System

Abstract

A system is provided.SOLUTION: A system comprising: means for measuring a user's golf swing to obtain a head speed and a trajectory; means for transmitting the obtained information to a cloud sever; means for storing the information in a database in the cloud sever; means for inputting the information to a AI analysis engine; means for generating an advice on improvement of the user's technique by the AI analysis engine; and means for transmitting and displaying the generated advice to the user device based on the AI analysis result.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Currently, there are many technologies available to measure golf swing head speed and trajectory, but there is a lack of services that effectively utilize the detailed result data. Specifically, there are no methods for analyzing data to provide advice useful for improving technique, no means for recommending the best golf clubs and balls for each user, and no systems for effectively displaying advertisements tailored to each user. In this situation, there is a need for a system that can improve golf technique and increase purchase satisfaction by utilizing golf swing data. [Means for solving the problem]

[0005] The present invention provides a system including means for measuring a user's golf swing and acquiring head speed and trajectory data, means for transmitting the acquired data to a cloud server, means for the cloud server to store the data in a database and input the data to an AI analysis engine, means for the AI ​​analysis engine to generate advice for improving the user's technique, means for transmitting the generated advice to a user terminal and displaying it, means for recommending optimal golf clubs and balls to the user based on the results of the AI ​​analysis, and means for analyzing user behavior data and displaying appropriate advertisements on the user terminal.This system enables users to receive appropriate advice based on their measurement data, receive recommendations for optimal golf clubs and balls, and view advertisements of interest.

[0006] "User terminal" refers to an electronic device for acquiring, transmitting, receiving, and displaying golf swing data, and specifically includes smartphones, tablets, dedicated measuring devices, etc.

[0007] "Head speed" is a numerical value that measures the speed at which the head of a golf club moves during a swing, and primarily represents the speed at the moment the club face hits the ball.

[0008] "Trajectory data" refers to information about the flight of a golf ball, and primarily includes data such as the trajectory, angle, speed, and height of the ball.

[0009] "Cloud server" refers to a remote server accessible via the Internet that is a computing resource that stores, processes, and manages data.

[0010] "Database" refers to a system for efficiently storing, retrieving, and managing structured data, especially measurement data and user data.

[0011] An "AI analysis engine" refers to a software system that uses artificial intelligence technology to analyze data and generate results tailored to a specific purpose (in this case, advice on improving golf skills or product recommendations).

[0012] "Advice" refers to advice and recommended actions for improving a user's skills generated by the AI ​​analysis engine.

[0013] "Recommending golf clubs and golf balls" refers to the AI ​​analysis engine selecting and providing golf clubs and golf balls that it determines are best suited to a user based on the user's swing data.

[0014] "Advertising" refers to commercial messages and promotional content selected based on user interest and behavioral data.

[0015] "Measuring device" refers to a device for measuring head speed and trajectory data of a golf swing, and specifically includes a club with a sensor and a dedicated measuring device. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7]FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0017] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0020] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0021] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0022] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0029] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0036] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0037] This invention relates to a system that utilizes a user's golf swing data to help improve their technique, and also recommends optimal golf clubs and balls and displays advertisements. The system is composed of a user terminal, a cloud server, an AI analysis engine, and a database.

[0038] Measuring head speed and trajectory

[0039] User performs a golf swing:

[0040] Users use a dedicated golf swing measuring device at a driving range or at home. This measuring device has the ability to collect head speed and trajectory data in real time. Users install a dedicated app on their smartphone or tablet, which connects to the measuring device.

[0041] The device retrieves the data from the meter:

[0042] The measuring device measures clubhead speed and trajectory data and transmits the data via Bluetooth or Wi-Fi to the user's device (smartphone or tablet), which temporarily stores the data and uploads it to a cloud server when the measurement session is over.

[0043] Data transmission and storage

[0044] The device sends the measurement data to the server:

[0045] The user device transmits the acquired head speed and trajectory data to the cloud server, along with related information such as the user ID and the measurement date and time.

[0046] The server saves the data to the database:

[0047] The server validates the data received, checks for any irregularities, and stores it in a database that serves as the basis for future analysis, recommendations, and advertising.

[0048] AI-powered analysis and advice generation

[0049] The server inputs the data into the AI ​​analytics engine:

[0050] The cloud server inputs the stored data into an AI analysis engine, which uses deep learning and machine learning algorithms to analyze the data and generate advice on how to improve the user's skills.

[0051] AI-generated advice:

[0052] The AI ​​analysis engine uses the user's past and current data to automatically generate advice on how to improve their technique, such as suggesting adjustments to the angle of their swing or recommending specific training methods.

[0053] The server sends the advice to the user's device:

[0054] The generated advice is sent to the user's device via a cloud server, where the user can view the advice via a dedicated app on their smartphone or tablet.

[0055] Golf club and ball recommendations

[0056] The server recommends products based on the results of AI analysis:

[0057] Based on the results of the AI ​​analysis engine, the server refers to a database of known products to recommend the best golf clubs and balls for the user. Product selection is based on swing data, head speed, trajectory data, etc.

[0058] The recommendations are displayed on the user's device:

[0059] The recommended product information is sent to the user's device via a cloud server, and the user can check detailed information about the recommended golf clubs and balls through a dedicated app.

[0060] Advertisement display

[0061] The server analyzes the collected data and selects advertisements:

[0062] The cloud server analyzes the user's swing data and past behavioral data to select appropriate advertisements. This advertisement selection utilizes AI technology, and advertisements are automatically selected based on the user's interests.

[0063] Display ads on user devices:

[0064] The selected advertisements are sent to the user's device via a cloud server, and the user can view them through a dedicated app. For example, if a user is looking for beginner golf clubs, an advertisement based on that information will be displayed.

[0065] As described above, the system of the present invention utilizes the user's golf swing data in a variety of ways to support skill improvement, as well as to provide optimal product recommendations and effective advertising displays.

[0066] The processing flow will be explained below.

[0067] Step 1:

[0068] The user performs a golf swing

[0069] The user uses a dedicated golf swing measurement device at a driving range or at home. The device has the ability to acquire head speed and trajectory data in real time. The user installs a dedicated app on their smartphone or tablet and sets it to measurement mode.

[0070] Step 2:

[0071] The device acquires the data from the measuring device.

[0072] The device (smartphone or tablet) receives data from the measurement device via Bluetooth or Wi-Fi, and temporarily stores the received head speed and trajectory data in the app.

[0073] Step 3:

[0074] The device sends the measurement data to the server

[0075] The device sends the stored measurement data to the cloud server. The data sent includes the user ID, measurement date and time, and measurement details. The data is encrypted and sent securely.

[0076] Step 4:

[0077] The server saves the data to a database

[0078] The cloud server validates the received data to check for any invalid data, and after the data validation is complete, the server stores the data in the appropriate table in the database.

[0079] Step 5:

[0080] The server inputs the data into the AI ​​analysis engine

[0081] The server inputs the saved swing data into the AI ​​analysis engine. The swing data includes head speed, trajectory angle, swing amplitude, etc. The AI ​​then preprocesses the data and begins analysis.

[0082] Step 6:

[0083] AI generates advice

[0084] The AI ​​analysis engine analyzes the data and generates advice for the user to improve their technique. Based on the analysis results, specific advice is generated, including swing improvements and practice methods. Example: "Your accuracy will improve if you swing with your right shoulder angle lowered by 5 degrees."

[0085] Step 7:

[0086] The server sends the advice to the user terminal.

[0087] The server sends the generated advice to the user's device. The user's device receives the advice and notifies the user within a dedicated app. The user can then browse the app to view the detailed advice content.

[0088] Step 8:

[0089] The server recommends products based on the results of AI analysis.

[0090] The server references product information in the database and recommends the best golf clubs and balls for each user based on the results of AI analysis. Products are selected based on the user's swing characteristics and skill level.

[0091] Step 9:

[0092] Recommendation results are displayed on the user's device

[0093] The server sends the recommended product information to the user's device, which displays the recommended golf clubs and balls in the app. The user can view details of the recommended products and is also provided with information such as a purchase link.

[0094] Step 10:

[0095] The server analyzes the collected data and selects advertisements

[0096] The server analyzes past swing data and behavioral data to select advertisements based on the user's interests and behavioral patterns, and uses appropriate AI algorithms to maximize the relevance of the advertisements.

[0097] Step 11:

[0098] Displaying advertisements on user devices

[0099] The server sends the selected advertisements to the user's device, which then displays them in the appropriate location within the app. Users can click on the advertisements they find interesting to access more information or purchase information.

[0100] Example 1

[0101] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0102] Conventional golf swing analysis systems lack a comprehensive system that not only supports users' skill improvement but also recommends optimal golf equipment and displays effective advertisements. As a result, users are forced to use multiple devices and apps simultaneously, lacking a means to efficiently improve their swing technique. Furthermore, there is no established method for providing more accurate advice and recommendations by integrating and analyzing a user's swing data with past behavioral data.

[0103] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0104] In this invention, the server includes: means for measuring a user's golf swing and acquiring head speed and trajectory data; means for transmitting the acquired data to a cloud server via a terminal; means for the cloud server to store the data in a database and verify invalid data; means for the cloud server to input the stored data to an AI analysis engine; means for the AI ​​analysis engine to generate advice for improving the user's technique using a deep learning or machine learning algorithm; means for transmitting the generated advice to the user's terminal via the cloud server and displaying it; means for referring to a known product database based on the AI ​​analysis results to recommend the most suitable golf equipment to the user; and means for analyzing user behavior data, selecting appropriate advertisements, and displaying them on the user's terminal. This allows users to receive comprehensive support for improving their swing technique through a single system, and also enables them to receive highly accurate product recommendations and advertisements based on their individual data.

[0105] "User" refers to a person who uses a golf swing measuring device and receives analysis of swing data and advice on improving technique.

[0106] "Device" refers to an electronic device such as a smartphone or tablet that is used to receive and temporarily store data obtained from a golf swing measurement device and send it to a cloud server.

[0107] "Cloud server" refers to a group of servers accessible via the Internet that provide functions such as data storage, analysis, advice generation, product recommendations, and advertisement selection.

[0108] "Head speed" is an index that indicates how fast the head of a golf club moves during a swing.

[0109] "Trajectory data" refers to data that indicates the angle and trajectory of a golf ball when it is hit.

[0110] "AI analysis engine" refers to a software engine that uses deep learning and machine learning algorithms to analyze a user's swing data and generate advice on improving technique and product recommendations.

[0111] "Database" refers to a data structure for systematically managing user swing data, analysis results, product information, etc. stored on a cloud server.

[0112] "Advice for improving technique" refers to specific suggestions and training methods for improving the user's swing technique.

[0113] "Golf equipment" refers to tools such as golf clubs and balls used by users to play golf.

[0114] "Advertising" refers to promotional content that provides information about appropriate products and services based on user interests and behavioral data.

[0115] "Behavioral data" refers to data that indicates the user's behavioral history, such as the user's past swing data and operation history within the app.

[0116] This invention relates to a system that utilizes golf swing data to support skill improvement, recommends optimal golf equipment, and displays advertisements. This system is composed of a user terminal, a cloud server, an AI analysis engine, and a database.

[0117] First, the user performs a golf swing. The user uses a dedicated golf swing measuring device at home or at a golf driving range. This measuring device has the function of acquiring head speed and trajectory data in real time. The user connects to the measuring device via a dedicated app installed on a smartphone or tablet.

[0118] The device then receives the data from the measuring device. The measuring device measures head speed and trajectory data and transmits the data via Bluetooth or Wi-Fi to the user's device (smartphone or tablet). The device temporarily stores the received data and uploads it to a cloud server when the measurement session is over.

[0119] The cloud server is responsible for transmitting and storing the data. The user device sends the acquired head speed and trajectory data to the cloud server. This data includes relevant information such as the user ID and measurement date and time. The server verifies the received data, checks for any fraudulent data, and stores it in a database. This data serves as the basis for future analysis, recommendations, and advertising displays.

[0120] After the data is saved, the server inputs it into the AI ​​analysis engine. The cloud server passes the saved data to the AI ​​analysis engine, which then analyzes the data using deep learning and machine learning algorithms to generate advice on how to improve the user's skills.

[0121] AI generates advice. The AI ​​analysis engine automatically generates advice to improve a user's technique based on their past and current data. For example, it may suggest adjusting the angle of their swing or recommend a specific training method. The generated advice is sent to the user's device via a cloud server, and the user can view the advice via a dedicated app on their smartphone or tablet.

[0122] Next, the server recommends products based on the AI ​​analysis results. Based on the results of the AI ​​analysis engine, the server refers to a database of known products to recommend the most suitable golf clubs and balls for the user. Products are selected based on swing data, head speed, trajectory data, etc. Recommended product information is sent to the user's device via a cloud server, and the user can check detailed information about the recommended golf clubs and balls through a dedicated app.

[0123] The server also analyzes the collected data and selects advertisements. The cloud server analyzes the user's swing data and past behavioral data to select appropriate advertisements. This advertisement selection utilizes AI technology, which automatically selects advertisements based on the user's interests. The selected advertisements are sent to the user's device via the cloud server, and the user can view them through a dedicated app. For example, if a user is looking for clubs for beginners, an advertisement based on that information will be displayed.

[0124] As a concrete example, the following is an example of a prompt sentence to be input to a generative AI model:

[0125] "Please give me some advice on improving my technique based on my golf swing data."

[0126] "Please analyze my swing data and recommend the right golf clubs for me."

[0127] "Show me ads based on swing data."

[0128] As described above, the system of the present invention utilizes the user's golf swing data in a variety of ways to support skill improvement, as well as to provide optimal product recommendations and effective advertising displays.

[0129] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0130] Step 1:

[0131] The user performs a golf swing

[0132] A user uses a dedicated golf swing measurement device at a driving range or at home. This measurement device has the ability to acquire head speed and trajectory data in real time. The input is the user's swing motion, and the output is the measured head speed and trajectory data. For example, when a user swings with a driver, the head speed is recorded as 40 m / s and the trajectory is 15 degrees.

[0133] Step 2:

[0134] The device acquires the data from the measuring device.

[0135] The measuring device measures head speed and trajectory data and transmits the data to the user's device via Bluetooth or Wi-Fi. The device temporarily stores the received data. The input is the data transmitted from the measuring device, and the output is the temporarily stored swing data. For example, data such as "Session 1: head speed = 40 m / s, trajectory = 15 degrees" is stored on the device.

[0136] Step 3:

[0137] The device sends the measurement data to the server

[0138] The user device sends the saved measurement data to the cloud server. The sent data includes related information such as the user ID, measurement date and time, head speed, and trajectory. The input is the temporarily saved swing data, and the output is the swing data sent to the cloud server. For example, the following data is sent: "User ID: 123, Date and time: 2023-01-01, Head speed: 40 m / s, Trajectory: 15 degrees."

[0139] Step 4:

[0140] The server saves the data to a database

[0141] The server validates the received data and checks for any invalid data. The data is then saved in the database. The input is the swing data sent to the cloud server, and the output is the swing data saved in the database. For example, the following data is saved in the database: "User ID: 123, Date and Time: 2023-01-01, Head Speed: 40 m / s, Trajectory: 15 degrees."

[0142] Step 5:

[0143] The server inputs the data into the AI ​​analysis engine

[0144] The cloud server passes the stored data to the AI ​​analysis engine. The input is the swing data stored in the database, and the output is the data input to the AI ​​analysis engine. This transfer occurs periodically or is triggered when the user requests advice.

[0145] Step 6:

[0146] AI generates advice

[0147] The AI ​​analysis engine analyzes the input data and generates advice to improve the user's technique. The input is the swing data entered into the AI ​​analysis engine, and the output is the generated advice. For example, specific advice such as "Start your swing faster to improve head speed" is generated.

[0148] Step 7:

[0149] The server sends the advice to the user terminal.

[0150] The server sends the generated advice to the user's device. The input is the generated advice, and the output is the advice sent to the user's device. The user receives a notification through a dedicated app and can view the details of the advice. For example, a notification such as "New advice has arrived: Practice starting your swing faster" may be displayed.

[0151] Step 8:

[0152] The server recommends products based on the results of AI analysis.

[0153] The server refers to a known product database to recommend the best golf clubs and balls to the user based on the results of the AI ​​analysis engine. The input is the results of the AI ​​analysis engine, and the output is a list of recommended golf equipment. For example, a recommendation may be made such as, "The best driver for you is the ABC model from XYZ company."

[0154] Step 9:

[0155] Recommendation results are displayed on the user's device

[0156] The server sends the recommended product information to the user's device and displays it to the user through a dedicated app. The input is the recommendation result sent from the server, and the output is the product information displayed on the user's device. For example, a message such as "The recommended screwdriver is the ABC model from XYZ. Click here for details" is displayed.

[0157] Step 10:

[0158] The server analyzes the collected data and selects advertisements

[0159] The server analyzes the user's swing data and past behavioral data to select appropriate advertisements. The input is the user's behavioral data, and the output is the selected advertisement. Using AI technology, advertisements are automatically selected based on the user's interests. For example, an advertisement such as "Here are the golf training products that are perfect for you" is selected.

[0160] Step 11:

[0161] Displaying advertisements on user devices

[0162] The server sends the selected advertisement to the user's device and displays it on a dedicated app. The input is the advertisement sent from the server, and the output is the advertisement displayed on the user's device. Users can tap on an advertisement that interests them to check details or purchase it. For example, an advertisement such as "20% off new golf training equipment! Click here for details" may be displayed.

[0163] (Application example 1)

[0164] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0165] Conventional golf swing assistant systems focus on recommending golf clubs and balls and displaying advertisements when helping users improve their technique, but do not support real-time training method suggestions. This makes it difficult for users to instantly obtain the information they need to improve their swing, making it difficult to achieve effective swing improvement.

[0166] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0167] In this invention, the server includes a means for delivering video content that suggests training methods in real time based on the user's golf swing data, a means for analyzing the user's swing data and behavioral patterns and selecting the most suitable advertisement for each individual user, and a means for transmitting and displaying the generated advice to the user's terminal, thereby enabling the user to instantly watch specific training videos to improve their swing on the spot.

[0168] A "user's golf swing" refers to the process in which a user performs a swing motion using a golf club.

[0169] "Head speed" is the speed achieved by the head portion of a golf club during a swing.

[0170] "Trajectory data" refers to data relating to the flight path, direction, and distance of a golf ball after it is hit.

[0171] A "cloud server" is a remote server for data storage and computation that is accessible from multiple user terminals via the Internet.

[0172] A "database" is a collection of structured data stored within a cloud server.

[0173] An "AI analysis engine" is software that uses machine learning algorithms and deep learning technology to analyze input data and derive results.

[0174] "Advice" refers to specific instructions and suggestions for improving golf swing technique generated by the AI ​​analysis engine.

[0175] A "user terminal" is an electronic device used by a user, such as a smartphone or tablet.

[0176] The "means for recommending golf clubs and balls" is a system that selects and displays the optimal golf clubs and balls based on the user's swing data.

[0177] "Means for displaying advertisements on user terminals" refers to a mechanism for displaying advertisements selected based on user behavior data on user terminals.

[0178] "Video content that suggests training methods in real time" is a service that provides training videos that can be viewed on the spot based on the user's golf swing data.

[0179] This invention is a system that utilizes a user's golf swing data to help improve their technique. This system consists of a user terminal, a cloud server, an AI analysis engine, and a database. Each component and its specific operation are explained below.

[0180] User terminal and measuring instrument

[0181] Users use a dedicated golf swing measuring device at a driving range or at home. This measuring device has the ability to acquire head speed and trajectory data in real time. Users install a dedicated app on their smartphone or tablet and connect it to the measuring device. The measuring device measures head speed and trajectory data and transmits the data to the user's device via Bluetooth or Wi-Fi. The device temporarily stores the received data and uploads it to a cloud server when the measurement session is over.

[0182] Cloud Servers and Databases

[0183] The cloud server receives the clubhead speed and trajectory data sent from the user's device. This data includes relevant information such as the user ID and the measurement date and time. The server verifies the received data, checks for any fraudulent data, and stores it in a database. This data serves as the basis for future analysis, recommendations, and advertisement display.

[0184] AI-powered analysis and advice generation

[0185] The cloud server inputs the stored data into an AI analysis engine. The AI ​​analysis engine uses deep learning and machine learning algorithms to analyze the data and generate advice on how to improve the user's technique. The generated advice is sent to the user's device via the cloud server. The user can view the advice via a dedicated app on their smartphone or tablet. The AI ​​analysis engine also suggests specific training methods for improving technique in real time based on the user's past and current data, and distributes them as video content. For example, if it is analyzed that the user's swing is a little overswing, training videos for correcting the swing will be suggested in real time.

[0186] Golf club and ball recommendations

[0187] Based on the results of the AI ​​analysis engine, the cloud server refers to a database of known products to recommend the most suitable golf clubs and balls for the user. Products are selected based on swing data, head speed, trajectory data, etc. Recommended product information is sent to the user's device via the cloud server, and the user can check detailed information about the recommended golf clubs and balls through a dedicated app.

[0188] Advertisement display

[0189] The cloud server analyzes the user's swing data and past behavioral data to select appropriate advertisements. This selection utilizes AI technology, which automatically selects advertisements based on the user's interests. The selected advertisements are sent to the user's device via the cloud server, and the user can view them through a dedicated app. For example, if a user is looking for clubs for beginners, an advertisement based on that information will be displayed.

[0190] Specific examples

[0191] For example, if the head speed is 120 m / s and the trajectory is high, the AI ​​will compare it with past data and generate advice such as "adjust the way you pull your arms" and display a link to the corresponding training video.An example of a prompt sentence is "Please advise on specific training methods to improve technique based on the user's golf swing data."

[0192] As described above, the present invention utilizes a user's golf swing data in a variety of ways to support skill improvement, as well as to realize optimal product recommendations and effective advertisement displays.

[0193] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0194] Step 1:

[0195] The user makes a golf swing. The user uses a dedicated golf swing measuring device at a golf driving range or at home to measure the swing. The data acquired at this time is head speed and trajectory data. The user installs a dedicated app on a smartphone or tablet and connects to the measuring device via Bluetooth or Wi-Fi.

[0196] Step 2:

[0197] The device receives the data from the measuring device. The device transmits the measured head speed and trajectory data to the user's device via Bluetooth or Wi-Fi. The device temporarily stores the received data and prepares it for the next step.

[0198] Step 3:

[0199] The user device sends the measurement data to the cloud server. The device sends the acquired head speed and trajectory data to the cloud server, and this data includes related information such as the user ID and measurement date and time. Input data: head speed, trajectory data, user ID, measurement date and time. Output data: data sent to the cloud server.

[0200] Step 4:

[0201] The server saves the data in the database. The cloud server verifies the received data and checks for any invalid data before saving it in the database. Input data: Data sent to the cloud server. Output data: Data saved in the database.

[0202] Step 5:

[0203] The server inputs the data into the AI ​​analysis engine. The cloud server inputs the saved data into the AI ​​analysis engine. Input data: Data saved in the database. Output data: Data input into the AI ​​analysis engine.

[0204] Step 6:

[0205] The AI ​​analysis engine generates advice to help users improve their technique. The AI ​​analysis engine uses deep learning and machine learning algorithms to analyze data, identify trends and problems in the user's swing, and generate specific advice to improve their technique. Input data: Data entered into the AI ​​analysis engine. Output data: Generated advice.

[0206] Step 7:

[0207] The server sends the generated advice to the user's device and displays it. The generated advice is sent to the user's device via the cloud server and displayed to the user through a dedicated app. Input data: Generated advice. Output data: Advice displayed on the user's device.

[0208] Step 8:

[0209] The server recommends the most suitable golf clubs and balls to the user based on the results of the AI ​​analysis. Based on the results of the AI ​​analysis engine, the server selects the most suitable golf clubs and balls from the database. Input data: AI analysis results. Output data: Recommended product information.

[0210] Step 9:

[0211] The server analyzes the user's behavioral data and displays appropriate advertisements on the user's device. The cloud server analyzes the user's swing data and past behavioral data, selects advertisements that match the user's interests and concerns, and sends them to the user's device. Input data: User's behavioral data. Output data: Advertisements displayed on the user's device.

[0212] Step 10:

[0213] The server delivers video content that suggests training methods in real time based on the user's golf swing data. The AI ​​analysis engine selects real-time training videos based on the user's swing data and sends them to the user's device. Input data: User's golf swing data. Output data: Video content delivered to the user's device.

[0214] Through the above steps, the present invention utilizes the user's golf swing data in a variety of ways to support skill improvement, as well as to provide optimal product recommendations and effective advertising displays.

[0215] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0216] This invention relates to a system that utilizes a user's golf swing data to recommend optimal golf clubs and balls and display advertisements to help improve skills, combined with an emotion engine that recognizes the user's emotions. The system is composed of a user terminal, a cloud server, an AI analysis engine, an emotion engine, and a database.

[0217] Measuring head speed and trajectory

[0218] User performs a golf swing:

[0219] The user uses a dedicated golf swing measurement device at a driving range or at home. The device has the ability to acquire head speed and trajectory data in real time. The user installs a dedicated app on their smartphone or tablet and sets it to measurement mode.

[0220] The device retrieves the data from the meter:

[0221] The device (smartphone or tablet) receives data from the measurement device via Bluetooth or Wi-Fi, and temporarily stores the received head speed and trajectory data in the app.

[0222] Data transmission and storage

[0223] The device sends the measurement data to the server:

[0224] The device sends the stored measurement data to the cloud server. The data sent includes the user ID, measurement date and time, and measurement details. The data is encrypted and sent securely.

[0225] The server saves the data to the database:

[0226] The cloud server validates the received data to check for any invalid data, and after the data validation is complete, the server stores the data in the appropriate table in the database.

[0227] AI-powered analysis and advice generation

[0228] The server inputs the data into the AI ​​analytics engine:

[0229] The cloud server inputs the saved swing data into the AI ​​analysis engine. The swing data includes head speed, trajectory angle, swing amplitude, etc. The AI ​​then preprocesses the data and begins analysis.

[0230] AI-generated advice:

[0231] The AI ​​analysis engine analyzes the data and generates advice for the user to improve their technique. Based on the analysis results, specific advice is generated, including swing improvements and practice methods. Example: "Your accuracy will improve if you swing with your right shoulder angle lowered by 5 degrees."

[0232] Advice display using emotion engine

[0233] The server sends the generated advice to the user's device:

[0234] The generated advice is sent to the user's device via the cloud server. The user's device receives the advice and notifies the user within a dedicated app. The user can then browse the app to view the detailed advice content.

[0235] The device recognizes the user's emotions:

[0236] The user device is equipped with emotion recognition devices such as a camera and microphone, which analyze facial expressions and tone of voice to recognize the user's emotions. The emotion recognition device acquires the user's emotion data in real time, and the emotion engine analyzes the data.

[0237] Emotion engine adapts advice:

[0238] The emotion engine adapts the generated advice based on the user's emotional data. For example, if it detects that the user is feeling stressed, it will provide gentle advice and suggest ways to relax.

[0239] Golf club and ball recommendations

[0240] The server recommends products based on the results of AI analysis:

[0241] The server references product information in the database and recommends the best golf clubs and balls for each user based on the results of AI analysis. Products are selected based on the user's swing characteristics and skill level. Furthermore, emotional data is used to select the best product for the user's current emotional state.

[0242] Advertisement display

[0243] The server analyzes the user's emotional data and selects advertisements:

[0244] The server analyzes past swing data, behavioral data, and emotional data to select advertisements based on the user's interests, behavioral patterns, and emotional state. For example, if the user is showing positive emotions, advertisements based on the user's emotional state will be displayed, such as advertisements for new products.

[0245] Display ads on user devices:

[0246] The selected advertisements are sent to the user's device via the cloud server, and the user's device displays the advertisements in the appropriate location within the app. Users can click on the advertisements they are interested in to access more information or purchase information.

[0247] As described above, the system of the present invention utilizes the user's golf swing data and emotional data in a multifaceted manner to support skill improvement and provide added value such as optimal product recommendations and effective advertising displays.

[0248] The processing flow will be explained below.

[0249] Step 1:

[0250] The user performs a golf swing

[0251] The user uses a dedicated golf swing measurement device at a driving range or at home. The device has the ability to acquire head speed and trajectory data in real time. The user installs a dedicated app on their smartphone or tablet and sets it to measurement mode.

[0252] Step 2:

[0253] The device acquires the data from the measuring device.

[0254] The device (smartphone or tablet) receives data from the measurement device via Bluetooth or Wi-Fi, and temporarily stores the received head speed and trajectory data in the app.

[0255] Step 3:

[0256] The device sends the measurement data to the server

[0257] The device sends the stored measurement data to the cloud server. The data sent includes the user ID, measurement date and time, and measurement details. The data is encrypted and sent securely.

[0258] Step 4:

[0259] The server saves the data to a database

[0260] The cloud server validates the received data to check for any invalid data, and after the data validation is complete, the server stores the data in the appropriate table in the database.

[0261] Step 5:

[0262] The server inputs the data into the AI ​​analysis engine

[0263] The cloud server inputs the saved swing data into the AI ​​analysis engine. The swing data includes head speed, trajectory angle, swing amplitude, etc. The AI ​​then preprocesses the data and begins analysis.

[0264] Step 6:

[0265] AI generates advice

[0266] The AI ​​analysis engine analyzes the data and generates advice for the user to improve their technique. Based on the analysis results, specific advice is generated, including swing improvements and practice methods. Example: "Your accuracy will improve if you swing with your right shoulder angle lowered by 5 degrees."

[0267] Step 7:

[0268] The server sends the generated advice to the user terminal.

[0269] The generated advice is sent to the user's device via the cloud server. The user's device receives the advice and notifies the user within a dedicated app. The user can then browse the app to view the detailed advice content.

[0270] Step 8:

[0271] The device recognizes the user's emotions

[0272] The user device is equipped with emotion recognition devices such as a camera and microphone, which analyze facial expressions and tone of voice to recognize the user's emotions. The emotion recognition device acquires the user's emotion data in real time, and the emotion engine analyzes the data.

[0273] Step 9:

[0274] Emotion engine adapts advice

[0275] The emotion engine adapts the generated advice based on the user's emotional data. For example, if it detects that the user is feeling stressed, it will provide gentle advice and suggest ways to relax.

[0276] Step 10:

[0277] The server recommends products based on the results of AI analysis.

[0278] The server references product information in the database and recommends the best golf clubs and balls for each user based on the results of AI analysis. Products are selected based on the user's swing characteristics and skill level. Furthermore, emotional data is used to select the best product for the user's current emotional state.

[0279] Step 11:

[0280] Recommendation results are displayed on the user's device

[0281] The server sends the recommended product information to the user's device, which displays the recommended golf clubs and balls in the app. The user can view details of the recommended products and is also provided with information such as a purchase link.

[0282] Step 12:

[0283] The server analyzes the user's emotional data and selects advertisements

[0284] The server analyzes past swing data, behavioral data, and emotional data to select advertisements based on the user's interests, behavioral patterns, and emotional state. For example, if the user is showing positive emotions, advertisements based on the user's emotional state will be displayed, such as advertisements for new products.

[0285] Step 13:

[0286] Displaying advertisements on user devices

[0287] The selected advertisements are sent to the user's device via the cloud server, and the user's device displays the advertisements in the appropriate location within the app. Users can click on the advertisements they are interested in to access more information or purchase information.

[0288] Example 2

[0289] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0290] Conventional golf skill improvement systems analyze users' swing data and provide advice to improve their skills, but they have limitations in providing adaptive advice that takes the user's emotional state into account, recommending sports equipment that is optimal for the user, and displaying personalized advertisements.The present invention aims to improve the user experience and increase the accuracy of skill improvement by introducing multifaceted data analysis that includes user emotional data.

[0291] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0292] In this invention, the server includes a means for measuring the user's golf swing and acquiring head speed and trajectory data, a means for transmitting the acquired data to the server via a network, and a means for the server to store the data in a database and input the data into an AI analysis engine, thereby enabling personalized advice on skill improvement, product recommendations, and advertisement display based on user emotion recognition and adaptation.

[0293] (definition statement)

[0294] "User" refers to an individual who performs a golf swing and uses the system.

[0295] "Server" refers to a computer system that receives swing data and emotion data, stores it in a database, and performs AI analysis.

[0296] "Terminal" refers to a portable electronic device such as a smartphone or tablet operated by a user.

[0297] "Head speed" refers to the speed at which the head of a golf club moves during a swing.

[0298] "Trajectory data" refers to information regarding the flight path of a golf ball.

[0299] "Network" refers to a communication environment that enables data communication between a terminal and a server.

[0300] "Database" refers to an information management system for storing received swing data and emotion data.

[0301] "AI analysis engine" refers to an artificial intelligence system that analyzes stored data and generates specific advice on improving swing technique.

[0302] "Emotion engine" refers to a system that has the ability to analyze a user's emotional data and adapt advice and recommendations.

[0303] "Sports equipment" refers to products such as golf clubs and golf balls that are related to a user's golf swing.

[0304] "Advertising" refers to marketing information provided based on user behavioral and emotional data.

[0305] MODE FOR CARRYING OUT THE INVENTION

[0306] The present invention is a system for measuring a user's golf swing and supporting skill improvement, and is configured as follows: The system is composed of a user terminal, a server, an AI analysis engine, an emotion engine, and a database.

[0307] Acquiring golf swing data

[0308] User performs a golf swing:

[0309] A user uses a dedicated golf swing measurement device (e.g., a general-purpose measurement device) at a golf driving range or at home. The measurement device can obtain golf club head speed and golf ball trajectory data in real time. The user installs a dedicated app on their smartphone or tablet and sets it to measurement mode.

[0310] The device retrieves the data from the meter:

[0311] The device (smartphone or tablet) receives data from the measuring device via Bluetooth or Wi-Fi, and the received data is temporarily stored in the app.

[0312] Data transmission and storage

[0313] The device sends the measurement data to the server:

[0314] The device sends the saved measurement data to a server (e.g., a general-purpose cloud server) via a network. The data sent includes the user ID, measurement date and time, and measurement details, and is encrypted before transmission.

[0315] The server saves the data to the database:

[0316] The server validates the received data to check for any invalid data. After the server checks the integrity of the data, it stores the data in a database (e.g., a general-purpose database management system).

[0317] AI analysis and advice generation

[0318] The server inputs the data into the AI ​​analytics engine:

[0319] The server inputs the saved swing data into an AI analysis engine (e.g., a general-purpose AI platform). The input data includes head speed, trajectory angle, and swing amplitude. The AI ​​analysis engine preprocesses the data and begins analysis.

[0320] AI-generated advice:

[0321] An AI analysis engine analyzes the data and generates advice for users to improve their technique, such as "Lowering the angle of your right shoulder by 5 degrees when swinging will improve your accuracy."

[0322] Advice display using emotion engine

[0323] The server sends the generated advice to the user's device:

[0324] The server sends the generated advice to the user's device via the network. The user's device receives the advice and notifies the user within a dedicated app.

[0325] The device recognizes the user's emotions:

[0326] User devices are equipped with emotion recognition devices (e.g., general-purpose emotion recognition technology) such as cameras and microphones. These devices analyze facial expressions and tone of voice to recognize the user's emotions. The emotion data acquired by the emotion recognition devices in real time is analyzed by the emotion engine.

[0327] Emotion engine adapts advice:

[0328] The emotion engine adapts the generated advice based on the user's emotional data. For example, if the user is feeling stressed, it will provide gentle advice and suggest ways to relax.

[0329] Golf club and ball recommendations

[0330] The server recommends products based on the results of AI analysis:

[0331] The server references product information from the database and recommends the most suitable sports equipment (e.g., golf clubs, golf balls) to the user based on the AI ​​analysis results and emotional data.

[0332] Displaying ads

[0333] The server analyzes the user's emotional data and selects advertisements:

[0334] The server analyzes past swing data, behavioral data, and emotional data to select advertisements based on the user's interests, behavioral patterns, and emotional state. For example, if the user shows positive emotions, advertisements for new products will be displayed.

[0335] Display ads on user devices:

[0336] The server sends the selected advertisements to the user's device via the network, and the user's device displays the advertisements in the appropriate location within the app. Users can click on the advertisements they are interested in to access more information or purchase websites.

[0337] Specific examples and prompts for the generative AI model

[0338] Examples:

[0339] The user measured their swing using a general-purpose measuring device at home and a dedicated smartphone app. The measurement data was sent to a cloud server, and the AI ​​analysis engine generated advice such as, "Swinging with your right shoulder angle lowered by 5 degrees will improve accuracy." The emotion engine also recognized that the user was feeling stressed, and provided gentle advice and suggested ways to reduce stress.

[0340] Prompt for the generative AI model:

[0341] "Please explain the process of your system that analyzes golf swing data and emotion data to provide optimal advice to users. Also, please explain how product recommendations and advertisements are displayed taking user emotions into account."

[0342] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0343] Step 1:

[0344] User performs a golf swing:

[0345] A user uses a dedicated golf swing measurement device at a driving range or at home. The measurement device captures head speed and trajectory data in real time during the swing. The input is the user's swing motion, and the output is head speed and trajectory data. Specifically, the user performs a golf swing, and the measurement device captures the data.

[0346] Step 2:

[0347] The device retrieves the data from the meter:

[0348] The device (smartphone or tablet) receives data from the measuring device via Bluetooth or Wi-Fi. The received data is temporarily stored within the app. The input is head speed and trajectory data, and the output is data stored within the device. Specifically, the device receives data from the measuring device in real time and stores it in dedicated memory within the app.

[0349] Step 3:

[0350] The device sends the measurement data to the server:

[0351] The device sends the stored measurement data to the cloud server. The data sent includes the user ID, measurement date and time, and measurement details, and is encrypted. The input is the measurement data in the device, and the output is the data sent to the server. Specifically, the device transfers the data in a secure format over the network.

[0352] Step 4:

[0353] The server saves the data to the database:

[0354] The server validates the data it receives and checks for any invalid data. It then stores the data in the database. The input is the data sent to the server, and the output is the data stored in the database. Specifically, the server checks the integrity of the data and stores it in the database in the correct format.

[0355] Step 5:

[0356] The server inputs the data into the AI ​​analytics engine:

[0357] The server inputs the saved swing data into the AI ​​analysis engine, which then preprocesses the data and begins analysis. The input is the swing data retrieved from the database, and the output is the data passed to the AI ​​analysis engine. Specifically, the server converts the data into the required format and passes it to the AI ​​analysis engine.

[0358] Step 6:

[0359] AI-generated advice:

[0360] The AI ​​analysis engine analyzes the data and generates advice for the user to improve their technique. Specific advice might be, "Lowering the angle of your right shoulder by 5 degrees while swinging will improve your accuracy." The input is preprocessed swing data, and the output is specific advice. In concrete terms, the AI ​​analysis engine uses a machine learning model to analyze the data and generate advice.

[0361] Step 7:

[0362] The server sends the generated advice to the user's device:

[0363] The advice generated by the server is sent to the user's device via the cloud. The user's device receives the advice and notifies the user within a dedicated app. The input is the advice generated on the server, and the output is the advice displayed on the user's device. Specifically, the server sends data via the network, and the device displays the received data on the user interface.

[0364] Step 8:

[0365] The device recognizes the user's emotions:

[0366] The user device is equipped with emotion recognition devices such as a camera and microphone, which are used to analyze the user's facial expressions and tone of voice to recognize emotions. The input is the user's facial expressions and voice audio data, and the output is recognized emotion data. Specifically, the emotion recognition software collects and analyzes data from the device in real time.

[0367] Step 9:

[0368] Emotion engine adapts advice:

[0369] The emotion engine adapts the advice it generates based on the user's emotion data. For example, if the user is feeling stressed, it will provide gentle advice and suggest ways to relax. The input is emotion data and advice, and the output is the adapted advice. Specifically, the emotion engine analyzes the emotion data and adjusts the content of the advice.

[0370] Step 10:

[0371] The server recommends products based on the results of AI analysis:

[0372] The server references product information in the database and recommends optimal sporting goods based on AI analysis results and emotional data. The input is the AI ​​analysis results and emotional data, and the output is recommended product information. Specifically, the server queries the database and extracts product information that best suits the user's characteristics.

[0373] Step 11:

[0374] The server analyzes the user's emotional data and selects advertisements:

[0375] The server analyzes past swing data, behavioral data, and emotional data, and selects advertisements based on the user's interests, behavioral patterns, and emotional state. The input is past data and emotional data, and the output is selected advertisement information. Specifically, the server selects the most appropriate advertisement from the history database and current emotional data.

[0376] Step 12:

[0377] Display ads on user devices:

[0378] The server sends the selected advertisement to the user's device via the cloud, and the device displays the advertisement in the appropriate location within the app. The input is the advertisement information sent from the server, and the output is the advertisement displayed on the user's device. Specifically, the user can click on the advertisement of interest and access the website for more information or to purchase.

[0379] (Application example 2)

[0380] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0381] Conventional golf training systems provide advice to improve skills based on a user's swing data, but generate uniform advice without considering the user's emotional state, which can reduce the user's motivation and the quality of the experience. Furthermore, when recommending the best golf clubs and balls for a user, the systems do not consider emotional data, making it impossible to provide products that are optimal for the user's current psychological state. As a result, maximizing the user experience is rarely achieved.

[0382] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring user emotion data, inputting the data to a recognition engine for analysis, means for the emotion recognition engine to optimize advice based on the user's emotional state, and means for recommending the most suitable golf clubs and balls to the user based on the user's emotion data and the AI ​​analysis results. This enables personalized advice and product recommendations that take the user's emotional state into consideration.

[0383] The "means for measuring a user's golf swing and acquiring head speed and trajectory data" refers to a device or method for measuring head speed and trajectory data in real time when a user makes a golf swing.

[0384] The "means for transmitting acquired data to a cloud server" refers to a device or method for securely transmitting the measured head speed and trajectory data to a cloud server via the Internet.

[0385] "Means for storing data in a database on a cloud server and inputting the data into an AI analysis engine" refers to a device or method that receives data on the cloud, stores it in a database in an appropriate format, and inputs it into an AI analysis engine.

[0386] The "means by which an AI analysis engine generates advice for improving a user's technique" refers to an artificial intelligence technology that analyzes inputted swing data of a user and generates specific advice for improving technique.

[0387] The "means for transmitting the generated advice to the user terminal and displaying it" refers to a method for transmitting the advice generated by the cloud server to the user terminal and notifying or displaying it on the user terminal.

[0388] "Means for recommending optimal golf clubs and balls to users based on AI analysis results" refers to a method for selecting and recommending golf clubs and balls that are suitable for the user's swing characteristics and skill level based on analyzed data.

[0389] "Means for acquiring user emotion data and inputting it into a recognition engine for analysis" refers to a device or method for acquiring emotion information using a device such as a user's camera or microphone, and inputting it into a recognition engine for analysis.

[0390] "Means for the emotion recognition engine to optimize advice based on the user's emotional state" refers to a method in which the emotion recognition engine optimizes the content based on the user's emotional data, and provides advice in gentle words to a user who is feeling stressed, for example.

[0391] "Means for recommending golf clubs and balls that are optimal for a user based on the user's emotional data and AI analysis results" refers to a method for combining the user's emotional data with the results of AI analysis to recommend golf clubs and balls that are optimal for the user's emotional state.

[0392] "Means for analyzing user behavioral data and emotional data and displaying appropriate advertisements on the user terminal" refers to a method for analyzing a user's past behavioral data and emotional data and displaying highly relevant advertisements on the user terminal.

[0393] An embodiment of the present invention is a system that acquires golf swing data of a user, provides advice for improving technique, and personalizes advice and recommended products using emotion data.

[0394] System configuration

[0395] The system consists of the following components:

[0396] 1. User device: Use a smartphone or tablet. iPhone (iOS 14 or later) or Android (Android 11 or later) is recommended.

[0397] 2. Measurement device: Golf swing measurement device. Use one that can connect via Bluetooth or Wi-Fi.

[0398] 3. Cloud server: Based on AWS (Amazon Web Services), it uses EC2 instances and RDS (relational database service).

[0399] 4. AI analytics engine: Use TensorFlow or PyTorch.

[0400] 5. Emotion Engine: Use the Affectiva SDK or Microsoft Azure's Emotion API.

[0401] Program processing

[0402] When a user performs a golf swing, the measuring device measures head speed and trajectory data and sends it to a smartphone, which then encrypts and transmits the data to a cloud server, where it is received and stored in a database.

[0403] The cloud server inputs the saved swing data into an AI analysis engine and generates advice to improve the user's technique. The advice is then sent to the user's device and displayed on the device.

[0404] The emotion engine uses the camera and microphone installed on the user's device to capture and analyze the user's emotional data in real time. The emotion recognition engine analyzes the user's emotional state and optimizes the advice and recommended products generated by the AI.

[0405] Specific examples

[0406] A user measures their head speed using a swing measuring device at a golf driving range and sends the measurement results to their smartphone. The smartphone app sends the data to a cloud server, where an AI analysis engine generates advice to improve their technique. The smartphone camera recognizes the user's facial expressions, and the emotion engine optimizes the advice based on the analysis results. For example, if the user is feeling stressed, the system will provide gentle advice.

[0407] The system also recommends the best golf clubs and balls for each user based on their emotional data and the results of AI analysis, and analyzes their behavioral and emotional data to display highly relevant advertisements on their devices.

[0408] Prompt Sentence Examples

[0409] A user uses a golf swing monitor to collect head speed and trajectory data. The emotion engine performs real-time emotion recognition and recommends the best golf clubs and balls. Also, display appropriate advertisements based on the user's emotional state.

[0410] In this way, embodiments of a system can be realized that allow for personalized advice and product recommendations that take into account the emotional state of the user.

[0411] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0412] Step 1:

[0413] The user performs a golf swing. The user uses a golf swing measurement device to obtain head speed and trajectory data in real time. The device transmits this data to a smartphone via Bluetooth or Wi-Fi. The input is the user's swing motion, and the output is head speed and trajectory data.

[0414] Step 2:

[0415] The device receives the measurement data and sends it to the cloud server. The smartphone or tablet encrypts the data received from the measuring device and sends it to the cloud server via a secure communication protocol (e.g., HTTPS). The input is the data obtained from the measuring device, and the output is the encrypted data.

[0416] Step 3:

[0417] The server stores the received data in a database. The cloud server validates the received data and checks for any invalid data. It then converts it into an appropriate format and stores it in a database (e.g., AWS RDS). The input is encrypted measurement data, and the output is the data stored in the database.

[0418] Step 4:

[0419] The server inputs the data into an AI analysis engine and generates advice for improving technique. The cloud server inputs the saved swing data into an AI analysis engine (e.g., TensorFlow) for analysis. The input is the swing data saved in the database, and the output is the analysis results and advice.

[0420] Step 5:

[0421] The server sends the generated advice to the user's device and displays it. The server also sends the generated advice to the user's device and notifies them within a dedicated app. The input is the advice from the AI ​​analysis engine, and the output is the advice displayed to the user.

[0422] Step 6:

[0423] The device acquires the user's emotional data and sends it to the emotion engine. The smartphone's camera and microphone are used to capture the user's facial expressions and voice in real time. The data is sent to the emotion engine for analysis. The input is the emotional data acquired by the camera and microphone, and the output is the analyzed emotional state.

[0424] Step 7:

[0425] The emotion recognition engine optimizes advice based on the user's emotional state. Based on the analysis results, the emotion engine adapts the advice generated by the AI ​​analysis engine to the user's emotional state. The input is the analysis results based on emotional data, and the output is optimized advice.

[0426] Step 8:

[0427] The server recommends the most suitable golf clubs and balls based on the user's emotional data and the results of AI analysis. The cloud server analyzes the emotional data and the results of AI analysis and recommends the most suitable golf clubs and balls to the user. The input is the emotional data and the results of AI analysis, and the output is the recommended product.

[0428] Step 9:

[0429] The server analyzes the user's behavioral and emotional data and displays appropriate advertisements on the user's device. The cloud server analyzes past behavioral and emotional data and displays advertisements based on the user's interests and emotional state. The input is the user's behavioral and emotional data, and the output is the advertisement to be displayed.

[0430] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0431] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0432] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0433] [Second embodiment]

[0434] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0435] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0436] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0437] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0438] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0439] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0440] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0441] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0442] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0443] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0444] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0445] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0446] This invention relates to a system that utilizes a user's golf swing data to help improve their technique, and also recommends optimal golf clubs and balls and displays advertisements. The system is composed of a user terminal, a cloud server, an AI analysis engine, and a database.

[0447] Measuring head speed and trajectory

[0448] User performs a golf swing:

[0449] Users use a dedicated golf swing measuring device at a driving range or at home. This measuring device has the ability to collect head speed and trajectory data in real time. Users install a dedicated app on their smartphone or tablet, which connects to the measuring device.

[0450] The device retrieves the data from the meter:

[0451] The measuring device measures clubhead speed and trajectory data and transmits the data via Bluetooth or Wi-Fi to the user's device (smartphone or tablet), which temporarily stores the data and uploads it to a cloud server when the measurement session is over.

[0452] Data transmission and storage

[0453] The device sends the measurement data to the server:

[0454] The user device transmits the acquired head speed and trajectory data to the cloud server, along with related information such as the user ID and the measurement date and time.

[0455] The server saves the data to the database:

[0456] The server validates the data received, checks for any irregularities, and stores it in a database that serves as the basis for future analysis, recommendations, and advertising.

[0457] AI-powered analysis and advice generation

[0458] The server inputs the data into the AI ​​analytics engine:

[0459] The cloud server inputs the stored data into an AI analysis engine, which uses deep learning and machine learning algorithms to analyze the data and generate advice on how to improve the user's skills.

[0460] AI-generated advice:

[0461] The AI ​​analysis engine uses the user's past and current data to automatically generate advice on how to improve their technique, such as suggesting adjustments to the angle of their swing or recommending specific training methods.

[0462] The server sends the advice to the user's device:

[0463] The generated advice is sent to the user's device via a cloud server, where the user can view the advice via a dedicated app on their smartphone or tablet.

[0464] Golf club and ball recommendations

[0465] The server recommends products based on the results of AI analysis:

[0466] Based on the results of the AI ​​analysis engine, the server refers to a database of known products to recommend the best golf clubs and balls for the user. Product selection is based on swing data, head speed, trajectory data, etc.

[0467] The recommendations are displayed on the user's device:

[0468] The recommended product information is sent to the user's device via a cloud server, and the user can check detailed information about the recommended golf clubs and balls through a dedicated app.

[0469] Advertisement display

[0470] The server analyzes the collected data and selects advertisements:

[0471] The cloud server analyzes the user's swing data and past behavioral data to select appropriate advertisements. This advertisement selection utilizes AI technology, and advertisements are automatically selected based on the user's interests.

[0472] Display ads on user devices:

[0473] The selected advertisements are sent to the user's device via a cloud server, and the user can view them through a dedicated app. For example, if a user is looking for beginner golf clubs, an advertisement based on that information will be displayed.

[0474] As described above, the system of the present invention utilizes the user's golf swing data in a variety of ways to support skill improvement, as well as to provide optimal product recommendations and effective advertising displays.

[0475] The processing flow will be explained below.

[0476] Step 1:

[0477] The user performs a golf swing

[0478] The user uses a dedicated golf swing measurement device at a driving range or at home. The device has the ability to acquire head speed and trajectory data in real time. The user installs a dedicated app on their smartphone or tablet and sets it to measurement mode.

[0479] Step 2:

[0480] The device acquires the data from the measuring device.

[0481] The device (smartphone or tablet) receives data from the measurement device via Bluetooth or Wi-Fi, and temporarily stores the received head speed and trajectory data in the app.

[0482] Step 3:

[0483] The device sends the measurement data to the server

[0484] The device sends the stored measurement data to the cloud server. The data sent includes the user ID, measurement date and time, and measurement details. The data is encrypted and sent securely.

[0485] Step 4:

[0486] The server saves the data to a database

[0487] The cloud server validates the received data to check for any invalid data, and after the data validation is complete, the server stores the data in the appropriate table in the database.

[0488] Step 5:

[0489] The server inputs the data into the AI ​​analysis engine

[0490] The server inputs the saved swing data into the AI ​​analysis engine. The swing data includes head speed, trajectory angle, swing amplitude, etc. The AI ​​then preprocesses the data and begins analysis.

[0491] Step 6:

[0492] AI generates advice

[0493] The AI ​​analysis engine analyzes the data and generates advice for the user to improve their technique. Based on the analysis results, specific advice is generated, including swing improvements and practice methods. Example: "Your accuracy will improve if you swing with your right shoulder angle lowered by 5 degrees."

[0494] Step 7:

[0495] The server sends the advice to the user terminal.

[0496] The server sends the generated advice to the user's device. The user's device receives the advice and notifies the user within a dedicated app. The user can then browse the app to view the detailed advice content.

[0497] Step 8:

[0498] The server recommends products based on the results of AI analysis.

[0499] The server references product information in the database and recommends the best golf clubs and balls for each user based on the results of AI analysis. Products are selected based on the user's swing characteristics and skill level.

[0500] Step 9:

[0501] Recommendation results are displayed on the user's device

[0502] The server sends the recommended product information to the user's device, which displays the recommended golf clubs and balls in the app. The user can view details of the recommended products and is also provided with information such as a purchase link.

[0503] Step 10:

[0504] The server analyzes the collected data and selects advertisements

[0505] The server analyzes past swing data and behavioral data to select advertisements based on the user's interests and behavioral patterns, and uses appropriate AI algorithms to maximize the relevance of the advertisements.

[0506] Step 11:

[0507] Displaying advertisements on user devices

[0508] The server sends the selected advertisements to the user's device, which then displays them in the appropriate location within the app. Users can click on the advertisements they find interesting to access more information or purchase information.

[0509] Example 1

[0510] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0511] Conventional golf swing analysis systems lack a comprehensive system that not only supports users' skill improvement but also recommends optimal golf equipment and displays effective advertisements. As a result, users are forced to use multiple devices and apps simultaneously, lacking a means to efficiently improve their swing technique. Furthermore, there is no established method for providing more accurate advice and recommendations by integrating and analyzing a user's swing data with past behavioral data.

[0512] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0513] In this invention, the server includes: means for measuring a user's golf swing and acquiring head speed and trajectory data; means for transmitting the acquired data to a cloud server via a terminal; means for the cloud server to store the data in a database and verify invalid data; means for the cloud server to input the stored data to an AI analysis engine; means for the AI ​​analysis engine to generate advice for improving the user's technique using a deep learning or machine learning algorithm; means for transmitting the generated advice to the user's terminal via the cloud server and displaying it; means for referring to a known product database based on the AI ​​analysis results to recommend the most suitable golf equipment to the user; and means for analyzing user behavior data, selecting appropriate advertisements, and displaying them on the user's terminal. This allows users to receive comprehensive support for improving their swing technique through a single system, and also enables them to receive highly accurate product recommendations and advertisements based on their individual data.

[0514] "User" refers to a person who uses a golf swing measuring device and receives analysis of swing data and advice on improving technique.

[0515] "Device" refers to an electronic device such as a smartphone or tablet that is used to receive and temporarily store data obtained from a golf swing measurement device and send it to a cloud server.

[0516] "Cloud server" refers to a group of servers accessible via the Internet that provide functions such as data storage, analysis, advice generation, product recommendations, and advertisement selection.

[0517] "Head speed" is an index that indicates how fast the head of a golf club moves during a swing.

[0518] "Trajectory data" refers to data that indicates the angle and trajectory of a golf ball when it is hit.

[0519] "AI analysis engine" refers to a software engine that uses deep learning and machine learning algorithms to analyze a user's swing data and generate advice on improving technique and product recommendations.

[0520] "Database" refers to a data structure for systematically managing user swing data, analysis results, product information, etc. stored on a cloud server.

[0521] "Advice for improving technique" refers to specific suggestions and training methods for improving the user's swing technique.

[0522] "Golf equipment" refers to tools such as golf clubs and balls used by users to play golf.

[0523] "Advertising" refers to promotional content that provides information about appropriate products and services based on user interests and behavioral data.

[0524] "Behavioral data" refers to data that indicates the user's behavioral history, such as the user's past swing data and operation history within the app.

[0525] This invention relates to a system that utilizes golf swing data to support skill improvement, recommends optimal golf equipment, and displays advertisements. This system is composed of a user terminal, a cloud server, an AI analysis engine, and a database.

[0526] First, the user performs a golf swing. The user uses a dedicated golf swing measuring device at home or at a golf driving range. This measuring device has the function of acquiring head speed and trajectory data in real time. The user connects to the measuring device via a dedicated app installed on a smartphone or tablet.

[0527] The device then receives the data from the measuring device. The measuring device measures head speed and trajectory data and transmits the data via Bluetooth or Wi-Fi to the user's device (smartphone or tablet). The device temporarily stores the received data and uploads it to a cloud server when the measurement session is over.

[0528] The cloud server is responsible for transmitting and storing the data. The user device sends the acquired head speed and trajectory data to the cloud server. This data includes relevant information such as the user ID and measurement date and time. The server verifies the received data, checks for any fraudulent data, and stores it in a database. This data serves as the basis for future analysis, recommendations, and advertising displays.

[0529] After the data is saved, the server inputs it into the AI ​​analysis engine. The cloud server passes the saved data to the AI ​​analysis engine, which then analyzes the data using deep learning and machine learning algorithms to generate advice on how to improve the user's skills.

[0530] AI generates advice. The AI ​​analysis engine automatically generates advice to improve a user's technique based on their past and current data. For example, it may suggest adjusting the angle of their swing or recommend a specific training method. The generated advice is sent to the user's device via a cloud server, and the user can view the advice via a dedicated app on their smartphone or tablet.

[0531] Next, the server recommends products based on the AI ​​analysis results. Based on the results of the AI ​​analysis engine, the server refers to a database of known products to recommend the most suitable golf clubs and balls for the user. Products are selected based on swing data, head speed, trajectory data, etc. Recommended product information is sent to the user's device via a cloud server, and the user can check detailed information about the recommended golf clubs and balls through a dedicated app.

[0532] The server also analyzes the collected data and selects advertisements. The cloud server analyzes the user's swing data and past behavioral data to select appropriate advertisements. This advertisement selection utilizes AI technology, which automatically selects advertisements based on the user's interests. The selected advertisements are sent to the user's device via the cloud server, and the user can view them through a dedicated app. For example, if a user is looking for clubs for beginners, an advertisement based on that information will be displayed.

[0533] As a concrete example, the following is an example of a prompt sentence to be input to a generative AI model:

[0534] "Please give me some advice on improving my technique based on my golf swing data."

[0535] "Please analyze my swing data and recommend the right golf clubs for me."

[0536] "Show me ads based on swing data."

[0537] As described above, the system of the present invention utilizes the user's golf swing data in a variety of ways to support skill improvement, as well as to provide optimal product recommendations and effective advertising displays.

[0538] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0539] Step 1:

[0540] The user performs a golf swing

[0541] A user uses a dedicated golf swing measurement device at a driving range or at home. This measurement device has the ability to acquire head speed and trajectory data in real time. The input is the user's swing motion, and the output is the measured head speed and trajectory data. For example, when a user swings with a driver, the head speed is recorded as 40 m / s and the trajectory is 15 degrees.

[0542] Step 2:

[0543] The device acquires the data from the measuring device.

[0544] The measuring device measures head speed and trajectory data and transmits the data to the user's device via Bluetooth or Wi-Fi. The device temporarily stores the received data. The input is the data transmitted from the measuring device, and the output is the temporarily stored swing data. For example, data such as "Session 1: head speed = 40 m / s, trajectory = 15 degrees" is stored on the device.

[0545] Step 3:

[0546] The device sends the measurement data to the server

[0547] The user device sends the saved measurement data to the cloud server. The sent data includes related information such as the user ID, measurement date and time, head speed, and trajectory. The input is the temporarily saved swing data, and the output is the swing data sent to the cloud server. For example, the following data is sent: "User ID: 123, Date and time: 2023-01-01, Head speed: 40 m / s, Trajectory: 15 degrees."

[0548] Step 4:

[0549] The server saves the data to a database

[0550] The server validates the received data and checks for any invalid data. The data is then saved in the database. The input is the swing data sent to the cloud server, and the output is the swing data saved in the database. For example, the following data is saved in the database: "User ID: 123, Date and Time: 2023-01-01, Head Speed: 40 m / s, Trajectory: 15 degrees."

[0551] Step 5:

[0552] The server inputs the data into the AI ​​analysis engine

[0553] The cloud server passes the stored data to the AI ​​analysis engine. The input is the swing data stored in the database, and the output is the data input to the AI ​​analysis engine. This transfer occurs periodically or is triggered when the user requests advice.

[0554] Step 6:

[0555] AI generates advice

[0556] The AI ​​analysis engine analyzes the input data and generates advice to improve the user's technique. The input is the swing data entered into the AI ​​analysis engine, and the output is the generated advice. For example, specific advice such as "Start your swing faster to improve head speed" is generated.

[0557] Step 7:

[0558] The server sends the advice to the user terminal.

[0559] The server sends the generated advice to the user's device. The input is the generated advice, and the output is the advice sent to the user's device. The user receives a notification through a dedicated app and can view the details of the advice. For example, a notification such as "New advice has arrived: Practice starting your swing faster" may be displayed.

[0560] Step 8:

[0561] The server recommends products based on the results of AI analysis.

[0562] The server refers to a known product database to recommend the best golf clubs and balls to the user based on the results of the AI ​​analysis engine. The input is the results of the AI ​​analysis engine, and the output is a list of recommended golf equipment. For example, a recommendation may be made such as, "The best driver for you is the ABC model from XYZ company."

[0563] Step 9:

[0564] Recommendation results are displayed on the user's device

[0565] The server sends the recommended product information to the user's device and displays it to the user through a dedicated app. The input is the recommendation result sent from the server, and the output is the product information displayed on the user's device. For example, a message such as "The recommended screwdriver is the ABC model from XYZ. Click here for details" is displayed.

[0566] Step 10:

[0567] The server analyzes the collected data and selects advertisements

[0568] The server analyzes the user's swing data and past behavioral data to select appropriate advertisements. The input is the user's behavioral data, and the output is the selected advertisement. Using AI technology, advertisements are automatically selected based on the user's interests. For example, an advertisement such as "Here are the golf training products that are perfect for you" is selected.

[0569] Step 11:

[0570] Displaying advertisements on user devices

[0571] The server sends the selected advertisement to the user's device and displays it on a dedicated app. The input is the advertisement sent from the server, and the output is the advertisement displayed on the user's device. Users can tap on an advertisement that interests them to check details or purchase it. For example, an advertisement such as "20% off new golf training equipment! Click here for details" may be displayed.

[0572] (Application example 1)

[0573] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0574] Conventional golf swing assistant systems focus on recommending golf clubs and balls and displaying advertisements when helping users improve their technique, but do not support real-time training method suggestions. This makes it difficult for users to instantly obtain the information they need to improve their swing, making it difficult to achieve effective swing improvement.

[0575] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0576] In this invention, the server includes a means for delivering video content that suggests training methods in real time based on the user's golf swing data, a means for analyzing the user's swing data and behavioral patterns and selecting the most suitable advertisement for each individual user, and a means for transmitting and displaying the generated advice to the user's terminal, thereby enabling the user to instantly watch specific training videos to improve their swing on the spot.

[0577] A "user's golf swing" refers to the process in which a user performs a swing motion using a golf club.

[0578] "Head speed" is the speed achieved by the head portion of a golf club during a swing.

[0579] "Trajectory data" refers to data relating to the flight path, direction, and distance of a golf ball after it is hit.

[0580] A "cloud server" is a remote server for data storage and computation that is accessible from multiple user terminals via the Internet.

[0581] A "database" is a collection of structured data stored within a cloud server.

[0582] An "AI analysis engine" is software that uses machine learning algorithms and deep learning technology to analyze input data and derive results.

[0583] "Advice" refers to specific instructions and suggestions for improving golf swing technique generated by the AI ​​analysis engine.

[0584] A "user terminal" is an electronic device used by a user, such as a smartphone or tablet.

[0585] The "means for recommending golf clubs and balls" is a system that selects and displays the optimal golf clubs and balls based on the user's swing data.

[0586] "Means for displaying advertisements on user terminals" refers to a mechanism for displaying advertisements selected based on user behavior data on user terminals.

[0587] "Video content that suggests training methods in real time" is a service that provides training videos that can be viewed on the spot based on the user's golf swing data.

[0588] This invention is a system that utilizes a user's golf swing data to help improve their technique. This system consists of a user terminal, a cloud server, an AI analysis engine, and a database. Each component and its specific operation are explained below.

[0589] User terminal and measuring instrument

[0590] Users use a dedicated golf swing measuring device at a driving range or at home. This measuring device has the ability to acquire head speed and trajectory data in real time. Users install a dedicated app on their smartphone or tablet and connect it to the measuring device. The measuring device measures head speed and trajectory data and transmits the data to the user's device via Bluetooth or Wi-Fi. The device temporarily stores the received data and uploads it to a cloud server when the measurement session is over.

[0591] Cloud Servers and Databases

[0592] The cloud server receives the clubhead speed and trajectory data sent from the user's device. This data includes relevant information such as the user ID and the measurement date and time. The server verifies the received data, checks for any fraudulent data, and stores it in a database. This data serves as the basis for future analysis, recommendations, and advertisement display.

[0593] AI-powered analysis and advice generation

[0594] The cloud server inputs the stored data into an AI analysis engine. The AI ​​analysis engine uses deep learning and machine learning algorithms to analyze the data and generate advice on how to improve the user's technique. The generated advice is sent to the user's device via the cloud server. The user can view the advice via a dedicated app on their smartphone or tablet. The AI ​​analysis engine also suggests specific training methods for improving technique in real time based on the user's past and current data, and distributes them as video content. For example, if it is analyzed that the user's swing is a little overswing, training videos for correcting the swing will be suggested in real time.

[0595] Golf club and ball recommendations

[0596] Based on the results of the AI ​​analysis engine, the cloud server refers to a database of known products to recommend the most suitable golf clubs and balls for the user. Products are selected based on swing data, head speed, trajectory data, etc. Recommended product information is sent to the user's device via the cloud server, and the user can check detailed information about the recommended golf clubs and balls through a dedicated app.

[0597] Advertisement display

[0598] The cloud server analyzes the user's swing data and past behavioral data to select appropriate advertisements. This selection utilizes AI technology, which automatically selects advertisements based on the user's interests. The selected advertisements are sent to the user's device via the cloud server, and the user can view them through a dedicated app. For example, if a user is looking for clubs for beginners, an advertisement based on that information will be displayed.

[0599] Specific examples

[0600] For example, if the head speed is 120 m / s and the trajectory is high, the AI ​​will compare it with past data and generate advice such as "adjust the way you pull your arms" and display a link to the corresponding training video.An example of a prompt sentence is "Please advise on specific training methods to improve technique based on the user's golf swing data."

[0601] As described above, the present invention utilizes a user's golf swing data in a variety of ways to support skill improvement, as well as to realize optimal product recommendations and effective advertisement displays.

[0602] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0603] Step 1:

[0604] The user makes a golf swing. The user uses a dedicated golf swing measuring device at a golf driving range or at home to measure the swing. The data acquired at this time is head speed and trajectory data. The user installs a dedicated app on a smartphone or tablet and connects to the measuring device via Bluetooth or Wi-Fi.

[0605] Step 2:

[0606] The device receives the data from the measuring device. The device transmits the measured head speed and trajectory data to the user's device via Bluetooth or Wi-Fi. The device temporarily stores the received data and prepares it for the next step.

[0607] Step 3:

[0608] The user device sends the measurement data to the cloud server. The device sends the acquired head speed and trajectory data to the cloud server, and this data includes related information such as the user ID and measurement date and time. Input data: head speed, trajectory data, user ID, measurement date and time. Output data: data sent to the cloud server.

[0609] Step 4:

[0610] The server saves the data in the database. The cloud server verifies the received data and checks for any invalid data before saving it in the database. Input data: Data sent to the cloud server. Output data: Data saved in the database.

[0611] Step 5:

[0612] The server inputs the data into the AI ​​analysis engine. The cloud server inputs the saved data into the AI ​​analysis engine. Input data: Data saved in the database. Output data: Data input into the AI ​​analysis engine.

[0613] Step 6:

[0614] The AI ​​analysis engine generates advice to help users improve their technique. The AI ​​analysis engine uses deep learning and machine learning algorithms to analyze data, identify trends and problems in the user's swing, and generate specific advice to improve their technique. Input data: Data entered into the AI ​​analysis engine. Output data: Generated advice.

[0615] Step 7:

[0616] The server sends the generated advice to the user's device and displays it. The generated advice is sent to the user's device via the cloud server and displayed to the user through a dedicated app. Input data: Generated advice. Output data: Advice displayed on the user's device.

[0617] Step 8:

[0618] The server recommends the most suitable golf clubs and balls to the user based on the results of the AI ​​analysis. Based on the results of the AI ​​analysis engine, the server selects the most suitable golf clubs and balls from the database. Input data: AI analysis results. Output data: Recommended product information.

[0619] Step 9:

[0620] The server analyzes the user's behavioral data and displays appropriate advertisements on the user's device. The cloud server analyzes the user's swing data and past behavioral data, selects advertisements that match the user's interests and concerns, and sends them to the user's device. Input data: User's behavioral data. Output data: Advertisements displayed on the user's device.

[0621] Step 10:

[0622] The server delivers video content that suggests training methods in real time based on the user's golf swing data. The AI ​​analysis engine selects real-time training videos based on the user's swing data and sends them to the user's device. Input data: User's golf swing data. Output data: Video content delivered to the user's device.

[0623] Through the above steps, the present invention utilizes the user's golf swing data in a variety of ways to support skill improvement, as well as to provide optimal product recommendations and effective advertising displays.

[0624] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0625] This invention relates to a system that utilizes a user's golf swing data to recommend optimal golf clubs and balls and display advertisements to help improve skills, combined with an emotion engine that recognizes the user's emotions. The system is composed of a user terminal, a cloud server, an AI analysis engine, an emotion engine, and a database.

[0626] Measuring head speed and trajectory

[0627] User performs a golf swing:

[0628] The user uses a dedicated golf swing measurement device at a driving range or at home. The device has the ability to acquire head speed and trajectory data in real time. The user installs a dedicated app on their smartphone or tablet and sets it to measurement mode.

[0629] The device retrieves the data from the meter:

[0630] The device (smartphone or tablet) receives data from the measurement device via Bluetooth or Wi-Fi, and temporarily stores the received head speed and trajectory data in the app.

[0631] Data transmission and storage

[0632] The device sends the measurement data to the server:

[0633] The device sends the stored measurement data to the cloud server. The data sent includes the user ID, measurement date and time, and measurement details. The data is encrypted and sent securely.

[0634] The server saves the data to the database:

[0635] The cloud server validates the received data to check for any invalid data, and after the data validation is complete, the server stores the data in the appropriate table in the database.

[0636] AI-powered analysis and advice generation

[0637] The server inputs the data into the AI ​​analytics engine:

[0638] The cloud server inputs the saved swing data into the AI ​​analysis engine. The swing data includes head speed, trajectory angle, swing amplitude, etc. The AI ​​then preprocesses the data and begins analysis.

[0639] AI-generated advice:

[0640] The AI ​​analysis engine analyzes the data and generates advice for the user to improve their technique. Based on the analysis results, specific advice is generated, including swing improvements and practice methods. Example: "Your accuracy will improve if you swing with your right shoulder angle lowered by 5 degrees."

[0641] Advice display using emotion engine

[0642] The server sends the generated advice to the user's device:

[0643] The generated advice is sent to the user's device via the cloud server. The user's device receives the advice and notifies the user within a dedicated app. The user can then browse the app to view the detailed advice content.

[0644] The device recognizes the user's emotions:

[0645] The user device is equipped with emotion recognition devices such as a camera and microphone, which analyze facial expressions and tone of voice to recognize the user's emotions. The emotion recognition device acquires the user's emotion data in real time, and the emotion engine analyzes the data.

[0646] Emotion engine adapts advice:

[0647] The emotion engine adapts the generated advice based on the user's emotional data. For example, if it detects that the user is feeling stressed, it will provide gentle advice and suggest ways to relax.

[0648] Golf club and ball recommendations

[0649] The server recommends products based on the results of AI analysis:

[0650] The server references product information in the database and recommends the best golf clubs and balls for each user based on the results of AI analysis. Products are selected based on the user's swing characteristics and skill level. Furthermore, emotional data is used to select the best product for the user's current emotional state.

[0651] Advertisement display

[0652] The server analyzes the user's emotional data and selects advertisements:

[0653] The server analyzes past swing data, behavioral data, and emotional data to select advertisements based on the user's interests, behavioral patterns, and emotional state. For example, if the user is showing positive emotions, advertisements based on the user's emotional state will be displayed, such as advertisements for new products.

[0654] Display ads on user devices:

[0655] The selected advertisements are sent to the user's device via the cloud server, and the user's device displays the advertisements in the appropriate location within the app. Users can click on the advertisements they are interested in to access more information or purchase information.

[0656] As described above, the system of the present invention utilizes the user's golf swing data and emotional data in a multifaceted manner to support skill improvement and provide added value such as optimal product recommendations and effective advertising displays.

[0657] The processing flow will be explained below.

[0658] Step 1:

[0659] The user performs a golf swing

[0660] The user uses a dedicated golf swing measurement device at a driving range or at home. The device has the ability to acquire head speed and trajectory data in real time. The user installs a dedicated app on their smartphone or tablet and sets it to measurement mode.

[0661] Step 2:

[0662] The device acquires the data from the measuring device.

[0663] The device (smartphone or tablet) receives data from the measurement device via Bluetooth or Wi-Fi, and temporarily stores the received head speed and trajectory data in the app.

[0664] Step 3:

[0665] The device sends the measurement data to the server

[0666] The device sends the stored measurement data to the cloud server. The data sent includes the user ID, measurement date and time, and measurement details. The data is encrypted and sent securely.

[0667] Step 4:

[0668] The server saves the data to a database

[0669] The cloud server validates the received data to check for any invalid data, and after the data validation is complete, the server stores the data in the appropriate table in the database.

[0670] Step 5:

[0671] The server inputs the data into the AI ​​analysis engine

[0672] The cloud server inputs the saved swing data into the AI ​​analysis engine. The swing data includes head speed, trajectory angle, swing amplitude, etc. The AI ​​then preprocesses the data and begins analysis.

[0673] Step 6:

[0674] AI generates advice

[0675] The AI ​​analysis engine analyzes the data and generates advice for the user to improve their technique. Based on the analysis results, specific advice is generated, including swing improvements and practice methods. Example: "Your accuracy will improve if you swing with your right shoulder angle lowered by 5 degrees."

[0676] Step 7:

[0677] The server sends the generated advice to the user terminal.

[0678] The generated advice is sent to the user's device via the cloud server. The user's device receives the advice and notifies the user within a dedicated app. The user can then browse the app to view the detailed advice content.

[0679] Step 8:

[0680] The device recognizes the user's emotions

[0681] The user device is equipped with emotion recognition devices such as a camera and microphone, which analyze facial expressions and tone of voice to recognize the user's emotions. The emotion recognition device acquires the user's emotion data in real time, and the emotion engine analyzes the data.

[0682] Step 9:

[0683] Emotion engine adapts advice

[0684] The emotion engine adapts the generated advice based on the user's emotional data. For example, if it detects that the user is feeling stressed, it will provide gentle advice and suggest ways to relax.

[0685] Step 10:

[0686] The server recommends products based on the results of AI analysis.

[0687] The server references product information in the database and recommends the best golf clubs and balls for each user based on the results of AI analysis. Products are selected based on the user's swing characteristics and skill level. Furthermore, emotional data is used to select the best product for the user's current emotional state.

[0688] Step 11:

[0689] Recommendation results are displayed on the user's device

[0690] The server sends the recommended product information to the user's device, which displays the recommended golf clubs and balls in the app. The user can view details of the recommended products and is also provided with information such as a purchase link.

[0691] Step 12:

[0692] The server analyzes the user's emotional data and selects advertisements

[0693] The server analyzes past swing data, behavioral data, and emotional data to select advertisements based on the user's interests, behavioral patterns, and emotional state. For example, if the user is showing positive emotions, advertisements based on the user's emotional state will be displayed, such as advertisements for new products.

[0694] Step 13:

[0695] Displaying advertisements on user devices

[0696] The selected advertisements are sent to the user's device via the cloud server, and the user's device displays the advertisements in the appropriate location within the app. Users can click on the advertisements they are interested in to access more information or purchase information.

[0697] Example 2

[0698] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0699] Conventional golf skill improvement systems analyze users' swing data and provide advice to improve their skills, but they have limitations in providing adaptive advice that takes the user's emotional state into account, recommending sports equipment that is optimal for the user, and displaying personalized advertisements.The present invention aims to improve the user experience and increase the accuracy of skill improvement by introducing multifaceted data analysis that includes user emotional data.

[0700] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0701] In this invention, the server includes a means for measuring the user's golf swing and acquiring head speed and trajectory data, a means for transmitting the acquired data to the server via a network, and a means for the server to store the data in a database and input the data into an AI analysis engine, thereby enabling personalized advice on skill improvement, product recommendations, and advertisement display based on user emotion recognition and adaptation.

[0702] (definition statement)

[0703] "User" refers to an individual who performs a golf swing and uses the system.

[0704] "Server" refers to a computer system that receives swing data and emotion data, stores it in a database, and performs AI analysis.

[0705] "Terminal" refers to a portable electronic device such as a smartphone or tablet operated by a user.

[0706] "Head speed" refers to the speed at which the head of a golf club moves during a swing.

[0707] "Trajectory data" refers to information regarding the flight path of a golf ball.

[0708] "Network" refers to a communication environment that enables data communication between a terminal and a server.

[0709] "Database" refers to an information management system for storing received swing data and emotion data.

[0710] "AI analysis engine" refers to an artificial intelligence system that analyzes stored data and generates specific advice on improving swing technique.

[0711] "Emotion engine" refers to a system that has the ability to analyze a user's emotional data and adapt advice and recommendations.

[0712] "Sports equipment" refers to products such as golf clubs and golf balls that are related to a user's golf swing.

[0713] "Advertising" refers to marketing information provided based on user behavioral and emotional data.

[0714] MODE FOR CARRYING OUT THE INVENTION

[0715] The present invention is a system for measuring a user's golf swing and supporting skill improvement, and is configured as follows: The system is composed of a user terminal, a server, an AI analysis engine, an emotion engine, and a database.

[0716] Acquiring golf swing data

[0717] User performs a golf swing:

[0718] A user uses a dedicated golf swing measurement device (e.g., a general-purpose measurement device) at a golf driving range or at home. The measurement device can obtain golf club head speed and golf ball trajectory data in real time. The user installs a dedicated app on their smartphone or tablet and sets it to measurement mode.

[0719] The device retrieves the data from the meter:

[0720] The device (smartphone or tablet) receives data from the measuring device via Bluetooth or Wi-Fi, and the received data is temporarily stored in the app.

[0721] Data transmission and storage

[0722] The device sends the measurement data to the server:

[0723] The device sends the saved measurement data to a server (e.g., a general-purpose cloud server) via a network. The data sent includes the user ID, measurement date and time, and measurement details, and is encrypted before transmission.

[0724] The server saves the data to the database:

[0725] The server validates the received data to check for any invalid data. After the server checks the integrity of the data, it stores the data in a database (e.g., a general-purpose database management system).

[0726] AI analysis and advice generation

[0727] The server inputs the data into the AI ​​analytics engine:

[0728] The server inputs the saved swing data into an AI analysis engine (e.g., a general-purpose AI platform). The input data includes head speed, trajectory angle, and swing amplitude. The AI ​​analysis engine preprocesses the data and begins analysis.

[0729] AI-generated advice:

[0730] An AI analysis engine analyzes the data and generates advice for users to improve their technique, such as "Lowering the angle of your right shoulder by 5 degrees when swinging will improve your accuracy."

[0731] Advice display using emotion engine

[0732] The server sends the generated advice to the user's device:

[0733] The server sends the generated advice to the user's device via the network. The user's device receives the advice and notifies the user within a dedicated app.

[0734] The device recognizes the user's emotions:

[0735] User devices are equipped with emotion recognition devices (e.g., general-purpose emotion recognition technology) such as cameras and microphones. These devices analyze facial expressions and tone of voice to recognize the user's emotions. The emotion data acquired by the emotion recognition devices in real time is analyzed by the emotion engine.

[0736] Emotion engine adapts advice:

[0737] The emotion engine adapts the generated advice based on the user's emotional data. For example, if the user is feeling stressed, it will provide gentle advice and suggest ways to relax.

[0738] Golf club and ball recommendations

[0739] The server recommends products based on the results of AI analysis:

[0740] The server references product information from the database and recommends the most suitable sports equipment (e.g., golf clubs, golf balls) to the user based on the AI ​​analysis results and emotional data.

[0741] Displaying ads

[0742] The server analyzes the user's emotional data and selects advertisements:

[0743] The server analyzes past swing data, behavioral data, and emotional data to select advertisements based on the user's interests, behavioral patterns, and emotional state. For example, if the user shows positive emotions, advertisements for new products will be displayed.

[0744] Display ads on user devices:

[0745] The server sends the selected advertisements to the user's device via the network, and the user's device displays the advertisements in the appropriate location within the app. Users can click on the advertisements they are interested in to access more information or purchase websites.

[0746] Specific examples and prompts for the generative AI model

[0747] Examples:

[0748] The user measured their swing using a general-purpose measuring device at home and a dedicated smartphone app. The measurement data was sent to a cloud server, and the AI ​​analysis engine generated advice such as, "Swinging with your right shoulder angle lowered by 5 degrees will improve accuracy." The emotion engine also recognized that the user was feeling stressed, and provided gentle advice and suggested ways to reduce stress.

[0749] Prompt for the generative AI model:

[0750] "Please explain the process of your system that analyzes golf swing data and emotion data to provide optimal advice to users. Also, please explain how product recommendations and advertisements are displayed taking user emotions into account."

[0751] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0752] Step 1:

[0753] User performs a golf swing:

[0754] A user uses a dedicated golf swing measurement device at a driving range or at home. The measurement device captures head speed and trajectory data in real time during the swing. The input is the user's swing motion, and the output is head speed and trajectory data. Specifically, the user performs a golf swing, and the measurement device captures the data.

[0755] Step 2:

[0756] The device retrieves the data from the meter:

[0757] The device (smartphone or tablet) receives data from the measuring device via Bluetooth or Wi-Fi. The received data is temporarily stored within the app. The input is head speed and trajectory data, and the output is data stored within the device. Specifically, the device receives data from the measuring device in real time and stores it in dedicated memory within the app.

[0758] Step 3:

[0759] The device sends the measurement data to the server:

[0760] The device sends the stored measurement data to the cloud server. The data sent includes the user ID, measurement date and time, and measurement details, and is encrypted. The input is the measurement data in the device, and the output is the data sent to the server. Specifically, the device transfers the data in a secure format over the network.

[0761] Step 4:

[0762] The server saves the data to the database:

[0763] The server validates the data it receives and checks for any invalid data. It then stores the data in the database. The input is the data sent to the server, and the output is the data stored in the database. Specifically, the server checks the integrity of the data and stores it in the database in the correct format.

[0764] Step 5:

[0765] The server inputs the data into the AI ​​analytics engine:

[0766] The server inputs the saved swing data into the AI ​​analysis engine, which then preprocesses the data and begins analysis. The input is the swing data retrieved from the database, and the output is the data passed to the AI ​​analysis engine. Specifically, the server converts the data into the required format and passes it to the AI ​​analysis engine.

[0767] Step 6:

[0768] AI-generated advice:

[0769] The AI ​​analysis engine analyzes the data and generates advice for the user to improve their technique. Specific advice might be, "Lowering the angle of your right shoulder by 5 degrees while swinging will improve your accuracy." The input is preprocessed swing data, and the output is specific advice. In concrete terms, the AI ​​analysis engine uses a machine learning model to analyze the data and generate advice.

[0770] Step 7:

[0771] The server sends the generated advice to the user's device:

[0772] The advice generated by the server is sent to the user's device via the cloud. The user's device receives the advice and notifies the user within a dedicated app. The input is the advice generated on the server, and the output is the advice displayed on the user's device. Specifically, the server sends data via the network, and the device displays the received data on the user interface.

[0773] Step 8:

[0774] The device recognizes the user's emotions:

[0775] The user device is equipped with emotion recognition devices such as a camera and microphone, which are used to analyze the user's facial expressions and tone of voice to recognize emotions. The input is the user's facial expressions and voice audio data, and the output is recognized emotion data. Specifically, the emotion recognition software collects and analyzes data from the device in real time.

[0776] Step 9:

[0777] Emotion engine adapts advice:

[0778] The emotion engine adapts the advice it generates based on the user's emotion data. For example, if the user is feeling stressed, it will provide gentle advice and suggest ways to relax. The input is emotion data and advice, and the output is the adapted advice. Specifically, the emotion engine analyzes the emotion data and adjusts the content of the advice.

[0779] Step 10:

[0780] The server recommends products based on the results of AI analysis:

[0781] The server references product information in the database and recommends optimal sporting goods based on AI analysis results and emotional data. The input is the AI ​​analysis results and emotional data, and the output is recommended product information. Specifically, the server queries the database and extracts product information that best suits the user's characteristics.

[0782] Step 11:

[0783] The server analyzes the user's emotional data and selects advertisements:

[0784] The server analyzes past swing data, behavioral data, and emotional data, and selects advertisements based on the user's interests, behavioral patterns, and emotional state. The input is past data and emotional data, and the output is selected advertisement information. Specifically, the server selects the most appropriate advertisement from the history database and current emotional data.

[0785] Step 12:

[0786] Display ads on user devices:

[0787] The server sends the selected advertisement to the user's device via the cloud, and the device displays the advertisement in the appropriate location within the app. The input is the advertisement information sent from the server, and the output is the advertisement displayed on the user's device. Specifically, the user can click on the advertisement of interest and access the website for more information or to purchase.

[0788] (Application example 2)

[0789] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0790] Conventional golf training systems provide advice to improve skills based on a user's swing data, but generate uniform advice without considering the user's emotional state, which can reduce the user's motivation and the quality of the experience. Furthermore, when recommending the best golf clubs and balls for a user, the systems do not consider emotional data, making it impossible to provide products that are optimal for the user's current psychological state. As a result, maximizing the user experience is rarely achieved.

[0791] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring user emotion data, inputting the data to a recognition engine for analysis, means for the emotion recognition engine to optimize advice based on the user's emotional state, and means for recommending the most suitable golf clubs and balls to the user based on the user's emotion data and the AI ​​analysis results. This enables personalized advice and product recommendations that take the user's emotional state into consideration.

[0792] The "means for measuring a user's golf swing and acquiring head speed and trajectory data" refers to a device or method for measuring head speed and trajectory data in real time when a user makes a golf swing.

[0793] The "means for transmitting acquired data to a cloud server" refers to a device or method for securely transmitting the measured head speed and trajectory data to a cloud server via the Internet.

[0794] "Means for storing data in a database on a cloud server and inputting the data into an AI analysis engine" refers to a device or method that receives data on the cloud, stores it in a database in an appropriate format, and inputs it into an AI analysis engine.

[0795] The "means by which an AI analysis engine generates advice for improving a user's technique" refers to an artificial intelligence technology that analyzes inputted swing data of a user and generates specific advice for improving technique.

[0796] The "means for transmitting the generated advice to the user terminal and displaying it" refers to a method for transmitting the advice generated by the cloud server to the user terminal and notifying or displaying it on the user terminal.

[0797] "Means for recommending optimal golf clubs and balls to users based on AI analysis results" refers to a method for selecting and recommending golf clubs and balls that are suitable for the user's swing characteristics and skill level based on analyzed data.

[0798] "Means for acquiring user emotion data and inputting it into a recognition engine for analysis" refers to a device or method for acquiring emotion information using a device such as a user's camera or microphone, and inputting it into a recognition engine for analysis.

[0799] "Means for the emotion recognition engine to optimize advice based on the user's emotional state" refers to a method in which the emotion recognition engine optimizes the content based on the user's emotional data, and provides advice in gentle words to a user who is feeling stressed, for example.

[0800] "Means for recommending golf clubs and balls that are optimal for a user based on the user's emotional data and AI analysis results" refers to a method for combining the user's emotional data with the results of AI analysis to recommend golf clubs and balls that are optimal for the user's emotional state.

[0801] "Means for analyzing user behavioral data and emotional data and displaying appropriate advertisements on the user terminal" refers to a method for analyzing a user's past behavioral data and emotional data and displaying highly relevant advertisements on the user terminal.

[0802] An embodiment of the present invention is a system that acquires golf swing data of a user, provides advice for improving technique, and personalizes advice and recommended products using emotion data.

[0803] System configuration

[0804] The system consists of the following components:

[0805] 1. User device: Use a smartphone or tablet. iPhone (iOS 14 or later) or Android (Android 11 or later) is recommended.

[0806] 2. Measurement device: Golf swing measurement device. Use one that can connect via Bluetooth or Wi-Fi.

[0807] 3. Cloud server: Based on AWS (Amazon Web Services), it uses EC2 instances and RDS (relational database service).

[0808] 4. AI analytics engine: Use TensorFlow or PyTorch.

[0809] 5. Emotion Engine: Use the Affectiva SDK or Microsoft Azure's Emotion API.

[0810] Program processing

[0811] When a user performs a golf swing, the measuring device measures head speed and trajectory data and sends it to a smartphone, which then encrypts and transmits the data to a cloud server, where it is received and stored in a database.

[0812] The cloud server inputs the saved swing data into an AI analysis engine and generates advice to improve the user's technique. The advice is then sent to the user's device and displayed on the device.

[0813] The emotion engine uses the camera and microphone installed on the user's device to capture and analyze the user's emotional data in real time. The emotion recognition engine analyzes the user's emotional state and optimizes the advice and recommended products generated by the AI.

[0814] Specific examples

[0815] A user measures their head speed using a swing measuring device at a golf driving range and sends the measurement results to their smartphone. The smartphone app sends the data to a cloud server, where an AI analysis engine generates advice to improve their technique. The smartphone camera recognizes the user's facial expressions, and the emotion engine optimizes the advice based on the analysis results. For example, if the user is feeling stressed, the system will provide gentle advice.

[0816] The system also recommends the best golf clubs and balls for each user based on their emotional data and the results of AI analysis, and analyzes their behavioral and emotional data to display highly relevant advertisements on their devices.

[0817] Prompt Sentence Examples

[0818] A user uses a golf swing monitor to collect head speed and trajectory data. The emotion engine performs real-time emotion recognition and recommends the best golf clubs and balls. Also, display appropriate advertisements based on the user's emotional state.

[0819] In this way, embodiments of a system can be realized that allow for personalized advice and product recommendations that take into account the emotional state of the user.

[0820] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0821] Step 1:

[0822] The user performs a golf swing. The user uses a golf swing measurement device to obtain head speed and trajectory data in real time. The device transmits this data to a smartphone via Bluetooth or Wi-Fi. The input is the user's swing motion, and the output is head speed and trajectory data.

[0823] Step 2:

[0824] The device receives the measurement data and sends it to the cloud server. The smartphone or tablet encrypts the data received from the measuring device and sends it to the cloud server via a secure communication protocol (e.g., HTTPS). The input is the data obtained from the measuring device, and the output is the encrypted data.

[0825] Step 3:

[0826] The server stores the received data in a database. The cloud server validates the received data and checks for any invalid data. It then converts it into an appropriate format and stores it in a database (e.g., AWS RDS). The input is encrypted measurement data, and the output is the data stored in the database.

[0827] Step 4:

[0828] The server inputs the data into an AI analysis engine and generates advice for improving technique. The cloud server inputs the saved swing data into an AI analysis engine (e.g., TensorFlow) for analysis. The input is the swing data saved in the database, and the output is the analysis results and advice.

[0829] Step 5:

[0830] The server sends the generated advice to the user's device and displays it. The server also sends the generated advice to the user's device and notifies them within a dedicated app. The input is the advice from the AI ​​analysis engine, and the output is the advice displayed to the user.

[0831] Step 6:

[0832] The device acquires the user's emotional data and sends it to the emotion engine. The smartphone's camera and microphone are used to capture the user's facial expressions and voice in real time. The data is sent to the emotion engine for analysis. The input is the emotional data acquired by the camera and microphone, and the output is the analyzed emotional state.

[0833] Step 7:

[0834] The emotion recognition engine optimizes advice based on the user's emotional state. Based on the analysis results, the emotion engine adapts the advice generated by the AI ​​analysis engine to the user's emotional state. The input is the analysis results based on emotional data, and the output is optimized advice.

[0835] Step 8:

[0836] The server recommends the most suitable golf clubs and balls based on the user's emotional data and the results of AI analysis. The cloud server analyzes the emotional data and the results of AI analysis and recommends the most suitable golf clubs and balls to the user. The input is the emotional data and the results of AI analysis, and the output is the recommended product.

[0837] Step 9:

[0838] The server analyzes the user's behavioral and emotional data and displays appropriate advertisements on the user's device. The cloud server analyzes past behavioral and emotional data and displays advertisements based on the user's interests and emotional state. The input is the user's behavioral and emotional data, and the output is the advertisement to be displayed.

[0839] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0840] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0841] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0842] [Third embodiment]

[0843] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0844] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0845] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0846] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0847] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0848] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0849] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0850] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0851] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0852] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0853] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0854] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0855] This invention relates to a system that utilizes a user's golf swing data to help improve their technique, and also recommends optimal golf clubs and balls and displays advertisements. The system is composed of a user terminal, a cloud server, an AI analysis engine, and a database.

[0856] Measuring head speed and trajectory

[0857] User performs a golf swing:

[0858] Users use a dedicated golf swing measuring device at a driving range or at home. This measuring device has the ability to collect head speed and trajectory data in real time. Users install a dedicated app on their smartphone or tablet, which connects to the measuring device.

[0859] The device retrieves the data from the meter:

[0860] The measuring device measures clubhead speed and trajectory data and transmits the data via Bluetooth or Wi-Fi to the user's device (smartphone or tablet), which temporarily stores the data and uploads it to a cloud server when the measurement session is over.

[0861] Data transmission and storage

[0862] The device sends the measurement data to the server:

[0863] The user device transmits the acquired head speed and trajectory data to the cloud server, along with related information such as the user ID and the measurement date and time.

[0864] The server saves the data to the database:

[0865] The server validates the data received, checks for any irregularities, and stores it in a database that serves as the basis for future analysis, recommendations, and advertising.

[0866] AI-powered analysis and advice generation

[0867] The server inputs the data into the AI ​​analytics engine:

[0868] The cloud server inputs the stored data into an AI analysis engine, which uses deep learning and machine learning algorithms to analyze the data and generate advice on how to improve the user's skills.

[0869] AI-generated advice:

[0870] The AI ​​analysis engine uses the user's past and current data to automatically generate advice on how to improve their technique, such as suggesting adjustments to the angle of their swing or recommending specific training methods.

[0871] The server sends the advice to the user's device:

[0872] The generated advice is sent to the user's device via a cloud server, where the user can view the advice via a dedicated app on their smartphone or tablet.

[0873] Golf club and ball recommendations

[0874] The server recommends products based on the results of AI analysis:

[0875] Based on the results of the AI ​​analysis engine, the server refers to a database of known products to recommend the best golf clubs and balls for the user. Product selection is based on swing data, head speed, trajectory data, etc.

[0876] The recommendations are displayed on the user's device:

[0877] The recommended product information is sent to the user's device via a cloud server, and the user can check detailed information about the recommended golf clubs and balls through a dedicated app.

[0878] Advertisement display

[0879] The server analyzes the collected data and selects advertisements:

[0880] The cloud server analyzes the user's swing data and past behavioral data to select appropriate advertisements. This advertisement selection utilizes AI technology, and advertisements are automatically selected based on the user's interests.

[0881] Display ads on user devices:

[0882] The selected advertisements are sent to the user's device via a cloud server, and the user can view them through a dedicated app. For example, if a user is looking for beginner golf clubs, an advertisement based on that information will be displayed.

[0883] As described above, the system of the present invention utilizes the user's golf swing data in a variety of ways to support skill improvement, as well as to provide optimal product recommendations and effective advertising displays.

[0884] The processing flow will be explained below.

[0885] Step 1:

[0886] The user performs a golf swing

[0887] The user uses a dedicated golf swing measurement device at a driving range or at home. The device has the ability to acquire head speed and trajectory data in real time. The user installs a dedicated app on their smartphone or tablet and sets it to measurement mode.

[0888] Step 2:

[0889] The device acquires the data from the measuring device.

[0890] The device (smartphone or tablet) receives data from the measurement device via Bluetooth or Wi-Fi, and temporarily stores the received head speed and trajectory data in the app.

[0891] Step 3:

[0892] The device sends the measurement data to the server

[0893] The device sends the stored measurement data to the cloud server. The data sent includes the user ID, measurement date and time, and measurement details. The data is encrypted and sent securely.

[0894] Step 4:

[0895] The server saves the data to a database

[0896] The cloud server validates the received data to check for any invalid data, and after the data validation is complete, the server stores the data in the appropriate table in the database.

[0897] Step 5:

[0898] The server inputs the data into the AI ​​analysis engine

[0899] The server inputs the saved swing data into the AI ​​analysis engine. The swing data includes head speed, trajectory angle, swing amplitude, etc. The AI ​​then preprocesses the data and begins analysis.

[0900] Step 6:

[0901] AI generates advice

[0902] The AI ​​analysis engine analyzes the data and generates advice for the user to improve their technique. Based on the analysis results, specific advice is generated, including swing improvements and practice methods. Example: "Your accuracy will improve if you swing with your right shoulder angle lowered by 5 degrees."

[0903] Step 7:

[0904] The server sends the advice to the user terminal.

[0905] The server sends the generated advice to the user's device. The user's device receives the advice and notifies the user within a dedicated app. The user can then browse the app to view the detailed advice content.

[0906] Step 8:

[0907] The server recommends products based on the results of AI analysis.

[0908] The server references product information in the database and recommends the best golf clubs and balls for each user based on the results of AI analysis. Products are selected based on the user's swing characteristics and skill level.

[0909] Step 9:

[0910] Recommendation results are displayed on the user's device

[0911] The server sends the recommended product information to the user's device, which displays the recommended golf clubs and balls in the app. The user can view details of the recommended products and is also provided with information such as a purchase link.

[0912] Step 10:

[0913] The server analyzes the collected data and selects advertisements

[0914] The server analyzes past swing data and behavioral data to select advertisements based on the user's interests and behavioral patterns, and uses appropriate AI algorithms to maximize the relevance of the advertisements.

[0915] Step 11:

[0916] Displaying advertisements on user devices

[0917] The server sends the selected advertisements to the user's device, which then displays them in the appropriate location within the app. Users can click on the advertisements they find interesting to access more information or purchase information.

[0918] Example 1

[0919] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0920] Conventional golf swing analysis systems lack a comprehensive system that not only supports users' skill improvement but also recommends optimal golf equipment and displays effective advertisements. As a result, users are forced to use multiple devices and apps simultaneously, lacking a means to efficiently improve their swing technique. Furthermore, there is no established method for providing more accurate advice and recommendations by integrating and analyzing a user's swing data with past behavioral data.

[0921] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0922] In this invention, the server includes: means for measuring a user's golf swing and acquiring head speed and trajectory data; means for transmitting the acquired data to a cloud server via a terminal; means for the cloud server to store the data in a database and verify invalid data; means for the cloud server to input the stored data to an AI analysis engine; means for the AI ​​analysis engine to generate advice for improving the user's technique using a deep learning or machine learning algorithm; means for transmitting the generated advice to the user's terminal via the cloud server and displaying it; means for referring to a known product database based on the AI ​​analysis results to recommend the most suitable golf equipment to the user; and means for analyzing user behavior data, selecting appropriate advertisements, and displaying them on the user's terminal. This allows users to receive comprehensive support for improving their swing technique through a single system, and also enables them to receive highly accurate product recommendations and advertisements based on their individual data.

[0923] "User" refers to a person who uses a golf swing measuring device and receives analysis of swing data and advice on improving technique.

[0924] "Device" refers to an electronic device such as a smartphone or tablet that is used to receive and temporarily store data obtained from a golf swing measurement device and send it to a cloud server.

[0925] "Cloud server" refers to a group of servers accessible via the Internet that provide functions such as data storage, analysis, advice generation, product recommendations, and advertisement selection.

[0926] "Head speed" is an index that indicates how fast the head of a golf club moves during a swing.

[0927] "Trajectory data" refers to data that indicates the angle and trajectory of a golf ball when it is hit.

[0928] "AI analysis engine" refers to a software engine that uses deep learning and machine learning algorithms to analyze a user's swing data and generate advice on improving technique and product recommendations.

[0929] "Database" refers to a data structure for systematically managing user swing data, analysis results, product information, etc. stored on a cloud server.

[0930] "Advice for improving technique" refers to specific suggestions and training methods for improving the user's swing technique.

[0931] "Golf equipment" refers to tools such as golf clubs and balls used by users to play golf.

[0932] "Advertising" refers to promotional content that provides information about appropriate products and services based on user interests and behavioral data.

[0933] "Behavioral data" refers to data that indicates the user's behavioral history, such as the user's past swing data and operation history within the app.

[0934] This invention relates to a system that utilizes golf swing data to support skill improvement, recommends optimal golf equipment, and displays advertisements. This system is composed of a user terminal, a cloud server, an AI analysis engine, and a database.

[0935] First, the user performs a golf swing. The user uses a dedicated golf swing measuring device at home or at a golf driving range. This measuring device has the function of acquiring head speed and trajectory data in real time. The user connects to the measuring device via a dedicated app installed on a smartphone or tablet.

[0936] The device then receives the data from the measuring device. The measuring device measures head speed and trajectory data and transmits the data via Bluetooth or Wi-Fi to the user's device (smartphone or tablet). The device temporarily stores the received data and uploads it to a cloud server when the measurement session is over.

[0937] The cloud server is responsible for transmitting and storing the data. The user device sends the acquired head speed and trajectory data to the cloud server. This data includes relevant information such as the user ID and measurement date and time. The server verifies the received data, checks for any fraudulent data, and stores it in a database. This data serves as the basis for future analysis, recommendations, and advertising displays.

[0938] After the data is saved, the server inputs it into the AI ​​analysis engine. The cloud server passes the saved data to the AI ​​analysis engine, which then analyzes the data using deep learning and machine learning algorithms to generate advice on how to improve the user's skills.

[0939] AI generates advice. The AI ​​analysis engine automatically generates advice to improve a user's technique based on their past and current data. For example, it may suggest adjusting the angle of their swing or recommend a specific training method. The generated advice is sent to the user's device via a cloud server, and the user can view the advice via a dedicated app on their smartphone or tablet.

[0940] Next, the server recommends products based on the AI ​​analysis results. Based on the results of the AI ​​analysis engine, the server refers to a database of known products to recommend the most suitable golf clubs and balls for the user. Products are selected based on swing data, head speed, trajectory data, etc. Recommended product information is sent to the user's device via a cloud server, and the user can check detailed information about the recommended golf clubs and balls through a dedicated app.

[0941] The server also analyzes the collected data and selects advertisements. The cloud server analyzes the user's swing data and past behavioral data to select appropriate advertisements. This advertisement selection utilizes AI technology, which automatically selects advertisements based on the user's interests. The selected advertisements are sent to the user's device via the cloud server, and the user can view them through a dedicated app. For example, if a user is looking for clubs for beginners, an advertisement based on that information will be displayed.

[0942] As a concrete example, the following is an example of a prompt sentence to be input to a generative AI model:

[0943] "Please give me some advice on improving my technique based on my golf swing data."

[0944] "Please analyze my swing data and recommend the right golf clubs for me."

[0945] "Show me ads based on swing data."

[0946] As described above, the system of the present invention utilizes the user's golf swing data in a variety of ways to support skill improvement, as well as to provide optimal product recommendations and effective advertising displays.

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

[0948] Step 1:

[0949] The user performs a golf swing

[0950] A user uses a dedicated golf swing measurement device at a driving range or at home. This measurement device has the ability to acquire head speed and trajectory data in real time. The input is the user's swing motion, and the output is the measured head speed and trajectory data. For example, when a user swings with a driver, the head speed is recorded as 40 m / s and the trajectory is 15 degrees.

[0951] Step 2:

[0952] The device acquires the data from the measuring device.

[0953] The measuring device measures head speed and trajectory data and transmits the data to the user's device via Bluetooth or Wi-Fi. The device temporarily stores the received data. The input is the data transmitted from the measuring device, and the output is the temporarily stored swing data. For example, data such as "Session 1: head speed = 40 m / s, trajectory = 15 degrees" is stored on the device.

[0954] Step 3:

[0955] The device sends the measurement data to the server

[0956] The user device sends the saved measurement data to the cloud server. The sent data includes related information such as the user ID, measurement date and time, head speed, and trajectory. The input is the temporarily saved swing data, and the output is the swing data sent to the cloud server. For example, the following data is sent: "User ID: 123, Date and time: 2023-01-01, Head speed: 40 m / s, Trajectory: 15 degrees."

[0957] Step 4:

[0958] The server saves the data to a database

[0959] The server validates the received data and checks for any invalid data. The data is then saved in the database. The input is the swing data sent to the cloud server, and the output is the swing data saved in the database. For example, the following data is saved in the database: "User ID: 123, Date and Time: 2023-01-01, Head Speed: 40 m / s, Trajectory: 15 degrees."

[0960] Step 5:

[0961] The server inputs the data into the AI ​​analysis engine

[0962] The cloud server passes the stored data to the AI ​​analysis engine. The input is the swing data stored in the database, and the output is the data input to the AI ​​analysis engine. This transfer occurs periodically or is triggered when the user requests advice.

[0963] Step 6:

[0964] AI generates advice

[0965] The AI ​​analysis engine analyzes the input data and generates advice to improve the user's technique. The input is the swing data entered into the AI ​​analysis engine, and the output is the generated advice. For example, specific advice such as "Start your swing faster to improve head speed" is generated.

[0966] Step 7:

[0967] The server sends the advice to the user terminal.

[0968] The server sends the generated advice to the user's device. The input is the generated advice, and the output is the advice sent to the user's device. The user receives a notification through a dedicated app and can view the details of the advice. For example, a notification such as "New advice has arrived: Practice starting your swing faster" may be displayed.

[0969] Step 8:

[0970] The server recommends products based on the results of AI analysis.

[0971] The server refers to a known product database to recommend the best golf clubs and balls to the user based on the results of the AI ​​analysis engine. The input is the results of the AI ​​analysis engine, and the output is a list of recommended golf equipment. For example, a recommendation may be made such as, "The best driver for you is the ABC model from XYZ company."

[0972] Step 9:

[0973] Recommendation results are displayed on the user's device

[0974] The server sends the recommended product information to the user's device and displays it to the user through a dedicated app. The input is the recommendation result sent from the server, and the output is the product information displayed on the user's device. For example, a message such as "The recommended screwdriver is the ABC model from XYZ. Click here for details" is displayed.

[0975] Step 10:

[0976] The server analyzes the collected data and selects advertisements

[0977] The server analyzes the user's swing data and past behavioral data to select appropriate advertisements. The input is the user's behavioral data, and the output is the selected advertisement. Using AI technology, advertisements are automatically selected based on the user's interests. For example, an advertisement such as "Here are the golf training products that are perfect for you" is selected.

[0978] Step 11:

[0979] Displaying advertisements on user devices

[0980] The server sends the selected advertisement to the user's device and displays it on a dedicated app. The input is the advertisement sent from the server, and the output is the advertisement displayed on the user's device. Users can tap on an advertisement that interests them to check details or purchase it. For example, an advertisement such as "20% off new golf training equipment! Click here for details" may be displayed.

[0981] (Application example 1)

[0982] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0983] Conventional golf swing assistant systems focus on recommending golf clubs and balls and displaying advertisements when helping users improve their technique, but do not support real-time training method suggestions. This makes it difficult for users to instantly obtain the information they need to improve their swing, making it difficult to achieve effective swing improvement.

[0984] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0985] In this invention, the server includes a means for delivering video content that suggests training methods in real time based on the user's golf swing data, a means for analyzing the user's swing data and behavioral patterns and selecting the most suitable advertisement for each individual user, and a means for transmitting and displaying the generated advice to the user's terminal, thereby enabling the user to instantly watch specific training videos to improve their swing on the spot.

[0986] A "user's golf swing" refers to the process in which a user performs a swing motion using a golf club.

[0987] "Head speed" is the speed achieved by the head portion of a golf club during a swing.

[0988] "Trajectory data" refers to data relating to the flight path, direction, and distance of a golf ball after it is hit.

[0989] A "cloud server" is a remote server for data storage and computation that is accessible from multiple user terminals via the Internet.

[0990] A "database" is a collection of structured data stored within a cloud server.

[0991] An "AI analysis engine" is software that uses machine learning algorithms and deep learning technology to analyze input data and derive results.

[0992] "Advice" refers to specific instructions and suggestions for improving golf swing technique generated by the AI ​​analysis engine.

[0993] A "user terminal" is an electronic device used by a user, such as a smartphone or tablet.

[0994] The "means for recommending golf clubs and balls" is a system that selects and displays the optimal golf clubs and balls based on the user's swing data.

[0995] "Means for displaying advertisements on user terminals" refers to a mechanism for displaying advertisements selected based on user behavior data on user terminals.

[0996] "Video content that suggests training methods in real time" is a service that provides training videos that can be viewed on the spot based on the user's golf swing data.

[0997] This invention is a system that utilizes a user's golf swing data to help improve their technique. This system consists of a user terminal, a cloud server, an AI analysis engine, and a database. Each component and its specific operation are explained below.

[0998] User terminal and measuring instrument

[0999] Users use a dedicated golf swing measuring device at a driving range or at home. This measuring device has the ability to acquire head speed and trajectory data in real time. Users install a dedicated app on their smartphone or tablet and connect it to the measuring device. The measuring device measures head speed and trajectory data and transmits the data to the user's device via Bluetooth or Wi-Fi. The device temporarily stores the received data and uploads it to a cloud server when the measurement session is over.

[1000] Cloud Servers and Databases

[1001] The cloud server receives the clubhead speed and trajectory data sent from the user's device. This data includes relevant information such as the user ID and the measurement date and time. The server verifies the received data, checks for any fraudulent data, and stores it in a database. This data serves as the basis for future analysis, recommendations, and advertisement display.

[1002] AI-powered analysis and advice generation

[1003] The cloud server inputs the stored data into an AI analysis engine. The AI ​​analysis engine uses deep learning and machine learning algorithms to analyze the data and generate advice on how to improve the user's technique. The generated advice is sent to the user's device via the cloud server. The user can view the advice via a dedicated app on their smartphone or tablet. The AI ​​analysis engine also suggests specific training methods for improving technique in real time based on the user's past and current data, and distributes them as video content. For example, if it is analyzed that the user's swing is a little overswing, training videos for correcting the swing will be suggested in real time.

[1004] Golf club and ball recommendations

[1005] Based on the results of the AI ​​analysis engine, the cloud server refers to a database of known products to recommend the most suitable golf clubs and balls for the user. Products are selected based on swing data, head speed, trajectory data, etc. Recommended product information is sent to the user's device via the cloud server, and the user can check detailed information about the recommended golf clubs and balls through a dedicated app.

[1006] Advertisement display

[1007] The cloud server analyzes the user's swing data and past behavioral data to select appropriate advertisements. This selection utilizes AI technology, which automatically selects advertisements based on the user's interests. The selected advertisements are sent to the user's device via the cloud server, and the user can view them through a dedicated app. For example, if a user is looking for clubs for beginners, an advertisement based on that information will be displayed.

[1008] Specific examples

[1009] For example, if the head speed is 120 m / s and the trajectory is high, the AI ​​will compare it with past data and generate advice such as "adjust the way you pull your arms" and display a link to the corresponding training video.An example of a prompt sentence is "Please advise on specific training methods to improve technique based on the user's golf swing data."

[1010] As described above, the present invention utilizes a user's golf swing data in a variety of ways to support skill improvement, as well as to realize optimal product recommendations and effective advertisement displays.

[1011] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1012] Step 1:

[1013] The user makes a golf swing. The user uses a dedicated golf swing measuring device at a golf driving range or at home to measure the swing. The data acquired at this time is head speed and trajectory data. The user installs a dedicated app on a smartphone or tablet and connects to the measuring device via Bluetooth or Wi-Fi.

[1014] Step 2:

[1015] The device receives the data from the measuring device. The device transmits the measured head speed and trajectory data to the user's device via Bluetooth or Wi-Fi. The device temporarily stores the received data and prepares it for the next step.

[1016] Step 3:

[1017] The user device sends the measurement data to the cloud server. The device sends the acquired head speed and trajectory data to the cloud server, and this data includes related information such as the user ID and measurement date and time. Input data: head speed, trajectory data, user ID, measurement date and time. Output data: data sent to the cloud server.

[1018] Step 4:

[1019] The server saves the data in the database. The cloud server verifies the received data and checks for any invalid data before saving it in the database. Input data: Data sent to the cloud server. Output data: Data saved in the database.

[1020] Step 5:

[1021] The server inputs the data into the AI ​​analysis engine. The cloud server inputs the saved data into the AI ​​analysis engine. Input data: Data saved in the database. Output data: Data input into the AI ​​analysis engine.

[1022] Step 6:

[1023] The AI ​​analysis engine generates advice to help users improve their technique. The AI ​​analysis engine uses deep learning and machine learning algorithms to analyze data, identify trends and problems in the user's swing, and generate specific advice to improve their technique. Input data: Data entered into the AI ​​analysis engine. Output data: Generated advice.

[1024] Step 7:

[1025] The server sends the generated advice to the user's device and displays it. The generated advice is sent to the user's device via the cloud server and displayed to the user through a dedicated app. Input data: Generated advice. Output data: Advice displayed on the user's device.

[1026] Step 8:

[1027] The server recommends the most suitable golf clubs and balls to the user based on the results of the AI ​​analysis. Based on the results of the AI ​​analysis engine, the server selects the most suitable golf clubs and balls from the database. Input data: AI analysis results. Output data: Recommended product information.

[1028] Step 9:

[1029] The server analyzes the user's behavioral data and displays appropriate advertisements on the user's device. The cloud server analyzes the user's swing data and past behavioral data, selects advertisements that match the user's interests and concerns, and sends them to the user's device. Input data: User's behavioral data. Output data: Advertisements displayed on the user's device.

[1030] Step 10:

[1031] The server delivers video content that suggests training methods in real time based on the user's golf swing data. The AI ​​analysis engine selects real-time training videos based on the user's swing data and sends them to the user's device. Input data: User's golf swing data. Output data: Video content delivered to the user's device.

[1032] Through the above steps, the present invention utilizes the user's golf swing data in a variety of ways to support skill improvement, as well as to provide optimal product recommendations and effective advertising displays.

[1033] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1034] This invention relates to a system that utilizes a user's golf swing data to recommend optimal golf clubs and balls and display advertisements to help improve skills, combined with an emotion engine that recognizes the user's emotions. The system is composed of a user terminal, a cloud server, an AI analysis engine, an emotion engine, and a database.

[1035] Measuring head speed and trajectory

[1036] User performs a golf swing:

[1037] The user uses a dedicated golf swing measurement device at a driving range or at home. The device has the ability to acquire head speed and trajectory data in real time. The user installs a dedicated app on their smartphone or tablet and sets it to measurement mode.

[1038] The device retrieves the data from the meter:

[1039] The device (smartphone or tablet) receives data from the measurement device via Bluetooth or Wi-Fi, and temporarily stores the received head speed and trajectory data in the app.

[1040] Data transmission and storage

[1041] The device sends the measurement data to the server:

[1042] The device sends the stored measurement data to the cloud server. The data sent includes the user ID, measurement date and time, and measurement details. The data is encrypted and sent securely.

[1043] The server saves the data to the database:

[1044] The cloud server validates the received data to check for any invalid data, and after the data validation is complete, the server stores the data in the appropriate table in the database.

[1045] AI-powered analysis and advice generation

[1046] The server inputs the data into the AI ​​analytics engine:

[1047] The cloud server inputs the saved swing data into the AI ​​analysis engine. The swing data includes head speed, trajectory angle, swing amplitude, etc. The AI ​​then preprocesses the data and begins analysis.

[1048] AI-generated advice:

[1049] The AI ​​analysis engine analyzes the data and generates advice for the user to improve their technique. Based on the analysis results, specific advice is generated, including swing improvements and practice methods. Example: "Your accuracy will improve if you swing with your right shoulder angle lowered by 5 degrees."

[1050] Advice display using emotion engine

[1051] The server sends the generated advice to the user's device:

[1052] The generated advice is sent to the user's device via the cloud server. The user's device receives the advice and notifies the user within a dedicated app. The user can then browse the app to view the detailed advice content.

[1053] The device recognizes the user's emotions:

[1054] The user device is equipped with emotion recognition devices such as a camera and microphone, which analyze facial expressions and tone of voice to recognize the user's emotions. The emotion recognition device acquires the user's emotion data in real time, and the emotion engine analyzes the data.

[1055] Emotion engine adapts advice:

[1056] The emotion engine adapts the generated advice based on the user's emotional data. For example, if it detects that the user is feeling stressed, it will provide gentle advice and suggest ways to relax.

[1057] Golf club and ball recommendations

[1058] The server recommends products based on the results of AI analysis:

[1059] The server references product information in the database and recommends the best golf clubs and balls for each user based on the results of AI analysis. Products are selected based on the user's swing characteristics and skill level. Furthermore, emotional data is used to select the best product for the user's current emotional state.

[1060] Advertisement display

[1061] The server analyzes the user's emotional data and selects advertisements:

[1062] The server analyzes past swing data, behavioral data, and emotional data to select advertisements based on the user's interests, behavioral patterns, and emotional state. For example, if the user is showing positive emotions, advertisements based on the user's emotional state will be displayed, such as advertisements for new products.

[1063] Display ads on user devices:

[1064] The selected advertisements are sent to the user's device via the cloud server, and the user's device displays the advertisements in the appropriate location within the app. Users can click on the advertisements they are interested in to access more information or purchase information.

[1065] As described above, the system of the present invention utilizes the user's golf swing data and emotional data in a multifaceted manner to support skill improvement and provide added value such as optimal product recommendations and effective advertising displays.

[1066] The processing flow will be explained below.

[1067] Step 1:

[1068] The user performs a golf swing

[1069] The user uses a dedicated golf swing measurement device at a driving range or at home. The device has the ability to acquire head speed and trajectory data in real time. The user installs a dedicated app on their smartphone or tablet and sets it to measurement mode.

[1070] Step 2:

[1071] The device acquires the data from the measuring device.

[1072] The device (smartphone or tablet) receives data from the measurement device via Bluetooth or Wi-Fi, and temporarily stores the received head speed and trajectory data in the app.

[1073] Step 3:

[1074] The device sends the measurement data to the server

[1075] The device sends the stored measurement data to the cloud server. The data sent includes the user ID, measurement date and time, and measurement details. The data is encrypted and sent securely.

[1076] Step 4:

[1077] The server saves the data to a database

[1078] The cloud server validates the received data to check for any invalid data, and after the data validation is complete, the server stores the data in the appropriate table in the database.

[1079] Step 5:

[1080] The server inputs the data into the AI ​​analysis engine

[1081] The cloud server inputs the saved swing data into the AI ​​analysis engine. The swing data includes head speed, trajectory angle, swing amplitude, etc. The AI ​​then preprocesses the data and begins analysis.

[1082] Step 6:

[1083] AI generates advice

[1084] The AI ​​analysis engine analyzes the data and generates advice for the user to improve their technique. Based on the analysis results, specific advice is generated, including swing improvements and practice methods. Example: "Your accuracy will improve if you swing with your right shoulder angle lowered by 5 degrees."

[1085] Step 7:

[1086] The server sends the generated advice to the user terminal.

[1087] The generated advice is sent to the user's device via the cloud server. The user's device receives the advice and notifies the user within a dedicated app. The user can then browse the app to view the detailed advice content.

[1088] Step 8:

[1089] The device recognizes the user's emotions

[1090] The user device is equipped with emotion recognition devices such as a camera and microphone, which analyze facial expressions and tone of voice to recognize the user's emotions. The emotion recognition device acquires the user's emotion data in real time, and the emotion engine analyzes the data.

[1091] Step 9:

[1092] Emotion engine adapts advice

[1093] The emotion engine adapts the generated advice based on the user's emotional data. For example, if it detects that the user is feeling stressed, it will provide gentle advice and suggest ways to relax.

[1094] Step 10:

[1095] The server recommends products based on the results of AI analysis.

[1096] The server references product information in the database and recommends the best golf clubs and balls for each user based on the results of AI analysis. Products are selected based on the user's swing characteristics and skill level. Furthermore, emotional data is used to select the best product for the user's current emotional state.

[1097] Step 11:

[1098] Recommendation results are displayed on the user's device

[1099] The server sends the recommended product information to the user's device, which displays the recommended golf clubs and balls in the app. The user can view details of the recommended products and is also provided with information such as a purchase link.

[1100] Step 12:

[1101] The server analyzes the user's emotional data and selects advertisements

[1102] The server analyzes past swing data, behavioral data, and emotional data to select advertisements based on the user's interests, behavioral patterns, and emotional state. For example, if the user is showing positive emotions, advertisements based on the user's emotional state will be displayed, such as advertisements for new products.

[1103] Step 13:

[1104] Displaying advertisements on user devices

[1105] The selected advertisements are sent to the user's device via the cloud server, and the user's device displays the advertisements in the appropriate location within the app. Users can click on the advertisements they are interested in to access more information or purchase information.

[1106] Example 2

[1107] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1108] Conventional golf skill improvement systems analyze users' swing data and provide advice to improve their skills, but they have limitations in providing adaptive advice that takes the user's emotional state into account, recommending sports equipment that is optimal for the user, and displaying personalized advertisements.The present invention aims to improve the user experience and increase the accuracy of skill improvement by introducing multifaceted data analysis that includes user emotional data.

[1109] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1110] In this invention, the server includes a means for measuring the user's golf swing and acquiring head speed and trajectory data, a means for transmitting the acquired data to the server via a network, and a means for the server to store the data in a database and input the data into an AI analysis engine, thereby enabling personalized advice on skill improvement, product recommendations, and advertisement display based on user emotion recognition and adaptation.

[1111] (definition statement)

[1112] "User" refers to an individual who performs a golf swing and uses the system.

[1113] "Server" refers to a computer system that receives swing data and emotion data, stores it in a database, and performs AI analysis.

[1114] "Terminal" refers to a portable electronic device such as a smartphone or tablet operated by a user.

[1115] "Head speed" refers to the speed at which the head of a golf club moves during a swing.

[1116] "Trajectory data" refers to information regarding the flight path of a golf ball.

[1117] "Network" refers to a communication environment that enables data communication between a terminal and a server.

[1118] "Database" refers to an information management system for storing received swing data and emotion data.

[1119] "AI analysis engine" refers to an artificial intelligence system that analyzes stored data and generates specific advice on improving swing technique.

[1120] "Emotion engine" refers to a system that has the ability to analyze a user's emotional data and adapt advice and recommendations.

[1121] "Sports equipment" refers to products such as golf clubs and golf balls that are related to a user's golf swing.

[1122] "Advertising" refers to marketing information provided based on user behavioral and emotional data.

[1123] MODE FOR CARRYING OUT THE INVENTION

[1124] The present invention is a system for measuring a user's golf swing and supporting skill improvement, and is configured as follows: The system is composed of a user terminal, a server, an AI analysis engine, an emotion engine, and a database.

[1125] Acquiring golf swing data

[1126] User performs a golf swing:

[1127] A user uses a dedicated golf swing measurement device (e.g., a general-purpose measurement device) at a golf driving range or at home. The measurement device can obtain golf club head speed and golf ball trajectory data in real time. The user installs a dedicated app on their smartphone or tablet and sets it to measurement mode.

[1128] The device retrieves the data from the meter:

[1129] The device (smartphone or tablet) receives data from the measuring device via Bluetooth or Wi-Fi, and the received data is temporarily stored in the app.

[1130] Data transmission and storage

[1131] The device sends the measurement data to the server:

[1132] The device sends the saved measurement data to a server (e.g., a general-purpose cloud server) via a network. The data sent includes the user ID, measurement date and time, and measurement details, and is encrypted before transmission.

[1133] The server saves the data to the database:

[1134] The server validates the received data to check for any invalid data. After the server checks the integrity of the data, it stores the data in a database (e.g., a general-purpose database management system).

[1135] AI analysis and advice generation

[1136] The server inputs the data into the AI ​​analytics engine:

[1137] The server inputs the saved swing data into an AI analysis engine (e.g., a general-purpose AI platform). The input data includes head speed, trajectory angle, and swing amplitude. The AI ​​analysis engine preprocesses the data and begins analysis.

[1138] AI-generated advice:

[1139] An AI analysis engine analyzes the data and generates advice for users to improve their technique, such as "Lowering the angle of your right shoulder by 5 degrees when swinging will improve your accuracy."

[1140] Advice display using emotion engine

[1141] The server sends the generated advice to the user's device:

[1142] The server sends the generated advice to the user's device via the network. The user's device receives the advice and notifies the user within a dedicated app.

[1143] The device recognizes the user's emotions:

[1144] User devices are equipped with emotion recognition devices (e.g., general-purpose emotion recognition technology) such as cameras and microphones. These devices analyze facial expressions and tone of voice to recognize the user's emotions. The emotion data acquired by the emotion recognition devices in real time is analyzed by the emotion engine.

[1145] Emotion engine adapts advice:

[1146] The emotion engine adapts the generated advice based on the user's emotional data. For example, if the user is feeling stressed, it will provide gentle advice and suggest ways to relax.

[1147] Golf club and ball recommendations

[1148] The server recommends products based on the results of AI analysis:

[1149] The server references product information from the database and recommends the most suitable sports equipment (e.g., golf clubs, golf balls) to the user based on the AI ​​analysis results and emotional data.

[1150] Displaying ads

[1151] The server analyzes the user's emotional data and selects advertisements:

[1152] The server analyzes past swing data, behavioral data, and emotional data to select advertisements based on the user's interests, behavioral patterns, and emotional state. For example, if the user shows positive emotions, advertisements for new products will be displayed.

[1153] Display ads on user devices:

[1154] The server sends the selected advertisements to the user's device via the network, and the user's device displays the advertisements in the appropriate location within the app. Users can click on the advertisements they are interested in to access more information or purchase websites.

[1155] Specific examples and prompts for the generative AI model

[1156] Examples:

[1157] The user measured their swing using a general-purpose measuring device at home and a dedicated smartphone app. The measurement data was sent to a cloud server, and the AI ​​analysis engine generated advice such as, "Swinging with your right shoulder angle lowered by 5 degrees will improve accuracy." The emotion engine also recognized that the user was feeling stressed, and provided gentle advice and suggested ways to reduce stress.

[1158] Prompt for the generative AI model:

[1159] "Please explain the process of your system that analyzes golf swing data and emotion data to provide optimal advice to users. Also, please explain how product recommendations and advertisements are displayed taking user emotions into account."

[1160] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1161] Step 1:

[1162] User performs a golf swing:

[1163] A user uses a dedicated golf swing measurement device at a driving range or at home. The measurement device captures head speed and trajectory data in real time during the swing. The input is the user's swing motion, and the output is head speed and trajectory data. Specifically, the user performs a golf swing, and the measurement device captures the data.

[1164] Step 2:

[1165] The device retrieves the data from the meter:

[1166] The device (smartphone or tablet) receives data from the measuring device via Bluetooth or Wi-Fi. The received data is temporarily stored within the app. The input is head speed and trajectory data, and the output is data stored within the device. Specifically, the device receives data from the measuring device in real time and stores it in dedicated memory within the app.

[1167] Step 3:

[1168] The device sends the measurement data to the server:

[1169] The device sends the stored measurement data to the cloud server. The data sent includes the user ID, measurement date and time, and measurement details, and is encrypted. The input is the measurement data in the device, and the output is the data sent to the server. Specifically, the device transfers the data in a secure format over the network.

[1170] Step 4:

[1171] The server saves the data to the database:

[1172] The server validates the data it receives and checks for any invalid data. It then stores the data in the database. The input is the data sent to the server, and the output is the data stored in the database. Specifically, the server checks the integrity of the data and stores it in the database in the correct format.

[1173] Step 5:

[1174] The server inputs the data into the AI ​​analytics engine:

[1175] The server inputs the saved swing data into the AI ​​analysis engine, which then preprocesses the data and begins analysis. The input is the swing data retrieved from the database, and the output is the data passed to the AI ​​analysis engine. Specifically, the server converts the data into the required format and passes it to the AI ​​analysis engine.

[1176] Step 6:

[1177] AI-generated advice:

[1178] The AI ​​analysis engine analyzes the data and generates advice for the user to improve their technique. Specific advice might be, "Lowering the angle of your right shoulder by 5 degrees while swinging will improve your accuracy." The input is preprocessed swing data, and the output is specific advice. In concrete terms, the AI ​​analysis engine uses a machine learning model to analyze the data and generate advice.

[1179] Step 7:

[1180] The server sends the generated advice to the user's device:

[1181] The advice generated by the server is sent to the user's device via the cloud. The user's device receives the advice and notifies the user within a dedicated app. The input is the advice generated on the server, and the output is the advice displayed on the user's device. Specifically, the server sends data via the network, and the device displays the received data on the user interface.

[1182] Step 8:

[1183] The device recognizes the user's emotions:

[1184] The user device is equipped with emotion recognition devices such as a camera and microphone, which are used to analyze the user's facial expressions and tone of voice to recognize emotions. The input is the user's facial expressions and voice audio data, and the output is recognized emotion data. Specifically, the emotion recognition software collects and analyzes data from the device in real time.

[1185] Step 9:

[1186] Emotion engine adapts advice:

[1187] The emotion engine adapts the advice it generates based on the user's emotion data. For example, if the user is feeling stressed, it will provide gentle advice and suggest ways to relax. The input is emotion data and advice, and the output is the adapted advice. Specifically, the emotion engine analyzes the emotion data and adjusts the content of the advice.

[1188] Step 10:

[1189] The server recommends products based on the results of AI analysis:

[1190] The server references product information in the database and recommends optimal sporting goods based on AI analysis results and emotional data. The input is the AI ​​analysis results and emotional data, and the output is recommended product information. Specifically, the server queries the database and extracts product information that best suits the user's characteristics.

[1191] Step 11:

[1192] The server analyzes the user's emotional data and selects advertisements:

[1193] The server analyzes past swing data, behavioral data, and emotional data, and selects advertisements based on the user's interests, behavioral patterns, and emotional state. The input is past data and emotional data, and the output is selected advertisement information. Specifically, the server selects the most appropriate advertisement from the history database and current emotional data.

[1194] Step 12:

[1195] Display ads on user devices:

[1196] The server sends the selected advertisement to the user's device via the cloud, and the device displays the advertisement in the appropriate location within the app. The input is the advertisement information sent from the server, and the output is the advertisement displayed on the user's device. Specifically, the user can click on the advertisement of interest and access the website for more information or to purchase.

[1197] (Application example 2)

[1198] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1199] Conventional golf training systems provide advice to improve skills based on a user's swing data, but generate uniform advice without considering the user's emotional state, which can reduce the user's motivation and the quality of the experience. Furthermore, when recommending the best golf clubs and balls for a user, the systems do not consider emotional data, making it impossible to provide products that are optimal for the user's current psychological state. As a result, maximizing the user experience is rarely achieved.

[1200] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring user emotion data, inputting the data to a recognition engine for analysis, means for the emotion recognition engine to optimize advice based on the user's emotional state, and means for recommending the most suitable golf clubs and balls to the user based on the user's emotion data and the AI ​​analysis results. This enables personalized advice and product recommendations that take the user's emotional state into consideration.

[1201] The "means for measuring a user's golf swing and acquiring head speed and trajectory data" refers to a device or method for measuring head speed and trajectory data in real time when a user makes a golf swing.

[1202] The "means for transmitting acquired data to a cloud server" refers to a device or method for securely transmitting the measured head speed and trajectory data to a cloud server via the Internet.

[1203] "Means for storing data in a database on a cloud server and inputting the data into an AI analysis engine" refers to a device or method that receives data on the cloud, stores it in a database in an appropriate format, and inputs it into an AI analysis engine.

[1204] The "means by which an AI analysis engine generates advice for improving a user's technique" refers to an artificial intelligence technology that analyzes inputted swing data of a user and generates specific advice for improving technique.

[1205] The "means for transmitting the generated advice to the user terminal and displaying it" refers to a method for transmitting the advice generated by the cloud server to the user terminal and notifying or displaying it on the user terminal.

[1206] "Means for recommending optimal golf clubs and balls to users based on AI analysis results" refers to a method for selecting and recommending golf clubs and balls that are suitable for the user's swing characteristics and skill level based on analyzed data.

[1207] "Means for acquiring user emotion data and inputting it into a recognition engine for analysis" refers to a device or method for acquiring emotion information using a device such as a user's camera or microphone, and inputting it into a recognition engine for analysis.

[1208] "Means for the emotion recognition engine to optimize advice based on the user's emotional state" refers to a method in which the emotion recognition engine optimizes the content based on the user's emotional data, and provides advice in gentle words to a user who is feeling stressed, for example.

[1209] "Means for recommending golf clubs and balls that are optimal for a user based on the user's emotional data and AI analysis results" refers to a method for combining the user's emotional data with the results of AI analysis to recommend golf clubs and balls that are optimal for the user's emotional state.

[1210] "Means for analyzing user behavioral data and emotional data and displaying appropriate advertisements on the user terminal" refers to a method for analyzing a user's past behavioral data and emotional data and displaying highly relevant advertisements on the user terminal.

[1211] An embodiment of the present invention is a system that acquires golf swing data of a user, provides advice for improving technique, and personalizes advice and recommended products using emotion data.

[1212] System configuration

[1213] The system consists of the following components:

[1214] 1. User device: Use a smartphone or tablet. iPhone (iOS 14 or later) or Android (Android 11 or later) is recommended.

[1215] 2. Measurement device: Golf swing measurement device. Use one that can connect via Bluetooth or Wi-Fi.

[1216] 3. Cloud server: Based on AWS (Amazon Web Services), it uses EC2 instances and RDS (relational database service).

[1217] 4. AI analytics engine: Use TensorFlow or PyTorch.

[1218] 5. Emotion Engine: Use the Affectiva SDK or Microsoft Azure's Emotion API.

[1219] Program processing

[1220] When a user performs a golf swing, the measuring device measures head speed and trajectory data and sends it to a smartphone, which then encrypts and transmits the data to a cloud server, where it is received and stored in a database.

[1221] The cloud server inputs the saved swing data into an AI analysis engine and generates advice to improve the user's technique. The advice is then sent to the user's device and displayed on the device.

[1222] The emotion engine uses the camera and microphone installed on the user's device to capture and analyze the user's emotional data in real time. The emotion recognition engine analyzes the user's emotional state and optimizes the advice and recommended products generated by the AI.

[1223] Specific examples

[1224] A user measures their head speed using a swing measuring device at a golf driving range and sends the measurement results to their smartphone. The smartphone app sends the data to a cloud server, where an AI analysis engine generates advice to improve their technique. The smartphone camera recognizes the user's facial expressions, and the emotion engine optimizes the advice based on the analysis results. For example, if the user is feeling stressed, the system will provide gentle advice.

[1225] The system also recommends the best golf clubs and balls for each user based on their emotional data and the results of AI analysis, and analyzes their behavioral and emotional data to display highly relevant advertisements on their devices.

[1226] Prompt Sentence Examples

[1227] A user uses a golf swing monitor to collect head speed and trajectory data. The emotion engine performs real-time emotion recognition and recommends the best golf clubs and balls. Also, display appropriate advertisements based on the user's emotional state.

[1228] In this way, embodiments of a system can be realized that allow for personalized advice and product recommendations that take into account the emotional state of the user.

[1229] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1230] Step 1:

[1231] The user performs a golf swing. The user uses a golf swing measurement device to obtain head speed and trajectory data in real time. The device transmits this data to a smartphone via Bluetooth or Wi-Fi. The input is the user's swing motion, and the output is head speed and trajectory data.

[1232] Step 2:

[1233] The device receives the measurement data and sends it to the cloud server. The smartphone or tablet encrypts the data received from the measuring device and sends it to the cloud server via a secure communication protocol (e.g., HTTPS). The input is the data obtained from the measuring device, and the output is the encrypted data.

[1234] Step 3:

[1235] The server stores the received data in a database. The cloud server validates the received data and checks for any invalid data. It then converts it into an appropriate format and stores it in a database (e.g., AWS RDS). The input is encrypted measurement data, and the output is the data stored in the database.

[1236] Step 4:

[1237] The server inputs the data into an AI analysis engine and generates advice for improving technique. The cloud server inputs the saved swing data into an AI analysis engine (e.g., TensorFlow) for analysis. The input is the swing data saved in the database, and the output is the analysis results and advice.

[1238] Step 5:

[1239] The server sends the generated advice to the user's device and displays it. The server also sends the generated advice to the user's device and notifies them within a dedicated app. The input is the advice from the AI ​​analysis engine, and the output is the advice displayed to the user.

[1240] Step 6:

[1241] The device acquires the user's emotional data and sends it to the emotion engine. The smartphone's camera and microphone are used to capture the user's facial expressions and voice in real time. The data is sent to the emotion engine for analysis. The input is the emotional data acquired by the camera and microphone, and the output is the analyzed emotional state.

[1242] Step 7:

[1243] The emotion recognition engine optimizes advice based on the user's emotional state. Based on the analysis results, the emotion engine adapts the advice generated by the AI ​​analysis engine to the user's emotional state. The input is the analysis results based on emotional data, and the output is optimized advice.

[1244] Step 8:

[1245] The server recommends the most suitable golf clubs and balls based on the user's emotional data and the results of AI analysis. The cloud server analyzes the emotional data and the results of AI analysis and recommends the most suitable golf clubs and balls to the user. The input is the emotional data and the results of AI analysis, and the output is the recommended product.

[1246] Step 9:

[1247] The server analyzes the user's behavioral and emotional data and displays appropriate advertisements on the user's device. The cloud server analyzes past behavioral and emotional data and displays advertisements based on the user's interests and emotional state. The input is the user's behavioral and emotional data, and the output is the advertisement to be displayed.

[1248] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1249] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1250] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1251] [Fourth embodiment]

[1252] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1253] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1254] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1255] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1256] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1257] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1258] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1259] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1260] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1261] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1262] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1263] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1264] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1265] This invention relates to a system that utilizes a user's golf swing data to help improve their technique, and also recommends optimal golf clubs and balls and displays advertisements. The system is composed of a user terminal, a cloud server, an AI analysis engine, and a database.

[1266] Measuring head speed and trajectory

[1267] User performs a golf swing:

[1268] Users use a dedicated golf swing measuring device at a driving range or at home. This measuring device has the ability to collect head speed and trajectory data in real time. Users install a dedicated app on their smartphone or tablet, which connects to the measuring device.

[1269] The device retrieves the data from the meter:

[1270] The measuring device measures clubhead speed and trajectory data and transmits the data via Bluetooth or Wi-Fi to the user's device (smartphone or tablet), which temporarily stores the data and uploads it to a cloud server when the measurement session is over.

[1271] Data transmission and storage

[1272] The device sends the measurement data to the server:

[1273] The user device transmits the acquired head speed and trajectory data to the cloud server, along with related information such as the user ID and the measurement date and time.

[1274] The server saves the data to the database:

[1275] The server validates the data received, checks for any irregularities, and stores it in a database that serves as the basis for future analysis, recommendations, and advertising.

[1276] AI-powered analysis and advice generation

[1277] The server inputs the data into the AI ​​analytics engine:

[1278] The cloud server inputs the stored data into an AI analysis engine, which uses deep learning and machine learning algorithms to analyze the data and generate advice on how to improve the user's skills.

[1279] AI-generated advice:

[1280] The AI ​​analysis engine uses the user's past and current data to automatically generate advice on how to improve their technique, such as suggesting adjustments to the angle of their swing or recommending specific training methods.

[1281] The server sends the advice to the user's device:

[1282] The generated advice is sent to the user's device via a cloud server, where the user can view the advice via a dedicated app on their smartphone or tablet.

[1283] Golf club and ball recommendations

[1284] The server recommends products based on the results of AI analysis:

[1285] Based on the results of the AI ​​analysis engine, the server refers to a database of known products to recommend the best golf clubs and balls for the user. Product selection is based on swing data, head speed, trajectory data, etc.

[1286] The recommendations are displayed on the user's device:

[1287] The recommended product information is sent to the user's device via a cloud server, and the user can check detailed information about the recommended golf clubs and balls through a dedicated app.

[1288] Advertisement display

[1289] The server analyzes the collected data and selects advertisements:

[1290] The cloud server analyzes the user's swing data and past behavioral data to select appropriate advertisements. This advertisement selection utilizes AI technology, and advertisements are automatically selected based on the user's interests.

[1291] Display ads on user devices:

[1292] The selected advertisements are sent to the user's device via a cloud server, and the user can view them through a dedicated app. For example, if a user is looking for beginner golf clubs, an advertisement based on that information will be displayed.

[1293] As described above, the system of the present invention utilizes the user's golf swing data in a variety of ways to support skill improvement, as well as to provide optimal product recommendations and effective advertising displays.

[1294] The processing flow will be explained below.

[1295] Step 1:

[1296] The user performs a golf swing

[1297] The user uses a dedicated golf swing measurement device at a driving range or at home. The device has the ability to acquire head speed and trajectory data in real time. The user installs a dedicated app on their smartphone or tablet and sets it to measurement mode.

[1298] Step 2:

[1299] The device acquires the data from the measuring device.

[1300] The device (smartphone or tablet) receives data from the measurement device via Bluetooth or Wi-Fi, and temporarily stores the received head speed and trajectory data in the app.

[1301] Step 3:

[1302] The device sends the measurement data to the server

[1303] The device sends the stored measurement data to the cloud server. The data sent includes the user ID, measurement date and time, and measurement details. The data is encrypted and sent securely.

[1304] Step 4:

[1305] The server saves the data to a database

[1306] The cloud server validates the received data to check for any invalid data, and after the data validation is complete, the server stores the data in the appropriate table in the database.

[1307] Step 5:

[1308] The server inputs the data into the AI ​​analysis engine

[1309] The server inputs the saved swing data into the AI ​​analysis engine. The swing data includes head speed, trajectory angle, swing amplitude, etc. The AI ​​then preprocesses the data and begins analysis.

[1310] Step 6:

[1311] AI generates advice

[1312] The AI ​​analysis engine analyzes the data and generates advice for the user to improve their technique. Based on the analysis results, specific advice is generated, including swing improvements and practice methods. Example: "Your accuracy will improve if you swing with your right shoulder angle lowered by 5 degrees."

[1313] Step 7:

[1314] The server sends the advice to the user terminal.

[1315] The server sends the generated advice to the user's device. The user's device receives the advice and notifies the user within a dedicated app. The user can then browse the app to view the detailed advice content.

[1316] Step 8:

[1317] The server recommends products based on the results of AI analysis.

[1318] The server references product information in the database and recommends the best golf clubs and balls for each user based on the results of AI analysis. Products are selected based on the user's swing characteristics and skill level.

[1319] Step 9:

[1320] Recommendation results are displayed on the user's device

[1321] The server sends the recommended product information to the user's device, which displays the recommended golf clubs and balls in the app. The user can view details of the recommended products and is also provided with information such as a purchase link.

[1322] Step 10:

[1323] The server analyzes the collected data and selects advertisements

[1324] The server analyzes past swing data and behavioral data to select advertisements based on the user's interests and behavioral patterns, and uses appropriate AI algorithms to maximize the relevance of the advertisements.

[1325] Step 11:

[1326] Displaying advertisements on user devices

[1327] The server sends the selected advertisements to the user's device, which then displays them in the appropriate location within the app. Users can click on the advertisements they find interesting to access more information or purchase information.

[1328] Example 1

[1329] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1330] Conventional golf swing analysis systems lack a comprehensive system that not only supports users' skill improvement but also recommends optimal golf equipment and displays effective advertisements. As a result, users are forced to use multiple devices and apps simultaneously, lacking a means to efficiently improve their swing technique. Furthermore, there is no established method for providing more accurate advice and recommendations by integrating and analyzing a user's swing data with past behavioral data.

[1331] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1332] In this invention, the server includes: means for measuring a user's golf swing and acquiring head speed and trajectory data; means for transmitting the acquired data to a cloud server via a terminal; means for the cloud server to store the data in a database and verify invalid data; means for the cloud server to input the stored data to an AI analysis engine; means for the AI ​​analysis engine to generate advice for improving the user's technique using a deep learning or machine learning algorithm; means for transmitting the generated advice to the user's terminal via the cloud server and displaying it; means for referring to a known product database based on the AI ​​analysis results to recommend the most suitable golf equipment to the user; and means for analyzing user behavior data, selecting appropriate advertisements, and displaying them on the user's terminal. This allows users to receive comprehensive support for improving their swing technique through a single system, and also enables them to receive highly accurate product recommendations and advertisements based on their individual data.

[1333] "User" refers to a person who uses a golf swing measuring device and receives analysis of swing data and advice on improving technique.

[1334] "Device" refers to an electronic device such as a smartphone or tablet that is used to receive and temporarily store data obtained from a golf swing measurement device and send it to a cloud server.

[1335] "Cloud server" refers to a group of servers accessible via the Internet that provide functions such as data storage, analysis, advice generation, product recommendations, and advertisement selection.

[1336] "Head speed" is an index that indicates how fast the head of a golf club moves during a swing.

[1337] "Trajectory data" refers to data that indicates the angle and trajectory of a golf ball when it is hit.

[1338] "AI analysis engine" refers to a software engine that uses deep learning and machine learning algorithms to analyze a user's swing data and generate advice on improving technique and product recommendations.

[1339] "Database" refers to a data structure for systematically managing user swing data, analysis results, product information, etc. stored on a cloud server.

[1340] "Advice for improving technique" refers to specific suggestions and training methods for improving the user's swing technique.

[1341] "Golf equipment" refers to tools such as golf clubs and balls used by users to play golf.

[1342] "Advertising" refers to promotional content that provides information about appropriate products and services based on user interests and behavioral data.

[1343] "Behavioral data" refers to data that indicates the user's behavioral history, such as the user's past swing data and operation history within the app.

[1344] This invention relates to a system that utilizes golf swing data to support skill improvement, recommends optimal golf equipment, and displays advertisements. This system is composed of a user terminal, a cloud server, an AI analysis engine, and a database.

[1345] First, the user performs a golf swing. The user uses a dedicated golf swing measuring device at home or at a golf driving range. This measuring device has the function of acquiring head speed and trajectory data in real time. The user connects to the measuring device via a dedicated app installed on a smartphone or tablet.

[1346] The device then receives the data from the measuring device. The measuring device measures head speed and trajectory data and transmits the data via Bluetooth or Wi-Fi to the user's device (smartphone or tablet). The device temporarily stores the received data and uploads it to a cloud server when the measurement session is over.

[1347] The cloud server is responsible for transmitting and storing the data. The user device sends the acquired head speed and trajectory data to the cloud server. This data includes relevant information such as the user ID and measurement date and time. The server verifies the received data, checks for any fraudulent data, and stores it in a database. This data serves as the basis for future analysis, recommendations, and advertising displays.

[1348] After the data is saved, the server inputs it into the AI ​​analysis engine. The cloud server passes the saved data to the AI ​​analysis engine, which then analyzes the data using deep learning and machine learning algorithms to generate advice on how to improve the user's skills.

[1349] AI generates advice. The AI ​​analysis engine automatically generates advice to improve a user's technique based on their past and current data. For example, it may suggest adjusting the angle of their swing or recommend a specific training method. The generated advice is sent to the user's device via a cloud server, and the user can view the advice via a dedicated app on their smartphone or tablet.

[1350] Next, the server recommends products based on the AI ​​analysis results. Based on the results of the AI ​​analysis engine, the server refers to a database of known products to recommend the most suitable golf clubs and balls for the user. Products are selected based on swing data, head speed, trajectory data, etc. Recommended product information is sent to the user's device via a cloud server, and the user can check detailed information about the recommended golf clubs and balls through a dedicated app.

[1351] The server also analyzes the collected data and selects advertisements. The cloud server analyzes the user's swing data and past behavioral data to select appropriate advertisements. This advertisement selection utilizes AI technology, which automatically selects advertisements based on the user's interests. The selected advertisements are sent to the user's device via the cloud server, and the user can view them through a dedicated app. For example, if a user is looking for clubs for beginners, an advertisement based on that information will be displayed.

[1352] As a concrete example, the following is an example of a prompt sentence to be input to a generative AI model:

[1353] "Please give me some advice on improving my technique based on my golf swing data."

[1354] "Please analyze my swing data and recommend the right golf clubs for me."

[1355] "Show me ads based on swing data."

[1356] As described above, the system of the present invention utilizes the user's golf swing data in a variety of ways to support skill improvement, as well as to provide optimal product recommendations and effective advertising displays.

[1357] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1358] Step 1:

[1359] The user performs a golf swing

[1360] A user uses a dedicated golf swing measurement device at a driving range or at home. This measurement device has the ability to acquire head speed and trajectory data in real time. The input is the user's swing motion, and the output is the measured head speed and trajectory data. For example, when a user swings with a driver, the head speed is recorded as 40 m / s and the trajectory is 15 degrees.

[1361] Step 2:

[1362] The device acquires the data from the measuring device.

[1363] The measuring device measures head speed and trajectory data and transmits the data to the user's device via Bluetooth or Wi-Fi. The device temporarily stores the received data. The input is the data transmitted from the measuring device, and the output is the temporarily stored swing data. For example, data such as "Session 1: head speed = 40 m / s, trajectory = 15 degrees" is stored on the device.

[1364] Step 3:

[1365] The device sends the measurement data to the server

[1366] The user device sends the saved measurement data to the cloud server. The sent data includes related information such as the user ID, measurement date and time, head speed, and trajectory. The input is the temporarily saved swing data, and the output is the swing data sent to the cloud server. For example, the following data is sent: "User ID: 123, Date and time: 2023-01-01, Head speed: 40 m / s, Trajectory: 15 degrees."

[1367] Step 4:

[1368] The server saves the data to a database

[1369] The server validates the received data and checks for any invalid data. The data is then saved in the database. The input is the swing data sent to the cloud server, and the output is the swing data saved in the database. For example, the following data is saved in the database: "User ID: 123, Date and Time: 2023-01-01, Head Speed: 40 m / s, Trajectory: 15 degrees."

[1370] Step 5:

[1371] The server inputs the data into the AI ​​analysis engine

[1372] The cloud server passes the stored data to the AI ​​analysis engine. The input is the swing data stored in the database, and the output is the data input to the AI ​​analysis engine. This transfer occurs periodically or is triggered when the user requests advice.

[1373] Step 6:

[1374] AI generates advice

[1375] The AI ​​analysis engine analyzes the input data and generates advice to improve the user's technique. The input is the swing data entered into the AI ​​analysis engine, and the output is the generated advice. For example, specific advice such as "Start your swing faster to improve head speed" is generated.

[1376] Step 7:

[1377] The server sends the advice to the user terminal.

[1378] The server sends the generated advice to the user's device. The input is the generated advice, and the output is the advice sent to the user's device. The user receives a notification through a dedicated app and can view the details of the advice. For example, a notification such as "New advice has arrived: Practice starting your swing faster" may be displayed.

[1379] Step 8:

[1380] The server recommends products based on the results of AI analysis.

[1381] The server refers to a known product database to recommend the best golf clubs and balls to the user based on the results of the AI ​​analysis engine. The input is the results of the AI ​​analysis engine, and the output is a list of recommended golf equipment. For example, a recommendation may be made such as, "The best driver for you is the ABC model from XYZ company."

[1382] Step 9:

[1383] Recommendation results are displayed on the user's device

[1384] The server sends the recommended product information to the user's device and displays it to the user through a dedicated app. The input is the recommendation result sent from the server, and the output is the product information displayed on the user's device. For example, a message such as "The recommended screwdriver is the ABC model from XYZ. Click here for details" is displayed.

[1385] Step 10:

[1386] The server analyzes the collected data and selects advertisements

[1387] The server analyzes the user's swing data and past behavioral data to select appropriate advertisements. The input is the user's behavioral data, and the output is the selected advertisement. Using AI technology, advertisements are automatically selected based on the user's interests. For example, an advertisement such as "Here are the golf training products that are perfect for you" is selected.

[1388] Step 11:

[1389] Displaying advertisements on user devices

[1390] The server sends the selected advertisement to the user's device and displays it on a dedicated app. The input is the advertisement sent from the server, and the output is the advertisement displayed on the user's device. Users can tap on an advertisement that interests them to check details or purchase it. For example, an advertisement such as "20% off new golf training equipment! Click here for details" may be displayed.

[1391] (Application example 1)

[1392] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1393] Conventional golf swing assistant systems focus on recommending golf clubs and balls and displaying advertisements when helping users improve their technique, but do not support real-time training method suggestions. This makes it difficult for users to instantly obtain the information they need to improve their swing, making it difficult to achieve effective swing improvement.

[1394] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1395] In this invention, the server includes a means for delivering video content that suggests training methods in real time based on the user's golf swing data, a means for analyzing the user's swing data and behavioral patterns and selecting the most suitable advertisement for each individual user, and a means for transmitting and displaying the generated advice to the user's terminal, thereby enabling the user to instantly watch specific training videos to improve their swing on the spot.

[1396] A "user's golf swing" refers to the process in which a user performs a swing motion using a golf club.

[1397] "Head speed" is the speed achieved by the head portion of a golf club during a swing.

[1398] "Trajectory data" refers to data relating to the flight path, direction, and distance of a golf ball after it is hit.

[1399] A "cloud server" is a remote server for data storage and computation that is accessible from multiple user terminals via the Internet.

[1400] A "database" is a collection of structured data stored within a cloud server.

[1401] An "AI analysis engine" is software that uses machine learning algorithms and deep learning technology to analyze input data and derive results.

[1402] "Advice" refers to specific instructions and suggestions for improving golf swing technique generated by the AI ​​analysis engine.

[1403] A "user terminal" is an electronic device used by a user, such as a smartphone or tablet.

[1404] The "means for recommending golf clubs and balls" is a system that selects and displays the optimal golf clubs and balls based on the user's swing data.

[1405] "Means for displaying advertisements on user terminals" refers to a mechanism for displaying advertisements selected based on user behavior data on user terminals.

[1406] "Video content that suggests training methods in real time" is a service that provides training videos that can be viewed on the spot based on the user's golf swing data.

[1407] This invention is a system that utilizes a user's golf swing data to help improve their technique. This system consists of a user terminal, a cloud server, an AI analysis engine, and a database. Each component and its specific operation are explained below.

[1408] User terminal and measuring instrument

[1409] Users use a dedicated golf swing measuring device at a driving range or at home. This measuring device has the ability to acquire head speed and trajectory data in real time. Users install a dedicated app on their smartphone or tablet and connect it to the measuring device. The measuring device measures head speed and trajectory data and transmits the data to the user's device via Bluetooth or Wi-Fi. The device temporarily stores the received data and uploads it to a cloud server when the measurement session is over.

[1410] Cloud Servers and Databases

[1411] The cloud server receives the clubhead speed and trajectory data sent from the user's device. This data includes relevant information such as the user ID and the measurement date and time. The server verifies the received data, checks for any fraudulent data, and stores it in a database. This data serves as the basis for future analysis, recommendations, and advertisement display.

[1412] AI-powered analysis and advice generation

[1413] The cloud server inputs the stored data into an AI analysis engine. The AI ​​analysis engine uses deep learning and machine learning algorithms to analyze the data and generate advice on how to improve the user's technique. The generated advice is sent to the user's device via the cloud server. The user can view the advice via a dedicated app on their smartphone or tablet. The AI ​​analysis engine also suggests specific training methods for improving technique in real time based on the user's past and current data, and distributes them as video content. For example, if it is analyzed that the user's swing is a little overswing, training videos for correcting the swing will be suggested in real time.

[1414] Golf club and ball recommendations

[1415] Based on the results of the AI ​​analysis engine, the cloud server refers to a database of known products to recommend the most suitable golf clubs and balls for the user. Products are selected based on swing data, head speed, trajectory data, etc. Recommended product information is sent to the user's device via the cloud server, and the user can check detailed information about the recommended golf clubs and balls through a dedicated app.

[1416] Advertisement display

[1417] The cloud server analyzes the user's swing data and past behavioral data to select appropriate advertisements. This selection utilizes AI technology, which automatically selects advertisements based on the user's interests. The selected advertisements are sent to the user's device via the cloud server, and the user can view them through a dedicated app. For example, if a user is looking for clubs for beginners, an advertisement based on that information will be displayed.

[1418] Specific examples

[1419] For example, if the head speed is 120 m / s and the trajectory is high, the AI ​​will compare it with past data and generate advice such as "adjust the way you pull your arms" and display a link to the corresponding training video.An example of a prompt sentence is "Please advise on specific training methods to improve technique based on the user's golf swing data."

[1420] As described above, the present invention utilizes a user's golf swing data in a variety of ways to support skill improvement, as well as to realize optimal product recommendations and effective advertisement displays.

[1421] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1422] Step 1:

[1423] The user makes a golf swing. The user uses a dedicated golf swing measuring device at a golf driving range or at home to measure the swing. The data acquired at this time is head speed and trajectory data. The user installs a dedicated app on a smartphone or tablet and connects to the measuring device via Bluetooth or Wi-Fi.

[1424] Step 2:

[1425] The device receives the data from the measuring device. The device transmits the measured head speed and trajectory data to the user's device via Bluetooth or Wi-Fi. The device temporarily stores the received data and prepares it for the next step.

[1426] Step 3:

[1427] The user device sends the measurement data to the cloud server. The device sends the acquired head speed and trajectory data to the cloud server, and this data includes related information such as the user ID and measurement date and time. Input data: head speed, trajectory data, user ID, measurement date and time. Output data: data sent to the cloud server.

[1428] Step 4:

[1429] The server saves the data in the database. The cloud server verifies the received data and checks for any invalid data before saving it in the database. Input data: Data sent to the cloud server. Output data: Data saved in the database.

[1430] Step 5:

[1431] The server inputs the data into the AI ​​analysis engine. The cloud server inputs the saved data into the AI ​​analysis engine. Input data: Data saved in the database. Output data: Data input into the AI ​​analysis engine.

[1432] Step 6:

[1433] The AI ​​analysis engine generates advice to help users improve their technique. The AI ​​analysis engine uses deep learning and machine learning algorithms to analyze data, identify trends and problems in the user's swing, and generate specific advice to improve their technique. Input data: Data entered into the AI ​​analysis engine. Output data: Generated advice.

[1434] Step 7:

[1435] The server sends the generated advice to the user's device and displays it. The generated advice is sent to the user's device via the cloud server and displayed to the user through a dedicated app. Input data: Generated advice. Output data: Advice displayed on the user's device.

[1436] Step 8:

[1437] The server recommends the most suitable golf clubs and balls to the user based on the results of the AI ​​analysis. Based on the results of the AI ​​analysis engine, the server selects the most suitable golf clubs and balls from the database. Input data: AI analysis results. Output data: Recommended product information.

[1438] Step 9:

[1439] The server analyzes the user's behavioral data and displays appropriate advertisements on the user's device. The cloud server analyzes the user's swing data and past behavioral data, selects advertisements that match the user's interests and concerns, and sends them to the user's device. Input data: User's behavioral data. Output data: Advertisements displayed on the user's device.

[1440] Step 10:

[1441] The server delivers video content that suggests training methods in real time based on the user's golf swing data. The AI ​​analysis engine selects real-time training videos based on the user's swing data and sends them to the user's device. Input data: User's golf swing data. Output data: Video content delivered to the user's device.

[1442] Through the above steps, the present invention utilizes the user's golf swing data in a variety of ways to support skill improvement, as well as to provide optimal product recommendations and effective advertising displays.

[1443] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1444] This invention relates to a system that utilizes a user's golf swing data to recommend optimal golf clubs and balls and display advertisements to help improve skills, combined with an emotion engine that recognizes the user's emotions. The system is composed of a user terminal, a cloud server, an AI analysis engine, an emotion engine, and a database.

[1445] Measuring head speed and trajectory

[1446] User performs a golf swing:

[1447] The user uses a dedicated golf swing measurement device at a driving range or at home. The device has the ability to acquire head speed and trajectory data in real time. The user installs a dedicated app on their smartphone or tablet and sets it to measurement mode.

[1448] The device retrieves the data from the meter:

[1449] The device (smartphone or tablet) receives data from the measurement device via Bluetooth or Wi-Fi, and temporarily stores the received head speed and trajectory data in the app.

[1450] Data transmission and storage

[1451] The device sends the measurement data to the server:

[1452] The device sends the stored measurement data to the cloud server. The data sent includes the user ID, measurement date and time, and measurement details. The data is encrypted and sent securely.

[1453] The server saves the data to the database:

[1454] The cloud server validates the received data to check for any invalid data, and after the data validation is complete, the server stores the data in the appropriate table in the database.

[1455] AI-powered analysis and advice generation

[1456] The server inputs the data into the AI ​​analytics engine:

[1457] The cloud server inputs the saved swing data into the AI ​​analysis engine. The swing data includes head speed, trajectory angle, swing amplitude, etc. The AI ​​then preprocesses the data and begins analysis.

[1458] AI-generated advice:

[1459] The AI ​​analysis engine analyzes the data and generates advice for the user to improve their technique. Based on the analysis results, specific advice is generated, including swing improvements and practice methods. Example: "Your accuracy will improve if you swing with your right shoulder angle lowered by 5 degrees."

[1460] Advice display using emotion engine

[1461] The server sends the generated advice to the user's device:

[1462] The generated advice is sent to the user's device via the cloud server. The user's device receives the advice and notifies the user within a dedicated app. The user can then browse the app to view the detailed advice content.

[1463] The device recognizes the user's emotions:

[1464] The user device is equipped with emotion recognition devices such as a camera and microphone, which analyze facial expressions and tone of voice to recognize the user's emotions. The emotion recognition device acquires the user's emotion data in real time, and the emotion engine analyzes the data.

[1465] Emotion engine adapts advice:

[1466] The emotion engine adapts the generated advice based on the user's emotional data. For example, if it detects that the user is feeling stressed, it will provide gentle advice and suggest ways to relax.

[1467] Golf club and ball recommendations

[1468] The server recommends products based on the results of AI analysis:

[1469] The server references product information in the database and recommends the best golf clubs and balls for each user based on the results of AI analysis. Products are selected based on the user's swing characteristics and skill level. Furthermore, emotional data is used to select the best product for the user's current emotional state.

[1470] Advertisement display

[1471] The server analyzes the user's emotional data and selects advertisements:

[1472] The server analyzes past swing data, behavioral data, and emotional data to select advertisements based on the user's interests, behavioral patterns, and emotional state. For example, if the user is showing positive emotions, advertisements based on the user's emotional state will be displayed, such as advertisements for new products.

[1473] Display ads on user devices:

[1474] The selected advertisements are sent to the user's device via the cloud server, and the user's device displays the advertisements in the appropriate location within the app. Users can click on the advertisements they are interested in to access more information or purchase information.

[1475] As described above, the system of the present invention utilizes the user's golf swing data and emotional data in a multifaceted manner to support skill improvement and provide added value such as optimal product recommendations and effective advertising displays.

[1476] The processing flow will be explained below.

[1477] Step 1:

[1478] The user performs a golf swing

[1479] The user uses a dedicated golf swing measurement device at a driving range or at home. The device has the ability to acquire head speed and trajectory data in real time. The user installs a dedicated app on their smartphone or tablet and sets it to measurement mode.

[1480] Step 2:

[1481] The device acquires the data from the measuring device.

[1482] The device (smartphone or tablet) receives data from the measurement device via Bluetooth or Wi-Fi, and temporarily stores the received head speed and trajectory data in the app.

[1483] Step 3:

[1484] The device sends the measurement data to the server

[1485] The device sends the stored measurement data to the cloud server. The data sent includes the user ID, measurement date and time, and measurement details. The data is encrypted and sent securely.

[1486] Step 4:

[1487] The server saves the data to a database

[1488] The cloud server validates the received data to check for any invalid data, and after the data validation is complete, the server stores the data in the appropriate table in the database.

[1489] Step 5:

[1490] The server inputs the data into the AI ​​analysis engine

[1491] The cloud server inputs the saved swing data into the AI ​​analysis engine. The swing data includes head speed, trajectory angle, swing amplitude, etc. The AI ​​then preprocesses the data and begins analysis.

[1492] Step 6:

[1493] AI generates advice

[1494] The AI ​​analysis engine analyzes the data and generates advice for the user to improve their technique. Based on the analysis results, specific advice is generated, including swing improvements and practice methods. Example: "Your accuracy will improve if you swing with your right shoulder angle lowered by 5 degrees."

[1495] Step 7:

[1496] The server sends the generated advice to the user terminal.

[1497] The generated advice is sent to the user's device via the cloud server. The user's device receives the advice and notifies the user within a dedicated app. The user can then browse the app to view the detailed advice content.

[1498] Step 8:

[1499] The device recognizes the user's emotions

[1500] The user device is equipped with emotion recognition devices such as a camera and microphone, which analyze facial expressions and tone of voice to recognize the user's emotions. The emotion recognition device acquires the user's emotion data in real time, and the emotion engine analyzes the data.

[1501] Step 9:

[1502] Emotion engine adapts advice

[1503] The emotion engine adapts the generated advice based on the user's emotional data. For example, if it detects that the user is feeling stressed, it will provide gentle advice and suggest ways to relax.

[1504] Step 10:

[1505] The server recommends products based on the results of AI analysis.

[1506] The server references product information in the database and recommends the best golf clubs and balls for each user based on the results of AI analysis. Products are selected based on the user's swing characteristics and skill level. Furthermore, emotional data is used to select the best product for the user's current emotional state.

[1507] Step 11:

[1508] Recommendation results are displayed on the user's device

[1509] The server sends the recommended product information to the user's device, which displays the recommended golf clubs and balls in the app. The user can view details of the recommended products and is also provided with information such as a purchase link.

[1510] Step 12:

[1511] The server analyzes the user's emotional data and selects advertisements

[1512] The server analyzes past swing data, behavioral data, and emotional data to select advertisements based on the user's interests, behavioral patterns, and emotional state. For example, if the user is showing positive emotions, advertisements based on the user's emotional state will be displayed, such as advertisements for new products.

[1513] Step 13:

[1514] Displaying advertisements on user devices

[1515] The selected advertisements are sent to the user's device via the cloud server, and the user's device displays the advertisements in the appropriate location within the app. Users can click on the advertisements they are interested in to access more information or purchase information.

[1516] Example 2

[1517] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1518] Conventional golf skill improvement systems analyze users' swing data and provide advice to improve their skills, but they have limitations in providing adaptive advice that takes the user's emotional state into account, recommending sports equipment that is optimal for the user, and displaying personalized advertisements.The present invention aims to improve the user experience and increase the accuracy of skill improvement by introducing multifaceted data analysis that includes user emotional data.

[1519] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1520] In this invention, the server includes a means for measuring the user's golf swing and acquiring head speed and trajectory data, a means for transmitting the acquired data to the server via a network, and a means for the server to store the data in a database and input the data into an AI analysis engine, thereby enabling personalized advice on skill improvement, product recommendations, and advertisement display based on user emotion recognition and adaptation.

[1521] (definition statement)

[1522] "User" refers to an individual who performs a golf swing and uses the system.

[1523] "Server" refers to a computer system that receives swing data and emotion data, stores it in a database, and performs AI analysis.

[1524] "Terminal" refers to a portable electronic device such as a smartphone or tablet operated by a user.

[1525] "Head speed" refers to the speed at which the head of a golf club moves during a swing.

[1526] "Trajectory data" refers to information regarding the flight path of a golf ball.

[1527] "Network" refers to a communication environment that enables data communication between a terminal and a server.

[1528] "Database" refers to an information management system for storing received swing data and emotion data.

[1529] "AI analysis engine" refers to an artificial intelligence system that analyzes stored data and generates specific advice on improving swing technique.

[1530] "Emotion engine" refers to a system that has the ability to analyze a user's emotional data and adapt advice and recommendations.

[1531] "Sports equipment" refers to products such as golf clubs and golf balls that are related to a user's golf swing.

[1532] "Advertising" refers to marketing information provided based on user behavioral and emotional data.

[1533] MODE FOR CARRYING OUT THE INVENTION

[1534] The present invention is a system for measuring a user's golf swing and supporting skill improvement, and is configured as follows: The system is composed of a user terminal, a server, an AI analysis engine, an emotion engine, and a database.

[1535] Acquiring golf swing data

[1536] User performs a golf swing:

[1537] A user uses a dedicated golf swing measurement device (e.g., a general-purpose measurement device) at a golf driving range or at home. The measurement device can obtain golf club head speed and golf ball trajectory data in real time. The user installs a dedicated app on their smartphone or tablet and sets it to measurement mode.

[1538] The device retrieves the data from the meter:

[1539] The device (smartphone or tablet) receives data from the measuring device via Bluetooth or Wi-Fi, and the received data is temporarily stored in the app.

[1540] Data transmission and storage

[1541] The device sends the measurement data to the server:

[1542] The device sends the saved measurement data to a server (e.g., a general-purpose cloud server) via a network. The data sent includes the user ID, measurement date and time, and measurement details, and is encrypted before transmission.

[1543] The server saves the data to the database:

[1544] The server validates the received data to check for any invalid data. After the server checks the integrity of the data, it stores the data in a database (e.g., a general-purpose database management system).

[1545] AI analysis and advice generation

[1546] The server inputs the data into the AI ​​analytics engine:

[1547] The server inputs the saved swing data into an AI analysis engine (e.g., a general-purpose AI platform). The input data includes head speed, trajectory angle, and swing amplitude. The AI ​​analysis engine preprocesses the data and begins analysis.

[1548] AI-generated advice:

[1549] An AI analysis engine analyzes the data and generates advice for users to improve their technique, such as "Lowering the angle of your right shoulder by 5 degrees when swinging will improve your accuracy."

[1550] Advice display using emotion engine

[1551] The server sends the generated advice to the user's device:

[1552] The server sends the generated advice to the user's device via the network. The user's device receives the advice and notifies the user within a dedicated app.

[1553] The device recognizes the user's emotions:

[1554] User devices are equipped with emotion recognition devices (e.g., general-purpose emotion recognition technology) such as cameras and microphones. These devices analyze facial expressions and tone of voice to recognize the user's emotions. The emotion data acquired by the emotion recognition devices in real time is analyzed by the emotion engine.

[1555] Emotion engine adapts advice:

[1556] The emotion engine adapts the generated advice based on the user's emotional data. For example, if the user is feeling stressed, it will provide gentle advice and suggest ways to relax.

[1557] Golf club and ball recommendations

[1558] The server recommends products based on the results of AI analysis:

[1559] The server references product information from the database and recommends the most suitable sports equipment (e.g., golf clubs, golf balls) to the user based on the AI ​​analysis results and emotional data.

[1560] Displaying ads

[1561] The server analyzes the user's emotional data and selects advertisements:

[1562] The server analyzes past swing data, behavioral data, and emotional data to select advertisements based on the user's interests, behavioral patterns, and emotional state. For example, if the user shows positive emotions, advertisements for new products will be displayed.

[1563] Display ads on user devices:

[1564] The server sends the selected advertisements to the user's device via the network, and the user's device displays the advertisements in the appropriate location within the app. Users can click on the advertisements they are interested in to access more information or purchase websites.

[1565] Specific examples and prompts for the generative AI model

[1566] Examples:

[1567] The user measured their swing using a general-purpose measuring device at home and a dedicated smartphone app. The measurement data was sent to a cloud server, and the AI ​​analysis engine generated advice such as, "Swinging with your right shoulder angle lowered by 5 degrees will improve accuracy." The emotion engine also recognized that the user was feeling stressed, and provided gentle advice and suggested ways to reduce stress.

[1568] Prompt for the generative AI model:

[1569] "Please explain the process of your system that analyzes golf swing data and emotion data to provide optimal advice to users. Also, please explain how product recommendations and advertisements are displayed taking user emotions into account."

[1570] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1571] Step 1:

[1572] User performs a golf swing:

[1573] A user uses a dedicated golf swing measurement device at a driving range or at home. The measurement device captures head speed and trajectory data in real time during the swing. The input is the user's swing motion, and the output is head speed and trajectory data. Specifically, the user performs a golf swing, and the measurement device captures the data.

[1574] Step 2:

[1575] The device retrieves the data from the meter:

[1576] The device (smartphone or tablet) receives data from the measuring device via Bluetooth or Wi-Fi. The received data is temporarily stored within the app. The input is head speed and trajectory data, and the output is data stored within the device. Specifically, the device receives data from the measuring device in real time and stores it in dedicated memory within the app.

[1577] Step 3:

[1578] The device sends the measurement data to the server:

[1579] The device sends the stored measurement data to the cloud server. The data sent includes the user ID, measurement date and time, and measurement details, and is encrypted. The input is the measurement data in the device, and the output is the data sent to the server. Specifically, the device transfers the data in a secure format over the network.

[1580] Step 4:

[1581] The server saves the data to the database:

[1582] The server validates the data it receives and checks for any invalid data. It then stores the data in the database. The input is the data sent to the server, and the output is the data stored in the database. Specifically, the server checks the integrity of the data and stores it in the database in the correct format.

[1583] Step 5:

[1584] The server inputs the data into the AI ​​analytics engine:

[1585] The server inputs the saved swing data into the AI ​​analysis engine, which then preprocesses the data and begins analysis. The input is the swing data retrieved from the database, and the output is the data passed to the AI ​​analysis engine. Specifically, the server converts the data into the required format and passes it to the AI ​​analysis engine.

[1586] Step 6:

[1587] AI-generated advice:

[1588] The AI ​​analysis engine analyzes the data and generates advice for the user to improve their technique. Specific advice might be, "Lowering the angle of your right shoulder by 5 degrees while swinging will improve your accuracy." The input is preprocessed swing data, and the output is specific advice. In concrete terms, the AI ​​analysis engine uses a machine learning model to analyze the data and generate advice.

[1589] Step 7:

[1590] The server sends the generated advice to the user's device:

[1591] The advice generated by the server is sent to the user's device via the cloud. The user's device receives the advice and notifies the user within a dedicated app. The input is the advice generated on the server, and the output is the advice displayed on the user's device. Specifically, the server sends data via the network, and the device displays the received data on the user interface.

[1592] Step 8:

[1593] The device recognizes the user's emotions:

[1594] The user device is equipped with emotion recognition devices such as a camera and microphone, which are used to analyze the user's facial expressions and tone of voice to recognize emotions. The input is the user's facial expressions and voice audio data, and the output is recognized emotion data. Specifically, the emotion recognition software collects and analyzes data from the device in real time.

[1595] Step 9:

[1596] Emotion engine adapts advice:

[1597] The emotion engine adapts the advice it generates based on the user's emotion data. For example, if the user is feeling stressed, it will provide gentle advice and suggest ways to relax. The input is emotion data and advice, and the output is the adapted advice. Specifically, the emotion engine analyzes the emotion data and adjusts the content of the advice.

[1598] Step 10:

[1599] The server recommends products based on the results of AI analysis:

[1600] The server references product information in the database and recommends optimal sporting goods based on AI analysis results and emotional data. The input is the AI ​​analysis results and emotional data, and the output is recommended product information. Specifically, the server queries the database and extracts product information that best suits the user's characteristics.

[1601] Step 11:

[1602] The server analyzes the user's emotional data and selects advertisements:

[1603] The server analyzes past swing data, behavioral data, and emotional data, and selects advertisements based on the user's interests, behavioral patterns, and emotional state. The input is past data and emotional data, and the output is selected advertisement information. Specifically, the server selects the most appropriate advertisement from the history database and current emotional data.

[1604] Step 12:

[1605] Display ads on user devices:

[1606] The server sends the selected advertisement to the user's device via the cloud, and the device displays the advertisement in the appropriate location within the app. The input is the advertisement information sent from the server, and the output is the advertisement displayed on the user's device. Specifically, the user can click on the advertisement of interest and access the website for more information or to purchase.

[1607] (Application example 2)

[1608] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1609] Conventional golf training systems provide advice to improve skills based on a user's swing data, but generate uniform advice without considering the user's emotional state, which can reduce the user's motivation and the quality of the experience. Furthermore, when recommending the best golf clubs and balls for a user, the systems do not consider emotional data, making it impossible to provide products that are optimal for the user's current psychological state. As a result, maximizing the user experience is rarely achieved.

[1610] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for acquiring user emotion data, inputting the data to a recognition engine for analysis, means for the emotion recognition engine to optimize advice based on the user's emotional state, and means for recommending the most suitable golf clubs and balls to the user based on the user's emotion data and the AI ​​analysis results. This enables personalized advice and product recommendations that take the user's emotional state into consideration.

[1611] The "means for measuring a user's golf swing and acquiring head speed and trajectory data" refers to a device or method for measuring head speed and trajectory data in real time when a user makes a golf swing.

[1612] The "means for transmitting acquired data to a cloud server" refers to a device or method for securely transmitting the measured head speed and trajectory data to a cloud server via the Internet.

[1613] "Means for storing data in a database on a cloud server and inputting the data into an AI analysis engine" refers to a device or method that receives data on the cloud, stores it in a database in an appropriate format, and inputs it into an AI analysis engine.

[1614] The "means by which an AI analysis engine generates advice for improving a user's technique" refers to an artificial intelligence technology that analyzes inputted swing data of a user and generates specific advice for improving technique.

[1615] The "means for transmitting the generated advice to the user terminal and displaying it" refers to a method for transmitting the advice generated by the cloud server to the user terminal and notifying or displaying it on the user terminal.

[1616] "Means for recommending optimal golf clubs and balls to users based on AI analysis results" refers to a method for selecting and recommending golf clubs and balls that are suitable for the user's swing characteristics and skill level based on analyzed data.

[1617] "Means for acquiring user emotion data and inputting it into a recognition engine for analysis" refers to a device or method for acquiring emotion information using a device such as a user's camera or microphone, and inputting it into a recognition engine for analysis.

[1618] "Means for the emotion recognition engine to optimize advice based on the user's emotional state" refers to a method in which the emotion recognition engine optimizes the content based on the user's emotional data, and provides advice in gentle words to a user who is feeling stressed, for example.

[1619] "Means for recommending golf clubs and balls that are optimal for a user based on the user's emotional data and AI analysis results" refers to a method for combining the user's emotional data with the results of AI analysis to recommend golf clubs and balls that are optimal for the user's emotional state.

[1620] "Means for analyzing user behavioral data and emotional data and displaying appropriate advertisements on the user terminal" refers to a method for analyzing a user's past behavioral data and emotional data and displaying highly relevant advertisements on the user terminal.

[1621] An embodiment of the present invention is a system that acquires golf swing data of a user, provides advice for improving technique, and personalizes advice and recommended products using emotion data.

[1622] System configuration

[1623] The system consists of the following components:

[1624] 1. User device: Use a smartphone or tablet. iPhone (iOS 14 or later) or Android (Android 11 or later) is recommended.

[1625] 2. Measurement device: Golf swing measurement device. Use one that can connect via Bluetooth or Wi-Fi.

[1626] 3. Cloud server: Based on AWS (Amazon Web Services), it uses EC2 instances and RDS (relational database service).

[1627] 4. AI analytics engine: Use TensorFlow or PyTorch.

[1628] 5. Emotion Engine: Use the Affectiva SDK or Microsoft Azure's Emotion API.

[1629] Program processing

[1630] When a user performs a golf swing, the measuring device measures head speed and trajectory data and sends it to a smartphone, which then encrypts and transmits the data to a cloud server, where it is received and stored in a database.

[1631] The cloud server inputs the saved swing data into an AI analysis engine and generates advice to improve the user's technique. The advice is then sent to the user's device and displayed on the device.

[1632] The emotion engine uses the camera and microphone installed on the user's device to capture and analyze the user's emotional data in real time. The emotion recognition engine analyzes the user's emotional state and optimizes the advice and recommended products generated by the AI.

[1633] Specific examples

[1634] A user measures their head speed using a swing measuring device at a golf driving range and sends the measurement results to their smartphone. The smartphone app sends the data to a cloud server, where an AI analysis engine generates advice to improve their technique. The smartphone camera recognizes the user's facial expressions, and the emotion engine optimizes the advice based on the analysis results. For example, if the user is feeling stressed, the system will provide gentle advice.

[1635] The system also recommends the best golf clubs and balls for each user based on their emotional data and the results of AI analysis, and analyzes their behavioral and emotional data to display highly relevant advertisements on their devices.

[1636] Prompt Sentence Examples

[1637] A user uses a golf swing monitor to collect head speed and trajectory data. The emotion engine performs real-time emotion recognition and recommends the best golf clubs and balls. Also, display appropriate advertisements based on the user's emotional state.

[1638] In this way, embodiments of a system can be realized that allow for personalized advice and product recommendations that take into account the emotional state of the user.

[1639] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1640] Step 1:

[1641] The user performs a golf swing. The user uses a golf swing measurement device to obtain head speed and trajectory data in real time. The device transmits this data to a smartphone via Bluetooth or Wi-Fi. The input is the user's swing motion, and the output is head speed and trajectory data.

[1642] Step 2:

[1643] The device receives the measurement data and sends it to the cloud server. The smartphone or tablet encrypts the data received from the measuring device and sends it to the cloud server via a secure communication protocol (e.g., HTTPS). The input is the data obtained from the measuring device, and the output is the encrypted data.

[1644] Step 3:

[1645] The server stores the received data in a database. The cloud server validates the received data and checks for any invalid data. It then converts it into an appropriate format and stores it in a database (e.g., AWS RDS). The input is encrypted measurement data, and the output is the data stored in the database.

[1646] Step 4:

[1647] The server inputs the data into an AI analysis engine and generates advice for improving technique. The cloud server inputs the saved swing data into an AI analysis engine (e.g., TensorFlow) for analysis. The input is the swing data saved in the database, and the output is the analysis results and advice.

[1648] Step 5:

[1649] The server sends the generated advice to the user's device and displays it. The server also sends the generated advice to the user's device and notifies them within a dedicated app. The input is the advice from the AI ​​analysis engine, and the output is the advice displayed to the user.

[1650] Step 6:

[1651] The device acquires the user's emotional data and sends it to the emotion engine. The smartphone's camera and microphone are used to capture the user's facial expressions and voice in real time. The data is sent to the emotion engine for analysis. The input is the emotional data acquired by the camera and microphone, and the output is the analyzed emotional state.

[1652] Step 7:

[1653] The emotion recognition engine optimizes advice based on the user's emotional state. Based on the analysis results, the emotion engine adapts the advice generated by the AI ​​analysis engine to the user's emotional state. The input is the analysis results based on emotional data, and the output is optimized advice.

[1654] Step 8:

[1655] The server recommends the most suitable golf clubs and balls based on the user's emotional data and the results of AI analysis. The cloud server analyzes the emotional data and the results of AI analysis and recommends the most suitable golf clubs and balls to the user. The input is the emotional data and the results of AI analysis, and the output is the recommended product.

[1656] Step 9:

[1657] The server analyzes the user's behavioral and emotional data and displays appropriate advertisements on the user's device. The cloud server analyzes past behavioral and emotional data and displays advertisements based on the user's interests and emotional state. The input is the user's behavioral and emotional data, and the output is the advertisement to be displayed.

[1658] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1659] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1660] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1661] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1662] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1663] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1664] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1665] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1666] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1667] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1668] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1669] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1670] In the above embodimen...

Claims

1. A means for measuring a user's golf swing and acquiring head speed and trajectory data; means for transmitting the acquired data to a cloud server; A method for storing data in a database on a cloud server and inputting the data into an AI analysis engine. A means for the AI ​​analysis engine to generate advice for users on improving their skills; means for transmitting the generated advice to a user terminal and displaying the advice; A method to recommend the best golf clubs and balls to users based on the results of AI analysis, A means for analyzing user behavior data and displaying appropriate advertisements on the user terminal; A system including:

2. 10. The system of claim 1, wherein the golf club and ball recommendations are made by referencing a database of known products.

3. 2. The system according to claim 1, wherein the system analyzes swing data and behavioral patterns of users and selects advertisements that are optimal for individual users.

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