system

Abstract

We provide the system. [Solution] An information processing device means that receives user exercise activity data and calculates points based on this data, A storage device that manages calculated points and provides information about exchangeable rewards that the user can select, A data processing device that collects data related to local physical facilities and social events and provides that information to users, An information generation method that analyzes users' exercise activity data and provides information on available benefits in real time based on that data, 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 method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, 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] In modern adults, especially in the middle-aged and elderly, there is a problem that it is difficult to continue exercise and maintain a healthy lifestyle. This is mainly due to a decrease in motivation for exercise and a lack of activities in local communities that suit individual interests. As a result, there are concerns about shortening of the healthy life span and deterioration of the quality of life.

Means for Solving the Problems

[0005] This invention solves the problem by providing a system that calculates points based on a user's exercise activity data and allows them to exchange those points for redeemable rewards related to local physical facilities and community events. This system features an algorithm that provides a personalized fitness experience, offers suggestions for maintaining health, proposes health-related products that can be redeemed with points, and provides recommendations tailored to the user's interests. This promotes continued exercise, increases participation in local communities, and enables the realization of a healthy and sustainable lifestyle.

[0006] A "user" refers to an individual who uses the system to record their exercise activities and receive related services.

[0007] "Exercise activity data" refers to information about the exercise performed by the user, including records of the type of exercise, duration, and intensity.

[0008] "Points" refer to a numerical evaluation calculated based on a user's exercise activity and used when exchanging points for rewards.

[0009] "Computer server means" refers to a server system that receives exercise activity data from users and calculates points based on that data.

[0010] A "database system" refers to an information management system for managing and storing information about calculated points and exchangeable rewards.

[0011] "Information processing means" refers to a system for collecting data related to local physical facilities and community events and providing it to users.

[0012] "Local physical facilities" refers to sports facilities and health-related facilities located within a region where users can receive services using points.

[0013] "Community events" refer to sports events, club activities, and other events held within a local area that users can participate in.

[0014] A "personalized fitness experience" refers to providing users with optimized fitness plans and health maintenance suggestions based on their individual exercise data.

[0015] "Health-related products" refer to products and services related to the user's health and fitness that can be exchanged using points.

[0016] "Recommendations tailored to user interests" refers to appropriate suggestions regarding events, products, and services that take into account the user's interests and needs. [Brief explanation of the drawing]

[0017] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This 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] This shows an emotion map where multiple emotions are mapped. [Figure 10] It shows an emotion map where multiple 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 combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Mode for Carrying Out the Invention

[0018] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0019] First, the language used in the following description will be explained.

[0020] 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 CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), etc.

[0021] 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.

[0022] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0023] 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).

[0024] 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."

[0025] [First Embodiment]

[0026] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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".

[0038] This invention is an integrated system that allows users to exchange points earned through fitness activities for local facilities and health-related services. The specific operation of each component will be described below.

[0039] When a user uses the system for the first time, they must first create an account. During this process, they enter personal information on their device, which is then sent to the server and securely stored in the database. Once registration is complete, the server sends a confirmation email, and the user can log in to their account.

[0040] After completing their daily exercise, users input their exercise activity data into their device. This data includes, for example, distance, time, and calories burned during activities like walking or running. This data is sent to a server and used for point calculation.

[0041] The server analyzes the received exercise activity data and runs an algorithm to calculate points. The calculated points are added to a database, allowing users to check their point balance. Points vary depending on the type, duration, intensity, and degree of goal achievement of the exercise.

[0042] Once a user's points reach a certain threshold, they can use those points within the system to exchange them for discounts or free services at local facilities, as well as health-related products. These include tickets to affiliated sports facilities, health foods, and fitness wear.

[0043] The device provides users with information on local community sports events and club activities. Users can register for events that interest them and gain opportunities to participate in various activities held in their community. This promotes continued exercise and participation in the local community.

[0044] This system aims to support the maintenance of a healthy lifestyle through fitness activities and strengthen ties with the local community. This will enable users to maintain sustained motivation and contribute to extending healthy life expectancy.

[0045] The following describes the processing flow.

[0046] Step 1:

[0047] The user launches the application and enters the required information (name, age, email address, password, etc.) on the account creation screen.

[0048] Step 2:

[0049] The terminal saves the entered information as temporary data and verifies the data's integrity and input format. If there are no problems, it sends the data to the server.

[0050] Step 3:

[0051] The server stores the received user information in a database and generates a unique user ID for the user. Next, it sends a confirmation email to the user upon completion of registration.

[0052] Step 4:

[0053] The user enters their email address and password on the regular login screen and sends an authentication request to the server.

[0054] Step 5:

[0055] The server compares the registration information in the database with the login information, and if a match is found, redirects the user to the dashboard screen.

[0056] Step 6:

[0057] After completing their daily exercise, users enter and save their exercise activity data (type, time, distance, etc.) on the exercise record screen of their device.

[0058] Step 7:

[0059] The device sends exercise activity data to the server, and the server executes a point calculation algorithm based on the received data.

[0060] Step 8:

[0061] The server updates the user's account with the calculated points and saves the latest point balance to the database.

[0062] Step 9:

[0063] Users can view available rewards and services on the points exchange screen, select their desired options, and submit a points exchange request.

[0064] Step 10:

[0065] The server receives the exchange request, verifies the user's point balance, completes the exchange process, and then transmits the information to the partner.

[0066] Step 11:

[0067] The terminal sends a notification to the user that the point exchange has been completed and displays details of the exchanged items.

[0068] Step 12:

[0069] Users can view events of interest on the local event information screen and, if they wish to participate, press the registration button.

[0070] Step 13:

[0071] The server receives the participation request, provides the participant information to the event organizer, and adds the user to the registration list.

[0072] (Example 1)

[0073] 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."

[0074] In modern lifestyles, lack of exercise and decreased motivation for maintaining health are serious problems. Furthermore, the lack of systems that efficiently support individual fitness activities makes it difficult for users to establish appropriate exercise habits. There is also a need for mechanisms that foster connections with the community and promote social participation.

[0075] 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.

[0076] In this invention, the server includes information processing means for receiving user exercise activity data and calculating points; storage means for managing the calculated points and providing exchangeable reward data; information providing means for collecting and providing information related to local facilities and events; and means equipped with a generation device for generating motivational messages from the user's exercise habits. This enables users to make healthy lifestyles a habit and strengthen their connection with the local community.

[0077] "User exercise activity data" refers to information about the exercise performed by the user, specifically measurable values ​​such as the type of exercise, duration, distance, and calories burned.

[0078] "Information processing means" refers to the functions of a processing device or software that calculates points based on received data and performs motion information analysis.

[0079] "Memory means" refers to a database or memory that holds calculated points and related information and provides data to the user as needed.

[0080] "Information provision means" refers to the function of a device or system that collects and disseminates information about local facilities and events to users and displays information tailored to the user's interests.

[0081] "Means equipped with a generation device" refers to a function or device for analyzing a user's exercise habits and preferences and generating appropriate motivational messages.

[0082] "Exchangeable rewards" refer to products or services offered based on a user's points, and include benefits and goods that users can acquire using their points.

[0083] This invention is a system that allows users to record exercise data and manage their health based on that data. The system consists of a user terminal, a server that processes the information, and services provided through these.

[0084] Users record their daily exercise activities on their devices. Specifically, they use a dedicated application to input activities such as walking, running, and cycling. This application allows users to input data such as distance, time, and calories burned, which is then used as exercise activity data.

[0085] The device sends this exercise data to the server. Communication takes place via an internet connection, and encrypted protocols (e.g., HTTPS) are used for data transmission. The device also periodically receives updates from the server to provide information on local community events and facilities.

[0086] The server analyzes the received exercise data and calculates points using a dedicated algorithm. This process utilizes a generative AI model and includes data analysis and the generation of personalized feedback. The calculated points are stored in a database and managed as the user's accumulated points. Once points reach a certain level, users can exchange them for local services and products.

[0087] For example, if a user jogs a total of 10km in a week, they send this data to the server, which then calculates points for it. For instance, let's say they earn 100 points. The server then generates a prompt message like, "You need 200 more points to get a free fitness pass. Why not go for another run today?" and notifies the user.

[0088] In this way, the system provides users with the motivation to continue exercising and supports their connection to the community and healthy lifestyle.

[0089] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0090] Step 1:

[0091] Users record their exercise activities using their devices.

[0092] Input: Exercise activity data entered by the user into the application (e.g., distance, time, calories burned).

[0093] Specific action: The user enters into the app that their run today was 5km and took 30 minutes.

[0094] Output: The input data is saved to the terminal's temporary memory.

[0095] Step 2:

[0096] The device sends exercise data to the server.

[0097] Input: Exercise activity data stored on the device.

[0098] Specific operation: Data is encrypted using HTTPS and sent to the server.

[0099] Output: The data was successfully received by the server.

[0100] Step 3:

[0101] The server analyzes the exercise data and calculates points.

[0102] Input: Exercise activity data sent to the server.

[0103] Specific operation: A generative AI model is used to analyze exercise activity data, and a point calculation algorithm is applied. For example, 100 points are calculated for a 5km run.

[0104] Output: Calculated points.

[0105] Step 4:

[0106] The server saves the calculated points to the database.

[0107] Input: Calculated points.

[0108] Specific action: The system will save points to the database along with the user ID.

[0109] Output: Points are added to the database, and the user's accumulated points are updated.

[0110] Step 5:

[0111] The server generates prompt messages using a generation AI model.

[0112] Input: User's cumulative points and exercise habit data.

[0113] Specific operation: The generative AI model creates prompt messages such as, "You can get a free fitness pass if you earn 200 more points. Why not go for a run today?"

[0114] Output: The generated prompt message.

[0115] Step 6:

[0116] The device notifies the user of a prompt message.

[0117] Input: The prompt message sent from the server.

[0118] Specific action: Use the notification function to display a prompt message on the app.

[0119] Output: A prompt message is displayed on the user's screen.

[0120] Step 7:

[0121] Users use points to select and exchange rewards.

[0122] Input: The reward selection screen that the user confirms and the number of points that can be exchanged.

[0123] Specific action: The user selects a fitness pass in exchange for 200 points within the app.

[0124] Output: The exchange is complete and the user's point balance has been updated.

[0125] (Application Example 1)

[0126] 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."

[0127] In modern society, it is important for individuals to maintain a healthy lifestyle while staying connected to their community. However, it is not easy to motivate individuals to continue fitness activities or increase opportunities to participate in community events amidst busy daily lives. Furthermore, there is a challenge in that systems for meaningfully utilizing the results gained through fitness activities in real life are not yet adequately developed.

[0128] 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.

[0129] In this invention, the server includes an information processing device that receives user exercise activity data and calculates points based on this data; a storage device that manages the calculated points and provides information on exchangeable rewards that the user can select; a data processing device that collects data related to local physical facilities and social events and provides this information to the user; and an information forming device that analyzes the user's exercise activity data and provides information on available rewards in real time based on that data. This allows the user to gain motivation to continue their fitness activities, promote participation in the local community, and efficiently utilize the points they earn in the real world.

[0130] "Information processing device means" refers to a part of a system that has the function of receiving exercise activity data from a user and calculating points based on that data.

[0131] A "memory device" is a means for managing calculated points and storing and providing information on rewards that users can select.

[0132] "Data processing device" refers to a system that collects data on physical facilities and social events in a region and provides that information to users.

[0133] "Information formation means" refers to a method that analyzes users' exercise activity data and generates and provides information on the use of benefits based on that data in real time.

[0134] The system implementing this invention consists of an application that operates via the user's smartphone and a server system located in the cloud.

[0135] Users record their exercise activity data using an application installed on their smartphone. The application uses fitness tracking APIs (such as Google Fit® or Apple HealthKit) to collect data such as the user's steps, running distance, and calories burned. The smartphone allows users to instantly view their exercise results through its user interface.

[0136] The server is located in a cloud environment (e.g., AWS® or Azure®) and receives exercise activity data sent by the user. This server uses information processing equipment to analyze the data and calculates points based on a specific algorithm. The calculated points are managed by storage equipment and securely stored in a database (e.g., Firebase). The server then provides the user with information about their point balance and available rewards in real time.

[0137] Furthermore, the server uses data processing equipment to collect data related to local physical facilities and community events, and delivers this information to the user's smartphone. This allows users to connect with their local community and expand their options for participating in healthy activities. For example, the server can deliver information about a new local running event, and upon receiving this information, the user can register to participate in the event.

[0138] In the generative AI model, the task is to design a system that analyzes data indicating a user has completed a 5km run and awards points in real time. An example of a prompt might be: "Design an app that calculates points in real time based on exercise data after a user completes a 5km run and displays a list of available local benefits."

[0139] Thus, this invention technically supports the maintenance of a healthy lifestyle through fitness activities and promotes participation in the local community.

[0140] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0141] Step 1:

[0142] The device records the user's exercise activity. Specifically, it uses fitness tracking APIs (e.g., Google Fit®, Apple HealthKit) to collect data such as exercise time, distance, and calories burned. This requires the user's fitness information as input, and the exercise data is stored on the device as output.

[0143] Step 2:

[0144] The device sends the collected exercise data to the server. Specifically, it uploads the data to a cloud server (e.g., AWS, Azure) via an internet connection. The device requires exercise data as input, and that data is sent to the server as output.

[0145] Step 3:

[0146] The server analyzes the received motion data. Specifically, it analyzes the data using an information processing device and executes a point calculation algorithm. The input is the motion data sent to the server, and the output is the calculated points.

[0147] Step 4:

[0148] The server records the calculated points and provides feedback to the user. Specifically, it uses a storage device to save the points to a database and then notifies the user of their point balance on their device. The input is the calculated points, and the output is the notification information sent to the user's device.

[0149] Step 5:

[0150] The server collects information on local physical facilities and events. Specifically, it uses data processing equipment to retrieve local activity information from external databases and APIs. The input is external information sources, and the output is local event data.

[0151] Step 6:

[0152] The server provides users with collected local information. Specifically, it notifies users' devices of community events they can participate in and special offers. The input is data on local events, and the output is notifications sent to the user's device.

[0153] Step 7:

[0154] The generating AI model designs a service for a specific situation based on a prompt. Specifically, it generates a service design in response to the prompt, "Design an app that calculates points in real time based on exercise data after a user runs 5 kilometers and displays a list of available local benefits." The input is the prompt, and the output is a proposed service design.

[0155] 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.

[0156] This invention is an integrated system that provides a more appropriate fitness experience by calculating points based on the user's exercise activity data and understanding the user's psychological state using an emotion engine. The specific operation of each component is described below.

[0157] Users first create an account through the application and enter their basic information. After creating an account, they are moved to a dedicated screen to begin recording their exercise activities. This screen is equipped with an emotion engine that recognizes the user's emotions from their facial expressions and voice. The user's emotional data is collected during or after exercise.

[0158] The device receives and temporarily stores this emotional data. In addition, it also sends user-entered exercise activity data (such as type of exercise, duration, and intensity) to the server.

[0159] The server analyzes the received exercise activity data and emotional data. Points are calculated based on the type and level of achievement of the exercise activity, but by using data from the emotional engine, the user's emotions while exercising are also taken into consideration. This information is used to enhance the purpose and motivation of exercise.

[0160] The server considers emotional data, exercise activity data, and the balance of points to suggest the optimal training plan and rewards for the user. For example, if a user is experiencing stress related to exercise, the server will suggest exercises that promote relaxation and appropriate rewards based on emotional data.

[0161] Users continue this cycle by executing the suggested training plan and submitting data again. Furthermore, information on local physical facilities and events is displayed, allowing users to participate in activities tailored to their emotional state. This provides a more personalized approach to maintaining health and enables the achievement of sustainable fitness.

[0162] This system integrates user emotions and exercise data to provide a personalized fitness experience, supporting continued exercise and the realization of a healthy lifestyle.

[0163] The following describes the processing flow.

[0164] Step 1:

[0165] The user launches the application and enters their basic information (name, email address, password, etc.) on the account registration screen.

[0166] Step 2:

[0167] The terminal checks the entered information, and if there are no formatting errors, it sends the information to the server.

[0168] Step 3:

[0169] The server stores the user's information in a database and sends a notification to the user confirming that their account registration is complete.

[0170] Step 4:

[0171] Before exercising, the user activates the emotion recognition function and begins their exercise activity. The emotion engine analyzes their facial expressions and tone of voice during this time, collecting emotional data.

[0172] Step 5:

[0173] The device temporarily stores collected emotional data and exercise activity data entered by the user (type of exercise, duration, and intensity).

[0174] Step 6:

[0175] The device sends emotional data and exercise activity data to the server.

[0176] Step 7:

[0177] The server analyzes the received data and calculates points to award to the user, taking into account not only the type and intensity of exercise but also their emotional state.

[0178] Step 8:

[0179] The server updates the point balance and suggests personalized fitness plans and special rewards to the user.

[0180] Step 9:

[0181] The user reviews the suggestions, selects an exercise plan and rewards, and sends their selections back to the server via their device.

[0182] Step 10:

[0183] The server updates its database based on user selections and incorporates them into future suggestions, continuously providing an optimized fitness experience for each individual user.

[0184] (Example 2)

[0185] 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".

[0186] In modern society, it is important for individual users to maintain their health through exercise in a sustainable manner, but conventional fitness systems do not adequately consider the psychological factors related to exercise activity. Therefore, it is difficult to continuously increase motivation for exercise, resulting in a large number of users being unable to continue exercising. There is a need to provide personalized fitness experiences that take into account the user's psychological state.

[0187] 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.

[0188] In this invention, the server includes information processing means for receiving user exercise activity data and emotional data and calculating points based on this data; storage means for managing the calculated points and providing information on exchangeable rewards that the user can select; information providing means for collecting data related to local exercise facilities and community events and providing that information to the user; and information analysis means equipped with a generation algorithm that analyzes the user's emotional state and makes optimal suggestions for exercise activities. This provides a personalized fitness experience based on the user's psychological state and exercise data, enabling continued exercise and improved motivation, as well as sustainable health maintenance.

[0189] A "user" refers to an individual who uses the system to record and manage their exercise activities.

[0190] "Exercise activity data" refers to information about the type, duration, and intensity of exercise performed by the user.

[0191] "Emotional data" refers to information that indicates a user's psychological state, analyzed from their facial expressions and voice.

[0192] "Points" refer to an evaluation value calculated by taking into account the user's exercise activity and the psychological state associated with it.

[0193] "Information processing means" refers to a device or program that has the function of analyzing exercise activity data and emotional data received from a user and calculating points.

[0194] "Memory means" refers to storage or databases used to manage information about points and rewards that users can choose.

[0195] "Information provision means" refers to a system that delivers information related to local sports facilities and community events to users.

[0196] A "generative algorithm" refers to a computational method for analyzing emotional states and suggesting appropriate exercise activities.

[0197] "Information analysis means" refers to a system that integrates and analyzes user emotional data and exercise activity data, and uses a generation algorithm to propose the optimal fitness plan for the user.

[0198] This invention is a system that provides a personalized fitness experience by comprehensively utilizing the user's exercise activity data and emotional data. Specific forms for implementing this system are described below.

[0199] Users create an account using a dedicated application via their smartphone or wearable device. During account creation, they enter basic information such as their name, age, gender, and fitness level. They then use a dedicated screen within the app to begin exercising. This screen incorporates an emotion engine that collects the user's facial expressions and voice in real time through the smartphone's camera and microphone, generating emotion data.

[0200] The device temporarily stores collected emotional data and user-entered exercise activity data in its storage, and then transmits the data to the server via Bluetooth® or an internet connection. This ensures secure and efficient data transfer.

[0201] The server uses a generative AI model to analyze the received data and calculate points based on the user's exercise activity. This model also takes emotional data into account, allowing it to provide an evaluation that reflects the user's psychological state during exercise. The calculated points are stored in a memory system and used to manage information about rewards that the user can choose.

[0202] The server also collects and provides data related to local sports facilities and community events, and suggests activities best suited to the user. Furthermore, it analyzes the user's emotional state and generates an optimal training plan based on those emotions. For example, by using a prompt such as, "Suggest an optimal exercise program for a user who is feeling stressed," the generating AI model will provide appropriate suggestions.

[0203] This allows users to enjoy a personalized fitness experience while achieving a sustainable and healthy lifestyle. The system integrates emotional and physical activity to provide a new level of fitness support.

[0204] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0205] Step 1:

[0206] The user launches the application on their smartphone or wearable device and enters basic information on the account creation screen. The entered basic information (e.g., name, age, gender, fitness level) is sent to the server. The output of this step is profile data containing the user's registered basic information.

[0207] Step 2:

[0208] The user begins exercising and uses a dedicated screen within the app. This screen is equipped with an emotion engine that detects emotions from facial expressions and voice, and the user's emotional data is collected. The input data is acquired through the device's camera and microphone, and data on the emotional state (e.g., stress, joy, relaxation) is generated as output.

[0209] Step 3:

[0210] The device collects exercise activity data (e.g., type of exercise, duration, intensity) through manual user input and temporarily stores it on the device along with emotional data. The data is then transmitted to the server via Bluetooth or Wi-Fi. The output of this step is that the exercise activity data and emotional data have been sent to the server.

[0211] Step 4:

[0212] The server analyzes the received exercise activity data and emotional data using a generating AI model. Based on the input data, the generating AI model processes the data and calculates points that take into account the exercise performance and emotional state. As output, an evaluation score for the user's activity is generated.

[0213] Step 5:

[0214] The server manages the calculated points using a memory system and associates them with available rewards and promotional information. This information is then notified to the user. As output, a list of available rewards for the user is generated and can be displayed within the app.

[0215] Step 6:

[0216] The server uses prompts to generate an AI model that creates a training plan that takes the user's emotional state into account. For example, by inputting the prompt, "Suggest an optimal exercise program for a user who is feeling stressed," the AI ​​model will suggest an appropriate fitness plan. The output of this step is a personalized training plan provided to the user.

[0217] Step 7:

[0218] The user reviews the proposed training plan, selects and performs activities as needed. The results are recorded again on the device and sent to the server in the next processing cycle. User feedback is collected as output and incorporated into the system.

[0219] (Application Example 2)

[0220] 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".

[0221] Traditional fitness systems could provide basic advice and rewards based on users' exercise data, but they were insufficient in providing a fitness experience that took into account the user's emotional state. As a result, they lacked features to provide feedback and motivation that were appropriate to the user's psychological state, making it difficult to provide health promotion support optimized for each individual user.

[0222] 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.

[0223] In this invention, the server includes a central processing unit means that receives user exercise activity data and emotional data and calculates points based on this data; a storage device means that manages the calculated points and provides information on exchangeable rewards that the user can select; an information processing device means that collects data related to local physical facilities and group events and provides that information to the user; and a human support device means that provides feedback based on the user's emotional state and monitors exercise activity. This makes it possible to provide users with a personalized fitness experience, increase their motivation to exercise, and efficiently support the maintenance of their health.

[0224] "User exercise activity data" refers to data that includes information such as the type, duration, and intensity of exercise performed by the user.

[0225] "Emotional data" refers to data that indicates a user's psychological state, and is information obtained through facial expression and voice analysis.

[0226] The term "central processing unit means" refers to a computer device that performs calculations based on received data and calculates motion points.

[0227] "Storage device" refers to a data storage device that manages calculated points and provides reward information to the user.

[0228] An "information processing device" is a computer device that collects local facility and event information and processes it to provide it to users.

[0229] A "human support device" is a device that provides feedback based on the user's emotions and supports their exercise activities.

[0230] A "fitness experience" refers to a series of experiences that a user gains during the process of exercising, including the sensations, results, and increased motivation they experience.

[0231] The system that realizes this invention combines various elements for collecting and analyzing user exercise activity data and emotional data. The specific configuration of the system is described below.

[0232] The server first receives exercise activity data and emotional data from the user. Emotional data is collected using a device with a camera and microphone, which analyzes facial expressions and voice. Image processing software such as OpenCV and TENSORFLOW® is used for the analysis.

[0233] User exercise and emotional data are converted into points by a central processing unit and managed by a memory device. This process considers the type, duration, intensity, and emotional state of the user's exercise activity. These points are then used with a generative AI model to suggest rewards optimized for the user.

[0234] The terminal collects local facility data and event information via an information processing device and provides this information to the user. This data is used to suggest optimal activities based on the user's emotional state.

[0235] For example, if a facial recognition camera detects that a user is experiencing stress during a home fitness session, the system will recommend relaxing music to the user. It also has a feature that notifies users to participate in local yoga events.

[0236] An example of a prompt for a generative AI model would be: "Analyze the user's emotional data during exercise in real time, and generate and present appropriate advice and reward plans."

[0237] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0238] Step 1:

[0239] The user initiates physical activity through the device's built-in camera and microphone. At this stage, the device acquires facial expressions and voice, receiving them as emotional data. This data is analyzed in real time using OpenCV and TensorFlow, and output as numerical information indicating the emotional state.

[0240] Step 2:

[0241] The device receives data on the type, duration, and intensity of exercise activities entered manually or automatically by the user. This data is entered as exercise activity data and sent to the server. This exercise activity data serves as foundational information for evaluating how well the user has achieved their fitness goals.

[0242] Step 3:

[0243] The server integrates and analyzes the emotional data obtained in Step 1 and the exercise activity data obtained in Step 2. Points are calculated, taking into account the emotional state and the degree of exercise achievement. These points serve as the basis for the reward plan offered to the user. A generative AI model is used for the calculation and integration.

[0244] Step 4:

[0245] The server generates a reward plan based on the calculated points and the user's emotions, and stores it in storage. The storage also accesses external resources, including local facility data and event information, to select the most suitable health promotion information for the user.

[0246] Step 5:

[0247] The server provides users with feedback on selected exercise results, reward suggestions, and local activity information. This feedback also includes a customized training plan determined by a generative AI model. The device incorporates specific actions to boost user motivation, such as playing certain music or sending notifications.

[0248] 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.

[0249] 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.

[0250] 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.

[0251] [Second Embodiment]

[0252] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0253] 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.

[0254] 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).

[0255] 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.

[0256] 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.

[0257] 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).

[0258] 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.

[0259] 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.

[0260] 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.

[0261] 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.

[0262] 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.

[0263] 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".

[0264] This invention is an integrated system that allows users to exchange points earned through fitness activities for local facilities and health-related services. The specific operation of each component will be described below.

[0265] When a user uses the system for the first time, they must first create an account. During this process, they enter personal information on their device, which is then sent to the server and securely stored in the database. Once registration is complete, the server sends a confirmation email, and the user can log in to their account.

[0266] After completing their daily exercise, users input their exercise activity data into their device. This data includes, for example, distance, time, and calories burned during activities like walking or running. This data is sent to a server and used for point calculation.

[0267] The server analyzes the received exercise activity data and runs an algorithm to calculate points. The calculated points are added to a database, allowing users to check their point balance. Points vary depending on the type, duration, intensity, and degree of goal achievement of the exercise.

[0268] Once a user's points reach a certain threshold, they can use those points within the system to exchange them for discounts or free services at local facilities, as well as health-related products. These include tickets to affiliated sports facilities, health foods, and fitness wear.

[0269] The device provides users with information on local community sports events and club activities. Users can register for events that interest them and gain opportunities to participate in various activities held in their community. This promotes continued exercise and participation in the local community.

[0270] This system aims to support the maintenance of a healthy lifestyle through fitness activities and strengthen ties with the local community. This will enable users to maintain sustained motivation and contribute to extending healthy life expectancy.

[0271] The following describes the processing flow.

[0272] Step 1:

[0273] The user launches the application and enters the required information (name, age, email address, password, etc.) on the account creation screen.

[0274] Step 2:

[0275] The terminal stores the input information as temporary data and checks the data integrity and input format. If there are no problems, it sends the data to the server.

[0276] Step 3:

[0277] The server stores the received user information in the database and generates a unique user ID for the user. Next, it sends a registration completion confirmation email to the user.

[0278] Step 4:

[0279] The user enters the email address and password on the normal login screen and sends an authentication request to the server.

[0280] Step 5:

[0281] The server compares the registration information and login information in the database. If there is a match, it redirects the user to the dashboard screen.

[0282] Step 6:

[0283] After the user finishes their daily exercise, they enter and save the exercise activity data (type, time, distance, etc.) on the exercise record screen of the terminal.

[0284] Step 7:

[0285] The terminal sends the exercise activity data to the server, and the server executes a point calculation algorithm based on the received data.

[0286] Step 8:

[0287] The server updates the calculated points to the user's account and saves the latest point balance in the database.

[0288] Step 9:

[0289] Users can view available rewards and services on the points exchange screen, select their desired options, and submit a points exchange request.

[0290] Step 10:

[0291] The server receives the exchange request, verifies the user's point balance, completes the exchange process, and then transmits the information to the partner.

[0292] Step 11:

[0293] The terminal sends a notification to the user that the point exchange has been completed and displays details of the exchanged items.

[0294] Step 12:

[0295] Users can view events of interest on the local event information screen and, if they wish to participate, press the registration button.

[0296] Step 13:

[0297] The server receives the participation request, provides the participant information to the event organizer, and adds the user to the registration list.

[0298] (Example 1)

[0299] 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."

[0300] In modern lifestyles, lack of exercise and decreased motivation for maintaining health are serious problems. Furthermore, the lack of systems that efficiently support individual fitness activities makes it difficult for users to establish appropriate exercise habits. There is also a need for mechanisms that foster connections with the community and promote social participation.

[0301] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0302] In this invention, the server includes information processing means for receiving the user's exercise activity data and calculating points, storage means for managing the calculated points and providing exchangeable reward data, information providing means for collecting and providing information related to local facilities and events, and means including a generating device for generating a motivating message from the user's exercise habits. Thereby, it becomes possible for the user to habituate a healthy lifestyle and strengthen the cooperation with the local community.

[0303] The "user's exercise activity data" is information related to the exercise performed by the user, and specifically refers to measurable numerical values such as the type of exercise, duration, distance, calorie consumption, etc.

[0304] The "information processing means" refers to the function of a processing device or software for calculating points based on the received data and analyzing exercise information.

[0305] The "storage means" refers to a database or memory for holding the calculated points and related information and providing data to the user as needed.

[0306] The "information providing means" refers to the function of a device or system for collecting and transmitting information on local facilities and events to the user and displaying information according to the user's interests.

[0307] The "means including a generating device" refers to a function or device for analyzing the user's exercise habits and preferences and generating an appropriate motivating message.

[0308] The "exchangeable reward" is a product or service provided based on the user's points, and refers to privileges and goods that the user can obtain by using points.

[0309] This invention is a system that allows users to record exercise data and manage their health based on that data. The system consists of a user terminal, a server that processes the information, and services provided through these.

[0310] Users record their daily exercise activities on their devices. Specifically, they use a dedicated application to input activities such as walking, running, and cycling. This application allows users to input data such as distance, time, and calories burned, which is then used as exercise activity data.

[0311] The device sends this exercise data to the server. Communication takes place via an internet connection, and encrypted protocols (e.g., HTTPS) are used for data transmission. The device also periodically receives updates from the server to provide information on local community events and facilities.

[0312] The server analyzes the received exercise data and calculates points using a dedicated algorithm. This process utilizes a generative AI model and includes data analysis and the generation of personalized feedback. The calculated points are stored in a database and managed as the user's accumulated points. Once points reach a certain level, users can exchange them for local services and products.

[0313] For example, if a user jogs a total of 10km in a week, they send this data to the server, which then calculates points for it. For instance, let's say they earn 100 points. The server then generates a prompt message like, "You need 200 more points to get a free fitness pass. Why not go for another run today?" and notifies the user.

[0314] In this way, the system provides users with the motivation to continue exercising and supports their connection to the community and healthy lifestyle.

[0315] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0316] Step 1:

[0317] Users record their exercise activities using their devices.

[0318] Input: Exercise activity data entered by the user into the application (e.g., distance, time, calories burned).

[0319] Specific action: The user enters into the app that their run today was 5km and took 30 minutes.

[0320] Output: The input data is saved to the terminal's temporary memory.

[0321] Step 2:

[0322] The device sends exercise data to the server.

[0323] Input: Exercise activity data stored on the device.

[0324] Specific operation: Data is encrypted using HTTPS and sent to the server.

[0325] Output: The data was successfully received by the server.

[0326] Step 3:

[0327] The server analyzes the exercise data and calculates points.

[0328] Input: Exercise activity data sent to the server.

[0329] Specific operation: A generative AI model is used to analyze exercise activity data, and a point calculation algorithm is applied. For example, 100 points are calculated for a 5km run.

[0330] Output: Calculated points.

[0331] Step 4:

[0332] The server saves the calculated points to the database.

[0333] Input: Calculated points.

[0334] Specific action: The system will save points to the database along with the user ID.

[0335] Output: Points are added to the database, and the user's accumulated points are updated.

[0336] Step 5:

[0337] The server generates prompt messages using a generation AI model.

[0338] Input: User's cumulative points and exercise habit data.

[0339] Specific operation: The generative AI model creates prompt messages such as, "You can get a free fitness pass if you earn 200 more points. Why not go for a run today?"

[0340] Output: The generated prompt message.

[0341] Step 6:

[0342] The device notifies the user of a prompt message.

[0343] Input: The prompt message sent from the server.

[0344] Specific action: Use the notification function to display a prompt message on the app.

[0345] Output: A prompt message is displayed on the user's screen.

[0346] Step 7:

[0347] Users use points to select and exchange rewards.

[0348] Input: The reward selection screen that the user confirms and the number of points that can be exchanged.

[0349] Specific action: The user selects a fitness pass in exchange for 200 points within the app.

[0350] Output: The exchange is complete and the user's point balance has been updated.

[0351] (Application Example 1)

[0352] 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 glasses 214 will be referred to as the "terminal."

[0353] In modern society, it is important for individuals to maintain a healthy lifestyle while staying connected to their community. However, it is not easy to motivate individuals to continue fitness activities or increase opportunities to participate in community events amidst busy daily lives. Furthermore, there is a challenge in that systems for meaningfully utilizing the results gained through fitness activities in real life are not yet adequately developed.

[0354] 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.

[0355] In this invention, the server includes an information processing device that receives user exercise activity data and calculates points based on this data; a storage device that manages the calculated points and provides information on exchangeable rewards that the user can select; a data processing device that collects data related to local physical facilities and social events and provides this information to the user; and an information forming device that analyzes the user's exercise activity data and provides information on available rewards in real time based on that data. This allows the user to gain motivation to continue their fitness activities, promote participation in the local community, and efficiently utilize the points they earn in the real world.

[0356] "Information processing device means" refers to a part of a system that has the function of receiving exercise activity data from a user and calculating points based on that data.

[0357] A "memory device" is a means for managing calculated points and storing and providing information on rewards that users can select.

[0358] "Data processing device" refers to a system that collects data on physical facilities and social events in a region and provides that information to users.

[0359] "Information formation means" refers to a method that analyzes users' exercise activity data and generates and provides information on the use of benefits based on that data in real time.

[0360] The system implementing this invention consists of an application that operates via the user's smartphone and a server system located in the cloud.

[0361] Users record their exercise activity data using an application installed on their smartphone. The application uses fitness tracking APIs (such as Google® Fit or Apple HealthKit) to collect data such as the user's steps, running distance, and calories burned. The smartphone allows users to instantly view their exercise results through its user interface.

[0362] The server is located in a cloud environment (e.g., AWS or Azure) and receives exercise activity data sent by the user. This server analyzes the data using information processing equipment and calculates points based on a specific algorithm. The calculated points are managed by storage equipment and securely stored in a database (e.g., Firebase). The server then provides the user with information about their point balance and available rewards in real time.

[0363] Furthermore, the server uses data processing equipment to collect data related to local physical facilities and community events, and delivers this information to the user's smartphone. This allows users to connect with their local community and expand their options for participating in healthy activities. For example, the server can deliver information about a new local running event, and upon receiving this information, the user can register to participate in the event.

[0364] In the generative AI model, the task is to design a system that analyzes data indicating a user has completed a 5km run and awards points in real time. An example of a prompt might be: "Design an app that calculates points in real time based on exercise data after a user completes a 5km run and displays a list of available local benefits."

[0365] Thus, this invention technically supports the maintenance of a healthy lifestyle through fitness activities and promotes participation in the local community.

[0366] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0367] Step 1:

[0368] The device records the user's exercise activity. Specifically, it uses fitness tracking APIs (e.g., Google Fit, Apple HealthKit) to collect data such as exercise time, distance, and calories burned. This requires the user's fitness information as input, and the exercise data is stored on the device as output.

[0369] Step 2:

[0370] The device sends the collected exercise data to the server. Specifically, it uploads the data to a cloud server (e.g., AWS, Azure) via an internet connection. The device requires exercise data as input, and that data is sent to the server as output.

[0371] Step 3:

[0372] The server analyzes the received motion data. Specifically, it analyzes the data using an information processing device and executes a point calculation algorithm. The input is the motion data sent to the server, and the output is the calculated points.

[0373] Step 4:

[0374] The server records the calculated points and provides feedback to the user. Specifically, it uses a storage device to save the points to a database and then notifies the user of their point balance on their device. The input is the calculated points, and the output is the notification information sent to the user's device.

[0375] Step 5:

[0376] The server collects information on local physical facilities and events. Specifically, it uses data processing equipment to retrieve local activity information from external databases and APIs. The input is external information sources, and the output is local event data.

[0377] Step 6:

[0378] The server provides users with collected local information. Specifically, it notifies users' devices of community events they can participate in and special offers. The input is data on local events, and the output is notifications sent to the user's device.

[0379] Step 7:

[0380] The generating AI model designs a service for a specific situation based on a prompt. Specifically, it generates a service design in response to the prompt, "Design an app that calculates points in real time based on exercise data after a user runs 5 kilometers and displays a list of available local benefits." The input is the prompt, and the output is a proposed service design.

[0381] 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.

[0382] This invention is an integrated system that provides a more appropriate fitness experience by calculating points based on the user's exercise activity data and understanding the user's psychological state using an emotion engine. The specific operation of each component is described below.

[0383] Users first create an account through the application and enter their basic information. After creating an account, they are moved to a dedicated screen to begin recording their exercise activities. This screen is equipped with an emotion engine that recognizes the user's emotions from their facial expressions and voice. The user's emotional data is collected during or after exercise.

[0384] The device receives and temporarily stores this emotional data. In addition, it also sends user-entered exercise activity data (such as type of exercise, duration, and intensity) to the server.

[0385] The server analyzes the received exercise activity data and emotional data. Points are calculated based on the type and level of achievement of the exercise activity, but by using data from the emotional engine, the user's emotions while exercising are also taken into consideration. This information is used to enhance the purpose and motivation of exercise.

[0386] The server considers emotional data, exercise activity data, and the balance of points to suggest the optimal training plan and rewards for the user. For example, if a user is experiencing stress related to exercise, the server will suggest exercises that promote relaxation and appropriate rewards based on emotional data.

[0387] Users continue this cycle by executing the suggested training plan and submitting data again. Furthermore, information on local physical facilities and events is displayed, allowing users to participate in activities tailored to their emotional state. This provides a more personalized approach to maintaining health and enables the achievement of sustainable fitness.

[0388] This system integrates user emotions and exercise data to provide a personalized fitness experience, supporting continued exercise and the realization of a healthy lifestyle.

[0389] The following describes the processing flow.

[0390] Step 1:

[0391] The user launches the application and enters their basic information (name, email address, password, etc.) on the account registration screen.

[0392] Step 2:

[0393] The terminal checks the entered information, and if there are no formatting errors, it sends the information to the server.

[0394] Step 3:

[0395] The server stores the user's information in a database and sends a notification to the user confirming that their account registration is complete.

[0396] Step 4:

[0397] Before exercising, the user activates the emotion recognition function and begins their exercise activity. The emotion engine analyzes their facial expressions and tone of voice during this time, collecting emotional data.

[0398] Step 5:

[0399] The device temporarily stores collected emotional data and exercise activity data entered by the user (type of exercise, duration, and intensity).

[0400] Step 6:

[0401] The device sends emotional data and exercise activity data to the server.

[0402] Step 7:

[0403] The server analyzes the received data and calculates points to award to the user, taking into account not only the type and intensity of exercise but also their emotional state.

[0404] Step 8:

[0405] The server updates the point balance and suggests personalized fitness plans and special rewards to the user.

[0406] Step 9:

[0407] The user reviews the suggestions, selects an exercise plan and rewards, and sends their selections back to the server via their device.

[0408] Step 10:

[0409] The server updates its database based on user selections and incorporates them into future suggestions, continuously providing an optimized fitness experience for each individual user.

[0410] (Example 2)

[0411] 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".

[0412] In modern society, it is important for individual users to maintain their health through exercise in a sustainable manner, but conventional fitness systems do not adequately consider the psychological factors related to exercise activity. Therefore, it is difficult to continuously increase motivation for exercise, resulting in a large number of users being unable to continue exercising. There is a need to provide personalized fitness experiences that take into account the user's psychological state.

[0413] 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.

[0414] In this invention, the server includes information processing means for receiving user exercise activity data and emotional data and calculating points based on this data; storage means for managing the calculated points and providing information on exchangeable rewards that the user can select; information providing means for collecting data related to local exercise facilities and community events and providing that information to the user; and information analysis means equipped with a generation algorithm that analyzes the user's emotional state and makes optimal suggestions for exercise activities. This provides a personalized fitness experience based on the user's psychological state and exercise data, enabling continued exercise and improved motivation, as well as sustainable health maintenance.

[0415] A "user" refers to an individual who uses the system to record and manage their exercise activities.

[0416] "Exercise activity data" refers to information about the type, duration, and intensity of exercise performed by the user.

[0417] "Emotional data" refers to information that indicates a user's psychological state, analyzed from their facial expressions and voice.

[0418] "Points" refer to an evaluation value calculated by taking into account the user's exercise activity and the psychological state associated with it.

[0419] "Information processing means" refers to a device or program that has the function of analyzing exercise activity data and emotional data received from a user and calculating points.

[0420] "Memory means" refers to storage or databases used to manage information about points and rewards that users can choose.

[0421] "Information provision means" refers to a system that delivers information related to local sports facilities and community events to users.

[0422] A "generative algorithm" refers to a computational method for analyzing emotional states and suggesting appropriate exercise activities.

[0423] "Information analysis means" refers to a system that integrates and analyzes user emotional data and exercise activity data, and uses a generation algorithm to propose the optimal fitness plan for the user.

[0424] This invention is a system that provides a personalized fitness experience by comprehensively utilizing the user's exercise activity data and emotional data. Specific forms for implementing this system are described below.

[0425] Users create an account using a dedicated application via their smartphone or wearable device. During account creation, they enter basic information such as their name, age, gender, and fitness level. They then use a dedicated screen within the app to begin exercising. This screen incorporates an emotion engine that collects the user's facial expressions and voice in real time through the smartphone's camera and microphone, generating emotion data.

[0426] The device temporarily stores collected emotional data and user-entered exercise activity data in its storage, and then transmits the data to the server via Bluetooth or an internet connection. This ensures secure and efficient data transfer.

[0427] The server uses a generative AI model to analyze the received data and calculate points based on the user's exercise activity. This model also takes emotional data into account, allowing it to provide an evaluation that reflects the user's psychological state during exercise. The calculated points are stored in a memory system and used to manage information about rewards that the user can choose.

[0428] The server also collects and provides data related to local sports facilities and community events, and suggests activities best suited to the user. Furthermore, it analyzes the user's emotional state and generates an optimal training plan based on those emotions. For example, by using a prompt such as, "Suggest an optimal exercise program for a user who is feeling stressed," the generating AI model will provide appropriate suggestions.

[0429] This allows users to enjoy a personalized fitness experience while achieving a sustainable and healthy lifestyle. The system integrates emotional and physical activity to provide a new level of fitness support.

[0430] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0431] Step 1:

[0432] The user launches the application on their smartphone or wearable device and enters basic information on the account creation screen. The entered basic information (e.g., name, age, gender, fitness level) is sent to the server. The output of this step is profile data containing the user's registered basic information.

[0433] Step 2:

[0434] The user begins exercising and uses a dedicated screen within the app. This screen is equipped with an emotion engine that detects emotions from facial expressions and voice, and the user's emotional data is collected. The input data is acquired through the device's camera and microphone, and data on the emotional state (e.g., stress, joy, relaxation) is generated as output.

[0435] Step 3:

[0436] The device collects exercise activity data (e.g., type of exercise, duration, intensity) through manual user input and temporarily stores it on the device along with emotional data. The data is then transmitted to the server via Bluetooth or Wi-Fi. The output of this step is that the exercise activity data and emotional data have been sent to the server.

[0437] Step 4:

[0438] The server analyzes the received exercise activity data and emotional data using a generating AI model. Based on the input data, the generating AI model processes the data and calculates points that take into account the exercise performance and emotional state. As output, an evaluation score for the user's activity is generated.

[0439] Step 5:

[0440] The server manages the calculated points using a memory system and associates them with available rewards and promotional information. This information is then notified to the user. As output, a list of available rewards for the user is generated and can be displayed within the app.

[0441] Step 6:

[0442] The server uses prompts to generate an AI model that creates a training plan that takes the user's emotional state into account. For example, by inputting the prompt, "Suggest an optimal exercise program for a user who is feeling stressed," the AI ​​model will suggest an appropriate fitness plan. The output of this step is a personalized training plan provided to the user.

[0443] Step 7:

[0444] The user reviews the proposed training plan, selects and performs activities as needed. The results are recorded again on the device and sent to the server in the next processing cycle. User feedback is collected as output and incorporated into the system.

[0445] (Application Example 2)

[0446] 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."

[0447] Traditional fitness systems could provide basic advice and rewards based on users' exercise data, but they were insufficient in providing a fitness experience that took into account the user's emotional state. As a result, they lacked features to provide feedback and motivation that were appropriate to the user's psychological state, making it difficult to provide health promotion support optimized for each individual user.

[0448] 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.

[0449] In this invention, the server includes a central processing unit means that receives user exercise activity data and emotional data and calculates points based on this data; a storage device means that manages the calculated points and provides information on exchangeable rewards that the user can select; an information processing device means that collects data related to local physical facilities and group events and provides that information to the user; and a human support device means that provides feedback based on the user's emotional state and monitors exercise activity. This makes it possible to provide users with a personalized fitness experience, increase their motivation to exercise, and efficiently support the maintenance of their health.

[0450] "User exercise activity data" refers to data that includes information such as the type, duration, and intensity of exercise performed by the user.

[0451] "Emotional data" refers to data that indicates a user's psychological state, and is information obtained through facial expression and voice analysis.

[0452] The term "central processing unit means" refers to a computer device that performs calculations based on received data and calculates motion points.

[0453] "Storage device" refers to a data storage device that manages calculated points and provides reward information to the user.

[0454] An "information processing device" is a computer device that collects local facility and event information and processes it to provide it to users.

[0455] A "human support device" is a device that provides feedback based on the user's emotions and supports their exercise activities.

[0456] A "fitness experience" refers to a series of experiences that a user gains during the process of exercising, including the sensations, results, and increased motivation they experience.

[0457] The system that realizes this invention combines various elements for collecting and analyzing user exercise activity data and emotional data. The specific configuration of the system is described below.

[0458] The server first receives exercise activity data and emotional data from the user. Emotional data is collected using a device with a camera and microphone, which analyzes facial expressions and voice. Image processing software such as OpenCV and TensorFlow is used for this analysis.

[0459] User exercise and emotional data are converted into points by a central processing unit and managed by a memory device. This process considers the type, duration, intensity, and emotional state of the user's exercise activity. These points are then used with a generative AI model to suggest rewards optimized for the user.

[0460] The terminal collects local facility data and event information via an information processing device and provides this information to the user. This data is used to suggest optimal activities based on the user's emotional state.

[0461] For example, if a facial recognition camera detects that a user is experiencing stress during a home fitness session, the system will recommend relaxing music to the user. It also has a feature that notifies users to participate in local yoga events.

[0462] An example of a prompt for a generative AI model would be: "Analyze the user's emotional data during exercise in real time, and generate and present appropriate advice and reward plans."

[0463] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0464] Step 1:

[0465] The user initiates physical activity through the device's built-in camera and microphone. At this stage, the device acquires facial expressions and voice, receiving them as emotional data. This data is analyzed in real time using OpenCV and TensorFlow, and output as numerical information indicating the emotional state.

[0466] Step 2:

[0467] The device receives data on the type, duration, and intensity of exercise activities entered manually or automatically by the user. This data is entered as exercise activity data and sent to the server. This exercise activity data serves as foundational information for evaluating how well the user has achieved their fitness goals.

[0468] Step 3:

[0469] The server integrates and analyzes the emotional data obtained in Step 1 and the exercise activity data obtained in Step 2. Points are calculated, taking into account the emotional state and the degree of exercise achievement. These points serve as the basis for the reward plan offered to the user. A generative AI model is used for the calculation and integration.

[0470] Step 4:

[0471] The server generates a reward plan based on the calculated points and the user's emotions, and stores it in storage. The storage also accesses external resources, including local facility data and event information, to select the most suitable health promotion information for the user.

[0472] Step 5:

[0473] The server provides users with feedback on selected exercise results, reward suggestions, and local activity information. This feedback also includes a customized training plan determined by a generative AI model. The device incorporates specific actions to boost user motivation, such as playing certain music or sending notifications.

[0474] 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.

[0475] 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.

[0476] 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.

[0477] [Third Embodiment]

[0478] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0479] 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.

[0480] 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).

[0481] 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.

[0482] 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.

[0483] 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).

[0484] 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.

[0485] 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.

[0486] 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.

[0487] 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.

[0488] 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.

[0489] 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".

[0490] This invention is an integrated system that allows users to exchange points earned through fitness activities for local facilities and health-related services. The specific operation of each component will be described below.

[0491] When a user uses the system for the first time, they must first create an account. During this process, they enter personal information on their device, which is then sent to the server and securely stored in the database. Once registration is complete, the server sends a confirmation email, and the user can log in to their account.

[0492] After completing their daily exercise, users input their exercise activity data into their device. This data includes, for example, distance, time, and calories burned during activities like walking or running. This data is sent to a server and used for point calculation.

[0493] The server analyzes the received exercise activity data and runs an algorithm to calculate points. The calculated points are added to a database, allowing users to check their point balance. Points vary depending on the type, duration, intensity, and degree of goal achievement of the exercise.

[0494] Once a user's points reach a certain threshold, they can use those points within the system to exchange them for discounts or free services at local facilities, as well as health-related products. These include tickets to affiliated sports facilities, health foods, and fitness wear.

[0495] The device provides users with information on local community sports events and club activities. Users can register for events that interest them and gain opportunities to participate in various activities held in their community. This promotes continued exercise and participation in the local community.

[0496] This system aims to support the maintenance of a healthy lifestyle through fitness activities and strengthen ties with the local community. This will enable users to maintain sustained motivation and contribute to extending healthy life expectancy.

[0497] The following describes the processing flow.

[0498] Step 1:

[0499] The user launches the application and enters the required information (name, age, email address, password, etc.) on the account creation screen.

[0500] Step 2:

[0501] The terminal saves the entered information as temporary data and verifies the data's integrity and input format. If there are no problems, it sends the data to the server.

[0502] Step 3:

[0503] The server stores the received user information in a database and generates a unique user ID for the user. Next, it sends a confirmation email to the user upon completion of registration.

[0504] Step 4:

[0505] The user enters their email address and password on the regular login screen and sends an authentication request to the server.

[0506] Step 5:

[0507] The server compares the registration information in the database with the login information, and if a match is found, redirects the user to the dashboard screen.

[0508] Step 6:

[0509] After completing their daily exercise, users enter and save their exercise activity data (type, time, distance, etc.) on the exercise record screen of their device.

[0510] Step 7:

[0511] The device sends exercise activity data to the server, and the server executes a point calculation algorithm based on the received data.

[0512] Step 8:

[0513] The server updates the user's account with the calculated points and saves the latest point balance to the database.

[0514] Step 9:

[0515] Users can view available rewards and services on the points exchange screen, select their desired options, and submit a points exchange request.

[0516] Step 10:

[0517] The server receives the exchange request, verifies the user's point balance, completes the exchange process, and then transmits the information to the partner.

[0518] Step 11:

[0519] The terminal sends a notification to the user that the point exchange has been completed and displays details of the exchanged items.

[0520] Step 12:

[0521] Users can view events of interest on the local event information screen and, if they wish to participate, press the registration button.

[0522] Step 13:

[0523] The server receives the participation request, provides the participant information to the event organizer, and adds the user to the registration list.

[0524] (Example 1)

[0525] 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."

[0526] In modern lifestyles, lack of exercise and decreased motivation for maintaining health are serious problems. Furthermore, the lack of systems that efficiently support individual fitness activities makes it difficult for users to establish appropriate exercise habits. There is also a need for mechanisms that foster connections with the community and promote social participation.

[0527] 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.

[0528] In this invention, the server includes information processing means for receiving user exercise activity data and calculating points; storage means for managing the calculated points and providing exchangeable reward data; information providing means for collecting and providing information related to local facilities and events; and means equipped with a generation device for generating motivational messages from the user's exercise habits. This enables users to make healthy lifestyles a habit and strengthen their connection with the local community.

[0529] "User exercise activity data" refers to information about the exercise performed by the user, specifically measurable values ​​such as the type of exercise, duration, distance, and calories burned.

[0530] "Information processing means" refers to the functions of a processing device or software that calculates points based on received data and performs motion information analysis.

[0531] "Memory means" refers to a database or memory that holds calculated points and related information and provides data to the user as needed.

[0532] "Information provision means" refers to the function of a device or system that collects and disseminates information about local facilities and events to users and displays information tailored to the user's interests.

[0533] "Means equipped with a generation device" refers to a function or device for analyzing a user's exercise habits and preferences and generating appropriate motivational messages.

[0534] "Exchangeable rewards" refer to products or services offered based on a user's points, and include benefits and goods that users can acquire using their points.

[0535] This invention is a system that allows users to record exercise data and manage their health based on that data. The system consists of a user terminal, a server that processes the information, and services provided through these.

[0536] Users record their daily exercise activities on their devices. Specifically, they use a dedicated application to input activities such as walking, running, and cycling. This application allows users to input data such as distance, time, and calories burned, which is then used as exercise activity data.

[0537] The device sends this exercise data to the server. Communication takes place via an internet connection, and encrypted protocols (e.g., HTTPS) are used for data transmission. The device also periodically receives updates from the server to provide information on local community events and facilities.

[0538] The server analyzes the received exercise data and calculates points using a dedicated algorithm. This process utilizes a generative AI model and includes data analysis and the generation of personalized feedback. The calculated points are stored in a database and managed as the user's accumulated points. Once points reach a certain level, users can exchange them for local services and products.

[0539] For example, if a user jogs a total of 10km in a week, they send this data to the server, which then calculates points for it. For instance, let's say they earn 100 points. The server then generates a prompt message like, "You need 200 more points to get a free fitness pass. Why not go for another run today?" and notifies the user.

[0540] In this way, the system provides users with the motivation to continue exercising and supports their connection to the community and healthy lifestyle.

[0541] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0542] Step 1:

[0543] Users record their exercise activities using their devices.

[0544] Input: Exercise activity data entered by the user into the application (e.g., distance, time, calories burned).

[0545] Specific action: The user enters into the app that their run today was 5km and took 30 minutes.

[0546] Output: The input data is saved to the terminal's temporary memory.

[0547] Step 2:

[0548] The device sends exercise data to the server.

[0549] Input: Exercise activity data stored on the device.

[0550] Specific operation: Data is encrypted using HTTPS and sent to the server.

[0551] Output: The data was successfully received by the server.

[0552] Step 3:

[0553] The server analyzes the exercise data and calculates points.

[0554] Input: Exercise activity data sent to the server.

[0555] Specific operation: A generative AI model is used to analyze exercise activity data, and a point calculation algorithm is applied. For example, 100 points are calculated for a 5km run.

[0556] Output: Calculated points.

[0557] Step 4:

[0558] The server saves the calculated points to the database.

[0559] Input: Calculated points.

[0560] Specific action: The system will save points to the database along with the user ID.

[0561] Output: Points are added to the database, and the user's accumulated points are updated.

[0562] Step 5:

[0563] The server generates prompt messages using a generation AI model.

[0564] Input: User's cumulative points and exercise habit data.

[0565] Specific operation: The generative AI model creates prompt messages such as, "You can get a free fitness pass if you earn 200 more points. Why not go for a run today?"

[0566] Output: The generated prompt message.

[0567] Step 6:

[0568] The device notifies the user of a prompt message.

[0569] Input: The prompt message sent from the server.

[0570] Specific action: Use the notification function to display a prompt message on the app.

[0571] Output: A prompt message is displayed on the user's screen.

[0572] Step 7:

[0573] Users use points to select and exchange rewards.

[0574] Input: The reward selection screen that the user confirms and the number of points that can be exchanged.

[0575] Specific action: The user selects a fitness pass in exchange for 200 points within the app.

[0576] Output: The exchange is complete and the user's point balance has been updated.

[0577] (Application Example 1)

[0578] 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."

[0579] In modern society, it is important for individuals to maintain a healthy lifestyle while staying connected to their community. However, it is not easy to motivate individuals to continue fitness activities or increase opportunities to participate in community events amidst busy daily lives. Furthermore, there is a challenge in that systems for meaningfully utilizing the results gained through fitness activities in real life are not yet adequately developed.

[0580] 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.

[0581] In this invention, the server includes an information processing device that receives user exercise activity data and calculates points based on this data; a storage device that manages the calculated points and provides information on exchangeable rewards that the user can select; a data processing device that collects data related to local physical facilities and social events and provides this information to the user; and an information forming device that analyzes the user's exercise activity data and provides information on available rewards in real time based on that data. This allows the user to gain motivation to continue their fitness activities, promote participation in the local community, and efficiently utilize the points they earn in the real world.

[0582] "Information processing device means" refers to a part of a system that has the function of receiving exercise activity data from a user and calculating points based on that data.

[0583] A "memory device" is a means for managing calculated points and storing and providing information on rewards that users can select.

[0584] "Data processing device" refers to a system that collects data on physical facilities and social events in a region and provides that information to users.

[0585] "Information formation means" refers to a method that analyzes users' exercise activity data and generates and provides information on the use of benefits based on that data in real time.

[0586] The system implementing this invention consists of an application that operates via the user's smartphone and a server system located in the cloud.

[0587] Users record their exercise activity data using an application installed on their smartphone. The application uses fitness tracking APIs (such as Google Fit or Apple HealthKit) to collect data such as the user's steps, running distance, and calories burned. The smartphone allows users to instantly view their exercise results through its user interface.

[0588] The server is located in a cloud environment (e.g., AWS or Azure) and receives exercise activity data sent by the user. This server analyzes the data using information processing equipment and calculates points based on a specific algorithm. The calculated points are managed by storage equipment and securely stored in a database (e.g., Firebase). The server then provides the user with information about their point balance and available rewards in real time.

[0589] Furthermore, the server uses data processing equipment to collect data related to local physical facilities and community events, and delivers this information to the user's smartphone. This allows users to connect with their local community and expand their options for participating in healthy activities. For example, the server can deliver information about a new local running event, and upon receiving this information, the user can register to participate in the event.

[0590] In the generative AI model, the task is to design a system that analyzes data indicating a user has completed a 5km run and awards points in real time. An example of a prompt might be: "Design an app that calculates points in real time based on exercise data after a user completes a 5km run and displays a list of available local benefits."

[0591] Thus, this invention technically supports the maintenance of a healthy lifestyle through fitness activities and promotes participation in the local community.

[0592] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0593] Step 1:

[0594] The device records the user's exercise activity. Specifically, it uses fitness tracking APIs (e.g., Google Fit, Apple HealthKit) to collect data such as exercise time, distance, and calories burned. This requires the user's fitness information as input, and the exercise data is stored on the device as output.

[0595] Step 2:

[0596] The device sends the collected exercise data to the server. Specifically, it uploads the data to a cloud server (e.g., AWS, Azure) via an internet connection. The device requires exercise data as input, and that data is sent to the server as output.

[0597] Step 3:

[0598] The server analyzes the received motion data. Specifically, it analyzes the data using an information processing device and executes a point calculation algorithm. The input is the motion data sent to the server, and the output is the calculated points.

[0599] Step 4:

[0600] The server records the calculated points and provides feedback to the user. Specifically, it uses a storage device to save the points to a database and then notifies the user of their point balance on their device. The input is the calculated points, and the output is the notification information sent to the user's device.

[0601] Step 5:

[0602] The server collects information on local physical facilities and events. Specifically, it uses data processing equipment to retrieve local activity information from external databases and APIs. The input is external information sources, and the output is local event data.

[0603] Step 6:

[0604] The server provides users with collected local information. Specifically, it notifies users' devices of community events they can participate in and special offers. The input is data on local events, and the output is notifications sent to the user's device.

[0605] Step 7:

[0606] The generating AI model designs a service for a specific situation based on a prompt. Specifically, it generates a service design in response to the prompt, "Design an app that calculates points in real time based on exercise data after a user runs 5 kilometers and displays a list of available local benefits." The input is the prompt, and the output is a proposed service design.

[0607] 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.

[0608] This invention is an integrated system that provides a more appropriate fitness experience by calculating points based on the user's exercise activity data and understanding the user's psychological state using an emotion engine. The specific operation of each component is described below.

[0609] Users first create an account through the application and enter their basic information. After creating an account, they are moved to a dedicated screen to begin recording their exercise activities. This screen is equipped with an emotion engine that recognizes the user's emotions from their facial expressions and voice. The user's emotional data is collected during or after exercise.

[0610] The device receives and temporarily stores this emotional data. In addition, it also sends user-entered exercise activity data (such as type of exercise, duration, and intensity) to the server.

[0611] The server analyzes the received exercise activity data and emotional data. Points are calculated based on the type and level of achievement of the exercise activity, but by using data from the emotional engine, the user's emotions while exercising are also taken into consideration. This information is used to enhance the purpose and motivation of exercise.

[0612] The server considers emotional data, exercise activity data, and the balance of points to suggest the optimal training plan and rewards for the user. For example, if a user is experiencing stress related to exercise, the server will suggest exercises that promote relaxation and appropriate rewards based on emotional data.

[0613] Users continue this cycle by executing the suggested training plan and submitting data again. Furthermore, information on local physical facilities and events is displayed, allowing users to participate in activities tailored to their emotional state. This provides a more personalized approach to maintaining health and enables the achievement of sustainable fitness.

[0614] This system integrates user emotions and exercise data to provide a personalized fitness experience, supporting continued exercise and the realization of a healthy lifestyle.

[0615] The following describes the processing flow.

[0616] Step 1:

[0617] The user launches the application and enters their basic information (name, email address, password, etc.) on the account registration screen.

[0618] Step 2:

[0619] The terminal checks the entered information, and if there are no formatting errors, it sends the information to the server.

[0620] Step 3:

[0621] The server stores the user's information in a database and sends a notification to the user confirming that their account registration is complete.

[0622] Step 4:

[0623] Before exercising, the user activates the emotion recognition function and begins their exercise activity. The emotion engine analyzes their facial expressions and tone of voice during this time, collecting emotional data.

[0624] Step 5:

[0625] The device temporarily stores collected emotional data and exercise activity data entered by the user (type of exercise, duration, and intensity).

[0626] Step 6:

[0627] The device sends emotional data and exercise activity data to the server.

[0628] Step 7:

[0629] The server analyzes the received data and calculates points to award to the user, taking into account not only the type and intensity of exercise but also their emotional state.

[0630] Step 8:

[0631] The server updates the point balance and suggests personalized fitness plans and special rewards to the user.

[0632] Step 9:

[0633] The user reviews the suggestions, selects an exercise plan and rewards, and sends their selections back to the server via their device.

[0634] Step 10:

[0635] The server updates its database based on user selections and incorporates them into future suggestions, continuously providing an optimized fitness experience for each individual user.

[0636] (Example 2)

[0637] 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."

[0638] In modern society, it is important for individual users to maintain their health through exercise in a sustainable manner, but conventional fitness systems do not adequately consider the psychological factors related to exercise activity. Therefore, it is difficult to continuously increase motivation for exercise, resulting in a large number of users being unable to continue exercising. There is a need to provide personalized fitness experiences that take into account the user's psychological state.

[0639] 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.

[0640] In this invention, the server includes information processing means for receiving user exercise activity data and emotional data and calculating points based on this data; storage means for managing the calculated points and providing information on exchangeable rewards that the user can select; information providing means for collecting data related to local exercise facilities and community events and providing that information to the user; and information analysis means equipped with a generation algorithm that analyzes the user's emotional state and makes optimal suggestions for exercise activities. This provides a personalized fitness experience based on the user's psychological state and exercise data, enabling continued exercise and improved motivation, as well as sustainable health maintenance.

[0641] A "user" refers to an individual who uses the system to record and manage their exercise activities.

[0642] "Exercise activity data" refers to information about the type, duration, and intensity of exercise performed by the user.

[0643] "Emotional data" refers to information that indicates a user's psychological state, analyzed from their facial expressions and voice.

[0644] "Points" refer to an evaluation value calculated by taking into account the user's exercise activity and the psychological state associated with it.

[0645] "Information processing means" refers to a device or program that has the function of analyzing exercise activity data and emotional data received from a user and calculating points.

[0646] "Memory means" refers to storage or databases used to manage information about points and rewards that users can choose.

[0647] "Information provision means" refers to a system that delivers information related to local sports facilities and community events to users.

[0648] A "generative algorithm" refers to a computational method for analyzing emotional states and suggesting appropriate exercise activities.

[0649] "Information analysis means" refers to a system that integrates and analyzes user emotional data and exercise activity data, and uses a generation algorithm to propose the optimal fitness plan for the user.

[0650] This invention is a system that provides a personalized fitness experience by comprehensively utilizing the user's exercise activity data and emotional data. Specific forms for implementing this system are described below.

[0651] Users create an account using a dedicated application via their smartphone or wearable device. During account creation, they enter basic information such as their name, age, gender, and fitness level. They then use a dedicated screen within the app to begin exercising. This screen incorporates an emotion engine that collects the user's facial expressions and voice in real time through the smartphone's camera and microphone, generating emotion data.

[0652] The device temporarily stores collected emotional data and user-entered exercise activity data in its storage, and then transmits the data to the server via Bluetooth or an internet connection. This ensures secure and efficient data transfer.

[0653] The server uses a generative AI model to analyze the received data and calculate points based on the user's exercise activity. This model also takes emotional data into account, allowing it to provide an evaluation that reflects the user's psychological state during exercise. The calculated points are stored in a memory system and used to manage information about rewards that the user can choose.

[0654] The server also collects and provides data related to local sports facilities and community events, and suggests activities best suited to the user. Furthermore, it analyzes the user's emotional state and generates an optimal training plan based on those emotions. For example, by using a prompt such as, "Suggest an optimal exercise program for a user who is feeling stressed," the generating AI model will provide appropriate suggestions.

[0655] This allows users to enjoy a personalized fitness experience while achieving a sustainable and healthy lifestyle. The system integrates emotional and physical activity to provide a new level of fitness support.

[0656] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0657] Step 1:

[0658] The user launches the application on their smartphone or wearable device and enters basic information on the account creation screen. The entered basic information (e.g., name, age, gender, fitness level) is sent to the server. The output of this step is profile data containing the user's registered basic information.

[0659] Step 2:

[0660] The user begins exercising and uses a dedicated screen within the app. This screen is equipped with an emotion engine that detects emotions from facial expressions and voice, and the user's emotional data is collected. The input data is acquired through the device's camera and microphone, and data on the emotional state (e.g., stress, joy, relaxation) is generated as output.

[0661] Step 3:

[0662] The device collects exercise activity data (e.g., type of exercise, duration, intensity) through manual user input and temporarily stores it on the device along with emotional data. The data is then transmitted to the server via Bluetooth or Wi-Fi. The output of this step is that the exercise activity data and emotional data have been sent to the server.

[0663] Step 4:

[0664] The server analyzes the received exercise activity data and emotional data using a generating AI model. Based on the input data, the generating AI model processes the data and calculates points that take into account the exercise performance and emotional state. As output, an evaluation score for the user's activity is generated.

[0665] Step 5:

[0666] The server manages the calculated points using a memory system and associates them with available rewards and promotional information. This information is then notified to the user. As output, a list of available rewards for the user is generated and can be displayed within the app.

[0667] Step 6:

[0668] The server uses prompts to generate an AI model that creates a training plan that takes the user's emotional state into account. For example, by inputting the prompt, "Suggest an optimal exercise program for a user who is feeling stressed," the AI ​​model will suggest an appropriate fitness plan. The output of this step is a personalized training plan provided to the user.

[0669] Step 7:

[0670] The user reviews the proposed training plan, selects and performs activities as needed. The results are recorded again on the device and sent to the server in the next processing cycle. User feedback is collected as output and incorporated into the system.

[0671] (Application Example 2)

[0672] 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."

[0673] Traditional fitness systems could provide basic advice and rewards based on users' exercise data, but they were insufficient in providing a fitness experience that took into account the user's emotional state. As a result, they lacked features to provide feedback and motivation that were appropriate to the user's psychological state, making it difficult to provide health promotion support optimized for each individual user.

[0674] 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.

[0675] In this invention, the server includes a central processing unit means that receives user exercise activity data and emotional data and calculates points based on this data; a storage device means that manages the calculated points and provides information on exchangeable rewards that the user can select; an information processing device means that collects data related to local physical facilities and group events and provides that information to the user; and a human support device means that provides feedback based on the user's emotional state and monitors exercise activity. This makes it possible to provide users with a personalized fitness experience, increase their motivation to exercise, and efficiently support the maintenance of their health.

[0676] "User exercise activity data" refers to data that includes information such as the type, duration, and intensity of exercise performed by the user.

[0677] "Emotional data" refers to data that indicates a user's psychological state, and is information obtained through facial expression and voice analysis.

[0678] The term "central processing unit means" refers to a computer device that performs calculations based on received data and calculates motion points.

[0679] "Storage device" refers to a data storage device that manages calculated points and provides reward information to the user.

[0680] An "information processing device" is a computer device that collects local facility and event information and processes it to provide it to users.

[0681] A "human support device" is a device that provides feedback based on the user's emotions and supports their exercise activities.

[0682] A "fitness experience" refers to a series of experiences that a user gains during the process of exercising, including the sensations, results, and increased motivation they experience.

[0683] The system that realizes this invention combines various elements for collecting and analyzing user exercise activity data and emotional data. The specific configuration of the system is described below.

[0684] The server first receives exercise activity data and emotional data from the user. Emotional data is collected using a device with a camera and microphone, which analyzes facial expressions and voice. Image processing software such as OpenCV and TensorFlow is used for this analysis.

[0685] User exercise and emotional data are converted into points by a central processing unit and managed by a memory device. This process considers the type, duration, intensity, and emotional state of the user's exercise activity. These points are then used with a generative AI model to suggest rewards optimized for the user.

[0686] The terminal collects local facility data and event information via an information processing device and provides this information to the user. This data is used to suggest optimal activities based on the user's emotional state.

[0687] For example, if a facial recognition camera detects that a user is experiencing stress during a home fitness session, the system will recommend relaxing music to the user. It also has a feature that notifies users to participate in local yoga events.

[0688] An example of a prompt for a generative AI model would be: "Analyze the user's emotional data during exercise in real time, and generate and present appropriate advice and reward plans."

[0689] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0690] Step 1:

[0691] The user initiates physical activity through the device's built-in camera and microphone. At this stage, the device acquires facial expressions and voice, receiving them as emotional data. This data is analyzed in real time using OpenCV and TensorFlow, and output as numerical information indicating the emotional state.

[0692] Step 2:

[0693] The device receives data on the type, duration, and intensity of exercise activities entered manually or automatically by the user. This data is entered as exercise activity data and sent to the server. This exercise activity data serves as foundational information for evaluating how well the user has achieved their fitness goals.

[0694] Step 3:

[0695] The server integrates and analyzes the emotional data obtained in Step 1 and the exercise activity data obtained in Step 2. Points are calculated, taking into account the emotional state and the degree of exercise achievement. These points serve as the basis for the reward plan offered to the user. A generative AI model is used for the calculation and integration.

[0696] Step 4:

[0697] The server generates a reward plan based on the calculated points and the user's emotions, and stores it in storage. The storage also accesses external resources, including local facility data and event information, to select the most suitable health promotion information for the user.

[0698] Step 5:

[0699] The server provides users with feedback on selected exercise results, reward suggestions, and local activity information. This feedback also includes a customized training plan determined by a generative AI model. The device incorporates specific actions to boost user motivation, such as playing certain music or sending notifications.

[0700] 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.

[0701] 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.

[0702] 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.

[0703] [Fourth Embodiment]

[0704] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0705] 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.

[0706] 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).

[0707] 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.

[0708] 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.

[0709] 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).

[0710] 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.

[0711] 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.

[0712] 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.

[0713] 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.

[0714] 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.

[0715] 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.

[0716] 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".

[0717] This invention is an integrated system that allows users to exchange points earned through fitness activities for local facilities and health-related services. The specific operation of each component will be described below.

[0718] When a user uses the system for the first time, they must first create an account. During this process, they enter personal information on their device, which is then sent to the server and securely stored in the database. Once registration is complete, the server sends a confirmation email, and the user can log in to their account.

[0719] After completing their daily exercise, users input their exercise activity data into their device. This data includes, for example, distance, time, and calories burned during activities like walking or running. This data is sent to a server and used for point calculation.

[0720] The server analyzes the received exercise activity data and runs an algorithm to calculate points. The calculated points are added to a database, allowing users to check their point balance. Points vary depending on the type, duration, intensity, and degree of goal achievement of the exercise.

[0721] Once a user's points reach a certain threshold, they can use those points within the system to exchange them for discounts or free services at local facilities, as well as health-related products. These include tickets to affiliated sports facilities, health foods, and fitness wear.

[0722] The device provides users with information on local community sports events and club activities. Users can register for events that interest them and gain opportunities to participate in various activities held in their community. This promotes continued exercise and participation in the local community.

[0723] This system aims to support the maintenance of a healthy lifestyle through fitness activities and strengthen ties with the local community. This will enable users to maintain sustained motivation and contribute to extending healthy life expectancy.

[0724] The following describes the processing flow.

[0725] Step 1:

[0726] The user launches the application and enters the required information (name, age, email address, password, etc.) on the account creation screen.

[0727] Step 2:

[0728] The terminal saves the entered information as temporary data and verifies the data's integrity and input format. If there are no problems, it sends the data to the server.

[0729] Step 3:

[0730] The server stores the received user information in a database and generates a unique user ID for the user. Next, it sends a confirmation email to the user upon completion of registration.

[0731] Step 4:

[0732] The user enters their email address and password on the regular login screen and sends an authentication request to the server.

[0733] Step 5:

[0734] The server compares the registration information in the database with the login information, and if a match is found, redirects the user to the dashboard screen.

[0735] Step 6:

[0736] After completing their daily exercise, users enter and save their exercise activity data (type, time, distance, etc.) on the exercise record screen of their device.

[0737] Step 7:

[0738] The device sends exercise activity data to the server, and the server executes a point calculation algorithm based on the received data.

[0739] Step 8:

[0740] The server updates the user's account with the calculated points and saves the latest point balance to the database.

[0741] Step 9:

[0742] Users can view available rewards and services on the points exchange screen, select their desired options, and submit a points exchange request.

[0743] Step 10:

[0744] The server receives the exchange request, verifies the user's point balance, completes the exchange process, and then transmits the information to the partner.

[0745] Step 11:

[0746] The terminal sends a notification to the user that the point exchange has been completed and displays details of the exchanged items.

[0747] Step 12:

[0748] Users can view events of interest on the local event information screen and, if they wish to participate, press the registration button.

[0749] Step 13:

[0750] The server receives the participation request, provides the participant information to the event organizer, and adds the user to the registration list.

[0751] (Example 1)

[0752] 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".

[0753] In modern lifestyles, lack of exercise and decreased motivation for maintaining health are serious problems. Furthermore, the lack of systems that efficiently support individual fitness activities makes it difficult for users to establish appropriate exercise habits. There is also a need for mechanisms that foster connections with the community and promote social participation.

[0754] 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.

[0755] In this invention, the server includes information processing means for receiving user exercise activity data and calculating points; storage means for managing the calculated points and providing exchangeable reward data; information providing means for collecting and providing information related to local facilities and events; and means equipped with a generation device for generating motivational messages from the user's exercise habits. This enables users to make healthy lifestyles a habit and strengthen their connection with the local community.

[0756] "User exercise activity data" refers to information about the exercise performed by the user, specifically measurable values ​​such as the type of exercise, duration, distance, and calories burned.

[0757] "Information processing means" refers to the functions of a processing device or software that calculates points based on received data and performs motion information analysis.

[0758] "Memory means" refers to a database or memory that holds calculated points and related information and provides data to the user as needed.

[0759] "Information provision means" refers to the function of a device or system that collects and disseminates information about local facilities and events to users and displays information tailored to the user's interests.

[0760] "Means equipped with a generation device" refers to a function or device for analyzing a user's exercise habits and preferences and generating appropriate motivational messages.

[0761] "Exchangeable rewards" refer to products or services offered based on a user's points, and include benefits and goods that users can acquire using their points.

[0762] This invention is a system that allows users to record exercise data and manage their health based on that data. The system consists of a user terminal, a server that processes the information, and services provided through these.

[0763] Users record their daily exercise activities on their devices. Specifically, they use a dedicated application to input activities such as walking, running, and cycling. This application allows users to input data such as distance, time, and calories burned, which is then used as exercise activity data.

[0764] The device sends this exercise data to the server. Communication takes place via an internet connection, and encrypted protocols (e.g., HTTPS) are used for data transmission. The device also periodically receives updates from the server to provide information on local community events and facilities.

[0765] The server analyzes the received exercise data and calculates points using a dedicated algorithm. This process utilizes a generative AI model and includes data analysis and the generation of personalized feedback. The calculated points are stored in a database and managed as the user's accumulated points. Once points reach a certain level, users can exchange them for local services and products.

[0766] For example, if a user jogs a total of 10km in a week, they send this data to the server, which then calculates points for it. For instance, let's say they earn 100 points. The server then generates a prompt message like, "You need 200 more points to get a free fitness pass. Why not go for another run today?" and notifies the user.

[0767] In this way, the system provides users with the motivation to continue exercising and supports their connection to the community and healthy lifestyle.

[0768] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0769] Step 1:

[0770] Users record their exercise activities using their devices.

[0771] Input: Exercise activity data entered by the user into the application (e.g., distance, time, calories burned).

[0772] Specific action: The user enters into the app that their run today was 5km and took 30 minutes.

[0773] Output: The input data is saved to the terminal's temporary memory.

[0774] Step 2:

[0775] The device sends exercise data to the server.

[0776] Input: Exercise activity data stored on the device.

[0777] Specific operation: Data is encrypted using HTTPS and sent to the server.

[0778] Output: The data was successfully received by the server.

[0779] Step 3:

[0780] The server analyzes the exercise data and calculates points.

[0781] Input: Exercise activity data sent to the server.

[0782] Specific operation: A generative AI model is used to analyze exercise activity data, and a point calculation algorithm is applied. For example, 100 points are calculated for a 5km run.

[0783] Output: Calculated points.

[0784] Step 4:

[0785] The server saves the calculated points to the database.

[0786] Input: Calculated points.

[0787] Specific action: The system will save points to the database along with the user ID.

[0788] Output: Points are added to the database, and the user's accumulated points are updated.

[0789] Step 5:

[0790] The server generates prompt messages using a generation AI model.

[0791] Input: User's cumulative points and exercise habit data.

[0792] Specific operation: The generative AI model creates prompt messages such as, "You can get a free fitness pass if you earn 200 more points. Why not go for a run today?"

[0793] Output: The generated prompt message.

[0794] Step 6:

[0795] The device notifies the user of a prompt message.

[0796] Input: The prompt message sent from the server.

[0797] Specific action: Use the notification function to display a prompt message on the app.

[0798] Output: A prompt message is displayed on the user's screen.

[0799] Step 7:

[0800] Users use points to select and exchange rewards.

[0801] Input: The reward selection screen that the user confirms and the number of points that can be exchanged.

[0802] Specific action: The user selects a fitness pass in exchange for 200 points within the app.

[0803] Output: The exchange is complete and the user's point balance has been updated.

[0804] (Application Example 1)

[0805] 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".

[0806] In modern society, it is important for individuals to maintain a healthy lifestyle while staying connected to their community. However, it is not easy to motivate individuals to continue fitness activities or increase opportunities to participate in community events amidst busy daily lives. Furthermore, there is a challenge in that systems for meaningfully utilizing the results gained through fitness activities in real life are not yet adequately developed.

[0807] 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.

[0808] In this invention, the server includes an information processing device that receives user exercise activity data and calculates points based on this data; a storage device that manages the calculated points and provides information on exchangeable rewards that the user can select; a data processing device that collects data related to local physical facilities and social events and provides this information to the user; and an information forming device that analyzes the user's exercise activity data and provides information on available rewards in real time based on that data. This allows the user to gain motivation to continue their fitness activities, promote participation in the local community, and efficiently utilize the points they earn in the real world.

[0809] "Information processing device means" refers to a part of a system that has the function of receiving exercise activity data from a user and calculating points based on that data.

[0810] A "memory device" is a means for managing calculated points and storing and providing information on rewards that users can select.

[0811] "Data processing device" refers to a system that collects data on physical facilities and social events in a region and provides that information to users.

[0812] "Information formation means" refers to a method that analyzes users' exercise activity data and generates and provides information on the use of benefits based on that data in real time.

[0813] The system implementing this invention consists of an application that operates via the user's smartphone and a server system located in the cloud.

[0814] Users record their exercise activity data using an application installed on their smartphone. The application uses fitness tracking APIs (such as Google Fit or Apple HealthKit) to collect data such as the user's steps, running distance, and calories burned. The smartphone allows users to instantly view their exercise results through its user interface.

[0815] The server is located in a cloud environment (e.g., AWS or Azure) and receives exercise activity data sent by the user. This server analyzes the data using information processing equipment and calculates points based on a specific algorithm. The calculated points are managed by storage equipment and securely stored in a database (e.g., Firebase). The server then provides the user with information about their point balance and available rewards in real time.

[0816] Furthermore, the server uses data processing equipment to collect data related to local physical facilities and community events, and delivers this information to the user's smartphone. This allows users to connect with their local community and expand their options for participating in healthy activities. For example, the server can deliver information about a new local running event, and upon receiving this information, the user can register to participate in the event.

[0817] In the generative AI model, the task is to design a system that analyzes data indicating a user has completed a 5km run and awards points in real time. An example of a prompt might be: "Design an app that calculates points in real time based on exercise data after a user completes a 5km run and displays a list of available local benefits."

[0818] Thus, this invention technically supports the maintenance of a healthy lifestyle through fitness activities and promotes participation in the local community.

[0819] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0820] Step 1:

[0821] The device records the user's exercise activity. Specifically, it uses fitness tracking APIs (e.g., Google Fit, Apple HealthKit) to collect data such as exercise time, distance, and calories burned. This requires the user's fitness information as input, and the exercise data is stored on the device as output.

[0822] Step 2:

[0823] The device sends the collected exercise data to the server. Specifically, it uploads the data to a cloud server (e.g., AWS, Azure) via an internet connection. The device requires exercise data as input, and that data is sent to the server as output.

[0824] Step 3:

[0825] The server analyzes the received motion data. Specifically, it analyzes the data using an information processing device and executes a point calculation algorithm. The input is the motion data sent to the server, and the output is the calculated points.

[0826] Step 4:

[0827] The server records the calculated points and provides feedback to the user. Specifically, it uses a storage device to save the points to a database and then notifies the user of their point balance on their device. The input is the calculated points, and the output is the notification information sent to the user's device.

[0828] Step 5:

[0829] The server collects information on local physical facilities and events. Specifically, it uses data processing equipment to retrieve local activity information from external databases and APIs. The input is external information sources, and the output is local event data.

[0830] Step 6:

[0831] The server provides users with collected local information. Specifically, it notifies users' devices of community events they can participate in and special offers. The input is data on local events, and the output is notifications sent to the user's device.

[0832] Step 7:

[0833] The generating AI model designs a service for a specific situation based on a prompt. Specifically, it generates a service design in response to the prompt, "Design an app that calculates points in real time based on exercise data after a user runs 5 kilometers and displays a list of available local benefits." The input is the prompt, and the output is a proposed service design.

[0834] 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.

[0835] This invention is an integrated system that provides a more appropriate fitness experience by calculating points based on the user's exercise activity data and understanding the user's psychological state using an emotion engine. The specific operation of each component is described below.

[0836] Users first create an account through the application and enter their basic information. After creating an account, they are moved to a dedicated screen to begin recording their exercise activities. This screen is equipped with an emotion engine that recognizes the user's emotions from their facial expressions and voice. The user's emotional data is collected during or after exercise.

[0837] The device receives and temporarily stores this emotional data. In addition, it also sends user-entered exercise activity data (such as type of exercise, duration, and intensity) to the server.

[0838] The server analyzes the received exercise activity data and emotional data. Points are calculated based on the type and level of achievement of the exercise activity, but by using data from the emotional engine, the user's emotions while exercising are also taken into consideration. This information is used to enhance the purpose and motivation of exercise.

[0839] The server considers emotional data, exercise activity data, and the balance of points to suggest the optimal training plan and rewards for the user. For example, if a user is experiencing stress related to exercise, the server will suggest exercises that promote relaxation and appropriate rewards based on emotional data.

[0840] Users continue this cycle by executing the suggested training plan and submitting data again. Furthermore, information on local physical facilities and events is displayed, allowing users to participate in activities tailored to their emotional state. This provides a more personalized approach to maintaining health and enables the achievement of sustainable fitness.

[0841] This system integrates user emotions and exercise data to provide a personalized fitness experience, supporting continued exercise and the realization of a healthy lifestyle.

[0842] The following describes the processing flow.

[0843] Step 1:

[0844] The user launches the application and enters their basic information (name, email address, password, etc.) on the account registration screen.

[0845] Step 2:

[0846] The terminal checks the entered information, and if there are no formatting errors, it sends the information to the server.

[0847] Step 3:

[0848] The server stores the user's information in a database and sends a notification to the user confirming that their account registration is complete.

[0849] Step 4:

[0850] Before exercising, the user activates the emotion recognition function and begins their exercise activity. The emotion engine analyzes their facial expressions and tone of voice during this time, collecting emotional data.

[0851] Step 5:

[0852] The device temporarily stores collected emotional data and exercise activity data entered by the user (type of exercise, duration, and intensity).

[0853] Step 6:

[0854] The device sends emotional data and exercise activity data to the server.

[0855] Step 7:

[0856] The server analyzes the received data and calculates points to award to the user, taking into account not only the type and intensity of exercise but also their emotional state.

[0857] Step 8:

[0858] The server updates the point balance and suggests personalized fitness plans and special rewards to the user.

[0859] Step 9:

[0860] The user reviews the suggestions, selects an exercise plan and rewards, and sends their selections back to the server via their device.

[0861] Step 10:

[0862] The server updates its database based on user selections and incorporates them into future suggestions, continuously providing an optimized fitness experience for each individual user.

[0863] (Example 2)

[0864] 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".

[0865] In modern society, it is important for individual users to maintain their health through exercise in a sustainable manner, but conventional fitness systems do not adequately consider the psychological factors related to exercise activity. Therefore, it is difficult to continuously increase motivation for exercise, resulting in a large number of users being unable to continue exercising. There is a need to provide personalized fitness experiences that take into account the user's psychological state.

[0866] 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.

[0867] In this invention, the server includes information processing means for receiving user exercise activity data and emotional data and calculating points based on this data; storage means for managing the calculated points and providing information on exchangeable rewards that the user can select; information providing means for collecting data related to local exercise facilities and community events and providing that information to the user; and information analysis means equipped with a generation algorithm that analyzes the user's emotional state and makes optimal suggestions for exercise activities. This provides a personalized fitness experience based on the user's psychological state and exercise data, enabling continued exercise and improved motivation, as well as sustainable health maintenance.

[0868] A "user" refers to an individual who uses the system to record and manage their exercise activities.

[0869] "Exercise activity data" refers to information about the type, duration, and intensity of exercise performed by the user.

[0870] "Emotional data" refers to information that indicates a user's psychological state, analyzed from their facial expressions and voice.

[0871] "Points" refer to an evaluation value calculated by taking into account the user's exercise activity and the psychological state associated with it.

[0872] "Information processing means" refers to a device or program that has the function of analyzing exercise activity data and emotional data received from a user and calculating points.

[0873] "Memory means" refers to storage or databases used to manage information about points and rewards that users can choose.

[0874] "Information provision means" refers to a system that delivers information related to local sports facilities and community events to users.

[0875] A "generative algorithm" refers to a computational method for analyzing emotional states and suggesting appropriate exercise activities.

[0876] "Information analysis means" refers to a system that integrates and analyzes user emotional data and exercise activity data, and uses a generation algorithm to propose the optimal fitness plan for the user.

[0877] This invention is a system that provides a personalized fitness experience by comprehensively utilizing the user's exercise activity data and emotional data. Specific forms for implementing this system are described below.

[0878] Users create an account using a dedicated application via their smartphone or wearable device. During account creation, they enter basic information such as their name, age, gender, and fitness level. They then use a dedicated screen within the app to begin exercising. This screen incorporates an emotion engine that collects the user's facial expressions and voice in real time through the smartphone's camera and microphone, generating emotion data.

[0879] The device temporarily stores collected emotional data and user-entered exercise activity data in its storage, and then transmits the data to the server via Bluetooth or an internet connection. This ensures secure and efficient data transfer.

[0880] The server uses a generative AI model to analyze the received data and calculate points based on the user's exercise activity. This model also takes emotional data into account, allowing it to provide an evaluation that reflects the user's psychological state during exercise. The calculated points are stored in a memory system and used to manage information about rewards that the user can choose.

[0881] The server also collects and provides data related to local sports facilities and community events, and suggests activities best suited to the user. Furthermore, it analyzes the user's emotional state and generates an optimal training plan based on those emotions. For example, by using a prompt such as, "Suggest an optimal exercise program for a user who is feeling stressed," the generating AI model will provide appropriate suggestions.

[0882] This allows users to enjoy a personalized fitness experience while achieving a sustainable and healthy lifestyle. The system integrates emotional and physical activity to provide a new level of fitness support.

[0883] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0884] Step 1:

[0885] The user launches the application on their smartphone or wearable device and enters basic information on the account creation screen. The entered basic information (e.g., name, age, gender, fitness level) is sent to the server. The output of this step is profile data containing the user's registered basic information.

[0886] Step 2:

[0887] The user begins exercising and uses a dedicated screen within the app. This screen is equipped with an emotion engine that detects emotions from facial expressions and voice, and the user's emotional data is collected. The input data is acquired through the device's camera and microphone, and data on the emotional state (e.g., stress, joy, relaxation) is generated as output.

[0888] Step 3:

[0889] The device collects exercise activity data (e.g., type of exercise, duration, intensity) through manual user input and temporarily stores it on the device along with emotional data. The data is then transmitted to the server via Bluetooth or Wi-Fi. The output of this step is that the exercise activity data and emotional data have been sent to the server.

[0890] Step 4:

[0891] The server analyzes the received exercise activity data and emotional data using a generating AI model. Based on the input data, the generating AI model processes the data and calculates points that take into account the exercise performance and emotional state. As output, an evaluation score for the user's activity is generated.

[0892] Step 5:

[0893] The server manages the calculated points using a memory system and associates them with available rewards and promotional information. This information is then notified to the user. As output, a list of available rewards for the user is generated and can be displayed within the app.

[0894] Step 6:

[0895] The server uses prompts to generate an AI model that creates a training plan that takes the user's emotional state into account. For example, by inputting the prompt, "Suggest an optimal exercise program for a user who is feeling stressed," the AI ​​model will suggest an appropriate fitness plan. The output of this step is a personalized training plan provided to the user.

[0896] Step 7:

[0897] The user reviews the proposed training plan, selects and performs activities as needed. The results are recorded again on the device and sent to the server in the next processing cycle. User feedback is collected as output and incorporated into the system.

[0898] (Application Example 2)

[0899] 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".

[0900] Traditional fitness systems could provide basic advice and rewards based on users' exercise data, but they were insufficient in providing a fitness experience that took into account the user's emotional state. As a result, they lacked features to provide feedback and motivation that were appropriate to the user's psychological state, making it difficult to provide health promotion support optimized for each individual user.

[0901] 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.

[0902] In this invention, the server includes a central processing unit means that receives user exercise activity data and emotional data and calculates points based on this data; a storage device means that manages the calculated points and provides information on exchangeable rewards that the user can select; an information processing device means that collects data related to local physical facilities and group events and provides that information to the user; and a human support device means that provides feedback based on the user's emotional state and monitors exercise activity. This makes it possible to provide users with a personalized fitness experience, increase their motivation to exercise, and efficiently support the maintenance of their health.

[0903] "User exercise activity data" refers to data that includes information such as the type, duration, and intensity of exercise performed by the user.

[0904] "Emotional data" refers to data that indicates a user's psychological state, and is information obtained through facial expression and voice analysis.

[0905] The term "central processing unit means" refers to a computer device that performs calculations based on received data and calculates motion points.

[0906] "Storage device" refers to a data storage device that manages calculated points and provides reward information to the user.

[0907] An "information processing device" is a computer device that collects local facility and event information and processes it to provide it to users.

[0908] A "human support device" is a device that provides feedback based on the user's emotions and supports their exercise activities.

[0909] A "fitness experience" refers to a series of experiences that a user gains during the process of exercising, including the sensations, results, and increased motivation they experience.

[0910] The system that realizes this invention combines various elements for collecting and analyzing user exercise activity data and emotional data. The specific configuration of the system is described below.

[0911] The server first receives exercise activity data and emotional data from the user. Emotional data is collected using a device with a camera and microphone, which analyzes facial expressions and voice. Image processing software such as OpenCV and TensorFlow is used for this analysis.

[0912] User exercise and emotional data are converted into points by a central processing unit and managed by a memory device. This process considers the type, duration, intensity, and emotional state of the user's exercise activity. These points are then used with a generative AI model to suggest rewards optimized for the user.

[0913] The terminal collects local facility data and event information via an information processing device and provides this information to the user. This data is used to suggest optimal activities based on the user's emotional state.

[0914] For example, if a facial recognition camera detects that a user is experiencing stress during a home fitness session, the system will recommend relaxing music to the user. It also has a feature that notifies users to participate in local yoga events.

[0915] An example of a prompt for a generative AI model would be: "Analyze the user's emotional data during exercise in real time, and generate and present appropriate advice and reward plans."

[0916] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0917] Step 1:

[0918] The user initiates physical activity through the device's built-in camera and microphone. At this stage, the device acquires facial expressions and voice, receiving them as emotional data. This data is analyzed in real time using OpenCV and TensorFlow, and output as numerical information indicating the emotional state.

[0919] Step 2:

[0920] The device receives data on the type, duration, and intensity of exercise activities entered manually or automatically by the user. This data is entered as exercise activity data and sent to the server. This exercise activity data serves as foundational information for evaluating how well the user has achieved their fitness goals.

[0921] Step 3:

[0922] The server integrates and analyzes the emotional data obtained in Step 1 and the exercise activity data obtained in Step 2. Points are calculated, taking into account the emotional state and the degree of exercise achievement. These points serve as the basis for the reward plan offered to the user. A generative AI model is used for the calculation and integration.

[0923] Step 4:

[0924] The server generates a reward plan based on the calculated points and the user's emotions, and stores it in storage. The storage also accesses external resources, including local facility data and event information, to select the most suitable health promotion information for the user.

[0925] Step 5:

[0926] The server provides users with feedback on selected exercise results, reward suggestions, and local activity information. This feedback also includes a customized training plan determined by a generative AI model. The device incorporates specific actions to boost user motivation, such as playing certain music or sending notifications.

[0927] 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.

[0928] 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.

[0929] 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.

[0930] 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.

[0931] 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.

[0932] 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.

[0933] 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.

[0934] 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.

[0935] 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."

[0936] 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.

[0937] 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.

[0938] 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.

[0939] 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.

[0940] 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.

[0941] 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.

[0942] 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.

[0943] 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.

[0944] 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.

[0945] 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.

[0946] 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.

[0947] 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 as being incorporated by reference.

[0948] The following is further disclosed regarding the embodiments described above.

[0949] (Claim 1)

[0950] A computer server means that receives user exercise activity data and calculates points based on this data,

[0951] A database means for managing calculated points and providing information on exchangeable rewards that users can select,

[0952] An information processing means that collects data related to local physical facilities and community events and provides that information to users,

[0953] A system that includes this.

[0954] (Claim 2)

[0955] The system according to claim 1, comprising an algorithm that provides a personalized fitness experience according to the user's exercise activity and makes suggestions to the user for maintaining their health.

[0956] (Claim 3)

[0957] The system according to claim 1, further comprising an information provision means that proposes health-related products that can be exchanged for points to users and provides recommendations tailored to the user's interests.

[0958] "Example 1"

[0959] (Claim 1)

[0960] An information processing means that receives user exercise activity data and calculates points based on this data,

[0961] A storage means for managing calculated points and providing data on exchangeable rewards that users can select,

[0962] A means of providing information that collects information related to local physical facilities and community events and provides that information to users,

[0963] A means equipped with a generating device that analyzes the user's exercise habits and generates motivational messages,

[0964] A system that includes this.

[0965] (Claim 2)

[0966] The system according to claim 1, comprising a calculation means for providing a personalized fitness experience based on the user's exercise information, and for making suggestions to the user for maintaining their health.

[0967] (Claim 3)

[0968] The system according to claim 1, further comprising a calculation means for proposing health-related products that can be exchanged for points to a user and for generating recommendation data according to the user's interests.

[0969] "Application Example 1"

[0970] (Claim 1)

[0971] An information processing device means that receives user exercise activity data and calculates points based on this data,

[0972] A storage device that manages calculated points and provides information about exchangeable rewards that the user can select,

[0973] A data processing device that collects data related to local physical facilities and social events and provides that information to users,

[0974] An information generation method that analyzes users' exercise activity data and provides information on available benefits in real time based on that data,

[0975] A system that includes this.

[0976] (Claim 2)

[0977] The system according to claim 1, comprising a calculation method that provides a personalized healthy activity experience according to the user's exercise activity, and which proposes options for maintaining health to the user.

[0978] (Claim 3)

[0979] The system according to claim 1, further comprising means for creating information that proposes health-related products that can be exchanged for points to users and provides advice tailored to the user's interests.

[0980] "Example 2 of combining an emotion engine"

[0981] (Claim 1)

[0982] An information processing means that receives user exercise activity data and emotional data, and calculates points based on this data,

[0983] A storage means for managing calculated points and providing information about exchangeable rewards that the user can select,

[0984] A means of providing information that collects data related to local sports facilities and community events and provides that information to users,

[0985] An information analysis means equipped with a generation algorithm that analyzes the user's emotional state and makes optimal suggestions for exercise activities,

[0986] A system that includes this.

[0987] (Claim 2)

[0988] The system according to claim 1, which provides a personalized fitness experience based on the user's psychological state and exercise data, and makes suggestions for sustainable health maintenance.

[0989] (Claim 3)

[0990] The system according to claim 1, further comprising an information provision means that proposes health-related items that can be exchanged for points based on the user's emotional state, and provides recommendations that correspond to the user's emotions.

[0991] "Application example 2 when combining with an emotional engine"

[0992] (Claim 1)

[0993] A central processing unit means that receives user exercise activity data and emotional data and calculates points based on this data,

[0994] A storage device that manages calculated points and provides information about exchangeable rewards that the user can select,

[0995] Information processing device means for collecting data related to local physical facilities and group events and providing that information to users,

[0996] A human assistance device means that provides feedback based on the user's emotional state and monitors exercise activity,

[0997] A system that includes this.

[0998] (Claim 2)

[0999] The system according to claim 1, which provides a personalized fitness experience in accordance with the user's exercise activity and emotional state, and offers health maintenance suggestions in real time.

[1000] (Claim 3)

[1001] The system according to claim 1, further comprising an information provision device means that proposes health-related products that can be exchanged for points to users and provides recommendations that promote increased motivation during exercise. [Explanation of Symbols]

[1002] 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. An information processing device means that receives user exercise activity data and calculates points based on this data, A storage device that manages calculated points and provides information about exchangeable rewards that the user can select, A data processing device that collects data related to local physical facilities and social events and provides that information to users, An information generation method that analyzes users' exercise activity data and provides information on available benefits in real time based on that data, A system that includes this.

2. The system according to claim 1, comprising a calculation method that provides a personalized healthy activity experience according to the user's exercise activity, and which proposes options for maintaining health to the user.

3. The system according to claim 1, further comprising a means for creating information that proposes health-related products that can be exchanged for points to users and provides advice tailored to the user's interests.

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