system

Abstract

We provide the system. [Solution] In an information processing device, there is a means for receiving target information from a user via an input means, A generation model means that analyzes the aforementioned target information to generate specific target settings and deadlines, A notification means for notifying the user of the generated goal setting information, A progress management means for managing progress information toward the goal provided by the generative model means, An advice provision means that generates advice information based on the aforementioned progress information and notifies the user, A reward calculation method that calculates and notifies reward information when a goal is achieved, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] An object of the present invention is to specifically set various goals that a user wishes to achieve and solve the difficulty of managing progress while continuously maintaining motivation. In the conventional method, it is difficult to clarify the ambiguity in goal setting and appropriately grasp the progress situation, and particularly, the motivation for achieving the goal is easily interrupted, which is an issue.

Means for Solving the Problems

[0005] This invention solves the aforementioned problems by providing a system in which an information processing device receives goal information from a user and uses a generative model to set specific goals and deadlines based on that information. Furthermore, by managing progress information and providing advice based on that information, it supports users in effectively progressing towards the goals they should achieve. In addition, it helps maintain motivation by calculating and notifying reward information when goals are achieved.

[0006] An "information processing device" is an electronic device that receives, processes, and outputs data from users.

[0007] "Input means" refers to a method or interface for a user to supply information to an information processing device.

[0008] "Goal information" refers to data related to the content and objectives that users want to achieve.

[0009] A "generative model means" is an algorithm or technique that generates a specific output based on the information received.

[0010] A "notification means" is a means of informing the user of the results generated by an information processing device.

[0011] "Progress management methods" refer to methods for evaluating and monitoring the status and progress of activities toward achieving a goal.

[0012] An "advice provision method" is a function that provides advice on areas for improvement and next steps based on the user's progress.

[0013] A "reward calculation method" is a method of determining rewards based on the degree of achievement of a goal and calculating the result.

[0014] "Reward information" refers to information about the compensation or incentives provided for achieving goals. [Brief explanation of the drawing]

[0015] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Mode for Carrying Out the Invention

[0016] An example of an embodiment of the system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0019] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0021] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0023] [First Embodiment]

[0024] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0025] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0028] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0031] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0035] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0036] The system of this invention receives goal information entered by the user, provides appropriate goal setting based on that information, manages progress, and provides rewards, all while providing consistent support.

[0037] The user has a device in their possession, and they input their goal information through that device. This goal information might be something like, "I want to lose 5kg." This information is then sent from the device to the server.

[0038] The server analyzes the received goal information and uses a generative model to set specific, achievable goals and deadlines for the user. In this process, the generative model takes into account past data and the user's current state when setting goals. The set goals and deadlines are sent from the server to the terminal and notified to the user.

[0039] During the progress management phase, users record their daily progress on their devices. For example, they might record activities such as "I went for a 30-minute run today." This data is then sent back to the server for analysis.

[0040] The server generates advice based on progress data. This advice, such as "Let's try strength training next," is provided to the user via the terminal. This advice is designed to support the user's actions toward achieving their goals.

[0041] Ultimately, the server evaluates the progress data, and if it determines that the set goal has been achieved, it generates reward information using a reward calculation mechanism and notifies the user. Reward information may include, for example, "500 points awarded for achieving the goal." The terminal displays this reward information to the user, encouraging them to set further goals and take on challenges.

[0042] As a concrete example, a user who sets a goal to lose weight would record their daily activities, receive feedback from the server, achieve their goal, and receive a reward. This allows users to continuously improve themselves based on clear goals.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] The terminal displays a goal input screen to the user. This interface allows the user to specifically input the goals they want to achieve and the areas they want to improve.

[0046] Step 2:

[0047] The user enters their goal information. This goal information refers to a specific objective, such as "I want to lose 5 kg." The entered data is immediately sent from the terminal to the server.

[0048] Step 3:

[0049] The server runs a generative model based on the target information it receives. The generative model sets specific, achievable targets and deadlines for the user, based on historical data, relevant literature, and other similar cases.

[0050] Step 4:

[0051] The server sends the generated goal settings and deadlines to the terminal. The terminal displays this to the user for review. The user can review the proposed goals and make modifications or additional settings as needed.

[0052] Step 5:

[0053] Users record their daily activities on their devices. For example, they might input specific details such as, "I went for a 30-minute run today." This data is sent to the server periodically or in real time.

[0054] Step 6:

[0055] The server analyzes the received activity data and evaluates the progress. Generative models are used for evaluation to generate the most effective advice for each user and determine what improvements are possible.

[0056] Step 7:

[0057] The server sends the generated advice to the terminal, which then displays it to the user. The advice includes specific action suggestions and points to note for the next step. For example, it might say, "We recommend combining this with strength training next."

[0058] Step 8:

[0059] The server verifies goal achievement based on the user's progress data. If achievement is confirmed, it determines the reward to be given to the user using a reward calculation mechanism and generates reward information.

[0060] Step 9:

[0061] The server sends the generated reward information to the device. The device then notifies the user of the reward. For example, it might display something like, "You have been awarded 500 points for achieving your goal." The rewards serve to maintain the user's motivation and encourage them to set new goals.

[0062] (Example 1)

[0063] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0064] Traditional goal management systems have faced challenges in effectively managing user progress toward achieving their goals and providing appropriate advice. Furthermore, they often lacked sufficient reward systems to sustain user motivation.

[0065] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0066] In this invention, the server includes means for receiving goal data from the user, means for generating a generation algorithm that analyzes the goal data to generate specific goal settings and deadlines, and means for notifying the user of the generated goal setting data. This makes it possible to set achievable and specific goals based on the goal data entered by the user and to always provide appropriate instructions according to the latest progress data. Furthermore, a reward system using reward data can increase the user's motivation and support goal achievement.

[0067] An "information processing device" is a device that has the functions of inputting, processing, and outputting data, and refers to a system that supports goal setting and progress management.

[0068] An "input device" is a device that receives information from the user and has the function of accepting target data and activity data.

[0069] "User" refers to an entity that uses the system to set goals and aims to achieve them.

[0070] "Target data" refers to information about the goals that the user wishes to achieve, and is the basic data entered into the system.

[0071] "Generation algorithm means" refers to technical means for analyzing input target data and generating specific target settings and deadlines suitable for the user.

[0072] "Communication methods" refer to means of notifying the user of generated data or information, and often refer to email or in-app notifications.

[0073] "Progress monitoring means" refers to means of recording and managing the user's progress toward achieving a goal, and includes a function to analyze activity data and evaluate progress.

[0074] "Means of providing instructions" refers to means of notifying users of appropriate advice based on progress data.

[0075] "Reward calculation method" refers to a technical means for calculating the reward provided to the user when a goal is achieved.

[0076] "Reward data" refers to data representing reward information awarded to users for achieving their goals, and includes points, medals, and other similar items.

[0077] This invention is a system that uses an information processing device to consistently handle everything from goal setting to progress management and reward provision in order to support the achievement of user-defined goals. Specific embodiments of the system are shown below.

[0078] The user uses a device they have on hand to input their desired goals. This device functions as an information processing unit and uses the input device to acquire the user's goal data. For example, a user can set a goal such as "reduce body fat percentage by 5% in 3 months." This goal data is transmitted from the device to the server via the internet.

[0079] The server operates in the cloud and analyzes the received target data. This analysis uses a generative AI model. This model considers existing achievement goal datasets and user profile information to generate specific, achievable goals and deadlines tailored to the user. For example, "Based on your goals, aim to reduce your body fat percentage by 1% every two weeks." The generated data is then sent back to the device using communication functions and the user is notified.

[0080] Progress is managed based on the user's daily activities. Users record activity data such as running time and calories burned on their device. The device then sends this data to a server, which evaluates the progress. Based on the progress data, a generative AI model builds and provides advice to the user. For example, it might suggest, "Next time, try incorporating strength training."

[0081] Ultimately, the server evaluates progress and calculates reward data as a bonus if the user achieves their goal. This bonus data can be implemented, for example, as a points system, and provided to the user in a specific form, such as "50 points awarded" depending on their level of achievement. This allows users to challenge themselves with further goals and maintain their motivation to achieve them.

[0082] An example of a prompt for the generative AI model would be, "Based on the target data entered by the user, please generate specific, achievable goals and their deadlines." By using this prompt, the server can leverage the generative AI to provide the user with the most appropriate advice and progress support.

[0083] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0084] Step 1:

[0085] Users input target data using a device. Specifically, they set a goal, such as "reduce body fat percentage by 5% in 3 months," through the device's input interface. The input includes the goal content and the timeframe for achieving it. This input is processed as digital data on the device and sent to the server.

[0086] Step 2:

[0087] The server analyzes the goal data received from the terminal. Based on the received data, it calls a generation AI model and generates specific goals and deadlines, taking into account the user's profile data and past goal achievement data. This analysis uses the prompt message, "Based on the goal data entered by the user, please generate specific, achievable goals and their deadlines." The output is the specific goals and their deadlines, and this information is sent back to the terminal.

[0088] Step 3:

[0089] The terminal notifies the user of specific goals and deadlines sent from the server. The input here is notification information from the server, and the output is a visual presentation to the user. On the terminal, specific goals are displayed via pop-up notifications, alerting the user.

[0090] Step 4:

[0091] Users record their daily activities on their devices. This includes inputting data such as running time and calories burned. The input is activity data, which is organized on the device and prepared for transmission to the server. The output is the organized activity data.

[0092] Step 5:

[0093] The server evaluates progress based on activity data submitted by the user. The server analyzes this data and uses a generative AI model to generate advice for the next action. The input is the user's daily activity data, and the output is specific advice generated by the generative AI model. This advice is then communicated to the user via their device.

[0094] Step 6:

[0095] Ultimately, the server evaluates the progress and, if it determines that the goal has been achieved, calculates reward data. The input here is the achievement status obtained through progress management, and the output is reward information as reward data. For example, reward data such as "50 points awarded for achieving the goal" is generated and notified to the user via the terminal.

[0096] (Application Example 1)

[0097] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0098] In today's information society, maintaining motivation and managing progress toward achieving personal goals is crucial, but there is a lack of effective methods to consistently support this. Furthermore, there is a need for a system that allows incentives for goal achievement to be used in real life as electronic currency or points. This invention aims to enhance motivation for goal achievement by managing the progress of user-set goals and awarding electronic currency or points as rewards.

[0099] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0100] In this invention, the server includes means for receiving goal information from the user via an input device, means for generating a model that analyzes the goal information to set specific goals and manage progress, means for calculating and notifying reward information as electronic currency or points when the goal is achieved, and means for enabling the user to use the reward at affiliated stores. As a result, the user is consistently supported in the process of achieving their goals and can utilize the reward to benefit their daily life.

[0101] An "information processing device" is a device used for inputting, analyzing, storing, and outputting data, and includes computers and servers.

[0102] An "input device" is a device used by users to provide information to a system, and includes keyboards and touchscreens.

[0103] A "user" refers to an individual or organization that operates an information processing device, inputs target information, and manages its progress.

[0104] "Target information" refers to information that indicates the specific challenges and objectives that the user aims to achieve, and serves as the starting point for the system's analysis.

[0105] "Generative modeling means" refers to technologies and methods used to analyze received information and create achievable goals and their deadlines for the user.

[0106] "Notification means" refers to methods or devices for communicating generated information or results to users, and includes push notifications and email communications.

[0107] A "progress management system" is a mechanism for tracking and evaluating the progress made towards goals set by the user.

[0108] "Advice provision means" refers to methods and devices for providing useful advice to users based on progress information and supporting them in achieving their goals.

[0109] A "reward calculation means" is a method or device for calculating a predetermined reward and providing it to the user when the user achieves a goal.

[0110] "Electronic currency" is a form of currency that is exchanged in digital format, unlike traditional banknotes and coins.

[0111] "Points" are units that accumulate based on a user's actions and transactions, and can be used as rewards.

[0112] A "participating store" is a store or organization that accepts rewards provided by the system and uses them to make purchases or provide services.

[0113] In order to implement this invention, a mechanism is needed in which target information is input through an information processing device via user operation, and that information is analyzed by a server.

[0114] The server automatically generates specific goals and deadlines using a generative AI model based on the goal information received from the information processing device. This generative AI model can present realistic and achievable goals by considering the user's past data and relevant statistical information.

[0115] The goal settings generated by the server are sent to the user's device via a notification system, allowing for visual tracking. Users record their daily activities on their devices, and the server analyzes this activity information to manage progress. Examples of specific activities include running and calorie consumption.

[0116] Based on progress information, the server uses an advice provision system to generate effective action plans and improvement suggestions for the user to achieve their goals. This advice is based on daily activities and includes specific instructions such as, "Next time, you should increase your aerobic exercise." If the user achieves their goals, the server uses a reward calculation system to automatically calculate electronic currency or points and award them to the user as a reward.

[0117] The system's programs are primarily written in Python, and Scikit-learn and TENSORFLOW® are used for data analysis and model generation. Communication between the server and the terminal is done using a RESTful API, and MySQL® is used as the database for data storage. The application's frontend is built using React.

[0118] As a concrete example, consider a case where a user sets a goal of "losing 2 kg in one month." The user registers information about their exercise and meals daily through the app. The server analyzes this activity, monitors progress in real time, and generates appropriate training menus and advice. Through this process, the user can earn points as a reward, which can be used for shopping at participating stores. An example of a prompt message would be, "Please enter your activity level for today. Example: '30 minutes of running, 20 minutes of strength training'."

[0119] In this way, this invention enables users to set goals, reliably manage their progress, and earn valuable rewards in real life.

[0120] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0121] Step 1:

[0122] The user enters goal information via the input device on the terminal. For example, they might set a goal such as "lose 2 kg in one month." This goal information is then sent to the server, guided to the user using prompt messages.

[0123] Step 2:

[0124] The server inputs the received goal information into the generating AI model. Based on past data and the user's current state, the generating AI model generates realistic and achievable specific goals and deadlines. During this generation process, statistical processing is performed using Scikit-learn for data analysis to obtain the goal setting results.

[0125] Step 3:

[0126] The server sends the generated goal setting results to the user's terminal via a notification mechanism. The terminal visually displays the goals and notifies the user. Throughout this process, data is exchanged appropriately using a RESTful API.

[0127] Step 4:

[0128] Users input daily activity information into their devices. This activity information includes exercise time and meal details. This data is sent from the user's device to a server and used for progress management.

[0129] Step 5:

[0130] The server analyzes the received activity information using a progress management system. This analysis includes data processing to understand the current progress and evaluate the degree to which the goal has been achieved. Based on the activity information, the server uses Scikit-learn to update the progress information.

[0131] Step 6:

[0132] Based on progress information, the server generates user-facing advice using a generative AI model and sends it to the user's terminal via an advice delivery system. This advice includes specific action plans to effectively support goal achievement.

[0133] Step 7:

[0134] The server evaluates the progress and, if it determines that the user has achieved their goal, calculates electronic currency or points using a reward calculation system. This calculation uses a points system built with the Django framework.

[0135] Step 8:

[0136] The server notifies the user of the calculated reward information and informs them that it can be used at participating stores. This supports users in using the electronic currency or points they have earned as rewards in their daily lives.

[0137] Through this series of processing steps, the system comprehensively supports the user in achieving their goals.

[0138] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0139] The present invention is an information processing device that supports users in achieving their goals, and in particular, by combining it with an emotion engine, it provides personalized support that takes into account the user's emotional state.

[0140] The device collects goal information and daily activity data based on user input. Users record their goals and activities on the device, setting specific goals such as "I want to lose 5 kg." This data is then sent to the server.

[0141] The server analyzes the received target information and activity data, and uses a generative model to set specific targets and deadlines. This generated target information is then sent back to the terminal and notified to the user.

[0142] The emotion engine recognizes the user's current emotional state using user input data and other information. This emotional information is then used as a factor influencing the goal information and advice set on the server.

[0143] The progress management system manages progress toward goal achievement based on daily activity data. This allows the server to monitor progress in real time and provide users with timely and necessary advice. The advice generated by the advice provision system may include suggestions such as "Let's try a new exercise method next," and is adjusted to take into account the user's emotional state.

[0144] The reward calculation system calculates a predetermined reward when the user achieves the goal they have set and notifies the user of the result. The reward functions as an incentive to increase the user's motivation.

[0145] As a concrete example, consider a user who sets a goal of improving their health and records their daily activities. The system takes the user's current emotional state into consideration, sets achievable goals, and provides advice based on their progress. Furthermore, it offers the user a reward upon recognition of their achievement. This allows the user to efficiently progress towards their goals while also considering their emotions.

[0146] The following describes the processing flow.

[0147] Step 1:

[0148] The terminal displays a goal input screen to the user. This screen is an interface for entering specific goals and areas for improvement, and is provided in a user-friendly format.

[0149] Step 2:

[0150] The user enters goal information via their device. For example, they might set a goal such as "I want to lose 5 kg." This entered data is then sent to the server.

[0151] Step 3:

[0152] The server analyzes the received target information. Using a generative model, it generates specific targets and deadlines for their achievement that are appropriate to the user's situation from this information.

[0153] Step 4:

[0154] The server uses an emotion engine to recognize the user's emotional state from their input and current behavioral data. For example, it can detect if a user is experiencing stress through text analysis and frequency information.

[0155] Step 5:

[0156] The server generates goal setting and advice that take the user's emotional state into account. This includes adjustments such as setting realistic goals and suggesting relaxation methods if the user is experiencing stress.

[0157] Step 6:

[0158] The server generates goal settings and advice and sends them to the terminal. The terminal notifies the user and displays them for daily review. The user then uses this information to develop an activity plan.

[0159] Step 7:

[0160] The user records their daily activities. The device also allows for the optional input of emotional data, recording information in detail. For example, information such as "I went for a 30-minute run today, and I'm a little tired" can be entered.

[0161] Step 8:

[0162] The device sends daily activity and emotional data it collects to the server. The server analyzes this data through progress management tools to understand progress and emotional trends.

[0163] Step 9:

[0164] The server generates new advice based on the progress. This advice includes suggestions that take into account changes in emotional state. The advice is sent to the terminal and displayed to the user.

[0165] Step 10:

[0166] The server checks whether the set goal has been achieved, and if so, calculates the reward using the reward calculation system. This reward information is then notified to the user via their terminal. For example, it might say, "You have been awarded 500 points as a reward for achieving your goal."

[0167] This process allows users to receive emotionally conscious support and achieve their goals more efficiently.

[0168] (Example 2)

[0169] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0170] Conventional goal achievement support systems lacked support that considered the user's emotional state, making it difficult to maintain motivation and provide effective advice. Furthermore, simple progress management based solely on user behavioral data failed to provide individualized support, hindering efficient goal achievement.

[0171] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0172] In this invention, the server includes means for receiving goal information and behavioral data from the user via input means, generation model means for analyzing the goal information and behavioral data to generate specific goal settings and deadlines, and notification means for notifying the user based on the generated goal setting information and emotional state. This makes it possible to provide personalized advice that takes into account the user's emotional state, thereby improving the efficiency of goal achievement.

[0173] "Input means" refers to devices or software used to receive goal information and behavioral data from users.

[0174] "Goal information" refers to information about the specific goals and objectives that the user wishes to achieve.

[0175] "Behavioral data" refers to data about the user's daily activities, including exercise levels and lifestyle habits.

[0176] A "generative modeling tool" is a function for setting realistic and achievable specific goals and their deadlines based on the information received.

[0177] A "notification method" is a means of communicating generated goal information and advice to the user.

[0178] A "progress management method" is a method for tracking and managing the progress toward set goals.

[0179] An "advice provision tool" is a function that generates and provides appropriate guidance and advice to users based on progress information and emotional state.

[0180] A "reward calculation method" is a method for calculating appropriate rewards according to the degree to which a user has achieved their goals.

[0181] "Emotional state" refers to the user's mental state, reflecting their current mood and motivation.

[0182] This invention provides an information processing device for supporting users in achieving their goals. Users input goal information and daily behavioral data via a terminal, and the system provides appropriate support for achieving those goals based on this data.

[0183] The device acquires goal information and behavioral data from the user using input methods. A specific example is when a user sets a goal of "losing 5 kg in the next three months" and inputs their daily exercise and food intake records to achieve that goal.

[0184] The data entered by the user is sent to the server. The server uses a generative AI model to analyze this data and set realistic and achievable specific goals and deadlines. The analysis also takes into account the user's emotional state using an emotion engine. For example, the generative AI model can suggest a "one-week plan combining moderate exercise and a balanced diet."

[0185] The server sends the generated goal information back to the terminal and notifies the user. This notification is intended to make it easier for the user to act according to the plan. Furthermore, progress tracking mechanisms are used to track and manage the user's progress in real time based on their behavioral data.

[0186] Furthermore, using an advice delivery system, the server generates and notifies users of personalized advice based on their progress and emotional state. For example, it can provide advice such as, "You seem a little tired today. How about trying some stretching?"

[0187] The reward calculation system calculates reward information when the user achieves a goal and notifies them via their device. This helps maintain user motivation and allows them to work more effectively towards achieving their goals.

[0188] An example of a prompt might be, "Analyze the user's current exercise and dietary data and suggest the optimal fitness plan for next week." This prompt allows the system to provide personalized feedback to each individual user.

[0189] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0190] Step 1:

[0191] Users input goal information and daily activity data via their device. They enter their goals on the device and record daily data such as exercise levels and dietary details. This input data is temporarily stored on the device before being sent to the server.

[0192] Step 2:

[0193] The server analyzes the received goal information and behavioral data. A generative AI model is used for the analysis, generating optimal goal settings for the user from this data. Specifically, it processes data such as "exercise time" and "calorie intake" entered by the user, and the AI ​​model proposes realistic goals that can be achieved within a achievable timeframe. This output might be something like, "Aim to lose 0.5 kg per week."

[0194] Step 3:

[0195] The server analyzes the user's emotional state and adjusts the generated goal information using an emotion engine. User emotional data (e.g., login records or specific keyword inputs) is input, and the server analyzes that emotional state. Based on the analysis results, goal setting and advice are adjusted. For example, if the user is stressed, a comment such as "Let's proceed at a comfortable pace" may be added.

[0196] Step 4:

[0197] The server sends final goal information and advice to the terminal and notifies the user. The notification includes a step-by-step approach to achieving the goal and provides advice tailored to the user's situation. For example, it might output specific instructions such as, "Let's go for a 30-minute walk for three days this week."

[0198] Step 5:

[0199] The server manages progress information and updates it in real time based on daily activity data. It receives the user's latest activity data as input, checks the degree of goal achievement using the progress management system, and outputs the progress status as information. This is provided to the user in the form of "You have achieved 80% of your goal this week."

[0200] Step 6:

[0201] The server uses a reward calculation mechanism to calculate rewards based on the degree of goal achievement. Rewards are calculated based on the goal achievement status obtained from progress management. For example, when a step is achieved, a message such as "Points earned for the next stage" is output and notified to the user via the terminal.

[0202] (Application Example 2)

[0203] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0204] While modern information processing technology allows users to set individual goals and receive progress management and advice based on those goals, providing appropriate support that takes into account the user's emotional state remains challenging. Furthermore, in physical stores, there is a lack of systems that can provide real-time, personalized suggestions to users as they select products and services that best suit their needs. This results in inefficiencies in supporting users in achieving their goals and assisting them in their purchasing decisions.

[0205] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0206] In this invention, the server includes a generation model means that analyzes the user's goal information and generates specific goal settings and deadlines; a means that adapts advice information and goal setting information based on the user's emotional state analyzed by an emotion engine; and a means that provides appropriate suggestions in real time when the user selects products or services related to their objectives. This enables effective goal achievement support that takes into account the user's emotions and personalized, real-time suggestions during purchasing activities at physical stores.

[0207] An "information processing device" refers to the entire system used to receive, analyze, notify, and manage input from users.

[0208] An "input device" refers to a device or interface used by a user to provide goal information and daily activity data to the system.

[0209] "Generative model means" refers to an algorithm or mechanism for generating specific goal settings and corresponding deadlines based on goal information received from the user.

[0210] "Notification means" refers to a method or device for informing users of generated goal setting information, progress information, advice information, and reward information.

[0211] "Progress management tools" refer to systems for continuously tracking and managing users' daily progress toward achieving their goals.

[0212] "Means of providing advice" refers to systems or mechanisms for providing users with advice generated based on progress information.

[0213] "Reward calculation method" refers to the process of calculating a predetermined reward when a user achieves a goal they have set, and notifying the user of that reward.

[0214] An "emotion engine" refers to a technology that analyzes a user's emotional state based on their input data and related information, and adjusts the system's operation based on the results.

[0215] A "real-time suggestion system" refers to a mechanism that provides immediate and appropriate suggestions to users when they are selecting products or services related to their purpose.

[0216] The system implementing this invention combines information processing technology and emotion analysis technology to support users in achieving their goals.

[0217] The server first receives goal information set by the user from the input device. Next, it uses a generative model to analyze this goal information and generate specific goal settings and corresponding deadlines. The server also uses an emotion engine to determine the user's emotional state from various input and sensor data. This analysis can utilize emotion analysis functions such as AWS® Rekognition or Google® Cloud Vision API. The results of the emotional state analysis are used to adjust goal settings and advice information, providing more personalized support.

[0218] The generated goal-setting information and advice information are transmitted to the user's device in real time via a notification system. At this time, a progress management system, tailored to the user's emotional state, monitors the progress towards the goal and further optimizes the advice information based on that progress. For example, if a user sets a goal of "losing 5kg" through fitness activities, the system can provide exercise suggestions and nutritional advice while considering daily activity data and sensor information such as heart rate. Upon achieving the goal, the system provides an incentive to the user through a reward calculation system.

[0219] Furthermore, the system provides personalized product recommendations via real-time suggestions when customers select products or services in physical stores. This allows customers to obtain the necessary information on the spot and make appropriate purchasing decisions.

[0220] A concrete example is when a user is choosing new fitness gear at a sports goods store; the system suggests shoes and apparel that take into account the user's current exercise goals and emotional state. Such suggestions allow users to efficiently work towards their goals.

[0221] Example prompt: "When a user is aiming for weight loss, what fitness products would be recommended, and what kind of support would be offered in different emotional states? Please provide specific product names and examples of support messages."

[0222] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0223] Step 1:

[0224] The terminal receives goal information and activity data from the user through an input device. This input includes specific goals (e.g., lose 5 kg), daily exercise levels, and dietary information. This data is then sent to a subsequent analysis step.

[0225] Step 2:

[0226] The server analyzes the received goal information and activity data using a generating AI model. Here, the data is structured, and appropriate goal settings and deadlines are generated. This process analyzes the user's activity patterns using a predetermined algorithm and sets achievable goals. Specific goal setting information is generated as output.

[0227] Step 3:

[0228] The server evaluates the generated goal setting information and activity data using an emotion engine to analyze the user's emotional state. This analysis utilizes AWS Rekognition and Google Cloud Vision APIs to determine emotions from voice, text, and sensor data. The output provides data on the user's current emotional state.

[0229] Step 4:

[0230] The server integrates the analyzed goal-setting information and emotional state data, and manages the progress information using a progress management system. During this process, advice tailored to the emotional state is generated. This generated advice is sent to the user as feedback. This feedback includes specific suggestions, such as, "Next, try relaxing yoga."

[0231] Step 5:

[0232] When the server achieves the goal set by the user, it calculates an incentive based on the degree of achievement using a reward calculation mechanism and notifies the user. This calculation takes into account both progress and emotional state. As output, the user is provided with appropriate reward information.

[0233] Step 6:

[0234] When a user selects products in a physical store, the terminal receives real-time suggestions from the server. The system considers the user's goal information, emotional state, and current location to suggest appropriate products and services. For example, new running shoes might be suggested as a purchase option.

[0235] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0236] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0237] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0238] [Second Embodiment]

[0239] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0240] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0241] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0242] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0243] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0244] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0245] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0246] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0247] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0248] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0249] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0250] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0251] The system of this invention receives goal information entered by the user, provides appropriate goal setting based on that information, manages progress, and provides rewards, all while providing consistent support.

[0252] The user has a device in their possession, and they input their goal information through that device. This goal information might be something like, "I want to lose 5kg." This information is then sent from the device to the server.

[0253] The server analyzes the received goal information and uses a generative model to set specific, achievable goals and deadlines for the user. In this process, the generative model takes into account past data and the user's current state when setting goals. The set goals and deadlines are sent from the server to the terminal and notified to the user.

[0254] During the progress management phase, users record their daily progress on their devices. For example, they might record activities such as "I went for a 30-minute run today." This data is then sent back to the server for analysis.

[0255] The server generates advice based on progress data. This advice, such as "Let's try strength training next," is provided to the user via the terminal. This advice is designed to support the user's actions toward achieving their goals.

[0256] Ultimately, the server evaluates the progress data, and if it determines that the set goal has been achieved, it generates reward information using a reward calculation mechanism and notifies the user. Reward information may include, for example, "500 points awarded for achieving the goal." The terminal displays this reward information to the user, encouraging them to set further goals and take on challenges.

[0257] As a concrete example, a user who sets a goal to lose weight would record their daily activities, receive feedback from the server, achieve their goal, and receive a reward. This allows users to continuously improve themselves based on clear goals.

[0258] The following describes the processing flow.

[0259] Step 1:

[0260] The terminal displays a goal input screen to the user. This interface allows the user to specifically input the goals they want to achieve and the areas they want to improve.

[0261] Step 2:

[0262] The user enters their goal information. This goal information refers to a specific objective, such as "I want to lose 5 kg." The entered data is immediately sent from the terminal to the server.

[0263] Step 3:

[0264] The server runs a generative model based on the target information it receives. The generative model sets specific, achievable targets and deadlines for the user, based on historical data, relevant literature, and other similar cases.

[0265] Step 4:

[0266] The server sends the generated goal settings and deadlines to the terminal. The terminal displays this to the user for review. The user can review the proposed goals and make modifications or additional settings as needed.

[0267] Step 5:

[0268] Users record their daily activities on their devices. For example, they might input specific details such as, "I went for a 30-minute run today." This data is sent to the server periodically or in real time.

[0269] Step 6:

[0270] The server analyzes the received activity data and evaluates the progress. Generative models are used for evaluation to generate the most effective advice for each user and determine what improvements are possible.

[0271] Step 7:

[0272] The server sends the generated advice to the terminal, which then displays it to the user. The advice includes specific action suggestions and points to note for the next step. For example, it might say, "We recommend combining this with strength training next."

[0273] Step 8:

[0274] The server verifies goal achievement based on the user's progress data. If achievement is confirmed, it determines the reward to be given to the user using a reward calculation mechanism and generates reward information.

[0275] Step 9:

[0276] The server sends the generated reward information to the device. The device then notifies the user of the reward. For example, it might display something like, "You have been awarded 500 points for achieving your goal." The rewards serve to maintain the user's motivation and encourage them to set new goals.

[0277] (Example 1)

[0278] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0279] Traditional goal management systems have faced challenges in effectively managing user progress toward achieving their goals and providing appropriate advice. Furthermore, they often lacked sufficient reward systems to sustain user motivation.

[0280] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0281] In this invention, the server includes means for receiving target data from a user, generation algorithm means for analyzing the target data to generate specific target settings and deadlines, and communication means for notifying the user of the generated target setting data. As a result, based on the target data input by the user, it becomes possible to set achievable and specific goals and provide appropriate instructions according to the always up-to-date progress data. In addition, a reward system using privilege data can enhance the user's motivation and support goal achievement.

[0282] An "information processing device" refers to a device having functions for inputting, processing, and outputting data, and refers to a system for assisting in goal setting and progress management.

[0283] An "input device" is a device for receiving information from a user and has a function of receiving target data and activity data.

[0284] A "user" refers to a subject who sets goals using the system and aims to achieve them.

[0285] "Target data" refers to information regarding the goals that a user wants to achieve and refers to the basic data input into the system.

[0286] "Generation algorithm means" refers to technical means for analyzing the input target data and generating specific target settings and deadlines suitable for the user.

[0287] "Communication means" is means for notifying the user of the generated data and information, and often refers to e-mails and in-app notifications.

[0288] "Progress monitoring means" is means for recording and managing the progress of a user towards goal achievement, and includes a function of analyzing activity data to evaluate the progress.

[0289] "Instruction providing means" refers to means for notifying a user of appropriate advice based on progress data.

[0290] "Reward calculation method" refers to a technical means for calculating the reward provided to the user when a goal is achieved.

[0291] "Reward data" refers to data representing reward information awarded to users for achieving their goals, and includes points, medals, and other similar items.

[0292] This invention is a system that uses an information processing device to consistently handle everything from goal setting to progress management and reward provision in order to support the achievement of user-defined goals. Specific embodiments of the system are shown below.

[0293] The user uses a device they have on hand to input their desired goals. This device functions as an information processing unit and uses the input device to acquire the user's goal data. For example, a user can set a goal such as "reduce body fat percentage by 5% in 3 months." This goal data is transmitted from the device to the server via the internet.

[0294] The server operates in the cloud and analyzes the received target data. This analysis uses a generative AI model. This model considers existing achievement goal datasets and user profile information to generate specific, achievable goals and deadlines tailored to the user. For example, "Based on your goals, aim to reduce your body fat percentage by 1% every two weeks." The generated data is then sent back to the device using communication functions and the user is notified.

[0295] Progress is managed based on the user's daily activities. Users record activity data such as running time and calories burned on their device. The device then sends this data to a server, which evaluates the progress. Based on the progress data, a generative AI model builds and provides advice to the user. For example, it might suggest, "Next time, try incorporating strength training."

[0296] Ultimately, the server evaluates progress and calculates reward data as a bonus if the user achieves their goal. This bonus data can be implemented, for example, as a points system, and provided to the user in a specific form, such as "50 points awarded" depending on their level of achievement. This allows users to challenge themselves with further goals and maintain their motivation to achieve them.

[0297] An example of a prompt for the generative AI model would be, "Based on the target data entered by the user, please generate specific, achievable goals and their deadlines." By using this prompt, the server can leverage the generative AI to provide the user with the most appropriate advice and progress support.

[0298] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0299] Step 1:

[0300] Users input target data using a device. Specifically, they set a goal, such as "reduce body fat percentage by 5% in 3 months," through the device's input interface. The input includes the goal content and the timeframe for achieving it. This input is processed as digital data on the device and sent to the server.

[0301] Step 2:

[0302] The server analyzes the goal data received from the terminal. Based on the received data, it calls a generation AI model and generates specific goals and deadlines, taking into account the user's profile data and past goal achievement data. This analysis uses the prompt message, "Based on the goal data entered by the user, please generate specific, achievable goals and their deadlines." The output is the specific goals and their deadlines, and this information is sent back to the terminal.

[0303] Step 3:

[0304] The terminal notifies the user of the specific goals and deadlines sent from the server. The input here is the notification information from the server, and the output is the visual presentation to the user. On the terminal, specific goals are displayed, such as through pop-up notifications, to alert the user.

[0305] Step 4:

[0306] The user records their daily activities on the terminal. At this time, data such as running time and calories consumed is input. The input is activity data, and this information is organized on the terminal and prepared to be sent to the server. The output is the organized activity data.

[0307] Step 5:

[0308] The server evaluates the progress based on the activity data sent by the user. The server analyzes this data and uses a generated AI model to generate advice for the next action. The input is the user's daily activity data, and the output is the specific advice generated by the generated AI model. This advice is notified to the user via the terminal.

[0309] Step 6:

[0310] Finally, the server evaluates the progress and calculates the bonus data if it determines that the goal has been achieved. The input here is the achievement status obtained through progress management, and the output is the reward information as bonus data. For example, bonus data such as "50 points are awarded for achieving the goal" is generated and notified to the user via the terminal.

[0311] (Application Example 1)

[0312] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0313] In today's information society, maintaining motivation and managing progress toward achieving personal goals is crucial, but there is a lack of effective methods to consistently support this. Furthermore, there is a need for a system that allows incentives for goal achievement to be used in real life as electronic currency or points. This invention aims to enhance motivation for goal achievement by managing the progress of user-set goals and awarding electronic currency or points as rewards.

[0314] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0315] In this invention, the server includes means for receiving goal information from the user via an input device, means for generating a model that analyzes the goal information to set specific goals and manage progress, means for calculating and notifying reward information as electronic currency or points when the goal is achieved, and means for enabling the user to use the reward at affiliated stores. As a result, the user is consistently supported in the process of achieving their goals and can utilize the reward to benefit their daily life.

[0316] An "information processing device" is a device used for inputting, analyzing, storing, and outputting data, and includes computers and servers.

[0317] An "input device" is a device used by users to provide information to a system, and includes keyboards and touchscreens.

[0318] A "user" refers to an individual or organization that operates an information processing device, inputs target information, and manages its progress.

[0319] "Target information" refers to information that indicates the specific challenges and objectives that the user aims to achieve, and serves as the starting point for the system's analysis.

[0320] "Generative modeling means" refers to technologies and methods used to analyze received information and create achievable goals and their deadlines for the user.

[0321] "Notification means" refers to methods or devices for communicating generated information or results to users, and includes push notifications and email communications.

[0322] A "progress management system" is a mechanism for tracking and evaluating the progress made towards goals set by the user.

[0323] "Advice provision means" refers to methods and devices for providing useful advice to users based on progress information and supporting them in achieving their goals.

[0324] A "reward calculation means" is a method or device for calculating a predetermined reward and providing it to the user when the user achieves a goal.

[0325] "Electronic currency" is a form of currency that is exchanged in digital format, unlike traditional banknotes and coins.

[0326] "Points" are units that accumulate based on a user's actions and transactions, and can be used as rewards.

[0327] A "participating store" is a store or organization that accepts rewards provided by the system and uses them to make purchases or provide services.

[0328] In order to implement this invention, a mechanism is needed in which target information is input through an information processing device via user operation, and that information is analyzed by a server.

[0329] The server automatically generates specific goals and deadlines using a generative AI model based on the goal information received from the information processing device. This generative AI model can present realistic and achievable goals by considering the user's past data and relevant statistical information.

[0330] The goal settings generated by the server are sent to the user's device via a notification system, allowing for visual tracking. Users record their daily activities on their devices, and the server analyzes this activity information to manage progress. Examples of specific activities include running and calorie consumption.

[0331] Based on progress information, the server uses an advice provision system to generate effective action plans and improvement suggestions for the user to achieve their goals. This advice is based on daily activities and includes specific instructions such as, "Next time, you should increase your aerobic exercise." If the user achieves their goals, the server uses a reward calculation system to automatically calculate electronic currency or points and award them to the user as a reward.

[0332] The system's programs are primarily written in Python, with Scikit-learn and TensorFlow used for data analysis and model generation. Communication between the server and the user is handled using a RESTful API, and MySQL is used as the database for data storage. The application's frontend is built using React.

[0333] As a concrete example, consider a case where a user sets a goal of "losing 2 kg in one month." The user registers information about their exercise and meals daily through the app. The server analyzes this activity, monitors progress in real time, and generates appropriate training menus and advice. Through this process, the user can earn points as a reward, which can be used for shopping at participating stores. An example of a prompt message would be, "Please enter your activity level for today. Example: '30 minutes of running, 20 minutes of strength training'."

[0334] In this way, this invention enables users to set goals, reliably manage their progress, and earn valuable rewards in real life.

[0335] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0336] Step 1:

[0337] The user enters goal information via the input device on the terminal. For example, they might set a goal such as "lose 2 kg in one month." This goal information is then sent to the server, guided to the user using prompt messages.

[0338] Step 2:

[0339] The server inputs the received goal information into the generating AI model. Based on past data and the user's current state, the generating AI model generates realistic and achievable specific goals and deadlines. During this generation process, statistical processing is performed using Scikit-learn for data analysis to obtain the goal setting results.

[0340] Step 3:

[0341] The server sends the generated goal setting results to the user's terminal via a notification mechanism. The terminal visually displays the goals and notifies the user. Throughout this process, data is exchanged appropriately using a RESTful API.

[0342] Step 4:

[0343] Users input daily activity information into their devices. This activity information includes exercise time and meal details. This data is sent from the user's device to a server and used for progress management.

[0344] Step 5:

[0345] The server analyzes the received activity information using a progress management system. This analysis includes data processing to understand the current progress and evaluate the degree to which the goal has been achieved. Based on the activity information, the server uses Scikit-learn to update the progress information.

[0346] Step 6:

[0347] Based on progress information, the server generates user-facing advice using a generative AI model and sends it to the user's terminal via an advice delivery system. This advice includes specific action plans to effectively support goal achievement.

[0348] Step 7:

[0349] The server evaluates the progress and, if it determines that the user has achieved their goal, calculates electronic currency or points using a reward calculation system. This calculation uses a points system built with the Django framework.

[0350] Step 8:

[0351] The server notifies the user of the calculated reward information and informs them that it can be used at participating stores. This supports users in using the electronic currency or points they have earned as rewards in their daily lives.

[0352] Through this series of processing steps, the system comprehensively supports the user in achieving their goals.

[0353] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0354] The present invention is an information processing device that supports users in achieving their goals, and in particular, by combining it with an emotion engine, it provides personalized support that takes into account the user's emotional state.

[0355] The device collects goal information and daily activity data based on user input. Users record their goals and activities on the device, setting specific goals such as "I want to lose 5 kg." This data is then sent to the server.

[0356] The server analyzes the received target information and activity data, and uses a generative model to set specific targets and deadlines. This generated target information is then sent back to the terminal and notified to the user.

[0357] The emotion engine recognizes the user's current emotional state using user input data and other information. This emotional information is then used as a factor influencing the goal information and advice set on the server.

[0358] The progress management system manages progress toward goal achievement based on daily activity data. This allows the server to monitor progress in real time and provide users with timely and necessary advice. The advice generated by the advice provision system may include suggestions such as "Let's try a new exercise method next," and is adjusted to take into account the user's emotional state.

[0359] The reward calculation system calculates a predetermined reward when the user achieves the goal they have set and notifies the user of the result. The reward functions as an incentive to increase the user's motivation.

[0360] As a concrete example, consider a user who sets a goal of improving their health and records their daily activities. The system takes the user's current emotional state into consideration, sets achievable goals, and provides advice based on their progress. Furthermore, it offers the user a reward upon recognition of their achievement. This allows the user to efficiently progress towards their goals while also considering their emotions.

[0361] The following describes the processing flow.

[0362] Step 1:

[0363] The terminal displays a goal input screen to the user. This screen is an interface for entering specific goals and areas for improvement, and is provided in a user-friendly format.

[0364] Step 2:

[0365] The user enters goal information via their device. For example, they might set a goal such as "I want to lose 5 kg." This entered data is then sent to the server.

[0366] Step 3:

[0367] The server analyzes the received target information. Using a generative model, it generates specific targets and deadlines for their achievement that are appropriate to the user's situation from this information.

[0368] Step 4:

[0369] The server uses an emotion engine to recognize the user's emotional state from their input and current behavioral data. For example, it can detect if a user is experiencing stress through text analysis and frequency information.

[0370] Step 5:

[0371] The server generates goal setting and advice that take the user's emotional state into account. This includes adjustments such as setting realistic goals and suggesting relaxation methods if the user is experiencing stress.

[0372] Step 6:

[0373] The server generates goal settings and advice and sends them to the terminal. The terminal notifies the user and displays them for daily review. The user then uses this information to develop an activity plan.

[0374] Step 7:

[0375] The user records their daily activities. The device also allows for the optional input of emotional data, recording information in detail. For example, information such as "I went for a 30-minute run today, and I'm a little tired" can be entered.

[0376] Step 8:

[0377] The device sends daily activity and emotional data it collects to the server. The server analyzes this data through progress management tools to understand progress and emotional trends.

[0378] Step 9:

[0379] The server generates new advice based on the progress. This advice includes suggestions that take into account changes in emotional state. The advice is sent to the terminal and displayed to the user.

[0380] Step 10:

[0381] The server checks whether the set goal has been achieved, and if so, calculates the reward using the reward calculation system. This reward information is then notified to the user via their terminal. For example, it might say, "You have been awarded 500 points as a reward for achieving your goal."

[0382] This process allows users to receive emotionally conscious support and achieve their goals more efficiently.

[0383] (Example 2)

[0384] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0385] Conventional goal achievement support systems lacked support that considered the user's emotional state, making it difficult to maintain motivation and provide effective advice. Furthermore, simple progress management based solely on user behavioral data failed to provide individualized support, hindering efficient goal achievement.

[0386] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0387] In this invention, the server includes means for receiving goal information and behavioral data from the user via input means, generation model means for analyzing the goal information and behavioral data to generate specific goal settings and deadlines, and notification means for notifying the user based on the generated goal setting information and emotional state. This makes it possible to provide personalized advice that takes into account the user's emotional state, thereby improving the efficiency of goal achievement.

[0388] "Input means" refers to devices or software used to receive goal information and behavioral data from users.

[0389] "Goal information" refers to information about the specific goals and objectives that the user wishes to achieve.

[0390] "Behavioral data" refers to data about the user's daily activities, including exercise levels and lifestyle habits.

[0391] A "generative modeling tool" is a function for setting realistic and achievable specific goals and their deadlines based on the information received.

[0392] A "notification method" is a means of communicating generated goal information and advice to the user.

[0393] A "progress management method" is a method for tracking and managing the progress toward set goals.

[0394] An "advice provision tool" is a function that generates and provides appropriate guidance and advice to users based on progress information and emotional state.

[0395] A "reward calculation method" is a method for calculating appropriate rewards according to the degree to which a user has achieved their goals.

[0396] "Emotional state" refers to the user's mental state, reflecting their current mood and motivation.

[0397] This invention provides an information processing device for supporting users in achieving their goals. Users input goal information and daily behavioral data via a terminal, and the system provides appropriate support for achieving those goals based on this data.

[0398] The device acquires goal information and behavioral data from the user using input methods. A specific example is when a user sets a goal of "losing 5 kg in the next three months" and inputs their daily exercise and food intake records to achieve that goal.

[0399] The data entered by the user is sent to the server. The server uses a generative AI model to analyze this data and set realistic and achievable specific goals and deadlines. The analysis also takes into account the user's emotional state using an emotion engine. For example, the generative AI model can suggest a "one-week plan combining moderate exercise and a balanced diet."

[0400] The server sends the generated goal information back to the terminal and notifies the user. This notification is intended to make it easier for the user to act according to the plan. Furthermore, progress tracking mechanisms are used to track and manage the user's progress in real time based on their behavioral data.

[0401] Furthermore, using an advice delivery system, the server generates and notifies users of personalized advice based on their progress and emotional state. For example, it can provide advice such as, "You seem a little tired today. How about trying some stretching?"

[0402] The reward calculation system calculates reward information when the user achieves a goal and notifies them via their device. This helps maintain user motivation and allows them to work more effectively towards achieving their goals.

[0403] An example of a prompt might be, "Analyze the user's current exercise and dietary data and suggest the optimal fitness plan for next week." This prompt allows the system to provide personalized feedback tailored to each individual user.

[0404] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0405] Step 1:

[0406] Users input goal information and daily activity data via their device. They enter their goals on the device and record daily data such as exercise levels and dietary details. This input data is temporarily stored on the device before being sent to the server.

[0407] Step 2:

[0408] The server analyzes the received goal information and behavioral data. A generative AI model is used for the analysis, generating optimal goal settings for the user from this data. Specifically, it processes data such as "exercise time" and "calorie intake" entered by the user, and the AI ​​model proposes realistic goals that can be achieved within a achievable timeframe. This output might be something like, "Aim to lose 0.5 kg per week."

[0409] Step 3:

[0410] The server analyzes the user's emotional state and adjusts the generated goal information using an emotion engine. User emotional data (e.g., login records or specific keyword inputs) is input, and the server analyzes that emotional state. Based on the analysis results, goal setting and advice are adjusted. For example, if the user is stressed, a comment such as "Let's proceed at a comfortable pace" may be added.

[0411] Step 4:

[0412] The server sends final goal information and advice to the terminal and notifies the user. The notification includes a step-by-step approach to achieving the goal and provides advice tailored to the user's situation. For example, it might output specific instructions such as, "Let's go for a 30-minute walk for three days this week."

[0413] Step 5:

[0414] The server manages progress information and updates it in real time based on daily activity data. It receives the user's latest activity data as input, checks the degree of goal achievement using the progress management system, and outputs the progress status as information. This is provided to the user in the form of "You have achieved 80% of your goal this week."

[0415] Step 6:

[0416] The server uses a reward calculation mechanism to calculate rewards based on the degree of goal achievement. Rewards are calculated based on the goal achievement status obtained from progress management. For example, when a step is achieved, a message such as "Points earned for the next stage" is output and notified to the user via the terminal.

[0417] (Application Example 2)

[0418] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0419] While modern information processing technology allows users to set individual goals and receive progress management and advice based on those goals, providing appropriate support that takes into account the user's emotional state remains challenging. Furthermore, in physical stores, there is a lack of systems that can provide real-time, personalized suggestions to users as they select products and services that best suit their needs. This results in inefficiencies in supporting users in achieving their goals and assisting them in their purchasing decisions.

[0420] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0421] In this invention, the server includes a generation model means that analyzes the user's goal information and generates specific goal settings and deadlines; a means that adapts advice information and goal setting information based on the user's emotional state analyzed by an emotion engine; and a means that provides appropriate suggestions in real time when the user selects products or services related to their objectives. This enables effective goal achievement support that takes into account the user's emotions and personalized, real-time suggestions during purchasing activities at physical stores.

[0422] An "information processing device" refers to the entire system used to receive, analyze, notify, and manage input from users.

[0423] An "input device" refers to a device or interface used by a user to provide goal information and daily activity data to the system.

[0424] "Generative model means" refers to an algorithm or mechanism for generating specific goal settings and corresponding deadlines based on goal information received from the user.

[0425] "Notification means" refers to a method or device for informing users of generated goal setting information, progress information, advice information, and reward information.

[0426] "Progress management tools" refer to systems for continuously tracking and managing users' daily progress toward achieving their goals.

[0427] "Means of providing advice" refers to systems or mechanisms for providing users with advice generated based on progress information.

[0428] "Reward calculation method" refers to the process of calculating a predetermined reward when a user achieves a goal they have set, and notifying the user of that reward.

[0429] An "emotion engine" refers to a technology that analyzes a user's emotional state based on their input data and related information, and adjusts the system's operation based on the results.

[0430] A "real-time suggestion system" refers to a mechanism that provides immediate and appropriate suggestions to users when they are selecting products or services related to their purpose.

[0431] The system implementing this invention combines information processing technology and emotion analysis technology to support users in achieving their goals.

[0432] The server first receives goal information set by the user from the input device. Next, it uses a generative model to analyze this goal information and generate specific goal settings and corresponding deadlines. The server also uses an emotion engine to determine the user's emotional state from various input and sensor data. This analysis can utilize emotion analysis functions such as AWS Rekognition or Google Cloud Vision API. The results of the emotional state analysis are used to adjust goal settings and advice information, providing more personalized support.

[0433] The generated goal-setting information and advice information are transmitted to the user's device in real time via a notification system. At this time, a progress management system, tailored to the user's emotional state, monitors the progress towards the goal and further optimizes the advice information based on that progress. For example, if a user sets a goal of "losing 5kg" through fitness activities, the system can provide exercise suggestions and nutritional advice while considering daily activity data and sensor information such as heart rate. Upon achieving the goal, the system provides an incentive to the user through a reward calculation system.

[0434] Furthermore, the system provides personalized product recommendations via real-time suggestions when customers select products or services in physical stores. This allows customers to obtain the necessary information on the spot and make appropriate purchasing decisions.

[0435] A concrete example is when a user is choosing new fitness gear at a sports goods store; the system suggests shoes and apparel that take into account the user's current exercise goals and emotional state. Such suggestions allow users to efficiently work towards their goals.

[0436] Example prompt: "When a user is aiming for weight loss, what fitness products would be recommended, and what kind of support would be offered in different emotional states? Please provide specific product names and examples of support messages."

[0437] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0438] Step 1:

[0439] The terminal receives goal information and activity data from the user through an input device. This input includes specific goals (e.g., lose 5 kg), daily exercise levels, and dietary information. This data is then sent to a subsequent analysis step.

[0440] Step 2:

[0441] The server analyzes the received goal information and activity data using a generating AI model. Here, the data is structured, and appropriate goal settings and deadlines are generated. This process analyzes the user's activity patterns using a predetermined algorithm and sets achievable goals. Specific goal setting information is generated as output.

[0442] Step 3:

[0443] The server evaluates the generated goal setting information and activity data using an emotion engine to analyze the user's emotional state. This analysis utilizes AWS Rekognition and Google Cloud Vision APIs to determine emotions from voice, text, and sensor data. The output provides data on the user's current emotional state.

[0444] Step 4:

[0445] The server integrates the analyzed goal-setting information and emotional state data, and manages the progress information using a progress management system. During this process, advice tailored to the emotional state is generated. This generated advice is sent to the user as feedback. This feedback includes specific suggestions, such as, "Next, try relaxing yoga."

[0446] Step 5:

[0447] When the server achieves the goal set by the user, it calculates an incentive based on the degree of achievement using a reward calculation mechanism and notifies the user. This calculation takes into account both progress and emotional state. As output, the user is provided with appropriate reward information.

[0448] Step 6:

[0449] When a user selects products in a physical store, the terminal receives real-time suggestions from the server. The system considers the user's goal information, emotional state, and current location to suggest appropriate products and services. For example, new running shoes might be suggested as a purchase option.

[0450] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0451] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0452] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0453] [Third Embodiment]

[0454] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0455] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0456] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0457] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0458] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0459] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0460] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0461] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0462] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0463] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0464] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0465] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0466] The system of this invention receives goal information entered by the user, provides appropriate goal setting based on that information, manages progress, and provides rewards, all while providing consistent support.

[0467] The user has a device in their possession, and they input their goal information through that device. This goal information might be something like, "I want to lose 5kg." This information is then sent from the device to the server.

[0468] The server analyzes the received goal information and uses a generative model to set specific, achievable goals and deadlines for the user. In this process, the generative model takes into account past data and the user's current state when setting goals. The set goals and deadlines are sent from the server to the terminal and notified to the user.

[0469] During the progress management phase, users record their daily progress on their devices. For example, they might record activities such as "I went for a 30-minute run today." This data is then sent back to the server for analysis.

[0470] The server generates advice based on progress data. This advice, such as "Let's try strength training next," is provided to the user via the terminal. This advice is designed to support the user's actions toward achieving their goals.

[0471] Ultimately, the server evaluates the progress data, and if it determines that the set goal has been achieved, it generates reward information using a reward calculation mechanism and notifies the user. Reward information may include, for example, "500 points awarded for achieving the goal." The terminal displays this reward information to the user, encouraging them to set further goals and take on challenges.

[0472] As a concrete example, a user who sets a goal to lose weight would record their daily activities, receive feedback from the server, achieve their goal, and receive a reward. This allows users to continuously improve themselves based on clear goals.

[0473] The following describes the processing flow.

[0474] Step 1:

[0475] The terminal displays a goal input screen to the user. This interface allows the user to specifically input the goals they want to achieve and the areas they want to improve.

[0476] Step 2:

[0477] The user enters their goal information. This goal information refers to a specific objective, such as "I want to lose 5 kg." The entered data is immediately sent from the terminal to the server.

[0478] Step 3:

[0479] The server runs a generative model based on the target information it receives. The generative model sets specific, achievable targets and deadlines for the user, based on historical data, relevant literature, and other similar cases.

[0480] Step 4:

[0481] The server sends the generated goal settings and deadlines to the terminal. The terminal displays this to the user for review. The user can review the proposed goals and make modifications or additional settings as needed.

[0482] Step 5:

[0483] Users record their daily activities on their devices. For example, they might input specific details such as, "I went for a 30-minute run today." This data is sent to the server periodically or in real time.

[0484] Step 6:

[0485] The server analyzes the received activity data and evaluates the progress. Generative models are used for evaluation to generate the most effective advice for each user and determine what improvements are possible.

[0486] Step 7:

[0487] The server sends the generated advice to the terminal, which then displays it to the user. The advice includes specific action suggestions and points to note for the next step. For example, it might say, "We recommend combining this with strength training next."

[0488] Step 8:

[0489] The server verifies goal achievement based on the user's progress data. If achievement is confirmed, it determines the reward to be given to the user using a reward calculation mechanism and generates reward information.

[0490] Step 9:

[0491] The server sends the generated reward information to the device. The device then notifies the user of the reward. For example, it might display something like, "You have been awarded 500 points for achieving your goal." The rewards serve to maintain the user's motivation and encourage them to set new goals.

[0492] (Example 1)

[0493] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0494] Traditional goal management systems have faced challenges in effectively managing user progress toward achieving their goals and providing appropriate advice. Furthermore, they often lacked sufficient reward systems to sustain user motivation.

[0495] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0496] In this invention, the server includes means for receiving goal data from the user, means for generating a generation algorithm that analyzes the goal data to generate specific goal settings and deadlines, and means for notifying the user of the generated goal setting data. This makes it possible to set achievable and specific goals based on the goal data entered by the user and to always provide appropriate instructions according to the latest progress data. Furthermore, a reward system using reward data can increase the user's motivation and support goal achievement.

[0497] An "information processing device" is a device that has the functions of inputting, processing, and outputting data, and refers to a system that supports goal setting and progress management.

[0498] An "input device" is a device that receives information from the user and has the function of accepting target data and activity data.

[0499] "User" refers to an entity that uses the system to set goals and aims to achieve them.

[0500] "Target data" refers to information about the goals that the user wishes to achieve, and is the basic data entered into the system.

[0501] "Generation algorithm means" refers to technical means for analyzing input target data and generating specific target settings and deadlines suitable for the user.

[0502] "Communication methods" refer to means of notifying the user of generated data or information, and often refer to email or in-app notifications.

[0503] "Progress monitoring means" refers to means of recording and managing the user's progress toward achieving a goal, and includes a function to analyze activity data and evaluate progress.

[0504] "Means of providing instructions" refers to means of notifying users of appropriate advice based on progress data.

[0505] "Reward calculation method" refers to a technical means for calculating the reward provided to the user when a goal is achieved.

[0506] "Reward data" refers to data representing reward information awarded to users for achieving their goals, and includes points, medals, and other similar items.

[0507] This invention is a system that uses an information processing device to consistently handle everything from goal setting to progress management and reward provision in order to support the achievement of user-defined goals. Specific embodiments of the system are shown below.

[0508] The user uses a device they have on hand to input their desired goals. This device functions as an information processing unit and uses the input device to acquire the user's goal data. For example, a user can set a goal such as "reduce body fat percentage by 5% in 3 months." This goal data is transmitted from the device to the server via the internet.

[0509] The server operates in the cloud and analyzes the received target data. This analysis uses a generative AI model. This model considers existing achievement goal datasets and user profile information to generate specific, achievable goals and deadlines tailored to the user. For example, "Based on your goals, aim to reduce your body fat percentage by 1% every two weeks." The generated data is then sent back to the device using communication functions and the user is notified.

[0510] Progress is managed based on the user's daily activities. Users record activity data such as running time and calories burned on their device. The device then sends this data to a server, which evaluates the progress. Based on the progress data, a generative AI model builds and provides advice to the user. For example, it might suggest, "Next time, try incorporating strength training."

[0511] Ultimately, the server evaluates progress and calculates reward data as a bonus if the user achieves their goal. This bonus data can be implemented, for example, as a points system, and provided to the user in a specific form, such as "50 points awarded" depending on their level of achievement. This allows users to challenge themselves with further goals and maintain their motivation to achieve them.

[0512] An example of a prompt for the generative AI model would be, "Based on the target data entered by the user, please generate specific, achievable goals and their deadlines." By using this prompt, the server can leverage the generative AI to provide the user with the most appropriate advice and progress support.

[0513] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0514] Step 1:

[0515] Users input target data using a device. Specifically, they set a goal, such as "reduce body fat percentage by 5% in 3 months," through the device's input interface. The input includes the goal content and the timeframe for achieving it. This input is processed as digital data on the device and sent to the server.

[0516] Step 2:

[0517] The server analyzes the goal data received from the terminal. Based on the received data, it calls a generation AI model and generates specific goals and deadlines, taking into account the user's profile data and past goal achievement data. This analysis uses the prompt message, "Based on the goal data entered by the user, please generate specific, achievable goals and their deadlines." The output is the specific goals and their deadlines, and this information is sent back to the terminal.

[0518] Step 3:

[0519] The terminal notifies the user of specific goals and deadlines sent from the server. The input here is notification information from the server, and the output is a visual presentation to the user. On the terminal, specific goals are displayed via pop-up notifications, alerting the user.

[0520] Step 4:

[0521] Users record their daily activities on their devices. This includes inputting data such as running time and calories burned. The input is activity data, which is organized on the device and prepared for transmission to the server. The output is the organized activity data.

[0522] Step 5:

[0523] The server evaluates progress based on activity data submitted by the user. The server analyzes this data and uses a generative AI model to generate advice for the next action. The input is the user's daily activity data, and the output is specific advice generated by the generative AI model. This advice is then communicated to the user via their device.

[0524] Step 6:

[0525] Ultimately, the server evaluates the progress and, if it determines that the goal has been achieved, calculates reward data. The input here is the achievement status obtained through progress management, and the output is reward information as reward data. For example, reward data such as "50 points awarded for achieving the goal" is generated and notified to the user via the terminal.

[0526] (Application Example 1)

[0527] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0528] In today's information society, maintaining motivation and managing progress toward achieving personal goals is crucial, but there is a lack of effective methods to consistently support this. Furthermore, there is a need for a system that allows incentives for goal achievement to be used in real life as electronic currency or points. This invention aims to enhance motivation for goal achievement by managing the progress of user-set goals and awarding electronic currency or points as rewards.

[0529] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0530] In this invention, the server includes means for receiving goal information from the user via an input device, means for generating a model that analyzes the goal information to set specific goals and manage progress, means for calculating and notifying reward information as electronic currency or points when the goal is achieved, and means for enabling the user to use the reward at affiliated stores. As a result, the user is consistently supported in the process of achieving their goals and can utilize the reward to benefit their daily life.

[0531] An "information processing device" is a device used for inputting, analyzing, storing, and outputting data, and includes computers and servers.

[0532] An "input device" is a device used by users to provide information to a system, and includes keyboards and touchscreens.

[0533] A "user" refers to an individual or organization that operates an information processing device, inputs target information, and manages its progress.

[0534] "Target information" refers to information that indicates the specific challenges and objectives that the user aims to achieve, and serves as the starting point for the system's analysis.

[0535] "Generative modeling means" refers to technologies and methods used to analyze received information and create achievable goals and their deadlines for the user.

[0536] "Notification means" refers to methods or devices for communicating generated information or results to users, and includes push notifications and email communications.

[0537] A "progress management system" is a mechanism for tracking and evaluating the progress made towards goals set by the user.

[0538] "Advice provision means" refers to methods and devices for providing useful advice to users based on progress information and supporting them in achieving their goals.

[0539] A "reward calculation means" is a method or device for calculating a predetermined reward and providing it to the user when the user achieves a goal.

[0540] "Electronic currency" is a form of currency that is exchanged in digital format, unlike traditional banknotes and coins.

[0541] "Points" are units that accumulate based on a user's actions and transactions, and can be used as rewards.

[0542] A "participating store" is a store or organization that accepts rewards provided by the system and uses them to make purchases or provide services.

[0543] In order to implement this invention, a mechanism is needed in which target information is input through an information processing device via user operation, and that information is analyzed by a server.

[0544] The server automatically generates specific goals and deadlines using a generative AI model based on the goal information received from the information processing device. This generative AI model can present realistic and achievable goals by considering the user's past data and relevant statistical information.

[0545] The goal settings generated by the server are sent to the user's device via a notification system, allowing for visual tracking. Users record their daily activities on their devices, and the server analyzes this activity information to manage progress. Examples of specific activities include running and calorie consumption.

[0546] Based on progress information, the server uses an advice provision system to generate effective action plans and improvement suggestions for the user to achieve their goals. This advice is based on daily activities and includes specific instructions such as, "Next time, you should increase your aerobic exercise." If the user achieves their goals, the server uses a reward calculation system to automatically calculate electronic currency or points and award them to the user as a reward.

[0547] The system's programs are primarily written in Python, with Scikit-learn and TensorFlow used for data analysis and model generation. Communication between the server and the user is handled using a RESTful API, and MySQL is used as the database for data storage. The application's frontend is built using React.

[0548] As a concrete example, consider a case where a user sets a goal of "losing 2 kg in one month." The user registers information about their exercise and meals daily through the app. The server analyzes this activity, monitors progress in real time, and generates appropriate training menus and advice. Through this process, the user can earn points as a reward, which can be used for shopping at participating stores. An example of a prompt message would be, "Please enter your activity level for today. Example: '30 minutes of running, 20 minutes of strength training'."

[0549] In this way, this invention enables users to set goals, reliably manage their progress, and earn valuable rewards in real life.

[0550] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0551] Step 1:

[0552] The user enters goal information via the input device on the terminal. For example, they might set a goal such as "lose 2 kg in one month." This goal information is then sent to the server, guided to the user using prompt messages.

[0553] Step 2:

[0554] The server inputs the received goal information into the generating AI model. Based on past data and the user's current state, the generating AI model generates realistic and achievable specific goals and deadlines. During this generation process, statistical processing is performed using Scikit-learn for data analysis to obtain the goal setting results.

[0555] Step 3:

[0556] The server sends the generated goal setting results to the user's terminal via a notification mechanism. The terminal visually displays the goals and notifies the user. Throughout this process, data is exchanged appropriately using a RESTful API.

[0557] Step 4:

[0558] Users input daily activity information into their devices. This activity information includes exercise time and meal details. This data is sent from the user's device to a server and used for progress management.

[0559] Step 5:

[0560] The server analyzes the received activity information using a progress management system. This analysis includes data processing to understand the current progress and evaluate the degree to which the goal has been achieved. Based on the activity information, the server uses Scikit-learn to update the progress information.

[0561] Step 6:

[0562] Based on progress information, the server generates user-facing advice using a generative AI model and sends it to the user's terminal via an advice delivery system. This advice includes specific action plans to effectively support goal achievement.

[0563] Step 7:

[0564] The server evaluates the progress and, if it determines that the user has achieved their goal, calculates electronic currency or points using a reward calculation system. This calculation uses a points system built with the Django framework.

[0565] Step 8:

[0566] The server notifies the user of the calculated reward information and informs them that it can be used at participating stores. This supports users in using the electronic currency or points they have earned as rewards in their daily lives.

[0567] Through this series of processing steps, the system comprehensively supports the user in achieving their goals.

[0568] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0569] The present invention is an information processing device that supports users in achieving their goals, and in particular, by combining it with an emotion engine, it provides personalized support that takes into account the user's emotional state.

[0570] The device collects goal information and daily activity data based on user input. Users record their goals and activities on the device, setting specific goals such as "I want to lose 5 kg." This data is then sent to the server.

[0571] The server analyzes the received target information and activity data, and uses a generative model to set specific targets and deadlines. This generated target information is then sent back to the terminal and notified to the user.

[0572] The emotion engine recognizes the user's current emotional state using user input data and other information. This emotional information is then used as a factor influencing the goal information and advice set on the server.

[0573] The progress management system manages progress toward goal achievement based on daily activity data. This allows the server to monitor progress in real time and provide users with timely and necessary advice. The advice generated by the advice provision system may include suggestions such as "Let's try a new exercise method next," and is adjusted to take into account the user's emotional state.

[0574] The reward calculation system calculates a predetermined reward when the user achieves the goal they have set and notifies the user of the result. The reward functions as an incentive to increase the user's motivation.

[0575] As a concrete example, consider a user who sets a goal of improving their health and records their daily activities. The system takes the user's current emotional state into consideration, sets achievable goals, and provides advice based on their progress. Furthermore, it offers the user a reward upon recognition of their achievement. This allows the user to efficiently progress towards their goals while also considering their emotions.

[0576] The following describes the processing flow.

[0577] Step 1:

[0578] The terminal displays a goal input screen to the user. This screen is an interface for entering specific goals and areas for improvement, and is provided in a user-friendly format.

[0579] Step 2:

[0580] The user enters goal information via their device. For example, they might set a goal such as "I want to lose 5 kg." This entered data is then sent to the server.

[0581] Step 3:

[0582] The server analyzes the received target information. Using a generative model, it generates specific targets and deadlines for their achievement that are appropriate to the user's situation from this information.

[0583] Step 4:

[0584] The server uses an emotion engine to recognize the user's emotional state from their input and current behavioral data. For example, it can detect if a user is experiencing stress through text analysis and frequency information.

[0585] Step 5:

[0586] The server generates goal setting and advice that take the user's emotional state into account. This includes adjustments such as setting realistic goals and suggesting relaxation methods if the user is experiencing stress.

[0587] Step 6:

[0588] The server generates goal settings and advice and sends them to the terminal. The terminal notifies the user and displays them for daily review. The user then uses this information to develop an activity plan.

[0589] Step 7:

[0590] The user records their daily activities. The device also allows for the optional input of emotional data, recording information in detail. For example, information such as "I went for a 30-minute run today, and I'm a little tired" can be entered.

[0591] Step 8:

[0592] The device sends daily activity and emotional data it collects to the server. The server analyzes this data through progress management tools to understand progress and emotional trends.

[0593] Step 9:

[0594] The server generates new advice based on the progress. This advice includes suggestions that take into account changes in emotional state. The advice is sent to the terminal and displayed to the user.

[0595] Step 10:

[0596] The server checks whether the set goal has been achieved, and if so, calculates the reward using the reward calculation system. This reward information is then notified to the user via their terminal. For example, it might say, "You have been awarded 500 points as a reward for achieving your goal."

[0597] This process allows users to receive emotionally conscious support and achieve their goals more efficiently.

[0598] (Example 2)

[0599] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0600] Conventional goal achievement support systems lacked support that considered the user's emotional state, making it difficult to maintain motivation and provide effective advice. Furthermore, simple progress management based solely on user behavioral data failed to provide individualized support, hindering efficient goal achievement.

[0601] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0602] In this invention, the server includes means for receiving goal information and behavioral data from the user via input means, generation model means for analyzing the goal information and behavioral data to generate specific goal settings and deadlines, and notification means for notifying the user based on the generated goal setting information and emotional state. This makes it possible to provide personalized advice that takes into account the user's emotional state, thereby improving the efficiency of goal achievement.

[0603] "Input means" refers to devices or software used to receive goal information and behavioral data from users.

[0604] "Goal information" refers to information about the specific goals and objectives that the user wishes to achieve.

[0605] "Behavioral data" refers to data about the user's daily activities, including exercise levels and lifestyle habits.

[0606] A "generative modeling tool" is a function for setting realistic and achievable specific goals and their deadlines based on the information received.

[0607] A "notification method" is a means of communicating generated goal information and advice to the user.

[0608] A "progress management method" is a method for tracking and managing the progress toward set goals.

[0609] An "advice provision tool" is a function that generates and provides appropriate guidance and advice to users based on progress information and emotional state.

[0610] A "reward calculation method" is a method for calculating appropriate rewards according to the degree to which a user has achieved their goals.

[0611] "Emotional state" refers to the user's mental state, reflecting their current mood and motivation.

[0612] This invention provides an information processing device for supporting users in achieving their goals. Users input goal information and daily behavioral data via a terminal, and the system provides appropriate support for achieving those goals based on this data.

[0613] The device acquires goal information and behavioral data from the user using input methods. A specific example is when a user sets a goal of "losing 5 kg in the next three months" and inputs their daily exercise and food intake records to achieve that goal.

[0614] The data entered by the user is sent to the server. The server uses a generative AI model to analyze this data and set realistic and achievable specific goals and deadlines. The analysis also takes into account the user's emotional state using an emotion engine. For example, the generative AI model can suggest a "one-week plan combining moderate exercise and a balanced diet."

[0615] The server sends the generated goal information back to the terminal and notifies the user. This notification is intended to make it easier for the user to act according to the plan. Furthermore, progress tracking mechanisms are used to track and manage the user's progress in real time based on their behavioral data.

[0616] Furthermore, using an advice delivery system, the server generates and notifies users of personalized advice based on their progress and emotional state. For example, it can provide advice such as, "You seem a little tired today. How about trying some stretching?"

[0617] The reward calculation system calculates reward information when the user achieves a goal and notifies them via their device. This helps maintain user motivation and allows them to work more effectively towards achieving their goals.

[0618] An example of a prompt might be, "Analyze the user's current exercise and dietary data and suggest the optimal fitness plan for next week." This prompt allows the system to provide personalized feedback to each individual user.

[0619] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0620] Step 1:

[0621] Users input goal information and daily activity data via their device. They enter their goals on the device and record daily data such as exercise levels and dietary details. This input data is temporarily stored on the device before being sent to the server.

[0622] Step 2:

[0623] The server analyzes the received goal information and behavioral data. A generative AI model is used for the analysis, generating optimal goal settings for the user from this data. Specifically, it processes data such as "exercise time" and "calorie intake" entered by the user, and the AI ​​model proposes realistic goals that can be achieved within a achievable timeframe. This output might be something like, "Aim to lose 0.5 kg per week."

[0624] Step 3:

[0625] The server analyzes the user's emotional state and adjusts the generated goal information using an emotion engine. User emotional data (e.g., login records or specific keyword inputs) is input, and the server analyzes that emotional state. Based on the analysis results, goal setting and advice are adjusted. For example, if the user is stressed, a comment such as "Let's proceed at a comfortable pace" may be added.

[0626] Step 4:

[0627] The server sends final goal information and advice to the terminal and notifies the user. The notification includes a step-by-step approach to achieving the goal and provides advice tailored to the user's situation. For example, it might output specific instructions such as, "Let's go for a 30-minute walk for three days this week."

[0628] Step 5:

[0629] The server manages progress information and updates it in real time based on daily activity data. It receives the user's latest activity data as input, checks the degree of goal achievement using the progress management system, and outputs the progress status as information. This is provided to the user in the form of "You have achieved 80% of your goal this week."

[0630] Step 6:

[0631] The server uses a reward calculation mechanism to calculate rewards based on the degree of goal achievement. Rewards are calculated based on the goal achievement status obtained from progress management. For example, when a step is achieved, a message such as "Points earned for the next stage" is output and notified to the user via the terminal.

[0632] (Application Example 2)

[0633] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0634] While modern information processing technology allows users to set individual goals and receive progress management and advice based on those goals, providing appropriate support that takes into account the user's emotional state remains challenging. Furthermore, in physical stores, there is a lack of systems that can provide real-time, personalized suggestions to users as they select products and services that best suit their needs. This results in inefficiencies in supporting users in achieving their goals and assisting them in their purchasing decisions.

[0635] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0636] In this invention, the server includes a generation model means that analyzes the user's goal information and generates specific goal settings and deadlines; a means that adapts advice information and goal setting information based on the user's emotional state analyzed by an emotion engine; and a means that provides appropriate suggestions in real time when the user selects products or services related to their objectives. This enables effective goal achievement support that takes into account the user's emotions and personalized, real-time suggestions during purchasing activities at physical stores.

[0637] An "information processing device" refers to the entire system used to receive, analyze, notify, and manage input from users.

[0638] An "input device" refers to a device or interface used by a user to provide goal information and daily activity data to the system.

[0639] "Generative model means" refers to an algorithm or mechanism for generating specific goal settings and corresponding deadlines based on goal information received from the user.

[0640] "Notification means" refers to a method or device for informing users of generated goal setting information, progress information, advice information, and reward information.

[0641] "Progress management tools" refer to systems for continuously tracking and managing users' daily progress toward achieving their goals.

[0642] "Means of providing advice" refers to systems or mechanisms for providing users with advice generated based on progress information.

[0643] "Reward calculation method" refers to the process of calculating a predetermined reward when a user achieves a goal they have set, and notifying the user of that reward.

[0644] An "emotion engine" refers to a technology that analyzes a user's emotional state based on their input data and related information, and adjusts the system's operation based on the results.

[0645] A "real-time suggestion system" refers to a mechanism that provides immediate and appropriate suggestions to users when they are selecting products or services related to their purpose.

[0646] The system implementing this invention combines information processing technology and emotion analysis technology to support users in achieving their goals.

[0647] The server first receives goal information set by the user from the input device. Next, it uses a generative model to analyze this goal information and generate specific goal settings and corresponding deadlines. The server also uses an emotion engine to determine the user's emotional state from various input and sensor data. This analysis can utilize emotion analysis functions such as AWS Rekognition or Google Cloud Vision API. The results of the emotional state analysis are used to adjust goal settings and advice information, providing more personalized support.

[0648] The generated goal-setting information and advice information are transmitted to the user's device in real time via a notification system. At this time, a progress management system, tailored to the user's emotional state, monitors the progress towards the goal and further optimizes the advice information based on that progress. For example, if a user sets a goal of "losing 5kg" through fitness activities, the system can provide exercise suggestions and nutritional advice while considering daily activity data and sensor information such as heart rate. Upon achieving the goal, the system provides an incentive to the user through a reward calculation system.

[0649] Furthermore, the system provides personalized product recommendations via real-time suggestions when customers select products or services in physical stores. This allows customers to obtain the necessary information on the spot and make appropriate purchasing decisions.

[0650] A concrete example is when a user is choosing new fitness gear at a sports goods store; the system suggests shoes and apparel that take into account the user's current exercise goals and emotional state. Such suggestions allow users to efficiently work towards their goals.

[0651] Example prompt: "When a user is aiming for weight loss, what fitness products would be recommended, and what kind of support would be offered in different emotional states? Please provide specific product names and examples of support messages."

[0652] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0653] Step 1:

[0654] The terminal receives goal information and activity data from the user through an input device. This input includes specific goals (e.g., lose 5 kg), daily exercise levels, and dietary information. This data is then sent to a subsequent analysis step.

[0655] Step 2:

[0656] The server analyzes the received goal information and activity data using a generating AI model. Here, the data is structured, and appropriate goal settings and deadlines are generated. This process analyzes the user's activity patterns using a predetermined algorithm and sets achievable goals. Specific goal setting information is generated as output.

[0657] Step 3:

[0658] The server evaluates the generated goal setting information and activity data using an emotion engine to analyze the user's emotional state. This analysis utilizes AWS Rekognition and Google Cloud Vision APIs to determine emotions from voice, text, and sensor data. The output provides data on the user's current emotional state.

[0659] Step 4:

[0660] The server integrates the analyzed goal-setting information and emotional state data, and manages the progress information using a progress management system. During this process, advice tailored to the emotional state is generated. This generated advice is sent to the user as feedback. This feedback includes specific suggestions, such as, "Next, try relaxing yoga."

[0661] Step 5:

[0662] When the server achieves the goal set by the user, it calculates an incentive based on the degree of achievement using a reward calculation mechanism and notifies the user. This calculation takes into account both progress and emotional state. As output, the user is provided with appropriate reward information.

[0663] Step 6:

[0664] When a user selects products in a physical store, the terminal receives real-time suggestions from the server. The system considers the user's goal information, emotional state, and current location to suggest appropriate products and services. For example, new running shoes might be suggested as a purchase option.

[0665] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0666] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0667] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0668] [Fourth Embodiment]

[0669] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0670] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0671] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0672] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0673] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0674] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0675] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0676] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0677] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0678] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0679] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0680] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0681] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0682] The system of this invention receives goal information entered by the user, provides appropriate goal setting based on that information, manages progress, and provides rewards, all while providing consistent support.

[0683] The user has a device in their possession, and they input their goal information through that device. This goal information might be something like, "I want to lose 5kg." This information is then sent from the device to the server.

[0684] The server analyzes the received goal information and uses a generative model to set specific, achievable goals and deadlines for the user. In this process, the generative model takes into account past data and the user's current state when setting goals. The set goals and deadlines are sent from the server to the terminal and notified to the user.

[0685] During the progress management phase, users record their daily progress on their devices. For example, they might record activities such as "I went for a 30-minute run today." This data is then sent back to the server for analysis.

[0686] The server generates advice based on progress data. This advice, such as "Let's try strength training next," is provided to the user via the terminal. This advice is designed to support the user's actions toward achieving their goals.

[0687] Ultimately, the server evaluates the progress data, and if it determines that the set goal has been achieved, it generates reward information using a reward calculation mechanism and notifies the user. Reward information may include, for example, "500 points awarded for achieving the goal." The terminal displays this reward information to the user, encouraging them to set further goals and take on challenges.

[0688] As a concrete example, a user who sets a goal to lose weight would record their daily activities, receive feedback from the server, achieve their goal, and receive a reward. This allows users to continuously improve themselves based on clear goals.

[0689] The following describes the processing flow.

[0690] Step 1:

[0691] The terminal displays a goal input screen to the user. This interface allows the user to specifically input the goals they want to achieve and the areas they want to improve.

[0692] Step 2:

[0693] The user enters their goal information. This goal information refers to a specific objective, such as "I want to lose 5 kg." The entered data is immediately sent from the terminal to the server.

[0694] Step 3:

[0695] The server runs a generative model based on the target information it receives. The generative model sets specific, achievable targets and deadlines for the user, based on historical data, relevant literature, and other similar cases.

[0696] Step 4:

[0697] The server sends the generated goal settings and deadlines to the terminal. The terminal displays this to the user for review. The user can review the proposed goals and make modifications or additional settings as needed.

[0698] Step 5:

[0699] Users record their daily activities on their devices. For example, they might input specific details such as, "I went for a 30-minute run today." This data is sent to the server periodically or in real time.

[0700] Step 6:

[0701] The server analyzes the received activity data and evaluates the progress. Generative models are used for evaluation to generate the most effective advice for each user and determine what improvements are possible.

[0702] Step 7:

[0703] The server sends the generated advice to the terminal, which then displays it to the user. The advice includes specific action suggestions and points to note for the next step. For example, it might say, "We recommend combining this with strength training next."

[0704] Step 8:

[0705] The server verifies goal achievement based on the user's progress data. If achievement is confirmed, it determines the reward to be given to the user using a reward calculation mechanism and generates reward information.

[0706] Step 9:

[0707] The server sends the generated reward information to the device. The device then notifies the user of the reward. For example, it might display something like, "You have been awarded 500 points for achieving your goal." The rewards serve to maintain the user's motivation and encourage them to set new goals.

[0708] (Example 1)

[0709] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0710] Traditional goal management systems have faced challenges in effectively managing user progress toward achieving their goals and providing appropriate advice. Furthermore, they often lacked sufficient reward systems to sustain user motivation.

[0711] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0712] In this invention, the server includes means for receiving goal data from the user, means for generating a generation algorithm that analyzes the goal data to generate specific goal settings and deadlines, and means for notifying the user of the generated goal setting data. This makes it possible to set achievable and specific goals based on the goal data entered by the user and to always provide appropriate instructions according to the latest progress data. Furthermore, a reward system using reward data can increase the user's motivation and support goal achievement.

[0713] An "information processing device" is a device that has the functions of inputting, processing, and outputting data, and refers to a system that supports goal setting and progress management.

[0714] An "input device" is a device that receives information from the user and has the function of accepting target data and activity data.

[0715] "User" refers to an entity that uses the system to set goals and aims to achieve them.

[0716] "Target data" refers to information about the goals that the user wishes to achieve, and is the basic data entered into the system.

[0717] "Generation algorithm means" refers to technical means for analyzing input target data and generating specific target settings and deadlines suitable for the user.

[0718] "Communication methods" refer to means of notifying the user of generated data or information, and often refer to email or in-app notifications.

[0719] "Progress monitoring means" refers to means of recording and managing the user's progress toward achieving a goal, and includes a function to analyze activity data and evaluate progress.

[0720] "Means of providing instructions" refers to means of notifying users of appropriate advice based on progress data.

[0721] "Reward calculation method" refers to a technical means for calculating the reward provided to the user when a goal is achieved.

[0722] "Reward data" refers to data representing reward information awarded to users for achieving their goals, and includes points, medals, and other similar items.

[0723] This invention is a system that uses an information processing device to consistently handle everything from goal setting to progress management and reward provision in order to support the achievement of user-defined goals. Specific embodiments of the system are shown below.

[0724] The user uses a device they have on hand to input their desired goals. This device functions as an information processing unit and uses the input device to acquire the user's goal data. For example, a user can set a goal such as "reduce body fat percentage by 5% in 3 months." This goal data is transmitted from the device to the server via the internet.

[0725] The server operates in the cloud and analyzes the received target data. This analysis uses a generative AI model. This model considers existing achievement goal datasets and user profile information to generate specific, achievable goals and deadlines tailored to the user. For example, "Based on your goals, aim to reduce your body fat percentage by 1% every two weeks." The generated data is then sent back to the device using communication functions and the user is notified.

[0726] Progress is managed based on the user's daily activities. Users record activity data such as running time and calories burned on their device. The device then sends this data to a server, which evaluates the progress. Based on the progress data, a generative AI model builds and provides advice to the user. For example, it might suggest, "Next time, try incorporating strength training."

[0727] Ultimately, the server evaluates progress and calculates reward data as a bonus if the user achieves their goal. This bonus data can be implemented, for example, as a points system, and provided to the user in a specific form, such as "50 points awarded" depending on their level of achievement. This allows users to challenge themselves with further goals and maintain their motivation to achieve them.

[0728] An example of a prompt for the generative AI model would be, "Based on the target data entered by the user, please generate specific, achievable goals and their deadlines." By using this prompt, the server can leverage the generative AI to provide the user with the most appropriate advice and progress support.

[0729] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0730] Step 1:

[0731] Users input target data using a device. Specifically, they set a goal, such as "reduce body fat percentage by 5% in 3 months," through the device's input interface. The input includes the goal content and the timeframe for achieving it. This input is processed as digital data on the device and sent to the server.

[0732] Step 2:

[0733] The server analyzes the goal data received from the terminal. Based on the received data, it calls a generation AI model and generates specific goals and deadlines, taking into account the user's profile data and past goal achievement data. This analysis uses the prompt message, "Based on the goal data entered by the user, please generate specific, achievable goals and their deadlines." The output is the specific goals and their deadlines, and this information is sent back to the terminal.

[0734] Step 3:

[0735] The terminal notifies the user of specific goals and deadlines sent from the server. The input here is notification information from the server, and the output is a visual presentation to the user. On the terminal, specific goals are displayed via pop-up notifications, alerting the user.

[0736] Step 4:

[0737] Users record their daily activities on their devices. This includes inputting data such as running time and calories burned. The input is activity data, which is organized on the device and prepared for transmission to the server. The output is the organized activity data.

[0738] Step 5:

[0739] The server evaluates progress based on activity data submitted by the user. The server analyzes this data and uses a generative AI model to generate advice for the next action. The input is the user's daily activity data, and the output is specific advice generated by the generative AI model. This advice is then communicated to the user via their device.

[0740] Step 6:

[0741] Ultimately, the server evaluates the progress and, if it determines that the goal has been achieved, calculates reward data. The input here is the achievement status obtained through progress management, and the output is reward information as reward data. For example, reward data such as "50 points awarded for achieving the goal" is generated and notified to the user via the terminal.

[0742] (Application Example 1)

[0743] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0744] In today's information society, maintaining motivation and managing progress toward achieving personal goals is crucial, but there is a lack of effective methods to consistently support this. Furthermore, there is a need for a system that allows incentives for goal achievement to be used in real life as electronic currency or points. This invention aims to enhance motivation for goal achievement by managing the progress of user-set goals and awarding electronic currency or points as rewards.

[0745] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0746] In this invention, the server includes means for receiving goal information from the user via an input device, means for generating a model that analyzes the goal information to set specific goals and manage progress, means for calculating and notifying reward information as electronic currency or points when the goal is achieved, and means for enabling the user to use the reward at affiliated stores. As a result, the user is consistently supported in the process of achieving their goals and can utilize the reward to benefit their daily life.

[0747] An "information processing device" is a device used for inputting, analyzing, storing, and outputting data, and includes computers and servers.

[0748] An "input device" is a device used by users to provide information to a system, and includes keyboards and touchscreens.

[0749] A "user" refers to an individual or organization that operates an information processing device, inputs target information, and manages its progress.

[0750] "Target information" refers to information that indicates the specific challenges and objectives that the user aims to achieve, and serves as the starting point for the system's analysis.

[0751] "Generative modeling means" refers to technologies and methods used to analyze received information and create achievable goals and their deadlines for the user.

[0752] "Notification means" refers to methods or devices for communicating generated information or results to users, and includes push notifications and email communications.

[0753] A "progress management system" is a mechanism for tracking and evaluating the progress made towards goals set by the user.

[0754] "Advice provision means" refers to methods and devices for providing useful advice to users based on progress information and supporting them in achieving their goals.

[0755] A "reward calculation means" is a method or device for calculating a predetermined reward and providing it to the user when the user achieves a goal.

[0756] "Electronic currency" is a form of currency that is exchanged in digital format, unlike traditional banknotes and coins.

[0757] "Points" are units that accumulate based on a user's actions and transactions, and can be used as rewards.

[0758] A "participating store" is a store or organization that accepts rewards provided by the system and uses them to make purchases or provide services.

[0759] In order to implement this invention, a mechanism is needed in which target information is input through an information processing device via user operation, and that information is analyzed by a server.

[0760] The server automatically generates specific goals and deadlines using a generative AI model based on the goal information received from the information processing device. This generative AI model can present realistic and achievable goals by considering the user's past data and relevant statistical information.

[0761] The goal settings generated by the server are sent to the user's device via a notification system, allowing for visual tracking. Users record their daily activities on their devices, and the server analyzes this activity information to manage progress. Examples of specific activities include running and calorie consumption.

[0762] Based on progress information, the server uses an advice provision system to generate effective action plans and improvement suggestions for the user to achieve their goals. This advice is based on daily activities and includes specific instructions such as, "Next time, you should increase your aerobic exercise." If the user achieves their goals, the server uses a reward calculation system to automatically calculate electronic currency or points and award them to the user as a reward.

[0763] The system's programs are primarily written in Python, with Scikit-learn and TensorFlow used for data analysis and model generation. Communication between the server and the user is handled using a RESTful API, and MySQL is used as the database for data storage. The application's frontend is built using React.

[0764] As a concrete example, consider a case where a user sets a goal of "losing 2 kg in one month." The user registers information about their exercise and meals daily through the app. The server analyzes this activity, monitors progress in real time, and generates appropriate training menus and advice. Through this process, the user can earn points as a reward, which can be used for shopping at participating stores. An example of a prompt message would be, "Please enter your activity level for today. Example: '30 minutes of running, 20 minutes of strength training'."

[0765] In this way, this invention enables users to set goals, reliably manage their progress, and earn valuable rewards in real life.

[0766] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0767] Step 1:

[0768] The user enters goal information via the input device on the terminal. For example, they might set a goal such as "lose 2 kg in one month." This goal information is then sent to the server, guided to the user using prompt messages.

[0769] Step 2:

[0770] The server inputs the received goal information into the generating AI model. Based on past data and the user's current state, the generating AI model generates realistic and achievable specific goals and deadlines. During this generation process, statistical processing is performed using Scikit-learn for data analysis to obtain the goal setting results.

[0771] Step 3:

[0772] The server sends the generated goal setting results to the user's terminal via a notification system. The terminal visually displays the goals and notifies the user. Throughout this process, data is exchanged appropriately using a RESTful API.

[0773] Step 4:

[0774] Users input daily activity information into their devices. This activity information includes exercise time and meal details. This data is sent from the user's device to a server and used for progress management.

[0775] Step 5:

[0776] The server analyzes the received activity information using a progress management system. This analysis includes data processing to understand the current progress and evaluate the degree to which the goal has been achieved. Based on the activity information, the server uses Scikit-learn to update the progress information.

[0777] Step 6:

[0778] Based on progress information, the server generates user-facing advice using a generative AI model and sends it to the user's terminal via an advice delivery system. This advice includes specific action plans to effectively support goal achievement.

[0779] Step 7:

[0780] The server evaluates the progress and, if it determines that the user has achieved their goal, calculates electronic currency or points using a reward calculation system. This calculation uses a points system built with the Django framework.

[0781] Step 8:

[0782] The server notifies the user of the calculated reward information and informs them that it can be used at participating stores. This supports users in using the electronic currency or points they have earned as rewards in their daily lives.

[0783] Through this series of processing steps, the system comprehensively supports the user in achieving their goals.

[0784] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0785] The present invention is an information processing device that supports users in achieving their goals, and in particular, by combining it with an emotion engine, it provides personalized support that takes into account the user's emotional state.

[0786] The device collects goal information and daily activity data based on user input. Users record their goals and activities on the device, setting specific goals such as "I want to lose 5 kg." This data is then sent to the server.

[0787] The server analyzes the received target information and activity data, and uses a generative model to set specific targets and deadlines. This generated target information is then sent back to the terminal and notified to the user.

[0788] The emotion engine recognizes the user's current emotional state using user input data and other information. This emotional information is then used as a factor influencing the goal information and advice set on the server.

[0789] The progress management system manages progress toward goal achievement based on daily activity data. This allows the server to monitor progress in real time and provide users with timely and necessary advice. The advice generated by the advice provision system may include suggestions such as "Let's try a new exercise method next," and is adjusted to take into account the user's emotional state.

[0790] The reward calculation system calculates a predetermined reward when the user achieves the goal they have set and notifies the user of the result. The reward functions as an incentive to increase the user's motivation.

[0791] As a concrete example, consider a user who sets a goal of improving their health and records their daily activities. The system takes the user's current emotional state into consideration, sets achievable goals, and provides advice based on their progress. Furthermore, it offers the user a reward upon recognition of their achievement. This allows the user to efficiently progress towards their goals while also considering their emotions.

[0792] The following describes the processing flow.

[0793] Step 1:

[0794] The terminal displays a goal input screen to the user. This screen is an interface for entering specific goals and areas for improvement, and is provided in a user-friendly format.

[0795] Step 2:

[0796] The user enters goal information via their device. For example, they might set a goal such as "I want to lose 5 kg." This entered data is then sent to the server.

[0797] Step 3:

[0798] The server analyzes the received target information. Using a generative model, it generates specific targets and deadlines for their achievement that are appropriate to the user's situation from this information.

[0799] Step 4:

[0800] The server uses an emotion engine to recognize the user's emotional state from their input and current behavioral data. For example, it can detect if a user is experiencing stress through text analysis and frequency information.

[0801] Step 5:

[0802] The server generates goal setting and advice that take the user's emotional state into account. This includes adjustments such as setting realistic goals and suggesting relaxation methods if the user is experiencing stress.

[0803] Step 6:

[0804] The server generates goal settings and advice and sends them to the terminal. The terminal notifies the user and displays them for daily review. The user then uses this information to develop an activity plan.

[0805] Step 7:

[0806] The user records their daily activities. The device also allows for the optional input of emotional data, recording information in detail. For example, information such as "I went for a 30-minute run today, and I'm a little tired" can be entered.

[0807] Step 8:

[0808] The device sends daily activity and emotional data it collects to the server. The server analyzes this data through progress management tools to understand progress and emotional trends.

[0809] Step 9:

[0810] The server generates new advice based on the progress. This advice includes suggestions that take into account changes in emotional state. The advice is sent to the terminal and displayed to the user.

[0811] Step 10:

[0812] The server checks whether the set goal has been achieved, and if so, calculates the reward using the reward calculation system. This reward information is then notified to the user via their terminal. For example, it might say, "You have been awarded 500 points as a reward for achieving your goal."

[0813] This process allows users to receive emotionally conscious support and achieve their goals more efficiently.

[0814] (Example 2)

[0815] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0816] Conventional goal achievement support systems lacked support that considered the user's emotional state, making it difficult to maintain motivation and provide effective advice. Furthermore, simple progress management based solely on user behavioral data failed to provide individualized support, hindering efficient goal achievement.

[0817] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0818] In this invention, the server includes means for receiving goal information and behavioral data from the user via input means, generation model means for analyzing the goal information and behavioral data to generate specific goal settings and deadlines, and notification means for notifying the user based on the generated goal setting information and emotional state. This makes it possible to provide personalized advice that takes into account the user's emotional state, thereby improving the efficiency of goal achievement.

[0819] "Input means" refers to devices or software used to receive goal information and behavioral data from users.

[0820] "Goal information" refers to information about the specific goals and objectives that the user wishes to achieve.

[0821] "Behavioral data" refers to data about the user's daily activities, including exercise levels and lifestyle habits.

[0822] A "generative modeling tool" is a function for setting realistic and achievable specific goals and their deadlines based on the information received.

[0823] A "notification method" is a means of communicating generated goal information and advice to the user.

[0824] A "progress management method" is a method for tracking and managing the progress toward set goals.

[0825] An "advice provision tool" is a function that generates and provides appropriate guidance and advice to users based on progress information and emotional state.

[0826] A "reward calculation method" is a method for calculating appropriate rewards according to the degree to which a user has achieved their goals.

[0827] "Emotional state" refers to the user's mental state, reflecting their current mood and motivation.

[0828] This invention provides an information processing device for supporting users in achieving their goals. Users input goal information and daily behavioral data via a terminal, and the system provides appropriate support for achieving those goals based on this data.

[0829] The device acquires goal information and behavioral data from the user using input methods. A specific example is when a user sets a goal of "losing 5 kg in the next three months" and inputs their daily exercise and food intake records to achieve that goal.

[0830] The data entered by the user is sent to the server. The server uses a generative AI model to analyze this data and set realistic and achievable specific goals and deadlines. The analysis also takes into account the user's emotional state using an emotion engine. For example, the generative AI model can suggest a "one-week plan combining moderate exercise and a balanced diet."

[0831] The server sends the generated goal information back to the terminal and notifies the user. This notification is intended to make it easier for the user to act according to the plan. Furthermore, progress tracking mechanisms are used to track and manage the user's progress in real time based on their behavioral data.

[0832] Furthermore, using an advice delivery system, the server generates and notifies users of personalized advice based on their progress and emotional state. For example, it can provide advice such as, "You seem a little tired today. How about trying some stretching?"

[0833] The reward calculation system calculates reward information when the user achieves a goal and notifies them via their device. This helps maintain user motivation and allows them to work more effectively towards achieving their goals.

[0834] An example of a prompt might be, "Analyze the user's current exercise and dietary data and suggest the optimal fitness plan for next week." This prompt allows the system to provide personalized feedback to each individual user.

[0835] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0836] Step 1:

[0837] Users input goal information and daily activity data via their device. They enter their goals on the device and record daily data such as exercise levels and dietary details. This input data is temporarily stored on the device before being sent to the server.

[0838] Step 2:

[0839] The server analyzes the received goal information and behavioral data. A generative AI model is used for the analysis, generating optimal goal settings for the user from this data. Specifically, it processes data such as "exercise time" and "calorie intake" entered by the user, and the AI ​​model proposes realistic goals that can be achieved within a achievable timeframe. This output might be something like, "Aim to lose 0.5 kg per week."

[0840] Step 3:

[0841] The server analyzes the user's emotional state and adjusts the generated goal information using an emotion engine. User emotional data (e.g., login records or specific keyword inputs) is input, and the server analyzes that emotional state. Based on the analysis results, goal setting and advice are adjusted. For example, if the user is stressed, a comment such as "Let's proceed at a comfortable pace" may be added.

[0842] Step 4:

[0843] The server sends final goal information and advice to the terminal and notifies the user. The notification includes a step-by-step approach to achieving the goal and provides advice tailored to the user's situation. For example, it might output specific instructions such as, "Let's go for a 30-minute walk for three days this week."

[0844] Step 5:

[0845] The server manages progress information and updates it in real time based on daily activity data. It receives the user's latest activity data as input, checks the degree of goal achievement using the progress management system, and outputs the progress status as information. This is provided to the user in the form of "You have achieved 80% of your goal this week."

[0846] Step 6:

[0847] The server uses a reward calculation mechanism to calculate rewards based on the degree of goal achievement. Rewards are calculated based on the goal achievement status obtained from progress management. For example, when a step is achieved, a message such as "Points earned for the next stage" is output and notified to the user via the terminal.

[0848] (Application Example 2)

[0849] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0850] While modern information processing technology allows users to set individual goals and receive progress management and advice based on those goals, providing appropriate support that takes into account the user's emotional state remains challenging. Furthermore, in physical stores, there is a lack of systems that can provide real-time, personalized suggestions to users as they select products and services that best suit their needs. This results in inefficiencies in supporting users in achieving their goals and assisting them in their purchasing decisions.

[0851] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0852] In this invention, the server includes a generation model means that analyzes the user's goal information and generates specific goal settings and deadlines; a means that adapts advice information and goal setting information based on the user's emotional state analyzed by an emotion engine; and a means that provides appropriate suggestions in real time when the user selects products or services related to their objectives. This enables effective goal achievement support that takes into account the user's emotions and personalized, real-time suggestions during purchasing activities at physical stores.

[0853] An "information processing device" refers to the entire system used to receive, analyze, notify, and manage input from users.

[0854] An "input device" refers to a device or interface used by a user to provide goal information and daily activity data to the system.

[0855] "Generative model means" refers to an algorithm or mechanism for generating specific goal settings and corresponding deadlines based on goal information received from the user.

[0856] "Notification means" refers to a method or device for informing users of generated goal setting information, progress information, advice information, and reward information.

[0857] "Progress management tools" refer to systems for continuously tracking and managing users' daily progress toward achieving their goals.

[0858] "Means of providing advice" refers to systems or mechanisms for providing users with advice generated based on progress information.

[0859] "Reward calculation method" refers to the process of calculating a predetermined reward when a user achieves a goal they have set, and notifying the user of that reward.

[0860] An "emotion engine" refers to a technology that analyzes a user's emotional state based on their input data and related information, and adjusts the system's operation based on the results.

[0861] A "real-time suggestion system" refers to a mechanism that provides immediate and appropriate suggestions to users when they are selecting products or services related to their purpose.

[0862] The system implementing this invention combines information processing technology and emotion analysis technology to support users in achieving their goals.

[0863] The server first receives goal information set by the user from the input device. Next, it uses a generative model to analyze this goal information and generate specific goal settings and corresponding deadlines. The server also uses an emotion engine to determine the user's emotional state from various input and sensor data. This analysis can utilize emotion analysis functions such as AWS Rekognition or Google Cloud Vision API. The results of the emotional state analysis are used to adjust goal settings and advice information, providing more personalized support.

[0864] The generated goal-setting information and advice information are transmitted to the user's device in real time via a notification system. At this time, a progress management system, tailored to the user's emotional state, monitors the progress towards the goal and further optimizes the advice information based on that progress. For example, if a user sets a goal of "losing 5kg" through fitness activities, the system can provide exercise suggestions and nutritional advice while considering daily activity data and sensor information such as heart rate. Upon achieving the goal, the system provides an incentive to the user through a reward calculation system.

[0865] Furthermore, the system provides personalized product recommendations via real-time suggestions when customers select products or services in physical stores. This allows customers to obtain the necessary information on the spot and make appropriate purchasing decisions.

[0866] A concrete example is when a user is choosing new fitness gear at a sports goods store; the system suggests shoes and apparel that take into account the user's current exercise goals and emotional state. Such suggestions allow users to efficiently work towards their goals.

[0867] Example prompt: "When a user is aiming for weight loss, what fitness products would be recommended, and what kind of support would be offered in different emotional states? Please provide specific product names and examples of support messages."

[0868] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0869] Step 1:

[0870] The terminal receives goal information and activity data from the user through an input device. This input includes specific goals (e.g., lose 5 kg), daily exercise levels, and dietary information. This data is then sent to a subsequent analysis step.

[0871] Step 2:

[0872] The server analyzes the received goal information and activity data using a generating AI model. Here, the data is structured, and appropriate goal settings and deadlines are generated. This process analyzes the user's activity patterns using a predetermined algorithm and sets achievable goals. Specific goal setting information is generated as output.

[0873] Step 3:

[0874] The server evaluates the generated goal setting information and activity data using an emotion engine to analyze the user's emotional state. This analysis utilizes AWS Rekognition and Google Cloud Vision APIs to determine emotions from voice, text, and sensor data. The output provides data on the user's current emotional state.

[0875] Step 4:

[0876] The server integrates the analyzed goal-setting information and emotional state data, and manages the progress information using a progress management system. During this process, advice tailored to the emotional state is generated. This generated advice is sent to the user as feedback. This feedback includes specific suggestions, such as, "Next, try relaxing yoga."

[0877] Step 5:

[0878] When the server achieves the goal set by the user, it calculates an incentive based on the degree of achievement using a reward calculation mechanism and notifies the user. This calculation takes into account both progress and emotional state. As output, the user is provided with appropriate reward information.

[0879] Step 6:

[0880] When a user selects products in a physical store, the terminal receives real-time suggestions from the server. The system considers the user's goal information, emotional state, and current location to suggest appropriate products and services. For example, new running shoes might be suggested as a purchase option.

[0881] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0882] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0883] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0884] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0885] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0886] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0887] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0888] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0889] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0890] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0891] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0892] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0893] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0894] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0895] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0896] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0897] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0898] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0899] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0900] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0901] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0902] The following is further disclosed regarding the embodiments described above.

[0903] (Claim 1)

[0904] In an information processing device, there is a means for receiving target information from a user via an input means,

[0905] A generation model means that analyzes the aforementioned target information to generate specific target settings and deadlines,

[0906] A notification means for notifying the user of the generated goal setting information,

[0907] A progress management means for managing progress information toward the goal provided by the generative model means,

[0908] An advice provision means that generates advice information based on the aforementioned progress information and notifies the user,

[0909] A reward calculation method that calculates and notifies reward information when a goal is achieved,

[0910] A system that includes this.

[0911] (Claim 2)

[0912] The system according to claim 1, wherein the input means includes means for receiving the user's daily activity data and analyzing the activity data to update progress information.

[0913] (Claim 3)

[0914] The system according to claim 1, wherein the reward calculation means includes means for calculating predetermined points according to the completion status of goals set in the progress management means and notifying the user.

[0915] "Example 1"

[0916] (Claim 1)

[0917] In an information processing device, a means for receiving target data from the user via an input device,

[0918] A generation algorithm means that analyzes the aforementioned target data to generate specific target settings and deadlines,

[0919] A communication means for notifying the user of the generated goal setting data,

[0920] A progress monitoring means for managing progress data toward a goal provided by a generation algorithm means,

[0921] An instruction provision means that generates instruction data based on the aforementioned progress data and notifies the user,

[0922] A reward calculation method that calculates and notifies reward data when a goal is achieved,

[0923] A system that includes this.

[0924] (Claim 2)

[0925] The system according to claim 1, wherein the input device includes means for receiving the user's daily activity data and analyzing the activity data to update progress data.

[0926] (Claim 3)

[0927] The system according to claim 1, wherein the reward calculation means includes means for calculating predetermined points according to the completion status of a goal set in the progress monitoring means and notifying the user.

[0928] "Application Example 1"

[0929] (Claim 1)

[0930] In an information processing device, a means for receiving target information from a user via an input device,

[0931] A generation model means that analyzes the aforementioned target information to generate specific target settings and deadlines,

[0932] A notification means for notifying the user of the generated goal setting information,

[0933] A progress management means for managing progress information toward the goal provided by the generative model means,

[0934] An advice provision means that generates advice information based on the aforementioned progress information and notifies the user,

[0935] A reward calculation method that calculates and notifies reward information as electronic currency or points when a goal is achieved,

[0936] A means to enable users to use their rewards at participating stores,

[0937] A system that includes this.

[0938] (Claim 2)

[0939] The system according to claim 1, wherein the input device includes means for receiving information on the user's daily activities and for analyzing the activity information to update progress information.

[0940] (Claim 3)

[0941] The system according to claim 1, wherein the reward calculation means includes means for calculating a predetermined electronic currency or points according to the completion status of the goals set in the progress management means and notifying the user.

[0942] "Example 2 of combining an emotion engine"

[0943] (Claim 1)

[0944] A means for receiving goal information and behavioral data from the user via an input means,

[0945] A generation model means that analyzes the aforementioned target information and behavioral data to generate specific target settings and deadlines,

[0946] A notification means that notifies the user based on the generated goal setting information and emotional state,

[0947] A progress management means for managing progress information toward the goal provided by the generative model means,

[0948] An advice provision means that generates advice information considering the aforementioned progress information and emotional state and notifies the user of that advice,

[0949] A reward calculation method that calculates and notifies reward information when a goal is achieved,

[0950] A system that includes this.

[0951] (Claim 2)

[0952] The system according to claim 1, wherein the input means includes means for receiving the user's daily activity data and updating progress information by analyzing the activity data and emotional state.

[0953] (Claim 3)

[0954] The system according to claim 1, wherein the reward calculation means includes means for calculating a predetermined reward according to the completion status of the goal set in the progress management means and the emotional state, and notifying the user.

[0955] "Application example 2 when combining with an emotional engine"

[0956] (Claim 1)

[0957] In an information processing device, a means for receiving target information from a user via an input device,

[0958] A generation model means that analyzes the aforementioned target information to generate specific target settings and deadlines,

[0959] A notification means for notifying the user of the generated goal setting information,

[0960] A progress management means for managing progress information toward the goal provided by the generative model means,

[0961] An advice provision means that generates advice information based on the aforementioned progress information and notifies the user,

[0962] A reward calculation method that calculates and notifies reward information when a goal is achieved,

[0963] A means for analyzing the user's emotional state using an emotion engine and matching the aforementioned advice information and goal setting information based on the emotional information,

[0964] A means of providing appropriate suggestions in real time when users select products or services related to their purpose,

[0965] A system that includes this.

[0966] (Claim 2)

[0967] The system according to claim 1, wherein the input device includes means for receiving the user's daily activity data and for analyzing the activity data and emotional information to update progress information.

[0968] (Claim 3)

[0969] The system according to claim 1, wherein the reward calculation means includes means for calculating a predetermined incentive according to the completion status of the goals set in the progress management means and the emotional state of the user, and notifying the user. [Explanation of Symbols]

[0970] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. In an information processing device, there is a means for receiving target information from a user via an input means, A generation model means that analyzes the aforementioned target information to generate specific target settings and deadlines, A notification means for notifying the user of the generated goal setting information, A progress management means for managing progress information toward the goal provided by the generative model means, An advice provision means that generates advice information based on the aforementioned progress information and notifies the user, A reward calculation method that calculates and notifies reward information when a goal is achieved, A system that includes this.

2. The system according to claim 1, wherein the input means includes means for receiving the user's daily activity data and analyzing the activity data to update progress information.

3. The system according to claim 1, wherein the reward calculation means includes means for calculating predetermined points according to the completion status of goals set in the progress management means and notifying the user.

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