates the information and, if successful, generates a token and sends it to the device.

[0329] Input: User's email address and password

[0330] Output: Authentication token

[0331] Terminal: After receiving the authentication token, the user is taken to the dashboard screen and can use the system.

[0332] Step 2:

[0333] Habit Setting and Deposits

[0334] On the device: The user opens the "Set up a new habit" screen and enters the habit (e.g., study English for 30 minutes every day) and the deposit amount. The entered data is sent to the server.

[0335] Server: Receives the entered customs and deposit information, stores it in the database, and returns a success message.

[0336] Output: A success message is printed to the terminal.

[0337] Input: The new habit and deposit amount set by the user

[0338] Output: Success message

[0339] Step 3:

[0340] Habit Tracking

[0341] Device: To record daily progress, users open the "Progress Input" screen and enter the time spent studying and the content they have watched. The input data is sent to the server. In some cases, automatic tracking is also performed.

[0342] Input: User progress data (e.g., 30 minutes of study time)

[0343] Server: Receives progress data and sends it to the AI ​​model, which analyzes the data and evaluates the habit completion.

[0344] Output: Habit achievement evaluation results

[0345] AI model: Analyzes progress data and evaluates habit achievement, which is stored in a database.

[0346] Server: Stores the evaluation results in a database and sends the results to the device.

[0347] On device: Users will receive progress notifications and be able to track their progress.

[0348] Output: Habit completion assessment results sent to the user

[0349] Step 4:

[0350] Reward System

[0351] AI model: Calculates the reward amount based on the habit achievement level. For example, if the achievement level is 50%, set the daily reward to 100 yen.

[0352] Output: Reward amount

[0353] Server: Receives the reward amount and cashbacks the user's financial account. This is done using the Cashback API.

[0354] Input: Reward calculation result

[0355] Output: Cashback success / failure message

[0356] On your device: Display a cashback notification to the user. For example, "You've received a cashback of 100 yen for achieving today's learning goal."

[0357] Output: Cashback notification to be sent to the user

[0358] The system allows users to form new habits effectively and enjoyably, and keeps them motivated through rewards.

[0359] 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.

[0360] The present invention is a system designed to help users enjoy and continue new habits, and aims to increase motivation by taking into account the user's emotional state. This system tracks the habits set by the user and their progress, and provides monetary rewards based on the user's progress and emotional state. The program and specific processing of this system are described in detail below.

[0361] Program processing explanation

[0362] User registration and login

[0363] On the device: The user installs and launches the app, clicks the "Sign Up" button on the screen, and enters their email address and password.

[0364] Server: The server receives the input data and stores it in the database. If registration is successful, it returns a success message to the device.

[0365] Device: The user enters the registered email address and password on the login screen and clicks the login button. The server authenticates the entered information, and if authentication is successful, generates a token and sends it to the device.

[0366] Terminal: Receives the token, moves to the dashboard screen, and the user can use the system.

[0367] Habit Setting and Deposits

[0368] On the device: The user opens the "Set up a new habit" screen and enters the habit. For example, "30 minutes of exercise every day." Next, they enter the amount they want to deposit. For example, they enter "10,000 yen."

[0369] Server: The server receives the entered habits and deposit information, stores it in the database, and returns a success message to the terminal.

[0370] Terminal: Prompts the user that their habits and deposits have been set up.

[0371] Habit Tracking

[0372] On the device: To record their daily progress, users open the "Progress Input" screen in the app. For example, they enter "30 minutes of exercise today" and submit.

[0373] Server: The server receives the progress data and sends it to the AI ​​model.

[0374] AI model: The AI ​​model analyzes the progress data and evaluates the habit achievement, for example, rating it as "progressing as expected."

[0375] Server: The server stores the evaluation results in a database and sends the results to the device.

[0376] On your device: Notify users that their habit has been assessed and display their progress.

[0377] Reward System

[0378] AI model: The AI ​​model calculates the reward amount based on the habit achievement level. For example, it determines "50% achievement means 100 yen per day."

[0379] Server: The server receives the reward calculation results and executes cashback to the user's bank account.

[0380] On the device: Display a cashback notification to the user. For example, display a notification such as "You've received a cashback of 100 yen for achieving your exercise goal today."

[0381] Introducing the Emotion Engine

[0382] Recognition of emotional states

[0383] On the device: To record their emotional state, users can open the "Emotion Input" screen within the app and self-report their feelings. For example, they can enter "I'm happy today." Alternatively, the device can automatically recognize their emotional state from their facial expressions and voice.

[0384] Server: The server receives the emotion data and stores it in a database.

[0385] Emotional data analysis and reflection

[0386] AI model: Analyzes emotional data and evaluates how a user's emotional state affects habit completion.

[0387] Server: Adjusts reward amount and motivational message based on the evaluation results.

[0388] Device: Display an appropriate motivational message to the user, for example, "You're working especially hard today!"

[0389] Linking cashback and emotional states

[0390] AI model: Calculates the optimal reward amount based on emotional data and habit completion. For example, it determines that "the user's emotional state is high, so an additional 20 yen cashback will be given."

[0391] Server: Receives the reward calculation results and sends the cashback to the user's bank account.

[0392] Device: Display a cashback notification to the user along with a pleasurable message based on their emotional state. For example, "You've received a cashback of 120 yen because you achieved your exercise goal today and are feeling happy."

[0393] Specific examples

[0394] Case 2: Using the Emotion Engine to set the habit "30 minutes of exercise every day" and set a deposit of 10,000 yen

[0395] 1. User Registration and Login

[0396] Device: Yamada launches the app and clicks "New Registration."

[0397] Device: Yamada enters her email address and password and clicks "Register."

[0398] Server: Saves the input data and returns a success message.

[0399] Device: Yamada enters her email address and password on the login screen and clicks "Login."

[0400] Server: The server generates an authentication token and sends it to the device.

[0401] Device: Yamada's device receives the token and transitions to the dashboard.

[0402] 2. Habit setting and deposits

[0403] Device: Yamada enters "30 minutes of exercise every day" in "Set a new habit" and clicks "Next."

[0404] Terminal: Enter the deposit amount "10,000 yen" and click "Complete".

[0405] Server: The server saves the information and returns a completion message.

[0406] Device: Yamada's device will display a message indicating that the setup is complete.

[0407] 3. Habit Tracking

[0408] Device: Yamada enters "30 minutes of exercise" in "Enter progress" and submits.

[0409] Server: The server stores the data and sends it to the AI ​​model.

[0410] AI model: The AI ​​model analyzes the progress and sends the evaluation results to the server.

[0411] Server: The server notifies Yamada's device of the evaluation results.

[0412] Device: Yamada's device displays the progress and evaluation results.

[0413] 4. Emotional state input and analysis

[0414] Device: Yamada inputs "Happy" in the "Emotion Input" field and sends it. Alternatively, the device will analyze his facial expressions and voice to recognize his emotions.

[0415] Server: The server stores the emotion data and sends it to the AI ​​model.

[0416] AI model: The AI ​​model analyzes the emotional data and evaluates it to reflect the habit achievement level.

[0417] Server: Adjusts reward amount and motivational message based on the evaluation results.

[0418] 5. Linking reward systems and emotional states

[0419] AI model: The AI ​​model determines the cashback of 100 yen + an additional 20 yen based on the emotional state and habit completion level.

[0420] Server: Save the reward amount, call the cashback API, and transfer 120 yen to Yamada's bank account.

[0421] Device: Yamada's device notifies him that the cashback has been completed and displays a pleasant message: "You've received a cashback of 120 yen because you achieved your exercise goal today and felt good."

[0422] This specific processing step allows users to pursue new habits in a fun way while receiving optimal rewards according to their emotional state.

[0423] The processing flow will be explained below.

[0424] Program processing details

[0425] User registration and login

[0426] Step 1:

[0427] On the device: The user installs and launches the app. They click the "Sign up" button.

[0428] Step 2:

[0429] Device: The user enters their email address and password and clicks the "Register" button.

[0430] Step 3:

[0431] Server: Receives input data and saves it in the database. If registration is successful, returns a success message to the device.

[0432] Step 4:

[0433] Device: The user enters the registered email address and password on the login screen and clicks the "Login" button.

[0434] Step 5:

[0435] Server: Authenticates the input information, and if successful, generates an authentication token and sends it to the device.

[0436] Step 6:

[0437] Terminal: Receive the token and proceed to the dashboard screen.

[0438] Habit Setting and Deposits

[0439] Step 1:

[0440] On the device: The user opens the "Set up a new habit" screen and enters "30 minutes of exercise daily." They then click the Next button.

[0441] Step 2:

[0442] Terminal: The user enters the amount to deposit (10,000 yen). Then clicks the Complete button.

[0443] Step 3:

[0444] Server: Receives the habit and deposit information, stores it in the database, and returns a success message to the terminal.

[0445] Step 4:

[0446] Terminal: Prompts the user that their habits and deposit setup is complete.

[0447] Habit Tracking

[0448] Step 1:

[0449] Device: The user opens the "Enter Progress" screen, enters today's exercise time as "30 minutes," and clicks the submit button.

[0450] Step 2:

[0451] Server: Receives progress data and stores it in a database.

[0452] Step 3:

[0453] Server: Sends saved progress data to the AI ​​model.

[0454] Step 4:

[0455] AI model: Analyzes the received data and evaluates it as "progressing as expected."

[0456] Step 5:

[0457] AI model: Sends the evaluation results to the server.

[0458] Step 6:

[0459] Server: Saves the evaluation results in a database and notifies the terminal of the evaluation results.

[0460] Step 7:

[0461] Device: Shows the user today's progress and assessment results.

[0462] Reward System

[0463] Step 1:

[0464] AI model: Calculates reward amount based on habit achievement. For example, "For 50% achievement, a cashback of 100 yen will be given."

[0465] Step 2:

[0466] AI model: Sends the calculation results to the server.

[0467] Step 3:

[0468] Server: Stores the reward amount in the database.

[0469] Step 4:

[0470] Server: Calls the API to execute the cashback and transfers the money to the user's bank account.

[0471] Step 5:

[0472] On the device: Display a cashback notification to the user, for example, "You've received a cashback of 100 yen for achieving your exercise goal today."

[0473] Introducing the Emotion Engine

[0474] Step 1:

[0475] On the device: The user opens the "Emotion Input" screen and reports their feelings. For example, they can type "I'm happy today." Alternatively, the device can automatically recognize their emotional state from their facial expressions and voice.

[0476] Step 2:

[0477] Server: The server receives the emotion data and stores it in a database.

[0478] Step 3:

[0479] AI model: Analyzes emotional data and evaluates how a user's emotional state affects habit completion.

[0480] Step 4:

[0481] Server: Adjusts reward amount and motivational message based on the evaluation results.

[0482] Step 5:

[0483] Device: Display an appropriate motivational message to the user, for example, "You're working especially hard today!"

[0484] Step 6:

[0485] AI model: Calculates the optimal reward amount based on emotional data and habit completion. For example, it determines that "the user's emotional state is high, so an additional 20 yen cashback will be given."

[0486] Step 7:

[0487] Server: Saves the reward calculation results in the database, calls the cashback API, and transfers the money to the user's bank account.

[0488] Step 8:

[0489] Device: Display a cashback notification to the user along with a pleasurable message based on their emotional state. For example, a notification like "You've received a cashback of 120 yen because you achieved your exercise goal today and are feeling happy" will be displayed.

[0490] Specific examples

[0491] Case 1: Using the Emotion Engine, you set the habit "30 minutes of exercise every day" and set a deposit of 10,000 yen.

[0492] 1. User Registration and Login

[0493] Step 1: Yamada launches the app and clicks "New Registration."

[0494] Step 2: Sam enters her email address and password and clicks "Register."

[0495] Step 3: The server saves the data and returns a success message.

[0496] Step 4: On the login screen, Yamada enters her email address and password and clicks "Login."

[0497] Step 5: The server generates an authentication token and sends it to the device.

[0498] Step 6: Yamada's device receives the token and goes to the dashboard.

[0499] 2. Habit setting and deposits

[0500] Step 1: Yamada enters "30 minutes of exercise every day" in "Set a new habit" and clicks "Next."

[0501] Step 2: Enter the deposit amount "10,000 yen" and click "Complete".

[0502] Step 3: The server saves the information and returns a completion message.

[0503] Step 4: Yamada's device will display a message that the setup is complete.

[0504] 3. Habit Tracking

[0505] Step 1: Yamada enters "30 minutes of exercise" in "Enter progress" and submits it.

[0506] Step 2: The server stores the data and sends it to the AI ​​model.

[0507] Step 3: The AI ​​model analyzes the progress and sends the evaluation results to the server.

[0508] Step 4: The server notifies Yamada's device of the evaluation results.

[0509] Step 5: Yamada's device displays the progress and evaluation results.

[0510] 4. Emotional state input and analysis

[0511] Step 1: Yamada inputs "I'm happy today" in "Emotion Input" and sends it. Alternatively, the device will analyze facial expressions and voice to recognize the emotion.

[0512] Step 2: The server stores the emotion data and sends it to the AI ​​model.

[0513] Step 3: The AI ​​model analyzes the emotional data and evaluates it to reflect the habit completion level.

[0514] Step 4: The server adjusts the reward amount and motivational message based on the evaluation results.

[0515] 5. Linking reward systems and emotional states

[0516] Step 1: The AI ​​model determines the cashback of 100 yen + an additional 20 yen based on the emotional state and habit completion.

[0517] Step 2: The server stores the reward amount in the database.

[0518] Step 3: Call the cashback API and transfer 120 yen to Yamada's bank account.

[0519] Step 4: Yamada's device notifies him that the cashback has been completed and displays a pleasant message: "You've received a cashback of 120 yen because you achieved your exercise goal today and felt happy."

[0520] This specific processing step allows users to pursue new habits in a fun way while receiving optimal rewards according to their emotional state.

[0521] Example 2

[0522] 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."

[0523] Conventional systems for forming new habits primarily record the user's progress and provide rewards based on the level of achievement. However, these systems have the problem of making it difficult to maintain motivation because they do not take into account the user's emotional state. There is a need for a system that can support more effective habit formation by appropriately responding to the user's emotional state.

[0524] 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.

[0525] In this invention, the server includes input means for the user to set a new habit and make a deposit, means for the server to store the received data in a database, means for tracking the user's habit progress, means for the generative AI model to analyze the progress data and evaluate the habit achievement level, means for calculating a reward amount based on the evaluation results, means for executing cashback to the user's bank account, input means for recording the user's emotional state, means for the terminal to automatically recognize the user's emotional state from the user's facial expressions and voice, and means for receiving and analyzing the emotional data and adjusting the reward amount and motivational message based on the evaluation results. This makes it possible to adjust the optimal reward amount according to the user's emotional state, enabling the user to form a new habit while maintaining motivation.

[0526] "User" refers to an individual who is the intended user of this system.

[0527] Habits are activities or behaviors that users plan to perform on a daily basis.

[0528] A "deposit" is the amount a user pays upfront to receive financial rewards for the habits they set.

[0529] "Input means" refers to the interface or device through which a user inputs data into a system.

[0530] "Server" refers to a computer system that receives, processes, and stores data submitted by users.

[0531] A "database" refers to a digital storage device for efficiently storing and managing data collected within a system.

[0532] "Tracking" refers to the continuous recording and monitoring of a user's habit progress and activities.

[0533] A "generative AI model" refers to an artificial intelligence algorithm that analyzes collected data, calculates the degree of habit completion and reward amount, and evaluates the user's emotional state.

[0534] "Analysis" refers to the process of examining collected data in detail to understand its content and patterns.

[0535] "Habit completion level" refers to an indicator that shows the extent to which a user has achieved the habits they have set.

[0536] "Evaluation results" refer to the conclusions reached based on the habit achievement and emotional state analyzed by the generative AI model.

[0537] "Reward amount" refers to the monetary reward the system provides to the user based on the user's level of habit achievement.

[0538] "Cashback" refers to the process of returning reward amounts to the user's bank account.

[0539] "Emotional state" refers to information that indicates the user's current psychological feelings.

[0540] "Facial Expression" refers to a user's facial expression that is used to recognize the user's emotional state.

[0541] "Voice" refers to audio data used to recognize the user's emotional state.

[0542] "Motivational messages" refer to messages provided by the system to motivate users and encourage them to continue using the system.

[0543] "Behavioral patterns" refers to data that shows a user's past activities and behavioral tendencies.

[0544] The present invention is a system designed to help users enjoy and continue new habits, and aims to increase motivation by taking into account the user's emotional state. The system tracks the user's established habits and their progress, and provides monetary rewards according to the user's progress and emotional state. Specific embodiments for implementing the present invention are described in detail below.

[0545] User registration and login

[0546] A user installs and launches the application on a device such as a smartphone or tablet. First, the user clicks the "New Registration" button and enters their email address and password. The server receives this input data and stores it in a database. If registration is successful, a success message is returned to the device. Next, the user enters their email address and password on the login screen and clicks the login button. The server authenticates the entered information, and if authentication is successful, generates a token and sends it to the device. The user receives the token and can proceed to the dashboard screen to use the system.

[0547] Habit Setting and Deposits

[0548] The user opens the "Setting a new habit" screen and enters the specific habit. For example, the user can enter "30 minutes of exercise every day." The user then enters the amount to deposit, for example, "10,000 yen." The server receives this input data and stores it in the database. After a success message is returned to the terminal, the user can confirm that the setup is complete.

[0549] Habit Tracking

[0550] To record their daily progress, users open the "Progress Input" screen in the app, enter progress information (for example, "30 minutes of exercise today") and submit it. The server receives the progress data and sends it to the generative AI model. The generative AI model analyzes the progress data and evaluates the degree of habit achievement. For example, the generative AI model may evaluate the progress as "progressing as expected." This evaluation result is sent to the server and stored in a database. Finally, the result is notified to the user's device, allowing the user to check their progress.

[0551] Reward System

[0552] The generative AI model calculates the reward amount based on the degree of habit achievement. For example, it may determine "100 yen as the daily reward for achieving 50%." The server receives the reward calculation results and executes a cashback to the user's bank account. The user can check the cashback notification on their device. For example, it may display "100 yen has been cashbacked for achieving today's exercise goal."

[0553] Introducing the Emotion Engine

[0554] Recognition of emotional states

[0555] To record their emotional state, users can open the "Emotion Input" screen in the app and self-report their feelings. For example, they can enter "I'm happy today." Alternatively, the device can automatically recognize their emotional state from their facial expressions and voice. The server receives the emotional data and stores it in a database.

[0556] Emotional data analysis and reflection

[0557] The generative AI model analyzes the emotional data and evaluates how the user's emotional state affects their habit achievement. The server then adjusts the reward amount and motivational message based on the evaluation results. For example, it displays an appropriate motivational message to the user, such as, "You're working especially hard today!"

[0558] Linking cashback and emotional states

[0559] The generative AI model calculates the optimal reward amount based on emotional data and the degree of habit achievement. For example, it may decide to "give the user an additional 20 yen cashback because their emotions are high." The server receives the reward calculation results and executes the cashback into the user's bank account. The user receives a cashback notification on their device, and a motivational message based on their emotional state is also displayed. For example, it may say, "You've received a cashback of 120 yen because you achieved your exercise goal today and felt happy."

[0560] Specific examples

[0561] Prompt Sentence Examples

[0562] Please enter your new email address and password to register.

[0563] "Enter the specific habit and amount to set up a new habit and make a deposit."

[0564] "Record your progress today on the progress entry screen and press the submit button."

[0565] "Enter your emotional state for the day on the emotion input screen, or have it recognized automatically by analyzing your facial expressions and voice."

[0566] The present invention allows users to enjoyably pursue new habits while receiving optimal rewards according to their emotional state.

[0567] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0568] Step 1:

[0569] The user installs and launches the application. They click the "New Registration" button on the screen and enter their email address and password. The entered data is sent from the device to the server. The server stores the received data in a database and returns a success message indicating that registration was successful.

[0570] Step 2:

[0571] The user enters the registered email address and password on the login screen and clicks the login button. The input data is sent from the terminal to the server. The server compares the received data with the database, and if authentication is successful, generates an authentication token and sends it to the terminal. The user receives the token, moves to the dashboard screen, and can use the system.

[0572] Step 3:

[0573] The user opens the "Setting a new habit" screen and enters the specific habit. Next, they enter the amount they want to deposit. The entered data is sent from the device to the server. The server stores the received habit and deposit information in a database and returns a success message. The user can confirm that the setup is complete.

[0574] Step 4:

[0575] To record their daily progress, users open the "Progress Input" screen in the app, enter their progress information, and submit it. The input data is sent from the device to the server. The server then sends the progress data to the generative AI model, which analyzes it. The generative AI model analyzes the progress data and evaluates the degree of habit achievement. The evaluation results are sent to the server and stored in a database. The server then sends the evaluation results to the user's device, allowing the user to check their progress and evaluation results.

[0576] Step 5:

[0577] The generative AI model calculates the reward amount based on the degree of habit achievement. For example, if 50% achievement is achieved, it determines the daily reward to be 100 yen. The calculation result is sent to the server, which then executes a cashback to the user's bank account. The user receives a cashback notification on their device. For example, it displays a message saying, "You have received a cashback of 100 yen for achieving today's exercise goal."

[0578] Step 6:

[0579] To record their emotional state, users can open the "Emotion Input" screen in the app and self-report their emotional state. Alternatively, the device can automatically recognize their emotional state from their facial expressions and voice. Emotion data is sent from the device to a server, which then stores the data in a database.

[0580] Step 7:

[0581] The generative AI model analyzes the emotional data and evaluates how the user's emotional state affects their habit achievement. The analysis results are sent to the server, which adjusts the reward amount and motivational message based on the evaluation results. The server then sends the adjustment results to the user's device, and the user is notified with an appropriate motivational message. For example, "You're working especially hard today!"

[0582] Step 8:

[0583] The generative AI model calculates the optimal reward amount based on emotional data and the degree of habit achievement. For example, it may decide to "give the user an additional 20 yen cashback because their emotions are high." The calculation result is sent to the server, which then deposits the cashback into the user's bank account. The user receives a cashback notification on their device, and a motivational message based on their emotional state is also displayed. For example, it may say, "You've received a cashback of 120 yen because you achieved your exercise goal today and felt happy."

[0584] (Application example 2)

[0585] 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."

[0586] Conventional habit formation support systems only evaluate users' achievements without considering their emotional state, which makes it difficult to maintain motivation. Furthermore, the reward system is limited, making it ineffective in promoting actual behavioral change. Furthermore, the system does not consider providing incentives through collaboration with virtual stores, limiting its effectiveness as a means of helping users establish new habits in a fun way.

[0587] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0588] In this invention, the server includes an input means for a user to set a new habit and make a deposit, a means for the server to store the received data in a database, a means for tracking the user's habit progress, a means for an AI to analyze the progress data and evaluate the degree of habit achievement, a means for calculating a reward amount based on the evaluation result, a means for providing cashback to the user's bank account, a means for receiving the reward in the virtual store, and a means for recognizing the user's emotional state and adjusting the reward amount based thereon, thereby enabling the user to continue the new habit while enjoying it and receive individual incentives according to their emotional state.

[0589] "User" refers to a person who uses the System to set new habits and track their progress.

[0590] Habits are new behaviors or activities that users incorporate into their daily lives, such as exercising or reading.

[0591] A "deposit" refers to the amount of money a user deposits in advance to receive rewards based on the progress of the habits they set.

[0592] "Input means" refers to the interface that allows users to set habits, enter progress, and record emotional states.

[0593] "Server" refers to the central system that receives, processes, and stores data entered by users in a database.

[0594] "Database" refers to the system for storing and managing User habits, progress, and emotional data.

[0595] "Tracking Method" refers to the method by which a User records their daily progress and transmits that data to a server.

[0596] "AI" refers to artificial intelligence technology that analyzes progress and emotional data to evaluate the user's level of habit achievement and reward amount.

[0597] "Habit completion" refers to an indicator that evaluates the degree to which a user has achieved the habits they have set.

[0598] "Reward amount" refers to a monetary incentive calculated based on the user's habit completion.

[0599] "Cashback" refers to money that is transferred to a user's bank account when they complete a habit, based on their level of achievement.

[0600] "Virtual store" refers to an online shopping platform where users can use rewards to purchase goods and services.

[0601] "Emotional state" refers to data that indicates a user's current emotions, and refers to information obtained through self-reporting, facial expression recognition, etc.

[0602] The system that realizes this application example is composed of various hardware and software components that work together to enable users to continue their new habits in an enjoyable way. Specific embodiments of each part of the system are described below.

[0603] Hardware and software used

[0604] Hardware: Smartphone (including facial recognition and voice recognition functions via camera), server

[0605] software:

[0606] Platform: Android, iOS

[0607] Backend: Firebase, Google Cloud, AWS

[0608] AI model: TensorFlow, OpenAI GPT-3

[0609] Database: Firebase Firestore, MySQL

[0610] Frontend: React Native

[0611] Emotion recognition: Affectiva SDK, Google Cloud Vision API

[0612] Specific processing

[0613] User registration and login

[0614] A user installs the application on their smartphone and registers by entering their email address and password. The server receives this information, authenticates the user information using Firebase Auth, generates an authentication token, and returns it to the user's device, allowing the user to log in and use the system.

[0615] Setting a new habit and depositing

[0616] The user is presented with an interface to set up a new habit and enter the deposit amount, which the server receives and stores in Firebase Firestore. Based on this information, the user can enjoyably pursue the habit they set up.

[0617] Habit completion and emotional state tracking

[0618] Users enter their daily progress on their smartphones and send it to a server. The server then sends this data to an AI model that uses TensorFlow to analyze habit completion. The system also tracks the user's emotional state. It uses Google Cloud Vision API and Affectiva SDK to recognize emotions from facial expressions and voice. This data is stored in Firebase Firestore for later analysis.

[0619] Reward systems and virtual stores

[0620] Based on the evaluation results, the AI ​​model calculates the reward amount, taking into account the progress data and emotional state. The reward is not only cashed back into the user's bank account, but also provided as a coupon that can be used in virtual stores, allowing users to purchase products and services in the virtual stores.

[0621] Example: Yamada's case

[0622] For example, let's say a user wants to make reading 30 minutes a day a habit and uses this system. The user installs the app, creates an account, and logs in. Then, they set up the habit of "reading 30 minutes a day" and enter a deposit of 5,000 yen. By recording their daily progress and entering their emotional state, the system calculates rewards based on their habit achievement and emotional state. The user can then use coupons to purchase products in the virtual store.

[0623] Prompt Sentence Examples

[0624] To help users develop literacy habits, VirtuHabit implements an in-app system that evaluates progress and rewards users based on their emotional state, such as coupons and special offers for virtual stores.

[0625] Thus, the present invention provides a system that allows users to enjoyably continue new habits and receive rewards according to their emotional state.

[0626] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0627] Step 1:

[0628] User registration and login

[0629] Input: Email address, Password

[0630] Server: The user installs the application and enters their email address and password on the registration screen. The server registers the user information using Firebase Auth and generates an authentication token. The authentication token is sent to the device.

[0631] Output: Authentication token

[0632] Step 2:

[0633] Setting a new habit and depositing

[0634] Input: Habit name, Deposit amount

[0635] Device: The user enters the name of the habit, such as "30 minutes of exercise every day," and the deposit amount (e.g., 10,000 yen) on the habit setting screen. This is then sent to the server.

[0636] Server: The server stores the received habit information and deposit amount in Firebase Firestore.

[0637] Output: Save complete message

[0638] Step 3:

[0639] Habit Tracking

[0640] Input: Daily progress data (e.g., "Today's exercise time: 30 minutes")

[0641] Terminal: The user enters progress data on the progress input screen and sends it to the server.

[0642] Server: The server receives this progress data, sends it to the AI ​​model for analysis, evaluates habit completion using TensorFlow, and sends the results back to the server, which stores the results in Firebase Firestore.

[0643] Output: Progress evaluation results

[0644] Step 4:

[0645] Emotional state tracking

[0646] Input: Emotion data (e.g., "I feel happy today"), face image, or voice

[0647] Device: The user inputs their emotional state on the emotion input screen, captures a facial image with the device camera, or records a voice, which is then sent to the server.

[0648] Server: The server sends facial images and audio data to the Google Cloud Vision API and Affectiva SDK, analyzes the emotional state, and stores the results in Firebase Firestore.

[0649] Output: Emotion evaluation result

[0650] Step 5:

[0651] Reward calculation and cashback

[0652] Input: Habit achievement assessment results, emotional assessment results

[0653] Server: The server uses an AI model (TensorFlow) to calculate the optimal reward amount based on the progress data and emotional state. The calculation result is cashed back to the user's bank account.

[0654] Output: Cashback completion notification, reward amount

[0655] Step 6:

[0656] Use rewards in virtual stores

[0657] Input: Reward amount, shopping information at virtual store

[0658] Terminal: Users can select products and services in a virtual store and purchase them using their reward amount.

[0659] Server: The server receives the purchase information and updates the reward amount usage to Firebase Firestore.

[0660] Output: Purchase complete notification, updated balance

[0661] This allows users to enjoy new habits, continue them, and receive personalized incentives based on their emotional state.

[0662] 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.

[0663] 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.

[0664] 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.

[0665] [Second embodiment]

[0666] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0667] 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.

[0668] 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).

[0669] 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.

[0670] 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.

[0671] 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).

[0672] 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.

[0673] 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.

[0674] 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.

[0675] 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.

[0676] 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.

[0677] 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."

[0678] This invention is a system that provides financial incentives to help users enjoyably continue new habits and supports the habit-forming process. This system tracks the habits set by the user and their progress in achieving them, and provides monetary rewards according to the degree of progress. The program and specific processing of this system are described in detail below.

[0679] Program processing explanation

[0680] User registration and login

[0681] On the device: The user installs and launches the app, clicks the "Sign Up" button on the screen, and enters their email address and password.

[0682] Server: The server receives the input data, stores it in the database, and returns a success message to the terminal if the registration is successful.

[0683] Device: The user enters the registered email address and password on the login screen and clicks the login button. The server authenticates the entered information, and if authentication is successful, generates a token and sends it to the device.

[0684] Terminal: Receives the token, moves to the dashboard screen, and the user can use the system.

[0685] Habit Setting and Deposits

[0686] On the device: The user opens the "Set up a new habit" screen and enters the habit. For example, they might enter "30 minutes of exercise every day." Then they enter the amount they want to deposit. For example, they enter "10,000 yen."

[0687] Server: The server receives the entered habits and deposit information, stores it in the database, and returns a success message to the terminal.

[0688] Terminal: Prompts the user that their habits and deposits have been set up.

[0689] Habit Tracking

[0690] On the device: To record their daily progress, users open the "Progress Input" screen in the app. For example, they enter "30 minutes of exercise today" and submit.

[0691] Server: The server receives the progress data and sends it to the AI ​​model.

[0692] AI model: The AI ​​model analyzes the progress data and evaluates the habit achievement, for example, rating it as "progressing as expected."

[0693] Server: The server stores the evaluation results in a database and sends the results to the device.

[0694] On your device: Notify users that their habit has been assessed and display their progress.

[0695] Reward System

[0696] AI model: The AI ​​model calculates the reward amount based on the habit achievement level. For example, it determines "50% achievement means 100 yen per day."

[0697] Server: The server receives the reward calculation results and executes cashback to the user's bank account.

[0698] On the device: Display a cashback notification to the user. For example, display a notification such as "You've received a cashback of 100 yen for achieving your exercise goal today."

[0699] Specific examples

[0700] Case 1: When you set a new habit "exercise 30 minutes a day" and set a deposit of 10,000 yen

[0701] 1. User Registration and Login

[0702] Device: David launches the app and enters the required information to create a new account.

[0703] Server: The server receives the input information, stores it in a database, and returns a success message.

[0704] Device: Yamada enters her email address and password on the login screen and obtains an authentication token.

[0705] 2. Habit setting and deposits

[0706] Device: Yamada sets "30 minutes of exercise every day" and deposits 10,000 yen.

[0707] Server: The server receives and stores this information and returns a completion message.

[0708] 3. Habit Tracking

[0709] Device: Yamada enters today's exercise time as "30 minutes" and submits.

[0710] Server: The server receives the progress data and has the AI ​​model evaluate it.

[0711] AI model: The AI ​​model evaluates the results as "Progressing as expected" and saves them.

[0712] Server: The server notifies Yamada's device of the evaluation results.

[0713] 4. Reward System

[0714] AI model: The AI ​​model decides to give a cashback of 100 yen as a reward for one day.

[0715] Server: The server calls the cashback API and transfers 100 yen to Yamada's bank account.

[0716] Device: Notify "You've received a cashback of 100 yen for achieving your exercise goal today."

[0717] Through this specific process, users can develop new habits in a fun and efficient way.

[0718] The processing flow will be explained below.

[0719] Program processing details

[0720] User registration and login

[0721] Step 1:

[0722] On the device: The user installs and launches the app. They click the "Sign up" button.

[0723] Step 2:

[0724] Device: The user enters their email address and password and clicks the "Register" button.

[0725] Step 3:

[0726] Server: Receives input data and saves it in the database. If registration is successful, returns a success message to the device.

[0727] Step 4:

[0728] On the device: The user enters their email address and password on the login screen and clicks the "Login" button.

[0729] Step 5:

[0730] Server: Authenticates the input information, and if successful, generates an authentication token and sends it to the device.

[0731] Step 6:

[0732] Terminal: Receive the token and proceed to the dashboard screen.

[0733] Habit Setting and Deposits

[0734] Step 1:

[0735] On the device: The user opens the "Set up a new habit" screen and enters "30 minutes of exercise daily." They then click the Next button.

[0736] Step 2:

[0737] Terminal: The user enters the amount to deposit (10,000 yen). Then clicks the Complete button.

[0738] Step 3:

[0739] Server: Receives the habit and deposit information, stores it in the database, and returns a success message to the terminal.

[0740] Step 4:

[0741] Terminal: Prompts the user that their habits and deposit setup is complete.

[0742] Habit Tracking

[0743] Step 1:

[0744] Device: The user opens the "Enter Progress" screen, enters today's exercise time as "30 minutes," and clicks the submit button.

[0745] Step 2:

[0746] Server: Receives progress data and stores it in a database.

[0747] Step 3:

[0748] Server: Sends saved progress data to the AI ​​model.

[0749] Step 4:

[0750] AI model: Analyzes the received data and evaluates it as "progressing as expected."

[0751] Step 5:

[0752] AI model: Sends the evaluation results to the server.

[0753] Step 6:

[0754] Server: Saves the evaluation results in a database and notifies the terminal of the evaluation results.

[0755] Step 7:

[0756] Device: Shows the user today's progress and assessment results.

[0757] Reward System

[0758] Step 1:

[0759] AI model: Calculates reward amount based on habit achievement. For example, "For 50% achievement, a cashback of 100 yen will be given."

[0760] Step 2:

[0761] AI model: Sends the calculation results to the server.

[0762] Step 3:

[0763] Server: Stores the reward amount in the database.

[0764] Step 4:

[0765] Server: Calls the API to execute the cashback and transfers the money to the user's bank account.

[0766] Step 5:

[0767] On the device: Display a cashback notification to the user, for example, "You've received a cashback of 100 yen for achieving your exercise goal today."

[0768] Specific examples

[0769] Case 1: When you set a new habit "exercise 30 minutes a day" and set a deposit of 10,000 yen

[0770] 1. User Registration and Login

[0771] Step 1: Yamada launches the app and clicks "New Registration."

[0772] Step 2: Sam enters her email address and password and clicks "Register."

[0773] Step 3: The server saves the data and returns a success message.

[0774] Step 4: On the login screen, Yamada enters her email address and password and clicks "Login."

[0775] Step 5: The server generates an authentication token and sends it to the device.

[0776] Step 6: Yamada's device receives the token and is redirected to the dashboard.

[0777] 2. Habit setting and deposits

[0778] Step 1: Yamada enters "30 minutes of exercise every day" in "Set a new habit" and clicks "Next."

[0779] Step 2: Enter the deposit amount "10,000 yen" and click "Complete".

[0780] Step 3: The server saves the information and returns a completion message.

[0781] Step 4: Yamada's device will display a message that the setup is complete.

[0782] 3. Habit Tracking

[0783] Step 1: Yamada enters "30 minutes of exercise" in "Enter progress" and submits it.

[0784] Step 2: The server stores the data and sends it to the AI ​​model.

[0785] Step 3: The AI ​​model analyzes the progress and sends the evaluation results to the server.

[0786] Step 4: The server notifies Yamada's device of the evaluation results.

[0787] Step 5: Yamada's device displays the progress and evaluation results.

[0788] 4. Reward System

[0789] Step 1: The AI ​​model determines the cashback of 100 yen based on the achievement level.

[0790] Step 2: The server stores the reward amount in the database.

[0791] Step 3: Call the cashback API and transfer 100 yen to Yamada's bank account.

[0792] Step 4: Yamada's device will notify him that the cashback has been completed.

[0793] This specific processing step allows users to enjoyably pursue new habits while earning financial rewards.

[0794] Example 1

[0795] 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."

[0796] In modern society, it is difficult for users to form and maintain new habits. Effective methods for maintaining sustained motivation are scarce, and methods for utilizing economic incentives are limited. Furthermore, current systems lack mechanisms for tracking user progress and providing rewards based on that progress, making it difficult to maintain motivation for habit formation.

[0797] 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.

[0798] In this invention, the server includes an input means for a user to set a new habit and make a deposit, a means for the server to store the received data in a database, a means for tracking the user's habit progress, a means for an AI to analyze the progress data and evaluate the degree of habit achievement, a means for calculating a reward amount based on the evaluation result, a means for executing cashback to the user's financial institution account, and an authentication means for enabling the user to log in and use the system using a token. This allows the user to continue a new habit in a fun way and form a habit while receiving economic incentives.

[0799] "Input" is the interface on the system through which users can set new habits and make deposits.

[0800] A "database" is an information management system that stores and manages data received by a server.

[0801] "Tracking Tools" are features that allow users to monitor and record their habit progress.

[0802] The "AI model" is an artificial intelligence model that analyzes progress data and evaluates the user's level of habit achievement.

[0803] The "evaluation method" is a function for determining the degree of habit achievement based on the results of analysis by the AI ​​model.

[0804] The "remuneration calculation means" is a function for calculating the amount of remuneration to be provided to the user based on the evaluation results.

[0805] "Cashback method" is a system function that actually transfers rewards to the user's financial institution account.

[0806] "Authentication means" is a security feature that allows users to log in using a token and access the system.

[0807] The present invention is a system that provides economic incentives to users to help them continue new habits in a fun way and supports the habit formation process. The system receives user input, manages and analyzes data using a server and an AI model, evaluates the user's habit achievement, and provides rewards. Details of the system's program and the specific form of its processing are described below.

[0808] Handling user registration and login

[0809] Terminal: The user installs and launches the application. They click the "New Registration" button on the screen and enter their email address and password. This input method allows the user to create a new account within the system. For example, they enter the email address "example@example.com" and the password "password123."

[0810] Server: The server receives the entered data and stores it in the database. It executes the query "INSERT INTO users (email, password) VALUES ('example@example.com', 'password123');" and returns a success message to the terminal if registration is successful.

[0811] Terminal: The user enters the registered email address and password on the login screen and clicks the login button. The server authenticates the entered information, and if authentication is successful, generates a token and sends it to the terminal. The terminal receives this token, transitions to the dashboard screen, and the user can use the system.

[0812] Setting habits and processing deposits

[0813] On the device: The user opens the "Set up a new habit" screen and enters the habit. For example, they might enter "30 minutes of exercise every day," then enter the amount they want to deposit. For the deposit amount, they enter "10,000 yen."

[0814] Server: The server receives the entered habit and deposit information and stores it in the database. It executes the query "INSERT INTO habits (user_id, habit_detail, deposit_amount) VALUES (1, '30 minutes of exercise daily', 10000);" and returns a success message.

[0815] Terminal: Prompts the user that their habits and deposits have been set up.

[0816] Handling habit completion tracking

[0817] On the device: To record their daily progress, users open the "Progress Input" screen in the app. For example, they enter "30 minutes of exercise today" and submit.

[0818] Server: The server receives the progress data and sends it to the AI ​​model through the endpoint " / api / v1 / progress / evaluate".

[0819] AI model: The AI ​​model analyzes the progress data and evaluates the habit achievement level. For example, it evaluates the habit achievement level as "80%" based on the progress data.

[0820] Server: Save the evaluation results in the database and use the query "UPDATE progress SET evaluation = 'Habit achievement level 80%' WHERE user_id = 1;". The evaluation results are notified to the device.

[0821] On your device: Notify users that their habit has been assessed and display their progress.

[0822] Reward system processing

[0823] AI model: The AI ​​model calculates the reward amount based on the habit completion rate. For example, it determines "80 yen as the daily reward."

[0824] Server: Receives the reward calculation result and executes cashback to the user's financial institution account using the endpoint " / api / v1 / banking / cashback".

[0825] On the device: Notify the user that the cashback has been applied. For example, display a notification such as "You've received a cashback of 80 yen for achieving your exercise goal today."

[0826] Examples of concrete examples and prompts

[0827] To generate a prompt, enter the following:

[0828] Set a new habit of "30 minutes of exercise every day" and set a deposit of 10,000 yen. Then, record "30 minutes of exercise today" on the progress entry screen in the app, and explain how your habit achievement will be evaluated and how you will be rewarded.

[0829] Based on these prompts, the AI ​​model generates concrete examples to help users maintain their new habits in a fun and efficient way. The system is designed to encourage users to proactively establish new habits and achieve their goals while enjoying financial incentives.

[0830] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0831] Step 1: User Registration and Login

[0832] user:

[0833] Input: The user installs and launches the app, clicks the Sign Up button, and enters the email address "example@example.com" and the password "password123."

[0834] Specific operations: Enter the required information on the new registration screen and click the "Register" button.

[0835] Output: A success message is displayed.

[0836] server:

[0837] Input: The server receives the email address and password entered by the user.

[0838] Data processing: Execute the query "INSERT INTO users (email, password) VALUES ('example@example.com', 'password123');".

[0839] Output: The user information is saved to the database and a success message is returned.

[0840] user:

[0841] Input: On the login screen, enter the email address "example@example.com" and the password "password123".

[0842] Specific actions: Enter information on the login screen and click the Login button.

[0843] Output: Get the token.

[0844] server:

[0845] Input: The server receives the user's email address and password and performs authentication.

[0846] Data operation: Execute the query "SELECT FROM users WHERE email = 'example@example.com' AND password = 'password123';" and generate a token if authentication is successful.

[0847] Output: A token is generated and sent to the device.

[0848] Device:

[0849] Input: Receives a token.

[0850] Specific operation: Save the token and move to the dashboard screen.

[0851] Output: User can access the dashboard.

[0852] Step 2: Setting habits and depositing

[0853] user:

[0854] Input: On the "Set up a new habit" screen, enter the habit "30 minutes of exercise every day" and the deposit amount "10,000 yen."

[0855] Specific actions: Enter your habit and deposit information and click the "Save" button.

[0856] Output: A message will be displayed indicating that the setup is complete.

[0857] server:

[0858] Input: Receives the habits and deposit amount entered by the user.

[0859] Data processing: Run the query "INSERT INTO habits (user_id, habit_detail, deposit_amount) VALUES (1, '30 minutes of exercise daily', 10000);".

[0860] Output: Saves the information to the database and returns a success message.

[0861] Device:

[0862] Input: Receives a success message.

[0863] What it does: Prompts the user that their habits and deposits have been set up.

[0864] Output: A completion message is displayed on the screen.

[0865] Step 3: Track your habit completion

[0866] user:

[0867] Input: Open the progress input screen in the app, enter "Today's exercise time: 30 minutes" and submit.

[0868] Specific actions: Enter information on the progress input screen and click the submit button.

[0869] Output: Progress data is sent.

[0870] server:

[0871] Input: Receives the user's progress data.

[0872] Data processing: Call the endpoint " / api / v1 / progress / evaluate" to send progress data to the AI ​​model.

[0873] Output: Progress data sent to the AI ​​model.

[0874] AI model:

[0875] Input: Receives progress data.

[0876] Data calculation: Analyzes progress data and evaluates "Habit achievement rate 80%."

[0877] Output: Returns the evaluation result to the server.

[0878] server:

[0879] Input: Receives the evaluation results from the AI ​​model.

[0880] Data processing: Execute the query "UPDATE progress SET evaluation = 'Habit achievement level 80%' WHERE user_id = 1;" and save the evaluation results to the database.

[0881] Output: The evaluation results are saved and sent to the device.

[0882] Device:

[0883] Input: Receives notifications from the server.

[0884] What it does: Show the user a notification that says "Habit completion is 80%."

[0885] Output: Progress is displayed on the screen.

[0886] Step 4: Reward System

[0887] AI model:

[0888] Input: Receives the user's habit completion rate.

[0889] Data calculation: Calculate "daily reward of 80 yen" based on the achievement level.

[0890] Output: Returns the reward result to the server.

[0891] server:

[0892] Input: Receives the reward calculation results from the AI ​​model.

[0893] Data processing: Use the endpoint " / api / v1 / banking / cashback" to transfer 80 yen to the user's financial institution account.

[0894] Output: Notifies the terminal of the cashback execution result.

[0895] Device:

[0896] Enter: Receive cashback notifications.

[0897] Specific behavior: Notify the user that "You have received a cashback of 80 yen for achieving your exercise goal today."

[0898] Output: A cashback notification will appear on the screen.

[0899] (Application example 1)

[0900] 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."

[0901] Previous habit-forming systems lacked sufficient motivation to encourage users to continue newly established habits, making long-term habit formation particularly difficult. Furthermore, there was no system that accurately tracked users' progress or provided appropriate rewards. This made it difficult for users to continue the habit, often leading to abandonment. Furthermore, online education platforms and content distribution services lacked methods to encourage users to continue using the habit.

[0902] 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.

[0903] In this invention, the server includes an input means for a user to set a new habit and make a deposit, a means for the server to store the received data in a database, a means for tracking the user's habit progress, a means for an AI to analyze the progress data and evaluate the degree of habit achievement, a means for calculating a reward amount based on the evaluation result, a means for providing cashback to the user's financial account, an input means for setting a learning routine or a viewing routine as a habit set by the user, a means for the user to input or automatically track progress, and a means for notifying the user of progress and rewards. This allows users to form enjoyable and sustainable habits and encourages continued use of online education platforms and content distribution services.

[0904] A "user" is an individual who uses the system to set up new habits and track their progress.

[0905] A "habit" is an ongoing activity, such as a learning routine or viewing routine, that a user engages in regularly.

[0906] A "deposit" is an amount set by the user as an incentive to continue the habit.

[0907] "Progress" is data that shows the degree of achievement of the user's set habits.

[0908] "Tracking" refers to the system recording and monitoring the user's progress in achieving their habits.

[0909] A "server" is a computer system that receives and stores data sent by users and performs any necessary calculations or analyses.

[0910] "Database" means a digital storage system for storing user registration information, progress data, deposit information, reward information, etc.

[0911] "AI" refers to artificial intelligence that analyzes progress data, evaluates the degree of habit achievement, and calculates reward amounts.

[0912] "Rewards" are monetary incentives that users receive for completing their set habits.

[0913] "Cashback" refers to the actual amount of money transferred to a user's financial account based on the habits they achieve.

[0914] "Financial account" refers to a bank account, electronic money account, etc. that a user uses to receive cashback.

[0915] A "learning routine" refers to the regular execution of specific learning activities set by the user.

[0916] A "viewing routine" refers to the regular viewing of specific content set by a user.

[0917] The "input method" is the interface through which the user inputs new habits, deposit amounts, and progress.

[0918] "Notification" refers to the system sending messages to the user to inform them of progress, achievement of rewards, etc.

[0919] The present invention is a system involving three parties: a server, a terminal, and a user, and provides support for users to form new habits.

[0920] 1. Program Generation

[0921] The system consists of the following main components:

[0922] User device: a mobile device such as a smartphone or tablet.

[0923] Server: A computer system for processing and storing data.

[0924] AI model: An artificial intelligence program to assess habit completion.

[0925] 2. Natural language explanation

[0926] User registration and login

[0927] The terminal provides an interface where users can create a new account. The user enters their email address and password, which the server receives and stores in a database. Upon login, authenticated users are issued a token and taken to the dashboard screen.

[0928] Habit Setting and Deposits

[0929] The terminal presents a screen where the user can set up a new habit (e.g., 30 minutes of study per day or watching movies three times a week) and enter a deposit amount. The server stores this information in a database and returns a success message.

[0930] Habit Tracking

[0931] Users record their daily progress and send it from their device to the server. In some cases, progress data is tracked automatically. The server receives the progress data and sends it to the AI ​​model. The AI ​​model analyzes this data and evaluates the degree of habit achievement. The evaluation results are stored in a database and notified to the user.

[0932] Reward System

[0933] The AI ​​model calculates the reward amount based on the habit completion rate. The server receives the calculation result and issues a cashback to the user's financial account. The user can check their progress and reward achievement on their device.

[0934] 3. Hardware and Software Used

[0935] Smartphone app: Implemented using React Native and Flutter.

[0936] Server: Use Node.js or Django.

[0937] Database: Data is stored using PostgreSQL or MongoDB.

[0938] AI model: Use TensorFlow or PyTorch to assess habit completion.

[0939] Cashback API: Use Stripe or PayPal API to execute cashback.

[0940] Specific examples

[0941] Case 1: When you set a new habit of "studying English for 30 minutes every day" and set a deposit of 10,000 yen

[0942] 1. User Registration and Login

[0943] The device provides an interface for creating a new account, and the user enters the required information.

[0944] The server saves the input information in a database and returns a success message.

[0945] The terminal issues a token to the user and takes them to the dashboard screen.

[0946] 2. Habit setting and deposits

[0947] The device provides the user with a habit setting screen, where they input "30 minutes of English study every day" and "a deposit of 10,000 yen."

[0948] The server stores this information in a database and returns a success message.

[0949] 3. Habit Tracking

[0950] The terminal provides an interface for inputting the user's progress.

[0951] The server sends the received progress data to the AI ​​model and stores the evaluation results in a database.

[0952] The device notifies the user of the evaluation results.

[0953] 4. Reward System

[0954] The AI ​​model decides to set the daily reward at 100 yen.

[0955] The server calls the cashback API and transfers 100 yen to the user's financial account.

[0956] The device will notify you, "You have received a cash back of 100 yen for achieving today's learning goal."

[0957] Prompt Sentence Examples

[0958] Write a program that rewards users with 100 yen if they complete 30 minutes of English study every day.

[0959] This system allows users to form new habits in a fun and sustainable way, encouraging continued use of online education platforms and content delivery services.

[0960] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0961] Step 1:

[0962] User registration and login

[0963] Terminal: To create a new account, the user clicks the "Sign up" button on the screen and enters their email address and password. The entered data is sent to the server.

[0964] Server: Receives the input data, stores it in a database, verifies that the information entered is correct, and returns a success message if successful.

[0965] Output: A success message is printed to the terminal.

[0966] On the device: The user enters their email address and password on the login screen and sends them to the server, which authenticates the information and, if successful, generates a token and sends it to the device.

[0967] Input: User's email address and password

[0968] Output: Authentication token

[0969] Terminal: After receiving the authentication token, the user is taken to the dashboard screen and can use the system.

[0970] Step 2:

[0971] Habit Setting and Deposits

[0972] On the device: The user opens the "Set up a new habit" screen and enters the habit (e.g., study English for 30 minutes every day) and the deposit amount. The entered data is sent to the server.

[0973] Server: Receives the entered customs and deposit information, stores it in the database, and returns a success message.

[0974] Output: A success message is printed to the terminal.

[0975] Input: The new habit and deposit amount set by the user

[0976] Output: Success message

[0977] Step 3:

[0978] Habit Tracking

[0979] Device: To record daily progress, users open the "Progress Input" screen and enter the time spent studying and the content they have watched. The input data is sent to the server. In some cases, automatic tracking is also performed.

[0980] Input: User progress data (e.g., 30 minutes of study time)

[0981] Server: Receives progress data and sends it to the AI ​​model, which analyzes the data and evaluates the habit completion.

[0982] Output: Habit achievement evaluation results

[0983] AI model: Analyzes progress data and evaluates habit achievement, which is stored in a database.

[0984] Server: Stores the evaluation results in a database and sends the results to the device.

[0985] On device: Users will receive progress notifications and be able to track their progress.

[0986] Output: Habit completion assessment results sent to the user

[0987] Step 4:

[0988] Reward System

[0989] AI model: Calculates the reward amount based on the habit achievement level. For example, if the achievement level is 50%, set the daily reward to 100 yen.

[0990] Output: Reward amount

[0991] Server: Receives the reward amount and cashbacks the user's financial account. This is done using the Cashback API.

[0992] Input: Reward calculation result

[0993] Output: Cashback success / failure message

[0994] On your device: Display a cashback notification to the user. For example, "You've received a cashback of 100 yen for achieving today's learning goal."

[0995] Output: Cashback notification to be sent to the user

[0996] The system allows users to form new habits effectively and enjoyably, and keeps them motivated through rewards.

[0997] 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.

[0998] The present invention is a system designed to help users enjoy and continue new habits, and aims to increase motivation by taking into account the user's emotional state. This system tracks the habits set by the user and their progress, and provides monetary rewards based on the user's progress and emotional state. The program and specific processing of this system are described in detail below.

[0999] Program processing explanation

[1000] User registration and login

[1001] On the device: The user installs and launches the app, clicks the "Sign Up" button on the screen, and enters their email address and password.

[1002] Server: The server receives the input data and stores it in the database. If registration is successful, it returns a success message to the device.

[1003] Device: The user enters the registered email address and password on the login screen and clicks the login button. The server authenticates the entered information, and if authentication is successful, generates a token and sends it to the device.

[1004] Terminal: Receives the token, moves to the dashboard screen, and the user can use the system.

[1005] Habit Setting and Deposits

[1006] On the device: The user opens the "Set up a new habit" screen and enters the habit. For example, "30 minutes of exercise every day." Next, they enter the amount they want to deposit. For example, they enter "10,000 yen."

[1007] Server: The server receives the entered habits and deposit information, stores it in the database, and returns a success message to the terminal.

[1008] Terminal: Prompts the user that their habits and deposits have been set up.

[1009] Habit Tracking

[1010] On the device: To record their daily progress, users open the "Progress Input" screen in the app. For example, they enter "30 minutes of exercise today" and submit.

[1011] Server: The server receives the progress data and sends it to the AI ​​model.

[1012] AI model: The AI ​​model analyzes the progress data and evaluates the habit achievement, for example, rating it as "progressing as expected."

[1013] Server: The server stores the evaluation results in a database and sends the results to the device.

[1014] On your device: Notify users that their habit has been assessed and display their progress.

[1015] Reward System

[1016] AI model: The AI ​​model calculates the reward amount based on the habit achievement level. For example, it determines "50% achievement means 100 yen per day."

[1017] Server: The server receives the reward calculation results and executes cashback to the user's bank account.

[1018] On the device: Display a cashback notification to the user. For example, display a notification such as "You've received a cashback of 100 yen for achieving your exercise goal today."

[1019] Introducing the Emotion Engine

[1020] Recognition of emotional states

[1021] On the device: To record their emotional state, users can open the "Emotion Input" screen within the app and self-report their feelings. For example, they can enter "I'm happy today." Alternatively, the device can automatically recognize their emotional state from their facial expressions and voice.

[1022] Server: The server receives the emotion data and stores it in a database.

[1023] Emotional data analysis and reflection

[1024] AI model: Analyzes emotional data and evaluates how a user's emotional state affects habit completion.

[1025] Server: Adjusts reward amount and motivational message based on the evaluation results.

[1026] Device: Display an appropriate motivational message to the user, for example, "You're working especially hard today!"

[1027] Linking cashback and emotional states

[1028] AI model: Calculates the optimal reward amount based on emotional data and habit completion. For example, it determines that "the user's emotional state is high, so an additional 20 yen cashback will be given."

[1029] Server: Receives the reward calculation results and sends the cashback to the user's bank account.

[1030] Device: Display a cashback notification to the user along with a pleasurable message based on their emotional state. For example, "You've received a cashback of 120 yen because you achieved your exercise goal today and are feeling happy."

[1031] Specific examples

[1032] Case 2: Using the Emotion Engine to set the habit "30 minutes of exercise every day" and set a deposit of 10,000 yen

[1033] 1. User Registration and Login

[1034] Device: Yamada launches the app and clicks "New Registration."

[1035] Device: Yamada enters her email address and password and clicks "Register."

[1036] Server: Saves the input data and returns a success message.

[1037] Device: Yamada enters her email address and password on the login screen and clicks "Login."

[1038] Server: The server generates an authentication token and sends it to the device.

[1039] Device: Yamada's device receives the token and transitions to the dashboard.

[1040] 2. Habit setting and deposits

[1041] Device: Yamada enters "30 minutes of exercise every day" in "Set a new habit" and clicks "Next."

[1042] Terminal: Enter the deposit amount "10,000 yen" and click "Complete".

[1043] Server: The server saves the information and returns a completion message.

[1044] Device: Yamada's device will display a message indicating that the setup is complete.

[1045] 3. Habit Tracking

[1046] Device: Yamada enters "30 minutes of exercise" in "Enter progress" and submits.

[1047] Server: The server stores the data and sends it to the AI ​​model.

[1048] AI model: The AI ​​model analyzes the progress and sends the evaluation results to the server.

[1049] Server: The server notifies Yamada's device of the evaluation results.

[1050] Device: Yamada's device displays the progress and evaluation results.

[1051] 4. Emotional state input and analysis

[1052] Device: Yamada inputs "Happy" in the "Emotion Input" field and sends it. Alternatively, the device will analyze his facial expressions and voice to recognize his emotions.

[1053] Server: The server stores the emotion data and sends it to the AI ​​model.

[1054] AI model: The AI ​​model analyzes the emotional data and evaluates it to reflect the habit achievement level.

[1055] Server: Adjusts reward amount and motivational message based on the evaluation results.

[1056] 5. Linking reward systems and emotional states

[1057] AI model: The AI ​​model determines the cashback of 100 yen + an additional 20 yen based on the emotional state and habit completion level.

[1058] Server: Save the reward amount, call the cashback API, and transfer 120 yen to Yamada's bank account.

[1059] Device: Yamada's device notifies him that the cashback has been completed and displays a pleasant message: "You've received a cashback of 120 yen because you achieved your exercise goal today and felt good."

[1060] This specific processing step allows users to pursue new habits in a fun way while receiving optimal rewards according to their emotional state.

[1061] The processing flow will be explained below.

[1062] Program processing details

[1063] User registration and login

[1064] Step 1:

[1065] On the device: The user installs and launches the app. They click the "Sign up" button.

[1066] Step 2:

[1067] Device: The user enters their email address and password and clicks the "Register" button.

[1068] Step 3:

[1069] Server: Receives input data and saves it in the database. If registration is successful, returns a success message to the device.

[1070] Step 4:

[1071] Device: The user enters the registered email address and password on the login screen and clicks the "Login" button.

[1072] Step 5:

[1073] Server: Authenticates the input information, and if successful, generates an authentication token and sends it to the device.

[1074] Step 6:

[1075] Terminal: Receive the token and proceed to the dashboard screen.

[1076] Habit Setting and Deposits

[1077] Step 1:

[1078] On the device: The user opens the "Set up a new habit" screen and enters "30 minutes of exercise daily." They then click the Next button.

[1079] Step 2:

[1080] Terminal: The user enters the amount to deposit (10,000 yen). Then clicks the Complete button.

[1081] Step 3:

[1082] Server: Receives the habit and deposit information, stores it in the database, and returns a success message to the terminal.

[1083] Step 4:

[1084] Terminal: Prompts the user that their habits and deposit setup is complete.

[1085] Habit Tracking

[1086] Step 1:

[1087] Device: The user opens the "Enter Progress" screen, enters today's exercise time as "30 minutes," and clicks the submit button.

[1088] Step 2:

[1089] Server: Receives progress data and stores it in a database.

[1090] Step 3:

[1091] Server: Sends saved progress data to the AI ​​model.

[1092] Step 4:

[1093] AI model: Analyzes the received data and evaluates it as "progressing as expected."

[1094] Step 5:

[1095] AI model: Sends the evaluation results to the server.

[1096] Step 6:

[1097] Server: Saves the evaluation results in a database and notifies the terminal of the evaluation results.

[1098] Step 7:

[1099] Device: Shows the user today's progress and assessment results.

[1100] Reward System

[1101] Step 1:

[1102] AI model: Calculates reward amount based on habit achievement. For example, "For 50% achievement, a cashback of 100 yen will be given."

[1103] Step 2:

[1104] AI model: Sends the calculation results to the server.

[1105] Step 3:

[1106] Server: Stores the reward amount in the database.

[1107] Step 4:

[1108] Server: Calls the API to execute the cashback and transfers the money to the user's bank account.

[1109] Step 5:

[1110] On the device: Display a cashback notification to the user, for example, "You've received a cashback of 100 yen for achieving your exercise goal today."

[1111] Introducing the Emotion Engine

[1112] Step 1:

[1113] On the device: The user opens the "Emotion Input" screen and reports their feelings. For example, they can type "I'm happy today." Alternatively, the device can automatically recognize their emotional state from their facial expressions and voice.

[1114] Step 2:

[1115] Server: The server receives the emotion data and stores it in a database.

[1116] Step 3:

[1117] AI model: Analyzes emotional data and evaluates how a user's emotional state affects habit completion.

[1118] Step 4:

[1119] Server: Adjusts reward amount and motivational message based on the evaluation results.

[1120] Step 5:

[1121] Device: Display an appropriate motivational message to the user, for example, "You're working especially hard today!"

[1122] Step 6:

[1123] AI model: Calculates the optimal reward amount based on emotional data and habit completion. For example, it determines that "the user's emotional state is high, so an additional 20 yen cashback will be given."

[1124] Step 7:

[1125] Server: Saves the reward calculation results in the database, calls the cashback API, and transfers the money to the user's bank account.

[1126] Step 8:

[1127] Device: Display a cashback notification to the user along with a pleasurable message based on their emotional state. For example, a notification like "You've received a cashback of 120 yen because you achieved your exercise goal today and are feeling happy" will be displayed.

[1128] Specific examples

[1129] Case 1: Using the Emotion Engine, you set the habit "30 minutes of exercise every day" and set a deposit of 10,000 yen.

[1130] 1. User Registration and Login

[1131] Step 1: Yamada launches the app and clicks "New Registration."

[1132] Step 2: Sam enters her email address and password and clicks "Register."

[1133] Step 3: The server saves the data and returns a success message.

[1134] Step 4: On the login screen, Yamada enters her email address and password and clicks "Login."

[1135] Step 5: The server generates an authentication token and sends it to the device.

[1136] Step 6: Yamada's device receives the token and goes to the dashboard.

[1137] 2. Habit setting and deposits

[1138] Step 1: Yamada enters "30 minutes of exercise every day" in "Set a new habit" and clicks "Next."

[1139] Step 2: Enter the deposit amount "10,000 yen" and click "Complete".

[1140] Step 3: The server saves the information and returns a completion message.

[1141] Step 4: Yamada's device will display a message that the setup is complete.

[1142] 3. Habit Tracking

[1143] Step 1: Yamada enters "30 minutes of exercise" in "Enter progress" and submits it.

[1144] Step 2: The server stores the data and sends it to the AI ​​model.

[1145] Step 3: The AI ​​model analyzes the progress and sends the evaluation results to the server.

[1146] Step 4: The server notifies Yamada's device of the evaluation results.

[1147] Step 5: Yamada's device displays the progress and evaluation results.

[1148] 4. Emotional state input and analysis

[1149] Step 1: Yamada inputs "I'm happy today" in "Emotion Input" and sends it. Alternatively, the device will analyze facial expressions and voice to recognize the emotion.

[1150] Step 2: The server stores the emotion data and sends it to the AI ​​model.

[1151] Step 3: The AI ​​model analyzes the emotional data and evaluates it to reflect the habit completion level.

[1152] Step 4: The server adjusts the reward amount and motivational message based on the evaluation results.

[1153] 5. Linking reward systems and emotional states

[1154] Step 1: The AI ​​model determines the cashback of 100 yen + an additional 20 yen based on the emotional state and habit completion.

[1155] Step 2: The server stores the reward amount in the database.

[1156] Step 3: Call the cashback API and transfer 120 yen to Yamada's bank account.

[1157] Step 4: Yamada's device notifies him that the cashback has been completed and displays a pleasant message: "You've received a cashback of 120 yen because you achieved your exercise goal today and felt happy."

[1158] This specific processing step allows users to pursue new habits in a fun way while receiving optimal rewards according to their emotional state.

[1159] Example 2

[1160] 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."

[1161] Conventional systems for forming new habits primarily record the user's progress and provide rewards based on the level of achievement. However, these systems have the problem of making it difficult to maintain motivation because they do not take into account the user's emotional state. There is a need for a system that can support more effective habit formation by appropriately responding to the user's emotional state.

[1162] 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.

[1163] In this invention, the server includes input means for the user to set a new habit and make a deposit, means for the server to store the received data in a database, means for tracking the user's habit progress, means for the generative AI model to analyze the progress data and evaluate the habit achievement level, means for calculating a reward amount based on the evaluation results, means for executing cashback to the user's bank account, input means for recording the user's emotional state, means for the terminal to automatically recognize the user's emotional state from the user's facial expressions and voice, and means for receiving and analyzing the emotional data and adjusting the reward amount and motivational message based on the evaluation results. This makes it possible to adjust the optimal reward amount according to the user's emotional state, enabling the user to form a new habit while maintaining motivation.

[1164] "User" refers to an individual who is the intended user of this system.

[1165] Habits are activities or behaviors that users plan to perform on a daily basis.

[1166] A "deposit" is the amount a user pays upfront to receive financial rewards for the habits they set.

[1167] "Input means" refers to the interface or device through which a user inputs data into a system.

[1168] "Server" refers to a computer system that receives, processes, and stores data submitted by users.

[1169] A "database" refers to a digital storage device for efficiently storing and managing data collected within a system.

[1170] "Tracking" refers to the continuous recording and monitoring of a user's habit progress and activities.

[1171] A "generative AI model" refers to an artificial intelligence algorithm that analyzes collected data, calculates the degree of habit completion and reward amount, and evaluates the user's emotional state.

[1172] "Analysis" refers to the process of examining collected data in detail to understand its content and patterns.

[1173] "Habit completion level" refers to an indicator that shows the extent to which a user has achieved the habits they have set.

[1174] "Evaluation results" refer to the conclusions reached based on the habit achievement and emotional state analyzed by the generative AI model.

[1175] "Reward amount" refers to the monetary reward the system provides to the user based on the user's level of habit achievement.

[1176] "Cashback" refers to the process of returning reward amounts to the user's bank account.

[1177] "Emotional state" refers to information that indicates the user's current psychological feelings.

[1178] "Facial Expression" refers to a user's facial expression that is used to recognize the user's emotional state.

[1179] "Voice" refers to audio data used to recognize the user's emotional state.

[1180] "Motivational messages" refer to messages provided by the system to motivate users and encourage them to continue using the system.

[1181] "Behavioral patterns" refers to data that shows a user's past activities and behavioral tendencies.

[1182] The present invention is a system designed to help users enjoy and continue new habits, and aims to increase motivation by taking into account the user's emotional state. The system tracks the user's established habits and their progress, and provides monetary rewards according to the user's progress and emotional state. Specific embodiments for implementing the present invention are described in detail below.

[1183] User registration and login

[1184] A user installs and launches the application on a device such as a smartphone or tablet. First, the user clicks the "New Registration" button and enters their email address and password. The server receives this input data and stores it in a database. If registration is successful, a success message is returned to the device. Next, the user enters their email address and password on the login screen and clicks the login button. The server authenticates the entered information, and if authentication is successful, generates a token and sends it to the device. The user receives the token and can proceed to the dashboard screen to use the system.

[1185] Habit Setting and Deposits

[1186] The user opens the "Setting a new habit" screen and enters the specific habit. For example, the user can enter "30 minutes of exercise every day." The user then enters the amount to deposit, for example, "10,000 yen." The server receives this input data and stores it in the database. After a success message is returned to the terminal, the user can confirm that the setup is complete.

[1187] Habit Tracking

[1188] To record their daily progress, users open the "Progress Input" screen in the app, enter progress information (for example, "30 minutes of exercise today") and submit it. The server receives the progress data and sends it to the generative AI model. The generative AI model analyzes the progress data and evaluates the degree of habit achievement. For example, the generative AI model may evaluate the progress as "progressing as expected." This evaluation result is sent to the server and stored in a database. Finally, the result is notified to the user's device, allowing the user to check their progress.

[1189] Reward System

[1190] The generative AI model calculates the reward amount based on the degree of habit achievement. For example, it may determine "100 yen as the daily reward for achieving 50%." The server receives the reward calculation results and executes a cashback to the user's bank account. The user can check the cashback notification on their device. For example, it may display "100 yen has been cashbacked for achieving today's exercise goal."

[1191] Introducing the Emotion Engine

[1192] Recognition of emotional states

[1193] To record their emotional state, users can open the "Emotion Input" screen in the app and self-report their feelings. For example, they can enter "I'm happy today." Alternatively, the device can automatically recognize their emotional state from their facial expressions and voice. The server receives the emotional data and stores it in a database.

[1194] Emotional data analysis and reflection

[1195] The generative AI model analyzes the emotional data and evaluates how the user's emotional state affects their habit achievement. The server then adjusts the reward amount and motivational message based on the evaluation results. For example, it displays an appropriate motivational message to the user, such as, "You're working especially hard today!"

[1196] Linking cashback and emotional states

[1197] The generative AI model calculates the optimal reward amount based on emotional data and the degree of habit achievement. For example, it may decide to "give the user an additional 20 yen cashback because their emotions are high." The server receives the reward calculation results and executes the cashback into the user's bank account. The user receives a cashback notification on their device, and a motivational message based on their emotional state is also displayed. For example, it may say, "You've received a cashback of 120 yen because you achieved your exercise goal today and felt happy."

[1198] Specific examples

[1199] Prompt Sentence Examples

[1200] Please enter your new email address and password to register.

[1201] "Enter the specific habit and amount to set up a new habit and make a deposit."

[1202] "Record your progress today on the progress entry screen and press the submit button."

[1203] "Enter your emotional state for the day on the emotion input screen, or have it recognized automatically by analyzing your facial expressions and voice."

[1204] The present invention allows users to enjoyably pursue new habits while receiving optimal rewards according to their emotional state.

[1205] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1206] Step 1:

[1207] The user installs and launches the application. They click the "New Registration" button on the screen and enter their email address and password. The entered data is sent from the device to the server. The server stores the received data in a database and returns a success message indicating that registration was successful.

[1208] Step 2:

[1209] The user enters the registered email address and password on the login screen and clicks the login button. The input data is sent from the terminal to the server. The server compares the received data with the database, and if authentication is successful, generates an authentication token and sends it to the terminal. The user receives the token, moves to the dashboard screen, and can use the system.

[1210] Step 3:

[1211] The user opens the "Setting a new habit" screen and enters the specific habit. Next, they enter the amount they want to deposit. The entered data is sent from the device to the server. The server stores the received habit and deposit information in a database and returns a success message. The user can confirm that the setup is complete.

[1212] Step 4:

[1213] To record their daily progress, users open the "Progress Input" screen in the app, enter their progress information, and submit it. The input data is sent from the device to the server. The server then sends the progress data to the generative AI model, which analyzes it. The generative AI model analyzes the progress data and evaluates the degree of habit achievement. The evaluation results are sent to the server and stored in a database. The server then sends the evaluation results to the user's device, allowing the user to check their progress and evaluation results.

[1214] Step 5:

[1215] The generative AI model calculates the reward amount based on the degree of habit achievement. For example, if 50% achievement is achieved, it determines the daily reward to be 100 yen. The calculation result is sent to the server, which then executes a cashback to the user's bank account. The user receives a cashback notification on their device. For example, it displays a message saying, "You have received a cashback of 100 yen for achieving today's exercise goal."

[1216] Step 6:

[1217] To record their emotional state, users can open the "Emotion Input" screen in the app and self-report their emotional state. Alternatively, the device can automatically recognize their emotional state from their facial expressions and voice. Emotion data is sent from the device to a server, which then stores the data in a database.

[1218] Step 7:

[1219] The generative AI model analyzes the emotional data and evaluates how the user's emotional state affects their habit achievement. The analysis results are sent to the server, which adjusts the reward amount and motivational message based on the evaluation results. The server then sends the adjustment results to the user's device, and the user is notified with an appropriate motivational message. For example, "You're working especially hard today!"

[1220] Step 8:

[1221] The generative AI model calculates the optimal reward amount based on emotional data and the degree of habit achievement. For example, it may decide to "give the user an additional 20 yen cashback because their emotions are high." The calculation result is sent to the server, which then deposits the cashback into the user's bank account. The user receives a cashback notification on their device, and a motivational message based on their emotional state is also displayed. For example, it may say, "You've received a cashback of 120 yen because you achieved your exercise goal today and felt happy."

[1222] (Application example 2)

[1223] 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."

[1224] Conventional habit formation support systems only evaluate users' achievements without considering their emotional state, which makes it difficult to maintain motivation. Furthermore, the reward system is limited, making it ineffective in promoting actual behavioral change. Furthermore, the system does not consider providing incentives through collaboration with virtual stores, limiting its effectiveness as a means of helping users establish new habits in a fun way.

[1225] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1226] In this invention, the server includes an input means for a user to set a new habit and make a deposit, a means for the server to store the received data in a database, a means for tracking the user's habit progress, a means for an AI to analyze the progress data and evaluate the degree of habit achievement, a means for calculating a reward amount based on the evaluation result, a means for providing cashback to the user's bank account, a means for receiving the reward in the virtual store, and a means for recognizing the user's emotional state and adjusting the reward amount based thereon, thereby enabling the user to continue the new habit while enjoying it and receive individual incentives according to their emotional state.

[1227] "User" refers to a person who uses the System to set new habits and track their progress.

[1228] Habits are new behaviors or activities that users incorporate into their daily lives, such as exercising or reading.

[1229] A "deposit" refers to the amount of money a user deposits in advance to receive rewards based on the progress of the habits they set.

[1230] "Input means" refers to the interface that allows users to set habits, enter progress, and record emotional states.

[1231] "Server" refers to the central system that receives, processes, and stores data entered by users in a database.

[1232] "Database" refers to the system for storing and managing User habits, progress, and emotional data.

[1233] "Tracking Method" refers to the method by which a User records their daily progress and transmits that data to a server.

[1234] "AI" refers to artificial intelligence technology that analyzes progress and emotional data to evaluate the user's level of habit achievement and reward amount.

[1235] "Habit completion" refers to an indicator that evaluates the degree to which a user has achieved the habits they have set.

[1236] "Reward amount" refers to a monetary incentive calculated based on the user's habit completion.

[1237] "Cashback" refers to money that is transferred to a user's bank account when they complete a habit, based on their level of achievement.

[1238] "Virtual store" refers to an online shopping platform where users can use rewards to purchase goods and services.

[1239] "Emotional state" refers to data that indicates a user's current emotions, and refers to information obtained through self-reporting, facial expression recognition, etc.

[1240] The system that realizes this application example is composed of various hardware and software components that work together to enable users to continue their new habits in an enjoyable way. Specific embodiments of each part of the system are described below.

[1241] Hardware and software used

[1242] Hardware: Smartphone (including facial recognition and voice recognition functions via camera), server

[1243] software:

[1244] Platform: Android, iOS

[1245] Backend: Firebase, Google Cloud, AWS

[1246] AI model: TensorFlow, OpenAI GPT-3

[1247] Database: Firebase Firestore, MySQL

[1248] Frontend: React Native

[1249] Emotion recognition: Affectiva SDK, Google Cloud Vision API

[1250] Specific processing

[1251] User registration and login

[1252] A user installs the application on their smartphone and registers by entering their email address and password. The server receives this information, authenticates the user information using Firebase Auth, generates an authentication token, and returns it to the user's device, allowing the user to log in and use the system.

[1253] Setting a new habit and depositing

[1254] The user is presented with an interface to set up a new habit and enter the deposit amount, which the server receives and stores in Firebase Firestore. Based on this information, the user can enjoyably pursue the habit they set up.

[1255] Habit completion and emotional state tracking

[1256] Users enter their daily progress on their smartphones and send it to a server. The server then sends this data to an AI model that uses TensorFlow to analyze habit completion. The system also tracks the user's emotional state. It uses Google Cloud Vision API and Affectiva SDK to recognize emotions from facial expressions and voice. This data is stored in Firebase Firestore for later analysis.

[1257] Reward systems and virtual stores

[1258] Based on the evaluation results, the AI ​​model calculates the reward amount, taking into account the progress data and emotional state. The reward is not only cashed back into the user's bank account, but also provided as a coupon that can be used in virtual stores, allowing users to purchase products and services in the virtual stores.

[1259] Example: Yamada's case

[1260] For example, let's say a user wants to make reading 30 minutes a day a habit and uses this system. The user installs the app, creates an account, and logs in. Then, they set up the habit of "reading 30 minutes a day" and enter a deposit of 5,000 yen. By recording their daily progress and entering their emotional state, the system calculates rewards based on their habit achievement and emotional state. The user can then use coupons to purchase products in the virtual store.

[1261] Prompt Sentence Examples

[1262] To help users develop literacy habits, VirtuHabit implements an in-app system that evaluates progress and rewards users based on their emotional state, such as coupons and special offers for virtual stores.

[1263] Thus, the present invention provides a system that allows users to enjoyably continue new habits and receive rewards according to their emotional state.

[1264] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1265] Step 1:

[1266] User registration and login

[1267] Input: Email address, Password

[1268] Server: The user installs the application and enters their email address and password on the registration screen. The server registers the user information using Firebase Auth and generates an authentication token. The authentication token is sent to the device.

[1269] Output: Authentication token

[1270] Step 2:

[1271] Setting a new habit and depositing

[1272] Input: Habit name, Deposit amount

[1273] Device: The user enters the name of the habit, such as "30 minutes of exercise every day," and the deposit amount (e.g., 10,000 yen) on the habit setting screen. This is then sent to the server.

[1274] Server: The server stores the received habit information and deposit amount in Firebase Firestore.

[1275] Output: Save complete message

[1276] Step 3:

[1277] Habit Tracking

[1278] Input: Daily progress data (e.g., "Today's exercise time: 30 minutes")

[1279] Terminal: The user enters progress data on the progress input screen and sends it to the server.

[1280] Server: The server receives this progress data, sends it to the AI ​​model for analysis, evaluates habit completion using TensorFlow, and sends the results back to the server, which stores the results in Firebase Firestore.

[1281] Output: Progress evaluation results

[1282] Step 4:

[1283] Emotional state tracking

[1284] Input: Emotion data (e.g., "I feel happy today"), face image, or voice

[1285] Device: The user inputs their emotional state on the emotion input screen, captures a facial image with the device camera, or records a voice, which is then sent to the server.

[1286] Server: The server sends facial images and audio data to the Google Cloud Vision API and Affectiva SDK, analyzes the emotional state, and stores the results in Firebase Firestore.

[1287] Output: Emotion evaluation result

[1288] Step 5:

[1289] Reward calculation and cashback

[1290] Input: Habit achievement assessment results, emotional assessment results

[1291] Server: The server uses an AI model (TensorFlow) to calculate the optimal reward amount based on the progress data and emotional state. The calculation result is cashed back to the user's bank account.

[1292] Output: Cashback completion notification, reward amount

[1293] Step 6:

[1294] Use rewards in virtual stores

[1295] Input: Reward amount, shopping information at virtual store

[1296] Terminal: Users can select products and services in a virtual store and purchase them using their reward amount.

[1297] Server: The server receives the purchase information and updates the reward amount usage to Firebase Firestore.

[1298] Output: Purchase complete notification, updated balance

[1299] This allows users to enjoy new habits, continue them, and receive personalized incentives based on their emotional state.

[1300] 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.

[1301] 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.

[1302] 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.

[1303] [Third embodiment]

[1304] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1305] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1306] 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).

[1307] 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.

[1308] 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.

[1309] 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).

[1310] 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.

[1311] 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.

[1312] 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.

[1313] 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.

[1314] 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.

[1315] 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."

[1316] This invention is a system that provides financial incentives to help users enjoyably continue new habits and supports the habit-forming process. This system tracks the habits set by the user and their progress in achieving them, and provides monetary rewards according to the degree of progress. The program and specific processing of this system are described in detail below.

[1317] Program processing explanation

[1318] User registration and login

[1319] On the device: The user installs and launches the app, clicks the "Sign Up" button on the screen, and enters their email address and password.

[1320] Server: The server receives the input data, stores it in the database, and returns a success message to the terminal if the registration is successful.

[1321] Device: The user enters the registered email address and password on the login screen and clicks the login button. The server authenticates the entered information, and if authentication is successful, generates a token and sends it to the device.

[1322] Terminal: Receives the token, moves to the dashboard screen, and the user can use the system.

[1323] Habit Setting and Deposits

[1324] On the device: The user opens the "Set up a new habit" screen and enters the habit. For example, they might enter "30 minutes of exercise every day." Then they enter the amount they want to deposit. For example, they enter "10,000 yen."

[1325] Server: The server receives the entered habits and deposit information, stores it in the database, and returns a success message to the terminal.

[1326] Terminal: Prompts the user that their habits and deposits have been set up.

[1327] Habit Tracking

[1328] On the device: To record their daily progress, users open the "Progress Input" screen in the app. For example, they enter "30 minutes of exercise today" and submit.

[1329] Server: The server receives the progress data and sends it to the AI ​​model.

[1330] AI model: The AI ​​model analyzes the progress data and evaluates the habit achievement, for example, rating it as "progressing as expected."

[1331] Server: The server stores the evaluation results in a database and sends the results to the device.

[1332] On your device: Notify users that their habit has been assessed and display their progress.

[1333] Reward System

[1334] AI model: The AI ​​model calculates the reward amount based on the habit achievement level. For example, it determines "50% achievement means 100 yen per day."

[1335] Server: The server receives the reward calculation results and executes cashback to the user's bank account.

[1336] On the device: Display a cashback notification to the user. For example, display a notification such as "You've received a cashback of 100 yen for achieving your exercise goal today."

[1337] Specific examples

[1338] Case 1: When you set a new habit "exercise 30 minutes a day" and set a deposit of 10,000 yen

[1339] 1. User Registration and Login

[1340] Device: David launches the app and enters the required information to create a new account.

[1341] Server: The server receives the input information, stores it in a database, and returns a success message.

[1342] Device: Yamada enters her email address and password on the login screen and obtains an authentication token.

[1343] 2. Habit setting and deposits

[1344] Device: Yamada sets "30 minutes of exercise every day" and deposits 10,000 yen.

[1345] Server: The server receives and stores this information and returns a completion message.

[1346] 3. Habit Tracking

[1347] Device: Yamada enters today's exercise time as "30 minutes" and submits.

[1348] Server: The server receives the progress data and has the AI ​​model evaluate it.

[1349] AI model: The AI ​​model evaluates the results as "Progressing as expected" and saves them.

[1350] Server: The server notifies Yamada's device of the evaluation results.

[1351] 4. Reward System

[1352] AI model: The AI ​​model decides to give a cashback of 100 yen as a reward for one day.

[1353] Server: The server calls the cashback API and transfers 100 yen to Yamada's bank account.

[1354] Device: Notify "You've received a cashback of 100 yen for achieving your exercise goal today."

[1355] Through this specific process, users can develop new habits in a fun and efficient way.

[1356] The processing flow will be explained below.

[1357] Program processing details

[1358] User registration and login

[1359] Step 1:

[1360] On the device: The user installs and launches the app. They click the "Sign up" button.

[1361] Step 2:

[1362] Device: The user enters their email address and password and clicks the "Register" button.

[1363] Step 3:

[1364] Server: Receives input data and saves it in the database. If registration is successful, returns a success message to the device.

[1365] Step 4:

[1366] On the device: The user enters their email address and password on the login screen and clicks the "Login" button.

[1367] Step 5:

[1368] Server: Authenticates the input information, and if successful, generates an authentication token and sends it to the device.

[1369] Step 6:

[1370] Terminal: Receive the token and proceed to the dashboard screen.

[1371] Habit Setting and Deposits

[1372] Step 1:

[1373] On the device: The user opens the "Set up a new habit" screen and enters "30 minutes of exercise daily." They then click the Next button.

[1374] Step 2:

[1375] Terminal: The user enters the amount to deposit (10,000 yen). Then clicks the Complete button.

[1376] Step 3:

[1377] Server: Receives the habit and deposit information, stores it in the database, and returns a success message to the terminal.

[1378] Step 4:

[1379] Terminal: Prompts the user that their habits and deposit setup is complete.

[1380] Habit Tracking

[1381] Step 1:

[1382] Device: The user opens the "Enter Progress" screen, enters today's exercise time as "30 minutes," and clicks the submit button.

[1383] Step 2:

[1384] Server: Receives progress data and stores it in a database.

[1385] Step 3:

[1386] Server: Sends saved progress data to the AI ​​model.

[1387] Step 4:

[1388] AI model: Analyzes the received data and evaluates it as "progressing as expected."

[1389] Step 5:

[1390] AI model: Sends the evaluation results to the server.

[1391] Step 6:

[1392] Server: Saves the evaluation results in a database and notifies the terminal of the evaluation results.

[1393] Step 7:

[1394] Device: Shows the user today's progress and assessment results.

[1395] Reward System

[1396] Step 1:

[1397] AI model: Calculates reward amount based on habit achievement. For example, "For 50% achievement, a cashback of 100 yen will be given."

[1398] Step 2:

[1399] AI model: Sends the calculation results to the server.

[1400] Step 3:

[1401] Server: Stores the reward amount in the database.

[1402] Step 4:

[1403] Server: Calls the API to execute the cashback and transfers the money to the user's bank account.

[1404] Step 5:

[1405] On the device: Display a cashback notification to the user, for example, "You've received a cashback of 100 yen for achieving your exercise goal today."

[1406] Specific examples

[1407] Case 1: When you set a new habit "exercise 30 minutes a day" and set a deposit of 10,000 yen

[1408] 1. User Registration and Login

[1409] Step 1: Yamada launches the app and clicks "New Registration."

[1410] Step 2: Sam enters her email address and password and clicks "Register."

[1411] Step 3: The server saves the data and returns a success message.

[1412] Step 4: On the login screen, Yamada enters her email address and password and clicks "Login."

[1413] Step 5: The server generates an authentication token and sends it to the device.

[1414] Step 6: Yamada's device receives the token and is redirected to the dashboard.

[1415] 2. Habit setting and deposits

[1416] Step 1: Yamada enters "30 minutes of exercise every day" in "Set a new habit" and clicks "Next."

[1417] Step 2: Enter the deposit amount "10,000 yen" and click "Complete".

[1418] Step 3: The server saves the information and returns a completion message.

[1419] Step 4: Yamada's device will display a message that the setup is complete.

[1420] 3. Habit Tracking

[1421] Step 1: Yamada enters "30 minutes of exercise" in "Enter progress" and submits it.

[1422] Step 2: The server stores the data and sends it to the AI ​​model.

[1423] Step 3: The AI ​​model analyzes the progress and sends the evaluation results to the server.

[1424] Step 4: The server notifies Yamada's device of the evaluation results.

[1425] Step 5: Yamada's device displays the progress and evaluation results.

[1426] 4. Reward System

[1427] Step 1: The AI ​​model determines the cashback of 100 yen based on the achievement level.

[1428] Step 2: The server stores the reward amount in the database.

[1429] Step 3: Call the cashback API and transfer 100 yen to Yamada's bank account.

[1430] Step 4: Yamada's device will notify him that the cashback has been completed.

[1431] This specific processing step allows users to enjoyably pursue new habits while earning financial rewards.

[1432] Example 1

[1433] 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."

[1434] In modern society, it is difficult for users to form and maintain new habits. Effective methods for maintaining sustained motivation are scarce, and methods for utilizing economic incentives are limited. Furthermore, current systems lack mechanisms for tracking user progress and providing rewards based on that progress, making it difficult to maintain motivation for habit formation.

[1435] 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.

[1436] In this invention, the server includes an input means for a user to set a new habit and make a deposit, a means for the server to store the received data in a database, a means for tracking the user's habit progress, a means for an AI to analyze the progress data and evaluate the degree of habit achievement, a means for calculating a reward amount based on the evaluation result, a means for executing cashback to the user's financial institution account, and an authentication means for enabling the user to log in and use the system using a token. This allows the user to continue a new habit in a fun way and form a habit while receiving economic incentives.

[1437] "Input" is the interface on the system through which users can set new habits and make deposits.

[1438] A "database" is an information management system that stores and manages data received by a server.

[1439] "Tracking Tools" are features that allow users to monitor and record their habit progress.

[1440] The "AI model" is an artificial intelligence model that analyzes progress data and evaluates the user's level of habit achievement.

[1441] The "evaluation method" is a function for determining the degree of habit achievement based on the results of analysis by the AI ​​model.

[1442] The "remuneration calculation means" is a function for calculating the amount of remuneration to be provided to the user based on the evaluation results.

[1443] "Cashback method" is a system function that actually transfers rewards to the user's financial institution account.

[1444] "Authentication means" is a security feature that allows users to log in using a token and access the system.

[1445] The present invention is a system that provides economic incentives to users to help them continue new habits in a fun way and supports the habit formation process. The system receives user input, manages and analyzes data using a server and an AI model, evaluates the user's habit achievement, and provides rewards. Details of the system's program and the specific form of its processing are described below.

[1446] Handling user registration and login

[1447] Terminal: The user installs and launches the application. They click the "New Registration" button on the screen and enter their email address and password. This input method allows the user to create a new account within the system. For example, they enter the email address "example@example.com" and the password "password123."

[1448] Server: The server receives the entered data and stores it in the database. It executes the query "INSERT INTO users (email, password) VALUES ('example@example.com', 'password123');" and returns a success message to the terminal if registration is successful.

[1449] Terminal: The user enters the registered email address and password on the login screen and clicks the login button. The server authenticates the entered information, and if authentication is successful, generates a token and sends it to the terminal. The terminal receives this token, transitions to the dashboard screen, and the user can use the system.

[1450] Setting habits and processing deposits

[1451] On the device: The user opens the "Set up a new habit" screen and enters the habit. For example, they might enter "30 minutes of exercise every day," then enter the amount they want to deposit. For the deposit amount, they enter "10,000 yen."

[1452] Server: The server receives the entered habit and deposit information and stores it in the database. It executes the query "INSERT INTO habits (user_id, habit_detail, deposit_amount) VALUES (1, '30 minutes of exercise daily', 10000);" and returns a success message.

[1453] Terminal: Prompts the user that their habits and deposits have been set up.

[1454] Handling habit completion tracking

[1455] On the device: To record their daily progress, users open the "Progress Input" screen in the app. For example, they enter "30 minutes of exercise today" and submit.

[1456] Server: The server receives the progress data and sends it to the AI ​​model through the endpoint " / api / v1 / progress / evaluate".

[1457] AI model: The AI ​​model analyzes the progress data and evaluates the habit achievement level. For example, it evaluates the habit achievement level as "80%" based on the progress data.

[1458] Server: Save the evaluation results in the database and use the query "UPDATE progress SET evaluation = 'Habit achievement level 80%' WHERE user_id = 1;". The evaluation results are notified to the device.

[1459] On your device: Notify users that their habit has been assessed and display their progress.

[1460] Reward system processing

[1461] AI model: The AI ​​model calculates the reward amount based on the habit completion rate. For example, it determines "80 yen as the daily reward."

[1462] Server: Receives the reward calculation result and executes cashback to the user's financial institution account using the endpoint " / api / v1 / banking / cashback".

[1463] On the device: Notify the user that the cashback has been applied. For example, display a notification such as "You've received a cashback of 80 yen for achieving your exercise goal today."

[1464] Examples of concrete examples and prompts

[1465] To generate a prompt, enter the following:

[1466] Set a new habit of "30 minutes of exercise every day" and set a deposit of 10,000 yen. Then, record "30 minutes of exercise today" on the progress entry screen in the app, and explain how your habit achievement will be evaluated and how you will be rewarded.

[1467] Based on these prompts, the AI ​​model generates concrete examples to help users maintain their new habits in a fun and efficient way. The system is designed to encourage users to proactively establish new habits and achieve their goals while enjoying financial incentives.

[1468] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1469] Step 1: User Registration and Login

[1470] user:

[1471] Input: The user installs and launches the app, clicks the Sign Up button, and enters the email address "example@example.com" and the password "password123."

[1472] Specific operations: Enter the required information on the new registration screen and click the "Register" button.

[1473] Output: A success message is displayed.

[1474] server:

[1475] Input: The server receives the email address and password entered by the user.

[1476] Data processing: Execute the query "INSERT INTO users (email, password) VALUES ('example@example.com', 'password123');".

[1477] Output: The user information is saved to the database and a success message is returned.

[1478] user:

[1479] Input: On the login screen, enter the email address "example@example.com" and the password "password123".

[1480] Specific actions: Enter information on the login screen and click the Login button.

[1481] Output: Get the token.

[1482] server:

[1483] Input: The server receives the user's email address and password and performs authentication.

[1484] Data operation: Execute the query "SELECT FROM users WHERE email = 'example@example.com' AND password = 'password123';" and generate a token if authentication is successful.

[1485] Output: A token is generated and sent to the device.

[1486] Device:

[1487] Input: Receives a token.

[1488] Specific operation: Save the token and move to the dashboard screen.

[1489] Output: User can access the dashboard.

[1490] Step 2: Setting habits and depositing

[1491] user:

[1492] Input: On the "Set up a new habit" screen, enter the habit "30 minutes of exercise every day" and the deposit amount "10,000 yen."

[1493] Specific actions: Enter your habit and deposit information and click the "Save" button.

[1494] Output: A message will be displayed indicating that the setup is complete.

[1495] server:

[1496] Input: Receives the habits and deposit amount entered by the user.

[1497] Data processing: Run the query "INSERT INTO habits (user_id, habit_detail, deposit_amount) VALUES (1, '30 minutes of exercise daily', 10000);".

[1498] Output: Saves the information to the database and returns a success message.

[1499] Device:

[1500] Input: Receives a success message.

[1501] What it does: Prompts the user that their habits and deposits have been set up.

[1502] Output: A completion message is displayed on the screen.

[1503] Step 3: Track your habit completion

[1504] user:

[1505] Input: Open the progress input screen in the app, enter "Today's exercise time: 30 minutes" and submit.

[1506] Specific actions: Enter information on the progress input screen and click the submit button.

[1507] Output: Progress data is sent.

[1508] server:

[1509] Input: Receives the user's progress data.

[1510] Data processing: Call the endpoint " / api / v1 / progress / evaluate" to send progress data to the AI ​​model.

[1511] Output: Progress data sent to the AI ​​model.

[1512] AI model:

[1513] Input: Receives progress data.

[1514] Data calculation: Analyzes progress data and evaluates "Habit achievement rate 80%."

[1515] Output: Returns the evaluation result to the server.

[1516] server:

[1517] Input: Receives the evaluation results from the AI ​​model.

[1518] Data processing: Execute the query "UPDATE progress SET evaluation = 'Habit achievement level 80%' WHERE user_id = 1;" and save the evaluation results to the database.

[1519] Output: The evaluation results are saved and sent to the device.

[1520] Device:

[1521] Input: Receives notifications from the server.

[1522] What it does: Show the user a notification that says "Habit completion is 80%."

[1523] Output: Progress is displayed on the screen.

[1524] Step 4: Reward System

[1525] AI model:

[1526] Input: Receives the user's habit completion rate.

[1527] Data calculation: Calculate "daily reward of 80 yen" based on the achievement level.

[1528] Output: Returns the reward result to the server.

[1529] server:

[1530] Input: Receives the reward calculation results from the AI ​​model.

[1531] Data processing: Use the endpoint " / api / v1 / banking / cashback" to transfer 80 yen to the user's financial institution account.

[1532] Output: Notifies the terminal of the cashback execution result.

[1533] Device:

[1534] Enter: Receive cashback notifications.

[1535] Specific behavior: Notify the user that "You have received a cashback of 80 yen for achieving your exercise goal today."

[1536] Output: A cashback notification will appear on the screen.

[1537] (Application example 1)

[1538] 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."

[1539] Previous habit-forming systems lacked sufficient motivation to encourage users to continue newly established habits, making long-term habit formation particularly difficult. Furthermore, there was no system that accurately tracked users' progress or provided appropriate rewards. This made it difficult for users to continue the habit, often leading to abandonment. Furthermore, online education platforms and content distribution services lacked methods to encourage users to continue using the habit.

[1540] 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.

[1541] In this invention, the server includes an input means for a user to set a new habit and make a deposit, a means for the server to store the received data in a database, a means for tracking the user's habit progress, a means for an AI to analyze the progress data and evaluate the degree of habit achievement, a means for calculating a reward amount based on the evaluation result, a means for providing cashback to the user's financial account, an input means for setting a learning routine or a viewing routine as a habit set by the user, a means for the user to input or automatically track progress, and a means for notifying the user of progress and rewards. This allows users to form enjoyable and sustainable habits and encourages continued use of online education platforms and content distribution services.

[1542] A "user" is an individual who uses the system to set up new habits and track their progress.

[1543] A "habit" is an ongoing activity, such as a learning routine or viewing routine, that a user engages in regularly.

[1544] A "deposit" is an amount set by the user as an incentive to continue the habit.

[1545] "Progress" is data that shows the degree of achievement of the user's set habits.

[1546] "Tracking" refers to the system recording and monitoring the user's progress in achieving their habits.

[1547] A "server" is a computer system that receives and stores data sent by users and performs any necessary calculations or analyses.

[1548] "Database" means a digital storage system for storing user registration information, progress data, deposit information, reward information, etc.

[1549] "AI" refers to artificial intelligence that analyzes progress data, evaluates the degree of habit achievement, and calculates reward amounts.

[1550] "Rewards" are monetary incentives that users receive for completing their set habits.

[1551] "Cashback" refers to the actual amount of money transferred to a user's financial account based on the habits they achieve.

[1552] "Financial account" refers to a bank account, electronic money account, etc. that a user uses to receive cashback.

[1553] A "learning routine" refers to the regular execution of specific learning activities set by the user.

[1554] A "viewing routine" refers to the regular viewing of specific content set by a user.

[1555] The "input method" is the interface through which the user inputs new habits, deposit amounts, and progress.

[1556] "Notification" refers to the system sending messages to the user to inform them of progress, achievement of rewards, etc.

[1557] The present invention is a system involving three parties: a server, a terminal, and a user, and provides support for users to form new habits.

[1558] 1. Program Generation

[1559] The system consists of the following main components:

[1560] User device: a mobile device such as a smartphone or tablet.

[1561] Server: A computer system for processing and storing data.

[1562] AI model: An artificial intelligence program to assess habit completion.

[1563] 2. Natural language explanation

[1564] User registration and login

[1565] The terminal provides an interface where users can create a new account. The user enters their email address and password, which the server receives and stores in a database. Upon login, authenticated users are issued a token and taken to the dashboard screen.

[1566] Habit Setting and Deposits

[1567] The terminal presents a screen where the user can set up a new habit (e.g., 30 minutes of study per day or watching movies three times a week) and enter a deposit amount. The server stores this information in a database and returns a success message.

[1568] Habit Tracking

[1569] Users record their daily progress and send it from their device to the server. In some cases, progress data is tracked automatically. The server receives the progress data and sends it to the AI ​​model. The AI ​​model analyzes this data and evaluates the degree of habit achievement. The evaluation results are stored in a database and notified to the user.

[1570] Reward System

[1571] The AI ​​model calculates the reward amount based on the habit completion rate. The server receives the calculation result and issues a cashback to the user's financial account. The user can check their progress and reward achievement on their device.

[1572] 3. Hardware and Software Used

[1573] Smartphone app: Implemented using React Native and Flutter.

[1574] Server: Use Node.js or Django.

[1575] Database: Data is stored using PostgreSQL or MongoDB.

[1576] AI model: Use TensorFlow or PyTorch to assess habit completion.

[1577] Cashback API: Use Stripe or PayPal API to execute cashback.

[1578] Specific examples

[1579] Case 1: When you set a new habit of "studying English for 30 minutes every day" and set a deposit of 10,000 yen

[1580] 1. User Registration and Login

[1581] The device provides an interface for creating a new account, and the user enters the required information.

[1582] The server saves the input information in a database and returns a success message.

[1583] The terminal issues a token to the user and takes them to the dashboard screen.

[1584] 2. Habit setting and deposits

[1585] The device provides the user with a habit setting screen, where they input "30 minutes of English study every day" and "a deposit of 10,000 yen."

[1586] The server stores this information in a database and returns a success message.

[1587] 3. Habit Tracking

[1588] The terminal provides an interface for inputting the user's progress.

[1589] The server sends the received progress data to the AI ​​model and stores the evaluation results in a database.

[1590] The device notifies the user of the evaluation results.

[1591] 4. Reward System

[1592] The AI ​​model decides to set the daily reward at 100 yen.

[1593] The server calls the cashback API and transfers 100 yen to the user's financial account.

[1594] The device will notify you, "You have received a cash back of 100 yen for achieving today's learning goal."

[1595] Prompt Sentence Examples

[1596] Write a program that rewards users with 100 yen if they complete 30 minutes of English study every day.

[1597] This system allows users to form new habits in a fun and sustainable way, encouraging continued use of online education platforms and content delivery services.

[1598] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1599] Step 1:

[1600] User registration and login

[1601] Terminal: To create a new account, the user clicks the "Sign up" button on the screen and enters their email address and password. The entered data is sent to the server.

[1602] Server: Receives the input data, stores it in a database, verifies that the information entered is correct, and returns a success message if successful.

[1603] Output: A success message is printed to the terminal.

[1604] On the device: The user enters their email address and password on the login screen and sends them to the server, which authenticates the information and, if successful, generates a token and sends it to the device.

[1605] Input: User's email address and password

[1606] Output: Authentication token

[1607] Terminal: After receiving the authentication token, the user is taken to the dashboard screen and can use the system.

[1608] Step 2:

[1609] Habit Setting and Deposits

[1610] On the device: The user opens the "Set up a new habit" screen and enters the habit (e.g., study English for 30 minutes every day) and the deposit amount. The entered data is sent to the server.

[1611] Server: Receives the entered customs and deposit information, stores it in the database, and returns a success message.

[1612] Output: A success message is printed to the terminal.

[1613] Input: The new habit and deposit amount set by the user

[1614] Output: Success message

[1615] Step 3:

[1616] Habit Tracking

[1617] Device: To record daily progress, users open the "Progress Input" screen and enter the time spent studying and the content they have watched. The input data is sent to the server. In some cases, automatic tracking is also performed.

[1618] Input: User progress data (e.g., 30 minutes of study time)

[1619] Server: Receives progress data and sends it to the AI ​​model, which analyzes the data and evaluates the habit completion.

[1620] Output: Habit achievement evaluation results

[1621] AI model: Analyzes progress data and evaluates habit achievement, which is stored in a database.

[1622] Server: Stores the evaluation results in a database and sends the results to the device.

[1623] On device: Users will receive progress notifications and be able to track their progress.

[1624] Output: Habit completion assessment results sent to the user

[1625] Step 4:

[1626] Reward System

[1627] AI model: Calculates the reward amount based on the habit achievement level. For example, if the achievement level is 50%, set the daily reward to 100 yen.

[1628] Output: Reward amount

[1629] Server: Receives the reward amount and cashbacks the user's financial account. This is done using the Cashback API.

[1630] Input: Reward calculation result

[1631] Output: Cashback success / failure message

[1632] On your device: Display a cashback notification to the user. For example, "You've received a cashback of 100 yen for achieving today's learning goal."

[1633] Output: Cashback notification to be sent to the user

[1634] The system allows users to form new habits effectively and enjoyably, and keeps them motivated through rewards.

[1635] 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.

[1636] The present invention is a system designed to help users enjoy and continue new habits, and aims to increase motivation by taking into account the user's emotional state. This system tracks the habits set by the user and their progress, and provides monetary rewards based on the user's progress and emotional state. The program and specific processing of this system are described in detail below.

[1637] Program processing explanation

[1638] User registration and login

[1639] On the device: The user installs and launches the app, clicks the "Sign Up" button on the screen, and enters their email address and password.

[1640] Server: The server receives the input data and stores it in the database. If registration is successful, it returns a success message to the device.

[1641] Device: The user enters the registered email address and password on the login screen and clicks the login button. The server authenticates the entered information, and if authentication is successful, generates a token and sends it to the device.

[1642] Terminal: Receives the token, moves to the dashboard screen, and the user can use the system.

[1643] Habit Setting and Deposits

[1644] On the device: The user opens the "Set up a new habit" screen and enters the habit. For example, "30 minutes of exercise every day." Next, they enter the amount they want to deposit. For example, they enter "10,000 yen."

[1645] Server: The server receives the entered habits and deposit information, stores it in the database, and returns a success message to the terminal.

[1646] Terminal: Prompts the user that their habits and deposits have been set up.

[1647] Habit Tracking

[1648] On the device: To record their daily progress, users open the "Progress Input" screen in the app. For example, they enter "30 minutes of exercise today" and submit.

[1649] Server: The server receives the progress data and sends it to the AI ​​model.

[1650] AI model: The AI ​​model analyzes the progress data and evaluates the habit achievement, for example, rating it as "progressing as expected."

[1651] Server: The server stores the evaluation results in a database and sends the results to the device.

[1652] On your device: Notify users that their habit has been assessed and display their progress.

[1653] Reward System

[1654] AI model: The AI ​​model calculates the reward amount based on the habit achievement level. For example, it determines "50% achievement means 100 yen per day."

[1655] Server: The server receives the reward calculation results and executes cashback to the user's bank account.

[1656] On the device: Display a cashback notification to the user. For example, display a notification such as "You've received a cashback of 100 yen for achieving your exercise goal today."

[1657] Introducing the Emotion Engine

[1658] Recognition of emotional states

[1659] On the device: To record their emotional state, users can open the "Emotion Input" screen within the app and self-report their feelings. For example, they can enter "I'm happy today." Alternatively, the device can automatically recognize their emotional state from their facial expressions and voice.

[1660] Server: The server receives the emotion data and stores it in a database.

[1661] Emotional data analysis and reflection

[1662] AI model: Analyzes emotional data and evaluates how a user's emotional state affects habit completion.

[1663] Server: Adjusts reward amount and motivational message based on the evaluation results.

[1664] Device: Display an appropriate motivational message to the user, for example, "You're working especially hard today!"

[1665] Linking cashback and emotional states

[1666] AI model: Calculates the optimal reward amount based on emotional data and habit completion. For example, it determines that "the user's emotional state is high, so an additional 20 yen cashback will be given."

[1667] Server: Receives the reward calculation results and sends the cashback to the user's bank account.

[1668] Device: Display a cashback notification to the user along with a pleasurable message based on their emotional state. For example, "You've received a cashback of 120 yen because you achieved your exercise goal today and are feeling happy."

[1669] Specific examples

[1670] Case 2: Using the Emotion Engine to set the habit "30 minutes of exercise every day" and set a deposit of 10,000 yen

[1671] 1. User Registration and Login

[1672] Device: Yamada launches the app and clicks "New Registration."

[1673] Device: Yamada enters her email address and password and clicks "Register."

[1674] Server: Saves the input data and returns a success message.

[1675] Device: Yamada enters her email address and password on the login screen and clicks "Login."

[1676] Server: The server generates an authentication token and sends it to the device.

[1677] Device: Yamada's device receives the token and transitions to the dashboard.

[1678] 2. Habit setting and deposits

[1679] Device: Yamada enters "30 minutes of exercise every day" in "Set a new habit" and clicks "Next."

[1680] Terminal: Enter the deposit amount "10,000 yen" and click "Complete".

[1681] Server: The server saves the information and returns a completion message.

[1682] Device: Yamada's device will display a message indicating that the setup is complete.

[1683] 3. Habit Tracking

[1684] Device: Yamada enters "30 minutes of exercise" in "Enter progress" and submits.

[1685] Server: The server stores the data and sends it to the AI ​​model.

[1686] AI model: The AI ​​model analyzes the progress and sends the evaluation results to the server.

[1687] Server: The server notifies Yamada's device of the evaluation results.

[1688] Device: Yamada's device displays the progress and evaluation results.

[1689] 4. Emotional state input and analysis

[1690] Device: Yamada inputs "Happy" in the "Emotion Input" field and sends it. Alternatively, the device will analyze his facial expressions and voice to recognize his emotions.

[1691] Server: The server stores the emotion data and sends it to the AI ​​model.

[1692] AI model: The AI ​​model analyzes the emotional data and evaluates it to reflect the habit achievement level.

[1693] Server: Adjusts reward amount and motivational message based on the evaluation results.

[1694] 5. Linking reward systems and emotional states

[1695] AI model: The AI ​​model determines the cashback of 100 yen + an additional 20 yen based on the emotional state and habit completion level.

[1696] Server: Save the reward amount, call the cashback API, and transfer 120 yen to Yamada's bank account.

[1697] Device: Yamada's device notifies him that the cashback has been completed and displays a pleasant message: "You've received a cashback of 120 yen because you achieved your exercise goal today and felt good."

[1698] This specific processing step allows users to pursue new habits in a fun way while receiving optimal rewards according to their emotional state.

[1699] The processing flow will be explained below.

[1700] Program processing details

[1701] User registration and login

[1702] Step 1:

[1703] On the device: The user installs and launches the app. They click the "Sign up" button.

[1704] Step 2:

[1705] Device: The user enters their email address and password and clicks the "Register" button.

[1706] Step 3:

[1707] Server: Receives input data and saves it in the database. If registration is successful, returns a success message to the device.

[1708] Step 4:

[1709] Device: The user enters the registered email address and password on the login screen and clicks the "Login" button.

[1710] Step 5:

[1711] Server: Authenticates the input information, and if successful, generates an authentication token and sends it to the device.

[1712] Step 6:

[1713] Terminal: Receive the token and proceed to the dashboard screen.

[1714] Habit Setting and Deposits

[1715] Step 1:

[1716] On the device: The user opens the "Set up a new habit" screen and enters "30 minutes of exercise daily." They then click the Next button.

[1717] Step 2:

[1718] Terminal: The user enters the amount to deposit (10,000 yen). Then clicks the Complete button.

[1719] Step 3:

[1720] Server: Receives the habit and deposit information, stores it in the database, and returns a success message to the terminal.

[1721] Step 4:

[1722] Terminal: Prompts the user that their habits and deposit setup is complete.

[1723] Habit Tracking

[1724] Step 1:

[1725] Device: The user opens the "Enter Progress" screen, enters today's exercise time as "30 minutes," and clicks the submit button.

[1726] Step 2:

[1727] Server: Receives progress data and stores it in a database.

[1728] Step 3:

[1729] Server: Sends saved progress data to the AI ​​model.

[1730] Step 4:

[1731] AI model: Analyzes the received data and evaluates it as "progressing as expected."

[1732] Step 5:

[1733] AI model: Sends the evaluation results to the server.

[1734] Step 6:

[1735] Server: Saves the evaluation results in a database and notifies the terminal of the evaluation results.

[1736] Step 7:

[1737] Device: Shows the user today's progress and assessment results.

[1738] Reward System

[1739] Step 1:

[1740] AI model: Calculates reward amount based on habit achievement. For example, "For 50% achievement, a cashback of 100 yen will be given."

[1741] Step 2:

[1742] AI model: Sends the calculation results to the server.

[1743] Step 3:

[1744] Server: Stores the reward amount in the database.

[1745] Step 4:

[1746] Server: Calls the API to execute the cashback and transfers the money to the user's bank account.

[1747] Step 5:

[1748] On the device: Display a cashback notification to the user, for example, "You've received a cashback of 100 yen for achieving your exercise goal today."

[1749] Introducing the Emotion Engine

[1750] Step 1:

[1751] On the device: The user opens the "Emotion Input" screen and reports their feelings. For example, they can type "I'm happy today." Alternatively, the device can automatically recognize their emotional state from their facial expressions and voice.

[1752] Step 2:

[1753] Server: The server receives the emotion data and stores it in a database.

[1754] Step 3:

[1755] AI model: Analyzes emotional data and evaluates how a user's emotional state affects habit completion.

[1756] Step 4:

[1757] Server: Adjusts reward amount and motivational message based on the evaluation results.

[1758] Step 5:

[1759] Device: Display an appropriate motivational message to the user, for example, "You're working especially hard today!"

[1760] Step 6:

[1761] AI model: Calculates the optimal reward amount based on emotional data and habit completion. For example, it determines that "the user's emotional state is high, so an additional 20 yen cashback will be given."

[1762] Step 7:

[1763] Server: Saves the reward calculation results in the database, calls the cashback API, and transfers the money to the user's bank account.

[1764] Step 8:

[1765] Device: Display a cashback notification to the user along with a pleasurable message based on their emotional state. For example, a notification like "You've received a cashback of 120 yen because you achieved your exercise goal today and are feeling happy" will be displayed.

[1766] Specific examples

[1767] Case 1: Using the Emotion Engine, you set the habit "30 minutes of exercise every day" and set a deposit of 10,000 yen.

[1768] 1. User Registration and Login

[1769] Step 1: Yamada launches the app and clicks "New Registration."

[1770] Step 2: Sam enters her email address and password and clicks "Register."

[1771] Step 3: The server saves the data and returns a success message.

[1772] Step 4: On the login screen, Yamada enters her email address and password and clicks "Login."

[1773] Step 5: The server generates an authentication token and sends it to the device.

[1774] Step 6: Yamada's device receives the token and goes to the dashboard.

[1775] 2. Habit setting and deposits

[1776] Step 1: Yamada enters "30 minutes of exercise every day" in "Set a new habit" and clicks "Next."

[1777] Step 2: Enter the deposit amount "10,000 yen" and click "Complete".

[1778] Step 3: The server saves the information and returns a completion message.

[1779] Step 4: Yamada's device will display a message that the setup is complete.

[1780] 3. Habit Tracking

[1781] Step 1: Yamada enters "30 minutes of exercise" in "Enter progress" and submits it.

[1782] Step 2: The server stores the data and sends it to the AI ​​model.

[1783] Step 3: The AI ​​model analyzes the progress and sends the evaluation results to the server.

[1784] Step 4: The server notifies Yamada's device of the evaluation results.

[1785] Step 5: Yamada's device displays the progress and evaluation results.

[1786] 4. Emotional state input and analysis

[1787] Step 1: Yamada inputs "I'm happy today" in "Emotion Input" and sends it. Alternatively, the device will analyze facial expressions and voice to recognize the emotion.

[1788] Step 2: The server stores the emotion data and sends it to the AI ​​model.

[1789] Step 3: The AI ​​model analyzes the emotional data and evaluates it to reflect the habit completion level.

[1790] Step 4: The server adjusts the reward amount and motivational message based on the evaluation results.

[1791] 5. Linking reward systems and emotional states

[1792] Step 1: The AI ​​model determines the cashback of 100 yen + an additional 20 yen based on the emotional state and habit completion.

[1793] Step 2: The server stores the reward amount in the database.

[1794] Step 3: Call the cashback API and transfer 120 yen to Yamada's bank account.

[1795] Step 4: Yamada's device notifies him that the cashback has been completed and displays a pleasant message: "You've received a cashback of 120 yen because you achieved your exercise goal today and felt happy."

[1796] This specific processing step allows users to pursue new habits in a fun way while receiving optimal rewards according to their emotional state.

[1797] Example 2

[1798] 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."

[1799] Conventional systems for forming new habits primarily record the user's progress and provide rewards based on the level of achievement. However, these systems have the problem of making it difficult to maintain motivation because they do not take into account the user's emotional state. There is a need for a system that can support more effective habit formation by appropriately responding to the user's emotional state.

[1800] 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.

[1801] In this invention, the server includes input means for the user to set a new habit and make a deposit, means for the server to store the received data in a database, means for tracking the user's habit progress, means for the generative AI model to analyze the progress data and evaluate the habit achievement level, means for calculating a reward amount based on the evaluation results, means for executing cashback to the user's bank account, input means for recording the user's emotional state, means for the terminal to automatically recognize the user's emotional state from the user's facial expressions and voice, and means for receiving and analyzing the emotional data and adjusting the reward amount and motivational message based on the evaluation results. This makes it possible to adjust the optimal reward amount according to the user's emotional state, enabling the user to form a new habit while maintaining motivation.

[1802] "User" refers to an individual who is the intended user of this system.

[1803] Habits are activities or behaviors that users plan to perform on a daily basis.

[1804] A "deposit" is the amount a user pays upfront to receive financial rewards for the habits they set.

[1805] "Input means" refers to the interface or device through which a user inputs data into a system.

[1806] "Server" refers to a computer system that receives, processes, and stores data submitted by users.

[1807] A "database" refers to a digital storage device for efficiently storing and managing data collected within a system.

[1808] "Tracking" refers to the continuous recording and monitoring of a user's habit progress and activities.

[1809] A "generative AI model" refers to an artificial intelligence algorithm that analyzes collected data, calculates the degree of habit completion and reward amount, and evaluates the user's emotional state.

[1810] "Analysis" refers to the process of examining collected data in detail to understand its content and patterns.

[1811] "Habit completion level" refers to an indicator that shows the extent to which a user has achieved the habits they have set.

[1812] "Evaluation results" refer to the conclusions reached based on the habit achievement and emotional state analyzed by the generative AI model.

[1813] "Reward amount" refers to the monetary reward the system provides to the user based on the user's level of habit achievement.

[1814] "Cashback" refers to the process of returning reward amounts to the user's bank account.

[1815] "Emotional state" refers to information that indicates the user's current psychological feelings.

[1816] "Facial Expression" refers to a user's facial expression that is used to recognize the user's emotional state.

[1817] "Voice" refers to audio data used to recognize the user's emotional state.

[1818] "Motivational messages" refer to messages provided by the system to motivate users and encourage them to continue using the system.

[1819] "Behavioral patterns" refers to data that shows a user's past activities and behavioral tendencies.

[1820] The present invention is a system designed to help users enjoy and continue new habits, and aims to increase motivation by taking into account the user's emotional state. The system tracks the user's established habits and their progress, and provides monetary rewards according to the user's progress and emotional state. Specific embodiments for implementing the present invention are described in detail below.

[1821] User registration and login

[1822] A user installs and launches the application on a device such as a smartphone or tablet. First, the user clicks the "New Registration" button and enters their email address and password. The server receives this input data and stores it in a database. If registration is successful, a success message is returned to the device. Next, the user enters their email address and password on the login screen and clicks the login button. The server authenticates the entered information, and if authentication is successful, generates a token and sends it to the device. The user receives the token and can proceed to the dashboard screen to use the system.

[1823] Habit Setting and Deposits

[1824] The user opens the "Setting a new habit" screen and enters the specific habit. For example, the user can enter "30 minutes of exercise every day." The user then enters the amount to deposit, for example, "10,000 yen." The server receives this input data and stores it in the database. After a success message is returned to the terminal, the user can confirm that the setup is complete.

[1825] Habit Tracking

[1826] To record their daily progress, users open the "Progress Input" screen in the app, enter progress information (for example, "30 minutes of exercise today") and submit it. The server receives the progress data and sends it to the generative AI model. The generative AI model analyzes the progress data and evaluates the degree of habit achievement. For example, the generative AI model may evaluate the progress as "progressing as expected." This evaluation result is sent to the server and stored in a database. Finally, the result is notified to the user's device, allowing the user to check their progress.

[1827] Reward System

[1828] The generative AI model calculates the reward amount based on the degree of habit achievement. For example, it may determine "100 yen as the daily reward for achieving 50%." The server receives the reward calculation results and executes a cashback to the user's bank account. The user can check the cashback notification on their device. For example, it may display "100 yen has been cashbacked for achieving today's exercise goal."

[1829] Introducing the Emotion Engine

[1830] Recognition of emotional states

[1831] To record their emotional state, users can open the "Emotion Input" screen in the app and self-report their feelings. For example, they can enter "I'm happy today." Alternatively, the device can automatically recognize their emotional state from their facial expressions and voice. The server receives the emotional data and stores it in a database.

[1832] Emotional data analysis and reflection

[1833] The generative AI model analyzes the emotional data and evaluates how the user's emotional state affects their habit achievement. The server then adjusts the reward amount and motivational message based on the evaluation results. For example, it displays an appropriate motivational message to the user, such as, "You're working especially hard today!"

[1834] Linking cashback and emotional states

[1835] The generative AI model calculates the optimal reward amount based on emotional data and the degree of habit achievement. For example, it may decide to "give the user an additional 20 yen cashback because their emotions are high." The server receives the reward calculation results and executes the cashback into the user's bank account. The user receives a cashback notification on their device, and a motivational message based on their emotional state is also displayed. For example, it may say, "You've received a cashback of 120 yen because you achieved your exercise goal today and felt happy."

[1836] Specific examples

[1837] Prompt Sentence Examples

[1838] Please enter your new email address and password to register.

[1839] "Enter the specific habit and amount to set up a new habit and make a deposit."

[1840] "Record your progress today on the progress entry screen and press the submit button."

[1841] "Enter your emotional state for the day on the emotion input screen, or have it recognized automatically by analyzing your facial expressions and voice."

[1842] The present invention allows users to enjoyably pursue new habits while receiving optimal rewards according to their emotional state.

[1843] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1844] Step 1:

[1845] The user installs and launches the application. They click the "New Registration" button on the screen and enter their email address and password. The entered data is sent from the device to the server. The server stores the received data in a database and returns a success message indicating that registration was successful.

[1846] Step 2:

[1847] The user enters the registered email address and password on the login screen and clicks the login button. The input data is sent from the terminal to the server. The server compares the received data with the database, and if authentication is successful, generates an authentication token and sends it to the terminal. The user receives the token, moves to the dashboard screen, and can use the system.

[1848] Step 3:

[1849] The user opens the "Setting a new habit" screen and enters the specific habit. Next, they enter the amount they want to deposit. The entered data is sent from the device to the server. The server stores the received habit and deposit information in a database and returns a success message. The user can confirm that the setup is complete.

[1850] Step 4:

[1851] To record their daily progress, users open the "Progress Input" screen in the app, enter their progress information, and submit it. The input data is sent from the device to the server. The server then sends the progress data to the generative AI model, which analyzes it. The generative AI model analyzes the progress data and evaluates the degree of habit achievement. The evaluation results are sent to the server and stored in a database. The server then sends the evaluation results to the user's device, allowing the user to check their progress and evaluation results.

[1852] Step 5:

[1853] The generative AI model calculates the reward amount based on the degree of habit achievement. For example, if 50% achievement is achieved, it determines the daily reward to be 100 yen. The calculation result is sent to the server, which then executes a cashback to the user's bank account. The user receives a cashback notification on their device. For example, it displays a message saying, "You have received a cashback of 100 yen for achieving today's exercise goal."

[1854] Step 6:

[1855] To record their emotional state, users can open the "Emotion Input" screen in the app and self-report their emotional state. Alternatively, the device can automatically recognize their emotional state from their facial expressions and voice. Emotion data is sent from the device to a server, which then stores the data in a database.

[1856] Step 7:

[1857] The generative AI model analyzes the emotional data and evaluates how the user's emotional state affects their habit achievement. The analysis results are sent to the server, which adjusts the reward amount and motivational message based on the evaluation results. The server then sends the adjustment results to the user's device, and the user is notified with an appropriate motivational message. For example, "You're working especially hard today!"

[1858] Step 8:

[1859] The generative AI model calculates the optimal reward amount based on emotional data and the degree of habit achievement. For example, it may decide to "give the user an additional 20 yen cashback because their emotions are high." The calculation result is sent to the server, which then deposits the cashback into the user's bank account. The user receives a cashback notification on their device, and a motivational message based on their emotional state is also displayed. For example, it may say, "You've received a cashback of 120 yen because you achieved your exercise goal today and felt happy."

[1860] (Application example 2)

[1861] 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."

[1862] Conventional habit formation support systems only evaluate users' achievements without considering their emotional state, which makes it difficult to maintain motivation. Furthermore, the reward system is limited, making it ineffective in promoting actual behavioral change. Furthermore, the system does not consider providing incentives through collaboration with virtual stores, limiting its effectiveness as a means of helping users establish new habits in a fun way.

[1863] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1864] In this invention, the server includes an input means for a user to set a new habit and make a deposit, a means for the server to store the received data in a database, a means for tracking the user's habit progress, a means for an AI to analyze the progress data and evaluate the degree of habit achievement, a means for calculating a reward amount based on the evaluation result, a means for providing cashback to the user's bank account, a means for receiving the reward in the virtual store, and a means for recognizing the user's emotional state and adjusting the reward amount based thereon, thereby enabling the user to continue the new habit while enjoying it and receive individual incentives according to their emotional state.

[1865] "User" refers to a person who uses the System to set new habits and track their progress.

[1866] Habits are new behaviors or activities that users incorporate into their daily lives, such as exercising or reading.

[1867] A "deposit" refers to the amount of money a user deposits in advance to receive rewards based on the progress of the habits they set.

[1868] "Input means" refers to the interface that allows users to set habits, enter progress, and record emotional states.

[1869] "Server" refers to the central system that receives, processes, and stores data entered by users in a database.

[1870] "Database" refers to the system for storing and managing User habits, progress, and emotional data.

[1871] "Tracking Method" refers to the method by which a User records their daily progress and transmits that data to a server.

[1872] "AI" refers to artificial intelligence technology that analyzes progress and emotional data to evaluate the user's level of habit achievement and reward amount.

[1873] "Habit completion" refers to an indicator that evaluates the degree to which a user has achieved the habits they have set.

[1874] "Reward amount" refers to a monetary incentive calculated based on the user's habit completion.

[1875] "Cashback" refers to money that is transferred to a user's bank account when they complete a habit, based on their level of achievement.

[1876] "Virtual store" refers to an online shopping platform where users can use rewards to purchase goods and services.

[1877] "Emotional state" refers to data that indicates a user's current emotions, and refers to information obtained through self-reporting, facial expression recognition, etc.

[1878] The system that realizes this application example is composed of various hardware and software components that work together to enable users to continue their new habits in an enjoyable way. Specific embodiments of each part of the system are described below.

[1879] Hardware and software used

[1880] Hardware: Smartphone (including facial recognition and voice recognition functions via camera), server

[1881] software:

[1882] Platform: Android, iOS

[1883] Backend: Firebase, Google Cloud, AWS

[1884] AI model: TensorFlow, OpenAI GPT-3

[1885] Database: Firebase Firestore, MySQL

[1886] Frontend: React Native

[1887] Emotion recognition: Affectiva SDK, Google Cloud Vision API

[1888] Specific processing

[1889] User registration and login

[1890] A user installs the application on their smartphone and registers by entering their email address and password. The server receives this information, authenticates the user information using Firebase Auth, generates an authentication token, and returns it to the user's device, allowing the user to log in and use the system.

[1891] Setting a new habit and depositing

[1892] The user is presented with an interface to set up a new habit and enter the deposit amount, which the server receives and stores in Firebase Firestore. Based on this information, the user can enjoyably pursue the habit they set up.

[1893] Habit completion and emotional state tracking

[1894] Users enter their daily progress on their smartphones and send it to a server. The server then sends this data to an AI model that uses TensorFlow to analyze habit completion. The system also tracks the user's emotional state. It uses Google Cloud Vision API and Affectiva SDK to recognize emotions from facial expressions and voice. This data is stored in Firebase Firestore for later analysis.

[1895] Reward systems and virtual stores

[1896] Based on the evaluation results, the AI ​​model calculates the reward amount, taking into account the progress data and emotional state. The reward is not only cashed back into the user's bank account, but also provided as a coupon that can be used in virtual stores, allowing users to purchase products and services in the virtual stores.

[1897] Example: Yamada's case

[1898] For example, let's say a user wants to make reading 30 minutes a day a habit and uses this system. The user installs the app, creates an account, and logs in. Then, they set up the habit of "reading 30 minutes a day" and enter a deposit of 5,000 yen. By recording their daily progress and entering their emotional state, the system calculates rewards based on their habit achievement and emotional state. The user can then use coupons to purchase products in the virtual store.

[1899] Prompt Sentence Examples

[1900] To help users develop literacy habits, VirtuHabit implements an in-app system that evaluates progress and rewards users based on their emotional state, such as coupons and special offers for virtual stores.

[1901] Thus, the present invention provides a system that allows users to enjoyably continue new habits and receive rewards according to their emotional state.

[1902] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1903] Step 1:

[1904] User registration and login

[1905] Input: Email address, Password

[1906] Server: The user installs the application and enters their email address and password on the registration screen. The server registers the user information using Firebase Auth and generates an authentication token. The authentication token is sent to the device.

[1907] Output: Authentication token

[1908] Step 2:

[1909] Setting a new habit and depositing

[1910] Input: Habit name, Deposit amount

[1911] Device: The user enters the name of the habit, such as "30 minutes of exercise every day," and the deposit amount (e.g., 10,000 yen) on the habit setting screen. This is then sent to the server.

[1912] Server: The server stores the received habit information and deposit amount in Firebase Firestore.

[1913] Output: Save complete message

[1914] Step 3:

[1915] Habit Tracking

[1916] Input: Daily progress data (e.g., "Today's exercise time: 30 minutes")

[1917] Terminal: The user enters progress data on the progress input screen and sends it to the server.

[1918] Server: The server receives this progress data, sends it to the AI ​​model for analysis, evaluates habit completion using TensorFlow, and sends the results back to the server, which stores the results in Firebase Firestore.

[1919] Output: Progress evaluation results

[1920] Step 4:

[1921] Emotional state tracking

[1922] Input: Emotion data (e.g., "I feel happy today"), face image, or voice

[1923] Device: The user inputs their emotional state on the emotion input screen, captures a facial image with the device camera, or records a voice, which is then sent to the server.

[1924] Server: The server sends facial images and audio data to the Google Cloud Vision API and Affectiva SDK, analyzes the emotional state, and stores the results in Firebase Firestore.

[1925] Output: Emotion evaluation result

[1926] Step 5:

[1927] Reward calculation and cashback

[1928] Input: Habit achievement assessment results, emotional assessment results

[1929] Server: The server uses an AI model (TensorFlow) to calculate the optimal reward amount based on the progress data and emotional state. The calculation result is cashed back to the user's bank account.

[1930] Output: Cashback completion notification, reward amount

[1931] Step 6:

[1932] Use rewards in virtual stores

[1933] Input: Reward amount, shopping information at virtual store

[1934] Terminal: Users can select products and services in a virtual store and purchase them using their reward amount.

[1935] Server: The server receives the purchase information and updates the reward amount usage to Firebase Firestore.

[1936] Output: Purchase complete notification, updated balance

[1937] This allows users to enjoy new habits, continue them, and receive personalized incentives based on their emotional state.

[1938] 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.

[1939] 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.

[1940] 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.

[1941] [Fourth embodiment]

[1942] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1943] 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.

[1944] 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).

[1945] 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.

[1946] 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.

[1947] 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).

[1948] 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.

[1949] 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.

[1950] 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.

[1951] 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.

[1952] 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.

[1953] 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.

[1954] 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."

[1955] This invention is a system that provides financial incentives to help users enjoyably continue new habits and supports the habit-forming process. This system tracks the habits set by the user and their progress in achieving them, and provides monetary rewards according to the degree of progress. The program and specific processing of this system are described in detail below.

[1956] Program processing explanation

[1957] User registration and login

[1958] On the device: The user installs and launches the app, clicks the "Sign Up" button on the screen, and enters their email address and password.

[1959] Server: The server receives the input data, stores it in the database, and returns a success message to the terminal if the registration is successful.

[1960] Device: The user enters the registered email address and password on the login screen and clicks the login button. The server authenticates the entered information, and if authentication is successful, generates a token and sends it to the device.

[1961] Terminal: Receives the token, moves to the dashboard screen, and the user can use the system.

[1962] Habit Setting and Deposits

[1963] On the device: The user opens the "Set up a new habit" screen and enters the habit. For example, they might enter "30 minutes of exercise every day." Then they enter the amount they want to deposit. For example, they enter "10,000 yen."

[1964] Server: The server receives the entered habits and deposit information, stores it in the database, and returns a success message to the terminal.

[1965] Terminal: Prompts the user that their habits and deposits have been set up.

[1966] Habit Tracking

[1967] On the device: To record their daily progress, users open the "Progress Input" screen in the app. For example, they enter "30 minutes of exercise today" and submit.

[1968] Server: The server receives the progress data and sends it to the AI ​​model.

[1969] AI model: The AI ​​model analyzes the progress data and evaluates the habit achievement, for example, rating it as "progressing as expected."

[1970] Server: The server stores the evaluation results in a database and sends the results to the device.

[1971] On your device: Notify users that their habit has been assessed and display their progress.

[1972] Reward System

[1973] AI model: The AI ​​model calculates the reward amount based on the habit achievement level. For example, it determines "50% achievement means 100 yen per day."

[1974] Server: The server receives the reward calculation results and executes cashback to the user's bank account.

[1975] On the device: Display a cashback notification to the user. For example, display a notification such as "You've received a cashback of 100 yen for achieving your exercise goal today."

[1976] Specific examples

[1977] Case 1: When you set a new habit "exercise 30 minutes a day" and set a deposit of 10,000 yen

[1978] 1. User Registration and Login

[1979] Device: David launches the app and enters the required information to create a new account.

[1980] Server: The server receives the input information, stores it in a database, and returns a success message.

[1981] Device: Yamada enters her email address and password on the login screen and obtains an authentication token.

[1982] 2. Habit setting and deposits

[1983] Device: Yamada sets "30 minutes of exercise every day" and deposits 10,000 yen.

[1984] Server: The server receives and stores this information and returns a completion message.

[1985] 3. Habit Tracking

[1986] Device: Yamada enters today's exercise time as "30 minutes" and submits.

[1987] Server: The server receives the progress data and has the AI ​​model evaluate it.

[1988] AI model: The AI ​​model evaluates the results as "Progressing as expected" and saves them.

[1989] Server: The server notifies Yamada's device of the evaluation results.

[1990] 4. Reward System

[1991] AI model: The AI ​​model decides to give a cashback of 100 yen as a reward for one day.

[1992] Server: The server calls the cashback API and transfers 100 yen to Yamada's bank account.

[1993] Device: Notify "You've received a cashback of 100 yen for achieving your exercise goal today."

[1994] Through this specific process, users can develop new habits in a fun and efficient way.

[1995] The processing flow will be explained below.

[1996] Program processing details

[1997] User registration and login

[1998] Step 1:

[1999] On the device: The user installs and launches the app. They click the "Sign up" button.

[2000] Step 2:

[2001] Device: The user enters their email address and password and clicks the "Register" button.

[2002] Step 3:

[2003] Server: Receives input data and saves it in the database. If registration is successful, returns a success message to the device.

[2004] Step 4:

[2005] On the device: The user enters their email address and password on the login screen and clicks the "Login" button.

[2006] Step 5:

[2007] Server: Authenticates the input information, and if successful, generates an authentication token and sends it to the device.

[2008] Step 6:

[2009] Terminal: Receive the token and proceed to the dashboard screen.

[2010] Habit Setting and Deposits

[2011] Step 1:

[2012] On the device: The user opens the "Set up a new habit" screen and enters "30 minutes of exercise daily." They then click the Next button.

[2013] Step 2:

[2014] Terminal: The user enters the amount to deposit (10,000 yen). Then clicks the Complete button.

[2015] Step 3:

[2016] Server: Receives the habit and deposit information, stores it in the database, and returns a success message to the terminal.

[2017] Step 4:

[2018] Terminal: Prompts the user that their habits and deposit setup is complete.

[2019] Habit Tracking

[2020] Step 1:

[2021] Device: The user opens the "Enter Progress" screen, enters today's exercise time as "30 minutes," and clicks the submit button.

[2022] Step 2:

[2023] Server: Receives progress data and stores it in a database.

[2024] Step 3:

[2025] Server: Sends saved progress data to the AI ​​model.

[2026] Step 4:

[2027] AI model: Analyzes the received data and evaluates it as "progressing as expected."

[2028] Step 5:

[2029] AI model: Sends the evaluation results to the server.

[2030] Step 6:

[2031] Server: Saves the evaluation results in a database and notifies the terminal of the evaluation results.

[2032] Step 7:

[2033] Device: Shows the user today's progress and assessment results.

[2034] Reward System

[2035] Step 1:

[2036] AI model: Calculates reward amount based on habit achievement. For example, "For 50% achievement, a cashback of 100 yen will be given."

[2037] Step 2:

[2038] AI model: Sends the calculation results to the server.

[2039] Step 3:

[2040] Server: Stores the reward amount in the database.

[2041] Step 4:

[2042] Server: Calls the API to execute the cashback and transfers the money to the user's bank account.

[2043] Step 5:

[2044] On the device: Display a cashback notification to the user, for example, "You've received a cashback of 100 yen for achieving your exercise goal today."

[2045] Specific examples

[2046] Case 1: When you set a new habit "exercise 30 minutes a day" and set a deposit of 10,000 yen

[2047] 1. User Registration and Login

[2048] Step 1: Yamada launches the app and clicks "New Registration."

[2049] Step 2: Sam enters her email address and password and clicks "Register."

[2050] Step 3: The server saves the data and returns a success message.

[2051] Step 4: On the login screen, Yamada enters her email address and password and clicks "Login."

[2052] Step 5: The server generates an authentication token and sends it to the device.

[2053] Step 6: Yamada's device receives the token and is redirected to the dashboard.

[2054] 2. Habit setting and deposits

[2055] Step 1: Yamada enters "30 minutes of exercise every day" in "Set a new habit" and clicks "Next."

[2056] Step 2: Enter the deposit amount "10,000 yen" and click "Complete".

[2057] Step 3: The server saves the information and returns a completion message.

[2058] Step 4: Yamada's device will display a message that the setup is complete.

[2059] 3. Habit Tracking

[2060] Step 1: Yamada enters "30 minutes of exercise" in "Enter progress" and submits it.

[2061] Step 2: The server stores the data and sends it to the AI ​​model.

[2062] Step 3: The AI ​​model analyzes the progress and sends the evaluation results to the server.

[2063] Step 4: The server notifies Yamada's device of the evaluation results.

[2064] Step 5: Yamada's device displays the progress and evaluation results.

[2065] 4. Reward System

[2066] Step 1: The AI ​​model determines the cashback of 100 yen based on the achievement level.

[2067] Step 2: The server stores the reward amount in the database.

[2068] Step 3: Call the cashback API and transfer 100 yen to Yamada's bank account.

[2069] Step 4: Yamada's device will notify him that the cashback has been completed.

[2070] This specific processing step allows users to enjoyably pursue new habits while earning financial rewards.

[2071] Example 1

[2072] 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."

[2073] In modern society, it is difficult for users to form and maintain new habits. Effective methods for maintaining sustained motivation are scarce, and methods for utilizing economic incentives are limited. Furthermore, current systems lack mechanisms for tracking user progress and providing rewards based on that progress, making it difficult to maintain motivation for habit formation.

[2074] 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.

[2075] In this invention, the server includes an input means for a user to set a new habit and make a deposit, a means for the server to store the received data in a database, a means for tracking the user's habit progress, a means for an AI to analyze the progress data and evaluate the degree of habit achievement, a means for calculating a reward amount based on the evaluation result, a means for executing cashback to the user's financial institution account, and an authentication means for enabling the user to log in and use the system using a token. This allows the user to continue a new habit in a fun way and form a habit while receiving economic incentives.

[2076] "Input" is the interface on the system through which users can set new habits and make deposits.

[2077] A "database" is an information management system that stores and manages data received by a server.

[2078] "Tracking Tools" are features that allow users to monitor and record their habit progress.

[2079] The "AI model" is an artificial intelligence model that analyzes progress data and evaluates the user's level of habit achievement.

[2080] The "evaluation method" is a function for determining the degree of habit achievement based on the results of analysis by the AI ​​model.

[2081] The "remuneration calculation means" is a function for calculating the amount of remuneration to be provided to the user based on the evaluation results.

[2082] "Cashback method" is a system function that actually transfers rewards to the user's financial institution account.

[2083] "Authentication means" is a security feature that allows users to log in using a token and access the system.

[2084] The present invention is a system that provides economic incentives to users to help them continue new habits in a fun way and supports the habit formation process. The system receives user input, manages and analyzes data using a server and an AI model, evaluates the user's habit achievement, and provides rewards. Details of the system's program and the specific form of its processing are described below.

[2085] Handling user registration and login

[2086] Terminal: The user installs and launches the application. They click the "New Registration" button on the screen and enter their email address and password. This input method allows the user to create a new account within the system. For example, they enter the email address "example@example.com" and the password "password123."

[2087] Server: The server receives the entered data and stores it in the database. It executes the query "INSERT INTO users (email, password) VALUES ('example@example.com', 'password123');" and returns a success message to the terminal if registration is successful.

[2088] Terminal: The user enters the registered email address and password on the login screen and clicks the login button. The server authenticates the entered information, and if authentication is successful, generates a token and sends it to the terminal. The terminal receives this token, transitions to the dashboard screen, and the user can use the system.

[2089] Setting habits and processing deposits

[2090] On the device: The user opens the "Set up a new habit" screen and enters the habit. For example, they might enter "30 minutes of exercise every day," then enter the amount they want to deposit. For the deposit amount, they enter "10,000 yen."

[2091] Server: The server receives the entered habit and deposit information and stores it in the database. It executes the query "INSERT INTO habits (user_id, habit_detail, deposit_amount) VALUES (1, '30 minutes of exercise daily', 10000);" and returns a success message.

[2092] Terminal: Prompts the user that their habits and deposits have been set up.

[2093] Handling habit completion tracking

[2094] On the device: To record their daily progress, users open the "Progress Input" screen in the app. For example, they enter "30 minutes of exercise today" and submit.

[2095] Server: The server receives the progress data and sends it to the AI ​​model through the endpoint " / api / v1 / progress / evaluate".

[2096] AI model: The AI ​​model analyzes the progress data and evaluates the habit achievement level. For example, it evaluates the habit achievement level as "80%" based on the progress data.

[2097] Server: Save the evaluation results in the database and use the query "UPDATE progress SET evaluation = 'Habit achievement level 80%' WHERE user_id = 1;". The evaluation results are notified to the device.

[2098] On your device: Notify users that their habit has been assessed and display their progress.

[2099] Reward system processing

[2100] AI model: The AI ​​model calculates the reward amount based on the habit completion rate. For example, it determines "80 yen as the daily reward."

[2101] Server: Receives the reward calculation result and executes cashback to the user's financial institution account using the endpoint " / api / v1 / banking / cashback".

[2102] On the device: Notify the user that the cashback has been applied. For example, display a notification such as "You've received a cashback of 80 yen for achieving your exercise goal today."

[2103] Examples of concrete examples and prompts

[2104] To generate a prompt, enter the following:

[2105] Set a new habit of "30 minutes of exercise every day" and set a deposit of 10,000 yen. Then, record "30 minutes of exercise today" on the progress entry screen in the app, and explain how your habit achievement will be evaluated and how you will be rewarded.

[2106] Based on these prompts, the AI ​​model generates concrete examples to help users maintain their new habits in a fun and efficient way. The system is designed to encourage users to proactively establish new habits and achieve their goals while enjoying financial incentives.

[2107] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2108] Step 1: User Registration and Login

[2109] user:

[2110] Input: The user installs and launches the app, clicks the Sign Up button, and enters the email address "example@example.com" and the password "password123."

[2111] Specific operations: Enter the required information on the new registration screen and click the "Register" button.

[2112] Output: A success message is displayed.

[2113] server:

[2114] Input: The server receives the email address and password entered by the user.

[2115] Data processing: Execute the query "INSERT INTO users (email, password) VALUES ('example@example.com', 'password123');".

[2116] Output: The user information is saved to the database and a success message is returned.

[2117] user:

[2118] Input: On the login screen, enter the email address "example@example.com" and the password "password123".

[2119] Specific actions: Enter information on the login screen and click the Login button.

[2120] Output: Get the token.

[2121] server:

[2122] Input: The server receives the user's email address and password and performs authentication.

[2123] Data operation: Execute the query "SELECT FROM users WHERE email = 'example@example.com' AND password = 'password123';" and generate a token if authentication is successful.

[2124] Output: A token is generated and sent to the device.

[2125] Device:

[2126] Input: Receives a token.

[2127] Specific operation: Save the token and move to the dashboard screen.

[2128] Output: User can access the dashboard.

[2129] Step 2: Setting habits and depositing

[2130] user:

[2131] Input: On the "Set up a new habit" screen, enter the habit "30 minutes of exercise every day" and the deposit amount "10,000 yen."

[2132] Specific actions: Enter your habit and deposit information and click the "Save" button.

[2133] Output: A message will be displayed indicating that the setup is complete.

[2134] server:

[2135] Input: Receives the habits and deposit amount entered by the user.

[2136] Data processing: Run the query "INSERT INTO habits (user_id, habit_detail, deposit_amount) VALUES (1, '30 minutes of exercise daily', 10000);".

[2137] Output: Saves the information to the database and returns a success message.

[2138] Device:

[2139] Input: Receives a success message.

[2140] What it does: Prompts the user that their habits and deposits have been set up.

[2141] Output: A completion message is displayed on the screen.

[2142] Step 3: Track your habit completion

[2143] user:

[2144] Input: Open the progress input screen in the app, enter "Today's exercise time: 30 minutes" and submit.

[2145] Specific actions: Enter information on the progress input screen and click the submit button.

[2146] Output: Progress data is sent.

[2147] server:

[2148] Input: Receives the user's progress data.

[2149] Data processing: Call the endpoint " / api / v1 / progress / evaluate" to send progress data to the AI ​​model.

[2150] Output: Progress data sent to the AI ​​model.

[2151] AI model:

[2152] Input: Receives progress data.

[2153] Data calculation: Analyzes progress data and evaluates "Habit achievement rate 80%."

[2154] Output: Returns the evaluation result to the server.

[2155] server:

[2156] Input: Receives the evaluation results from the AI ​​model.

[2157] Data processing: Execute the query "UPDATE progress SET evaluation = 'Habit achievement level 80%' WHERE user_id = 1;" and save the evaluation results to the database.

[2158] Output: The evaluation results are saved and sent to the device.

[2159] Device:

[2160] Input: Receives notifications from the server.

[2161] What it does: Show the user a notification that says "Habit completion is 80%."

[2162] Output: Progress is displayed on the screen.

[2163] Step 4: Reward System

[2164] AI model:

[2165] Input: Receives the user's habit completion rate.

[2166] Data calculation: Calculate "daily reward of 80 yen" based on the achievement level.

[2167] Output: Returns the reward result to the server.

[2168] server:

[2169] Input: Receives the reward calculation results from the AI ​​model.

[2170] Data processing: Use the endpoint " / api / v1 / banking / cashback" to transfer 80 yen to the user's financial institution account.

[2171] Output: Notifies the terminal of the cashback execution result.

[2172] Device:

[2173] Enter: Receive cashback notifications.

[2174] Specific behavior: Notify the user that "You have received a cashback of 80 yen for achieving your exercise goal today."

[2175] Output: A cashback notification will appear on the screen.

[2176] (Application example 1)

[2177] 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."

[2178] Previous habit-forming systems lacked sufficient motivation to encourage users to continue newly established habits, making long-term habit formation particularly difficult. Furthermore, there was no system that accurately tracked users' progress or provided appropriate rewards. This made it difficult for users to continue the habit, often leading to abandonment. Furthermore, online education platforms and content distribution services lacked methods to encourage users to continue using the habit.

[2179] 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.

[2180] In this invention, the server includes an input means for a user to set a new habit and make a deposit, a means for the server to store the received data in a database, a means for tracking the user's habit progress, a means for an AI to analyze the progress data and evaluate the degree of habit achievement, a means for calculating a reward amount based on the evaluation result, a means for providing cashback to the user's financial account, an input means for setting a learning routine or a viewing routine as a habit set by the user, a means for the user to input or automatically track progress, and a means for notifying the user of progress and rewards. This allows users to form enjoyable and sustainable habits and encourages continued use of online education platforms and content distribution services.

[2181] A "user" is an individual who uses the system to set up new habits and track their progress.

[2182] A "habit" is an ongoing activity, such as a learning routine or viewing routine, that a user engages in regularly.

[2183] A "deposit" is an amount set by the user as an incentive to continue the habit.

[2184] "Progress" is data that shows the degree of achievement of the user's set habits.

[2185] "Tracking" refers to the system recording and monitoring the user's progress in achieving their habits.

[2186] A "server" is a computer system that receives and stores data sent by users and performs any necessary calculations or analyses.

[2187] "Database" means a digital storage system for storing user registration information, progress data, deposit information, reward information, etc.

[2188] "AI" refers to artificial intelligence that analyzes progress data, evaluates the degree of habit achievement, and calculates reward amounts.

[2189] "Rewards" are monetary incentives that users receive for completing their set habits.

[2190] "Cashback" refers to the actual amount of money transferred to a user's financial account based on the habits they achieve.

[2191] "Financial account" refers to a bank account, electronic money account, etc. that a user uses to receive cashback.

[2192] A "learning routine" refers to the regular execution of specific learning activities set by the user.

[2193] A "viewing routine" refers to the regular viewing of specific content set by a user.

[2194] The "input method" is the interface through which the user inputs new habits, deposit amounts, and progress.

[2195] "Notification" refers to the system sending messages to the user to inform them of progress, achievement of rewards, etc.

[2196] The present invention is a system involving three parties: a server, a terminal, and a user, and provides support for users to form new habits.

[2197] 1. Program Generation

[2198] The system consists of the following main components:

[2199] User device: a mobile device such as a smartphone or tablet.

[2200] Server: A computer system for processing and storing data.

[2201] AI model: An artificial intelligence program to assess habit completion.

[2202] 2. Natural language explanation

[2203] User registration and login

[2204] The terminal provides an interface where users can create a new account. The user enters their email address and password, which the server receives and stores in a database. Upon login, authenticated users are issued a token and taken to the dashboard screen.

[2205] Habit Setting and Deposits

[2206] The terminal presents a screen where the user can set up a new habit (e.g., 30 minutes of study per day or watching movies three times a week) and enter a deposit amount. The server stores this information in a database and returns a success message.

[2207] Habit Tracking

[2208] Users record their daily progress and send it from their device to the server. In some cases, progress data is tracked automatically. The server receives the progress data and sends it to the AI ​​model. The AI ​​model analyzes this data and evaluates the degree of habit achievement. The evaluation results are stored in a database and notified to the user.

[2209] Reward System

[2210] The AI ​​model calculates the reward amount based on the habit completion rate. The server receives the calculation result and issues a cashback to the user's financial account. The user can check their progress and reward achievement on their device.

[2211] 3. Hardware and Software Used

[2212] Smartphone app: Implemented using React Native and Flutter.

[2213] Server: Use Node.js or Django.

[2214] Database: Data is stored using PostgreSQL or MongoDB.

[2215] AI model: Use TensorFlow or PyTorch to assess habit completion.

[2216] Cashback API: Use Stripe or PayPal API to execute cashback.

[2217] Specific examples

[2218] Case 1: When you set a new habit of "studying English for 30 minutes every day" and set a deposit of 10,000 yen

[2219] 1. User Registration and Login

[2220] The device provides an interface for creating a new account, and the user enters the required information.

[2221] The server saves the input information in a database and returns a success message.

[2222] The terminal issues a token to the user and takes them to the dashboard screen.

[2223] 2. Habit setting and deposits

[2224] The device provides the user with a habit setting screen, where they input "30 minutes of English study every day" and "a deposit of 10,000 yen."

[2225] The server stores this information in a database and returns a success message.

[2226] 3. Habit Tracking

[2227] The terminal provides an interface for inputting the user's progress.

[2228] The server sends the received progress data to the AI ​​model and stores the evaluation results in a database.

[2229] The device notifies the user of the evaluation results.

[2230] 4. Reward System

[2231] The AI ​​model decides to set the daily reward at 100 yen.

[2232] The server calls the cashback API and transfers 100 yen to the user's financial account.

[2233] The device will notify you, "You have received a cash back of 100 yen for achieving today's learning goal."

[2234] Prompt Sentence Examples

[2235] Write a program that rewards users with 100 yen if they complete 30 minutes of English study every day.

[2236] This system allows users to form new habits in a fun and sustainable way, encouraging continued use of online education platforms and content delivery services.

[2237] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2238] Step 1:

[2239] User registration and login

[2240] Terminal: To create a new account, the user clicks the "Sign up" button on the screen and enters their email address and password. The entered data is sent to the server.

[2241] Server: Receives the input data, stores it in a database, verifies that the information entered is correct, and returns a success message if successful.

[2242] Output: A success message is printed to the terminal.

[2243] On the device: The user enters their email address and password on the login screen and sends them to the server, which authenticates the information and, if successful, generates a token and sends it to the device.

[2244] Input: User's email address and password

[2245] Output: Authentication token

[2246] Terminal: After receiving the authentication token, the user is taken to the dashboard screen and can use the system.

[2247] Step 2:

[2248] Habit Setting and Deposits

[2249] On the device: The user opens the "Set up a new habit" screen and enters the habit (e.g., study English for 30 minutes every day) and the deposit amount. The entered data is sent to the server.

[2250] Server: Receives the entered customs and deposit information, stores it in the database, and returns a success message.

[2251] Output: A success message is printed to the terminal.

[2252] Input: The new habit and deposit amount set by the user

[2253] Output: Success message

[2254] Step 3:

[2255] Habit Tracking

[2256] Device: To record daily progress, users open the "Progress Input" screen and enter the time spent studying and the content they have watched. The input data is sent to the server. In some cases, automatic tracking is also performed.

[2257] Input: User progress data (e.g., 30 minutes of study time)

[2258] Server: Receives progress data and sends it to the AI ​​model, which analyzes the data and evaluates the habit completion.

[2259] Output: Habit achievement evaluation results

[2260] AI model: Analyzes progress data and evaluates habit achievement, which is stored in a database.

[2261] Server: Stores the evaluation results in a database and sends the results to the device.

[2262] On device: Users will receive progress notifications and be able to track their progress.

[2263] Output: Habit completion assessment results sent to the user

[2264] Step 4:

[2265] Reward System

[2266] AI model: Calculates the reward amount based on the habit achievement level. For example, if the achievement level is 50%, set the daily reward to 100 yen.

[2267] Output: Reward amount

[2268] Server: Receives the reward amount and cashbacks the user's financial account. This is done using the Cashback API.

[2269] Input: Reward calculation result

[2270] Output: Cashback success / failure message

[2271] On your device: Display a cashback notification to the user. For example, "You've received a cashback of 100 yen for achieving today's learning goal."

[2272] Output: Cashback notification to be sent to the user

[2273] The system allows users to form new habits effectively and enjoyably, and keeps them motivated through rewards.

[2274] 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.

[2275] The present invention is a system designed to help users enjoy and continue new habits, and aims to increase motivation by taking into account the user's emotional state. This system tracks the habits set by the user and their progress, and provides monetary rewards based on the user's progress and emotional state. The program and specific processing of this system are described in detail below.

[2276] Program processing explanation

[2277] User registration and login

[2278] On the device: The user installs and launches the app, clicks the "Sign Up" button on the screen, and enters their email address and password.

[2279] Server: The server receives the input data and stores it in the database. If registration is successful, it returns a success message to the device.

[2280] Device: The user enters the registered email address and password on the login screen and clicks the login button. The server authenticates the entered information, and if authentication is successful, generates a token and sends it to the device.

[2281] Terminal: Receives the token, moves to the dashboard screen, and the user can use the system.

[2282] Habit Setting and Deposits

[2283] On the device: The user opens the "Set up a new habit" screen and enters the habit. For example, "30 minutes of exercise every day." Next, they enter the amount they want to deposit. For example, they enter "10,000 yen."

[2284] Server: The server receives the entered habits and deposit information, stores it in the database, and returns a success message to the terminal.

[2285] Terminal: Prompts the user that their habits and deposits have been set up.

[2286] Habit Tracking

[2287] On the device: To record their daily progress, users open the "Progress Input" screen in the app. For example, they enter "30 minutes of exercise today" and submit.

[2288] Server: The server receives the progress data and sends it to the AI ​​model.

[2289] AI model: The AI ​​model analyzes the progress data and evaluates the habit achievement, for example, rating it as "progressing as expected."

[2290] Server: The server stores the evaluation results in a database and sends the results to the device.

[2291] On your device: Notify users that their habit has been assessed and display their progress.

[2292] Reward System

[2293] AI model: The AI ​​model calculates the reward amount based on the habit achievement level. For example, it determines "50% achievement means 100 yen per day."

[2294] Server: The server receives the reward calculation results and executes cashback to the user's bank account.

[2295] On the device: Display a cashback notification to the user. For example, display a notification such as "You've received a cashback of 100 yen for achieving your exercise goal today."

[2296] Introducing the Emotion Engine

[2297] Recognition of emotional states

[2298] On the device: To record their emotional state, users can open the "Emotion Input" screen within the app and self-report their feelings. For example, they can enter "I'm happy today." Alternatively, the device can automatically recognize their emotional state from their facial expressions and voice.

[2299] Server: The server receives the emotion data and stores it in a database.

[2300] Emotional data analysis and reflection

[2301] AI model: Analyzes emotional data and evaluates how a user's emotional state affects habit completion.

[2302] Server: Adjusts reward amount and motivational message based on the evaluation results.

[2303] Device: Display an appropriate motivational message to the user, for example, "You're working especially hard today!"

[2304] Linking cashback and emotional states

[2305] AI model: Calculates the optimal reward amount based on emotional data and habit completion. For example, it determines that "the user's emotional state is high, so an additional 20 yen cashback will be given."

[2306] Server: Receives the reward calculation results and sends the cashback to the user's bank account.

[2307] Device: Display a cashback notification to the user along with a pleasurable message based on their emotional state. For example, "You've received a cashback of 120 yen because you achieved your exercise goal today and are feeling happy."

[2308] Specific examples

[2309] Case 2: Using the Emotion Engine to set the habit "30 minutes of exercise every day" and set a deposit of 10,000 yen

[2310] 1. User Registration and Login

[2311] Device: Yamada launches the app and clicks "New Registration."

[2312] Device: Yamada enters her email address and password and clicks "Register."

[2313] Server: Saves the input data and returns a success message.

[2314] Device: Yamada enters her email address and password on the login screen and clicks "Login."

[2315] Server: The server generates an authentication token and sends it to the device.

[2316] Device: Yamada's device receives the token and transitions to the dashboard.

[2317] 2. Habit setting and deposits

[2318] Device: Yamada enters "30 minutes of exercise every day" in "Set a new habit" and clicks "Next."

[2319] Terminal: Enter the deposit amount "10,000 yen" and click "Complete".

[2320] Server: The server saves the information and returns a completion message.

[2321] Device: Yamada's device will display a message indicating that the setup is complete.

[2322] 3. Habit Tracking

[2323] Device: Yamada enters "30 minutes of exercise" in "Enter progress" and submits.

[2324] Server: The server stores the data and sends it to the AI ​​model.

[2325] AI model: The AI ​​model analyzes the progress and sends the evaluation results to the server.

[2326] Server: The server notifies Yamada's device of the evaluation results.

[2327] Device: Yamada's device displays the progress and evaluation results.

[2328] 4. Emotional state input and analysis

[2329] Device: Yamada inputs "Happy" in the "Emotion Input" field and sends it. Alternatively, the device will analyze his facial expressions and voice to recognize his emotions.

[2330] Server: The server stores the emotion data and sends it to the AI ​​model.

[2331] AI model: The AI ​​model analyzes the emotional data and evaluates it to reflect the habit achievement level.

[2332] Server: Adjusts reward amount and motivational message based on the evaluation results.

[2333] 5. Linking reward systems and emotional states

[2334] AI model: The AI ​​model determines the cashback of 100 yen + an additional 20 yen based on the emotional state and habit completion level.

[2335] Server: Save the reward amount, call the cashback API, and transfer 120 yen to Yamada's bank account.

[2336] Device: Yamada's device notifies him that the cashback has been completed and displays a pleasant message: "You've received a cashback of 120 yen because you achieved your exercise goal today and felt good."

[2337] This specific processing step allows users to pursue new habits in a fun way while receiving optimal rewards according to their emotional state.

[2338] The processing flow will be explained below.

[2339] Program processing details

[2340] User registration and login

[2341] Step 1:

[2342] On the device: The user installs and launches the app. They click the "Sign up" button.

[2343] Step 2:

[2344] Device: The user enters their email address and password and clicks the "Register" button.

[2345] Step 3:

[2346] Server: Receives input data and saves it in the database. If registration is successful, returns a success message to the device.

[2347] Step 4:

[2348] Device: The user enters the registered email address and password on the login screen and clicks the "Login" button.

[2349] Step 5:

[2350] Server: Authenticates the input information, and if successful, generates an authentication token and sends it to the device.

[2351] Step 6:

[2352] Terminal: Receive the token and proceed to the dashboard screen.

[2353] Habit Setting and Deposits

[2354] Step 1:

[2355] On the device: The user opens the "Set up a new habit" screen and enters "30 minutes of exercise daily." They then click the Next button.

[2356] Step 2:

[2357] Terminal: The user enters the amount to deposit (10,000 yen). Then clicks the Complete button.

[2358] Step 3:

[2359] Server: Receives the habit and deposit information, stores it in the database, and returns a success message to the terminal.

[2360] Step 4:

[2361] Terminal: Prompts the user that their habits and deposit setup is complete.

[2362] Habit Tracking

[2363] Step 1:

[2364] Device: The user opens the "Enter Progress" screen, enters today's exercise time as "30 minutes," and clicks the submit button.

[2365] Step 2:

[2366] Server: Receives progress data and stores it in a database.

[2367] Step 3:

[2368] Server: Sends saved progress data to the AI ​​model.

[2369] Step 4:

[2370] AI model: Analyzes the received data and evaluates it as "progressing as expected."

[2371] Step 5:

[2372] AI model: Sends the evaluation results to the server.

[2373] Step 6:

[2374] Server: Saves the evaluation results in a database and notifies the terminal of the evaluation results.

[2375] Step 7:

[2376] Device: Shows the user today's progress and assessment results.

[2377] Reward System

[2378] Step 1:

[2379] AI model: Calculates reward amount based on habit achievement. For example, "For 50% achievement, a cashback of 100 yen will be given."

[2380] Step 2:

[2381] AI model: Sends the calculation results to the server.

[2382] Step 3:

[2383] Server: Stores the reward amount in the database.

[2384] Step 4:

[2385] Server: Calls the API to execute the cashback and transfers the money to the user's bank account.

[2386] Step 5:

[2387] On the device: Display a cashback notification to the user, for example, "You've received a cashback of 100 yen for achieving your exercise goal today."

[2388] Introducing the Emotion Engine

[2389] Step 1:

[2390] On the device: The user opens the "Emotion Input" screen and reports their feelings. For example, they can type "I'm happy today." Alternatively, the device can automatically recognize their emotional state from their facial expressions and voice.

[2391] Step 2:

[2392] Server: The server receives the emotion data and stores it in a database.

[2393] Step 3:

[2394] AI model: Analyzes emotional data and evaluates how a user's emotional state affects habit completion.

[2395] Step 4:

[2396] Server: Adjusts reward amount and motivational message based on the evaluation results.

[2397] Step 5:

[2398] Device: Display an appropriate motivational message to the user, for example, "You're working especially hard today!"

[2399] Step 6:

[2400] AI model: Calculates the optimal reward amount based on emotional data and habit completion. For example, it determines that "the user's emotional state is high, so an additional 20 yen cashback will be given."

[2401] Step 7:

[2402] Server: Saves the reward calculation results in the database, calls the cashback API, and transfers the money to the user's bank account.

[2403] Step 8:

[2404] Device: Display a cashback notification to the user along with a pleasurable message based on their emotional state. For example, a notification like "You've received a cashback of 120 yen because you achieved your exercise goal today and are feeling happy" will be displayed.

[2405] Specific examples

[2406] Case 1: Using the Emotion Engine, you set the habit "30 minutes of exercise every day" and set a deposit of 10,000 yen.

[2407] 1. User Registration and Login

[2408] Step 1: Yamada launches the app and clicks "New Registration."

[2409] Step 2: Sam enters her email address and password and clicks "Register."

[2410] Step 3: The server saves the data and returns a success message.

[2411] Step 4: On the login screen, Yamada enters her email address and password and clicks "Login."

[2412] Step 5: The server generates an authentication token and sends it to the device.

[2413] Step 6: Yamada's device receives the token and goes to the dashboard.

[2414] 2. Habit setting and deposits

[2415] Step 1: Yamada enters "30 minutes of exercise every day" in "Set a new habit" and clicks "Next."

[2416] Step 2: Enter the deposit amount "10,000 yen" and click "Complete".

[2417] Step 3: The server saves the information and returns a completion message.

[2418] Step 4: Yamada's device will display a message that the setup is complete.

[2419] 3. Habit Tracking

[2420] Step 1: Yamada enters "30 minutes of exercise" in "Enter progress" and submits it.

[2421] Step 2: The server stores the data and sends it to the AI ​​model.

[2422] Step 3: The AI ​​model analyzes the progress and sends the evaluation results to the server.

[2423] Step 4: The server notifies Yamada's device of the evaluation results.

[2424] Step 5: Yamada's device displays the progress and evaluation results.

[2425] 4. Emotional state input and analysis

[2426] Step 1: Yamada inputs "I'm happy today" in "Emotion Input" and sends it. Alternatively, the device will analyze facial expressions and voice to recognize the emotion.

[2427] Step 2: The server stores the emotion data and sends it to the AI ​​model.

[2428] Step 3: The AI ​​model analyzes the emotional data and evaluates it to reflect the habit completion level.

[2429] Step 4: The server adjusts the reward amount and motivational message based on the evaluation results.

[2430] 5. Linking reward systems and emotional states

[2431] Step 1: The AI ​​model determines the cashback of 100 yen + an additional 20 yen based on the emotional state and habit completion.

[2432] Step 2: The server stores the reward amount in the database.

[2433] Step 3: Call the cashback API and transfer 120 yen to Yamada's bank account.

[2434] Step 4: Yamada's device notifies him that the cashback has been completed and displays a pleasant message: "You've received a cashback of 120 yen because you achieved your exercise goal today and felt happy."

[2435] This specific processing step allows users to pursue new habits in a fun way while receiving optimal rewards according to their emotional state.

[2436] Example 2

[2437] 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."

[2438] Conventional systems for forming new habits primarily record the user's progress and provide rewards based on the level of achievement. However, these systems have the problem of making it difficult to maintain motivation because they do not take into account the user's emotional state. There is a need for a system that can support more effective habit formation by appropriately responding to the user's emotional state.

[2439] 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.

[2440] In this invention, the server includes input means for the user to set a new habit and make a deposit, means for the server to store the received data in a database, means for tracking the user's habit progress, means for the generative AI model to analyze the progress data and evaluate the habit achievement level, means for calculating a reward amount based on the evaluation results, means for executing cashback to the user's bank account, input means for recording the user's emotional state, means for the terminal to automatically recognize the user's emotional state from the user's facial expressions and voice, and means for receiving and analyzing the emotional data and adjusting the reward amount and motivational message based on the evaluation results. This makes it possible to adjust the optimal reward amount according to the user's emotional state, enabling the user to form a new habit while maintaining motivation.

[2441] "User" refers to an individual who is the intended user of this system.

[2442] Habits are activities or behaviors that users plan to perform on a daily basis.

[2443] A "deposit" is the amount a user pays upfront to receive financial rewards for the habits they set.

[2444] "Input means" refers to the interface or device through which a user inputs data into a system.

[2445] "Server" refers to a computer system that receives, processes, and stores data submitted by users.

[2446] A "database" refers to a digital storage device for efficiently storing and managing data collected within a system.

[2447] "Tracking" refers to the continuous recording and monitoring of a user's habit progress and activities.

[2448] A "generative AI model" refers to an artificial intelligence algorithm that analyzes collected data, calculates the degree of habit completion and reward amount, and evaluates the user's emotional state.

[2449] "Analysis" refers to the process of examining collected data in detail to understand its content and patterns.

[2450] "Habit completion level" refers to an indicator that shows the extent to which a user has achieved the habits they have set.

[2451] "Evaluation results" refer to the conclusions reached based on the habit achievement and emotional state analyzed by the generative AI model.

[2452] "Reward amount" refers to the monetary reward the system provides to the user based on the user's level of habit achievement.

[2453] "Cashback" refers to the process of returning reward amounts to the user's bank account.

[2454] "Emotional state" refers to information that indicates the user's current psychological feelings.

[2455] "Facial Expression" refers to a user's facial expression that is used to recognize the user's emotional state.

[2456] "Voice" refers to audio data used to recognize the user's emotional state.

[2457] "Motivational messages" refer to messages provided by the system to motivate users and encourage them to continue using the system.

[2458] "Behavioral patterns" refers to data that shows a user's past activities and behavioral tendencies.

[2459] The present invention is a system designed to help users enjoy and continue new habits, and aims to increase motivation by taking into account the user's emotional state. The system tracks the user's established habits and their progress, and provides monetary rewards according to the user's progress and emotional state. Specific embodiments for implementing the present invention are described in detail below.

[2460] User registration and login

[2461] A user installs and launches the application on a device such as a smartphone or tablet. First, the user clicks the "New Registration" button and enters their email address and password. The server receives this input data and stores it in a database. If registration is successful, a success message is returned to the device. Next, the user enters their email address and password on the login screen and clicks the login button. The server authenticates the entered information, and if authentication is successful, generates a token and sends it to the device. The user receives the token and can proceed to the dashboard screen to use the system.

[2462] Habit Setting and Deposits

[2463] The user opens the "Setting a new habit" screen and enters the specific habit. For example, the user can enter "30 minutes of exercise every day." The user then enters the amount to deposit, for example, "10,000 yen." The server receives this input data and stores it in the database. After a success message is returned to the terminal, the user can confirm that the setup is complete.

[2464] Habit Tracking

[2465] To record their daily progress, users open the "Progress Input" screen in the app, enter progress information (for example, "30 minutes of exercise today") and submit it. The server receives the progress data and sends it to the generative AI model. The generative AI model analyzes the progress data and evaluates the degree of habit achievement. For example, the generative AI model may evaluate the progress as "progressing as expected." This evaluation result is sent to the server and stored in a database. Finally, the result is notified to the user's device, allowing the user to check their progress.

[2466] Reward System

[2467] The generative AI model calculates the reward amount based on the degree of habit achievement. For example, it may determine "100 yen as the daily reward for achieving 50%." The server receives the reward calculation results and executes a cashback to the user's bank account. The user can check the cashback notification on their device. For example, it may display "100 yen has been cashbacked for achieving today's exercise goal."

[2468] Introducing the Emotion Engine

[2469] Recognition of emotional states

[2470] To record their emotional state, users can open the "Emotion Input" screen in the app and self-report their feelings. For example, they can enter "I'm happy today." Alternatively, the device can automatically recognize their emotional state from their facial expressions and voice. The server receives the emotional data and stores it in a database.

[2471] Emotional data analysis and reflection

[2472] The generative AI model analyzes the emotional data and evaluates how the user's emotional state affects their habit achievement. The server then adjusts the reward amount and motivational message based on the evaluation results. For example, it displays an appropriate motivational message to the user, such as, "You're working especially hard today!"

[2473] Linking cashback and emotional states

[2474] The generative AI model calculates the optimal reward amount based on emotional data and the degree of habit achievement. For example, it ...

Claims

1. Input methods for users to set new habits and make deposits; A means for the server to store the received data in a database; A means for tracking the user's habit progress; AI analyzes progress data and evaluates habit achievement, A means for calculating a remuneration amount based on the evaluation result; A means for issuing cashback to the user's bank account; A system including:

2. The system according to claim 1, further comprising means for the AI ​​to adjust the optimal remuneration amount based on the user's behavioral patterns.

3. 10. The system of claim 1, further comprising means for providing an interface for a user to input progress.

Images