System

Abstract

A system is provided.SOLUTION: The system includes a means for acquiring the position information of a user, a means for acquiring environmental data such as the strength and direction of wind and temperature, a means for transmitting the position information and the environmental data, a means for receiving and analyzing the position information and the environmental data, a means for generating optimum golf play advice on the basis of an analysis result, and a means for providing the advice to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] The problem this invention aims to solve is the difficulty for beginner golfers in effectively improving their scores on the golf course due to their lack of experience. Another problem is that golf enthusiasts who cannot afford to hire expensive caddies have limited means of receiving appropriate playing advice in real time. In particular, the current situation is that the skills learned at driving ranges are not reflected in actual course play because environmental variables such as wind and lie conditions cannot be taken into account. [Means for solving the problem]

[0005] To solve this problem, the present invention provides the following means.

[0006] The system grasps the situation in real time by using a means for acquiring user location information and a means for acquiring environmental data such as wind strength, direction, and temperature. It also includes a means for transmitting the location information and environmental data, receiving it on the server side, and analyzing it. It also includes a means for generating optimal golf play advice based on the analysis results and providing it to the user via smart glasses and earphones. It also integrates the user's past play data into the analysis and generates advice that takes into account the user's playing tendencies and skill level. Furthermore, by monitoring the user's movements and environmental changes in real time and providing updated advice according to the situation, even beginners can make appropriate decisions and improve their scores.

[0007] "User" refers to a person who plays golf.

[0008] "Location information" refers to coordinate data of the user's current location.

[0009] "Environmental data" refers to data about external conditions such as wind strength and direction, temperature, and humidity.

[0010] "Acquisition means" refers to sensors and devices used to collect location and environmental data.

[0011] "Transmission means" refers to a communication function for transmitting acquired data to other devices or systems.

[0012] "Receiving means" refers to a function for receiving and analyzing transmitted data.

[0013] "Analysis means" refers to an algorithm or program that generates optimal advice for a user based on the received data.

[0014] "Advice" refers to instructions regarding the club the user should select, the direction to hit, and the strength of the shot when playing golf.

[0015] The "means for providing" refers to a device or system for conveying the generated advice to the user.

[0016] "Past play data" refers to history data of golf plays that the user has performed in the past.

[0017] "Real-time monitoring" refers to the process of continuously monitoring current conditions and changes in environmental conditions.

[0018] "Updated advice" refers to generating new advice tailored to the situation based on real-time monitoring. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

[0027] [First embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0040] DETAILED DESCRIPTION OF THE INVENTION The following describes a mode for carrying out the invention based on the claims.

[0041] System Configuration

[0042] This system consists of a user, a device (smart glasses and earphones), and a server. The device is responsible for acquiring location and environmental data, and the server analyzes the received data to generate optimal advice, which is then provided to the user via the device.

[0043] Initial Setup

[0044] Users download and install the dedicated application onto their smartphone, then register an account and enter their playing profile (such as handicap, favorite club, playing style, etc.), then put on the smart glasses and earphones and pair them with the app using Bluetooth or other means.

[0045] Data collection and transmission

[0046] The device (smart glasses) uses its built-in GPS to obtain the user's current location in real time. It also uses built-in sensors to measure environmental data such as wind strength, direction, and temperature. The obtained data is sent to a server via the smartphone.

[0047] Data analysis and advice generation

[0048] The server receives the transmitted location information and environmental data. It also takes into account the user's past playing data (e.g., previous scores and shot success rates) and analyzes them using a machine learning algorithm. Based on the analysis results, golf play advice appropriate for the current situation (specifically, recommended clubs, shot direction, strength, etc.) is generated.

[0049] Providing advice

[0050] The generated advice is sent to the device in text and audio formats, and visual information is displayed on the smart glasses display, while audio advice is provided through earphones, allowing users to receive appropriate playing strategies in real time.

[0051] Specific examples

[0052] Let's say a user is standing on the tee box of the first hole. The device (smart glasses) acquires their position, wind strength, and direction, and sends them to the server. The server analyzes this data and past play history to generate advice such as "Use a 3-wood and aim for the left side of the fairway." This advice is displayed on the smart glasses' display as "3-wood recommended, aim for the left side of the fairway," and is communicated to the user through the earphones by voice: "The wind is blowing from the right at 5 meters per second. Aim for the left side of the fairway."

[0053] This embodiment of the present invention allows users to receive optimal advice in real time, enabling even beginners to improve their scores in a short period of time.

[0054] The processing flow will be explained below.

[0055] Step 1: User registration and initial setup

[0056] Users install a dedicated application on their smartphone and create an account.

[0057] The user enters their playing profile (handicap, preferred club, playing style, etc.).

[0058] Users wear smart glasses and earphones and pair them with the app via Bluetooth or other means.

[0059] Step 2: Obtaining location information

[0060] The device (smart glasses) uses its built-in GPS function to obtain the user's current location in real time.

[0061] The device (smart glasses) transmits the acquired location information to a server via a smartphone.

[0062] Step 3: Get environment data

[0063] The device (smart glasses) uses built-in sensors to measure environmental data such as wind strength, direction, and temperature.

[0064] The device (smart glasses) sends the measured environmental data to a server via a smartphone.

[0065] Step 4: Receiving and consolidating data

[0066] The server receives the location information and environmental data transmitted from the terminal.

[0067] The server retrieves and integrates the user's past playing data (e.g., previous scores and shot success rates) from a database.

[0068] Step 5: Analyze the data

[0069] The server analyzes the real-time environment and the user's past play history based on the received and integrated data.

[0070] The server uses machine learning algorithms to generate optimal advice (recommended club, shot direction, strength, etc.).

[0071] Step 6: Generating and preparing advice

[0072] The server converts the generated advice into text and audio formats.

[0073] The server prepares the text information to be sent to the smart glasses and the audio information to be sent to the earphones.

[0074] Step 7: Providing advice

[0075] The device (smart glasses) displays the text advice received from the server on the display.

[0076] Example: "3 wood recommended, aim for the left side of the fairway."

[0077] The terminal (earphone) provides the user with the audio advice received from the server.

[0078] Example: "The wind is blowing from the right at 5 meters per second. Aim to the left side of the fairway."

[0079] Step 8: Real-time updates

[0080] The device (smart glasses) monitors changes in the user's location and environmental data in real time.

[0081] The device (smart glasses) sends new data to the server.

[0082] Step 9: Generate and serve update advice

[0083] The server reanalyzes the data and updates the advice as needed.

[0084] The server regenerates the updated advice in text and audio form.

[0085] The devices (smart glasses and earphones) will then provide the updated advice to the user again.

[0086] This is the specific flow of processing. This process allows the user to always receive the most appropriate golf playing advice in real time according to the situation.

[0087] Example 1

[0088] 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."

[0089] When playing golf, it is extremely difficult for users to accurately assess the current playing situation and environmental conditions and develop an optimal strategy. Furthermore, without a way to obtain appropriate advice in real time, the quality of play declines, especially for beginners and inexperienced players. Furthermore, it is difficult to effectively utilize past play data to improve.

[0090] 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.

[0091] In this invention, the server includes means for acquiring user location information, means for acquiring environmental data such as wind strength and direction and temperature, means for transmitting the location information and environmental data, means for receiving and analyzing the location information and environmental data, means for generating optimal sports play advice based on the analysis results, means for providing the advice to the user, means for analyzing the data taking into account the user's past play data, and means for updating the advice in real time based on the analyzed data. This allows the user to receive optimal play advice in real time, thereby improving the quality of their play. Furthermore, using past play data also contributes to improving the user's skills.

[0092] "Means for obtaining user location information" refers to a device that uses the Global Positioning System (GPS) or equivalent technology to determine the user's current location in real time.

[0093] "Means for acquiring environmental data such as wind strength, direction, and temperature" refers to devices that measure the surrounding environmental conditions using environmental sensors such as anemometers, temperature sensors, and wind vanes.

[0094] "Means for transmitting the location information and environmental data" refers to a device or function that transmits this data to a server via wireless communication technology (e.g., Bluetooth, Wi-Fi).

[0095] "Means for receiving and analyzing the location information and environmental data" refers to a series of processes in which the server processes the data received and analyzes it using statistical analysis and machine learning algorithms.

[0096] "Means for generating optimal sports play advice based on analysis results" refers to a function that generates specific advice such as optimal club selection, shot direction, and strength based on analyzed data.

[0097] The "means for providing the advice to the user" refers to a display device or an audio device for conveying the generated advice to the user in text or audio form.

[0098] "Means for performing analysis taking into account the user's past play data" refers to a function that improves the accuracy of analysis by using data such as the user's previous scores and shot success rates.

[0099] "Means for updating advice in real time based on analyzed data" refers to a function that updates the content of advice in a timely manner in response to changes in the environment and situation during play.

[0100] MODE FOR CARRYING OUT THE INVENTION

[0101] This invention is implemented using a system consisting of a user, a device (smart glasses and earphones), and a server. The device is responsible for acquiring the user's location information and environmental data, and the server analyzes the received data to generate optimal advice and provide it to the user through the device.

[0102] Hardware and Software Configuration

[0103] User

[0104] Users download and install a dedicated application onto their smartphone, which then functions as a central device for sending and receiving data.

[0105] Terminal

[0106] The device consists of smart glasses and earphones. The smart glasses use a built-in GPS to determine the user's current location. They also have built-in environmental sensors, such as an anemometer, temperature sensor, and wind vane, to acquire data such as wind strength and direction and temperature. The earphones are a device that provides audio advice to the user.

[0107] server

[0108] The server uses powerful computing resources and specialized software to analyze the received location and environmental data, using statistical analysis software and machine learning algorithms. Based on the analysis results, optimal play advice is generated.

[0109] Data Flow and Processing

[0110] Initial Setup

[0111] Users download and install the dedicated application onto their smartphone. They launch the application, register an account, and enter their playing profile (handicap, favorite club, playing style, etc.). After that, the user puts on the smart glasses and earphones and pairs them with the smartphone application via Bluetooth.

[0112] Data collection and transmission

[0113] When a user starts playing, the smart glasses on the device use their built-in GPS to obtain their current location in real time, while environmental sensors measure data such as wind strength, direction, and temperature. This data is then sent to a server via the smartphone.

[0114] Data analysis and advice generation

[0115] The server analyzes the received location and environmental data using statistical analysis and machine learning algorithms. The server also takes into account the user's past play data (e.g., score, shot success rate). Based on the analysis results, the server generates optimal play advice. The advice is provided in text and audio formats.

[0116] Providing advice

[0117] The generated advice is sent to the device, where visual information (e.g., recommended club, shot direction, etc.) is displayed on the smart glasses display, and audio advice is provided through earphones, allowing the user to receive appropriate playing strategies in real time.

[0118] Specific examples

[0119] For example, say a user is standing on the tee box of the first hole. The device's smart glasses use GPS to pinpoint its location, and environmental sensors measure that a wind is blowing from the right at 5 meters per second. This information is sent to a server via the smartphone. The server analyzes the received data and past play data and generates the advice "Use a 3-wood and aim for the left side of the fairway." This advice is displayed on the smart glasses' display as "3-wood recommended, aim for the left side of the fairway," and is communicated to the user via earphones via voice: "The wind is blowing from the right at 5 meters per second. Aim for the left side of the fairway."

[0120] Prompt Sentence Examples

[0121] If you input the following prompt into the generative AI model, it will return the above specific action description:

[0122] Please explain in detail the process of the smart glasses and earphone system that supports golf play. The system collects location and environmental data, sends it to a server for analysis, and then generates and provides appropriate playing advice to the user. Please explain each processing step, including the specific operation.

[0123] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0124] Step 1: User performs initial setup

[0125] Users download and install the dedicated application onto their smartphone. They launch the application, register an account, and enter their own playing profile (handicap, favorite club, playing style, etc.). They then put on the smart glasses and earphones and pair them with the smartphone application via Bluetooth.

[0126] Input: Smartphone, account information, play profile

[0127] Output: Paired smart glasses and earphones

[0128] Step 2: Device collects data

[0129] When a user starts playing, the smart glasses use their built-in GPS to obtain their current location in real time, while environmental sensors measure data such as wind strength, direction, and temperature. The acquired data is then stored in the smart glasses' internal memory.

[0130] Input: current user location, environmental conditions

[0131] Output: Collected location and environmental data

[0132] Step 3: The device sends the data to the server

[0133] The smart glasses collect location and environmental data and transmit it to a server via a smartphone, using Bluetooth and an internet connection.

[0134] Input: Collected location and environmental data

[0135] Output: Data sent to the server

[0136] Step 4: The server parses the data

[0137] The server receives the location and environmental data, and then analyzes it by integrating it with the user's past play data. Statistical analysis software and machine learning algorithms are used for the analysis. The analysis results in advice tailored to the situation at hand.

[0138] Input: location information, environmental data, past play data

[0139] Output: Best Play Advice

[0140] Step 5: Server generates advice

[0141] The server generates optimal play advice based on the analysis results, including recommended clubs, shot direction, and strength. The generated advice is saved in text and audio formats.

[0142] Input: Analysis results

[0143] Output: Play advice in text and audio format

[0144] Step 6: The server sends the advice to the device

[0145] The server generates text and audio advice and sends it to the smart glasses and earphones via an internet connection and Bluetooth.

[0146] Input: Text and audio advice

[0147] Output: Advice sent to terminal

[0148] Step 7: The device provides advice to the user

[0149] The smart glasses display visual information and provide real-time audio advice through earphones, allowing users to instantly receive appropriate playing strategies.

[0150] Input: Advice sent to terminal

[0151] Output: Visual and audio advice provided to the user

[0152] (Application example 1)

[0153] 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."

[0154] In conventional shopping experiences, it has been difficult for users to efficiently obtain necessary product information in stores and make optimal purchasing decisions. Furthermore, there has been no system that analyzes in-store environmental data and users' purchasing history in real time to provide optimal advice to individuals. This has led to users wasting time and sometimes being unable to find the perfect product. A new system is needed to solve these problems.

[0155] 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.

[0156] In this invention, the server includes means for acquiring user location information, means for acquiring environmental data such as wind strength and direction and temperature, means for acquiring product information to support user decision-making, means for transmitting the location information, environmental data and product information, means for receiving and analyzing the location information, environmental data and product information, means for generating optimal shopping advice based on the analysis results, and means for providing the advice to the user. This enables users to efficiently acquire information and make optimal purchasing decisions even in a physical store.

[0157] "User location information" is geographical coordinate data of the user's current location.

[0158] "Environmental data" refers to data relating to the surrounding conditions of the user's current location, such as wind strength and direction, temperature, and humidity.

[0159] "Product information" is data that includes detailed information about products in a store, such as price, stock status, and promotion information.

[0160] The "data transmission means" is a communication means for sending the acquired location information, environmental data, and product information to the server.

[0161] The "analysis means" is a means having a function of analyzing necessary information based on received data and generating optimal advice.

[0162] "Shopping advice" is information that includes recommendations and instructions to help users make optimal purchasing decisions.

[0163] "User movement" is information indicating changes in the user's position as they move around the store.

[0164] The "advice providing means" is a means for conveying the generated advice to the user, and presents the information visually or audibly.

[0165] System Configuration

[0166] This system consists of a user, a device (smart glasses and earphones), and a server. The device is responsible for acquiring location and environmental data as well as product information, and the server analyzes the received data to generate optimal shopping advice and provide it to the user via the device.

[0167] Initial Setup

[0168] Users download and install the dedicated application on their smartphone, then register an account and enter their user profile (such as purchase history, favorite product categories, alert settings, etc.), then put on the smart glasses and earphones and pair them with the application using Bluetooth or other means.

[0169] Data collection and transmission

[0170] The device (smart glasses) uses its built-in GPS to obtain the user's current location in real time. It also uses sensors in the smart glasses to measure environmental data such as wind strength, direction, and temperature. It also obtains product information for the store. This data is then sent to a server via the smartphone.

[0171] Data analysis and advice generation

[0172] The server receives the transmitted location and environmental data, as well as the product information. It also analyzes the data using machine learning algorithms, taking into account the user's past purchase history and preferences. Based on the analysis results, it generates shopping advice tailored to the current situation (specifically, recommended products, promotion information, product locations within the store, etc.).

[0173] Providing advice

[0174] The generated advice is sent to the device in text and audio formats, with visual information displayed on the smart glasses display and audio advice provided through earphones, allowing users to receive appropriate shopping strategies in real time.

[0175] Hardware and software used

[0176] Smart glasses: Equipped with built-in GPS and sensors to collect location and environmental data, and display visual information.

[0177] Earphones: Provides audio advice.

[0178] Server: Analyzes data and generates advice using machine learning algorithms such as TensorFlow.

[0179] Specific examples

[0180] For example, suppose a user arrives at a clothing section of a store. The smart glasses use GPS to pinpoint their location and measure the ambient temperature and humidity. This data is sent to a server, which generates advice such as, "We recommend the new jackets on sale. They're on the rack on the left," based on the user's past purchasing history and preferences. The smart glasses' display will show "New Jackets Sale - Left Rack," and a voice message will be heard through the earphones saying, "There are new jackets on the rack on the left."

[0181] Example prompts for generative AI models

[0182] "The user is in the clothing department. Based on environmental data, what products should you recommend, taking into account their purchasing history and preferences?"

[0183] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0184] Step 1:

[0185] The user downloads and installs a dedicated application onto their smartphone. Next, the user registers for an account and enters their user profile (purchase history, favorite product categories, alert settings, etc.). This information is entered on the user's smartphone and sent to the server. The input data is stored on the server as the user's account information. The output is user profile data securely stored on the server.

[0186] Step 2:

[0187] The user wears the smart glasses and earphones and pairs them with a dedicated application using Bluetooth. At this time, the system checks whether the smart glasses and earphones are working properly. The input is the user's Bluetooth pairing operation, and the output is a message indicating successful pairing.

[0188] Step 3:

[0189] The device (smart glasses) uses its built-in GPS to obtain the user's current location in real time. In addition, the smart glasses' sensors collect environmental data such as wind strength, direction, and temperature. The input is data from the GPS sensor and environmental sensors, and the output is the obtained location information and environmental data.

[0190] Step 4:

[0191] Obtain product information within the store. Smart glasses communicate with the store's sales floor information system to obtain the latest product information (price, stock status, promotion information, etc.). The input is data from the sales floor information system, and the output is the obtained product information.

[0192] Step 5:

[0193] The device transmits the acquired location information, environmental data, and product information to a server via a smartphone. The input is the connection between the smart glasses and the smartphone, and the output is the transmission of data to the server. The server receives this data.

[0194] Step 6:

[0195] The server integrates and analyzes the received location information, environmental data, product information, and the user's past purchasing history and preference data. The server uses TensorFlow to execute machine learning algorithms and generate optimal shopping advice (recommended products, promotion information, product locations in stores, etc.). The input is various data collected on the server, and the output is advice as the result of the analysis.

[0196] Step 7:

[0197] The generated advice is sent to the devices (smart glasses and earphones) in text and audio formats. Visual information is displayed on the smart glasses display, and audio advice is provided through the earphones. The input is advice data sent from the server, and the output is the display of visual information and playback of audio advice.

[0198] Step 8:

[0199] The user selects the most suitable product based on the visual information displayed on the smart glasses display and the audio advice provided through the earphones. At this stage, the user can obtain an appropriate shopping strategy in real time. The input is the advice content, and the output is the user's purchasing decision.

[0200] 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.

[0201] DETAILED DESCRIPTION OF THE INVENTION The following describes a mode for carrying out the invention based on the claims.

[0202] System Configuration

[0203] The system of the present invention includes a user, a terminal (smart glasses and earphones), a server, and an emotion engine that recognizes the user's emotions. The terminal is responsible for acquiring location information and environmental data, and the emotion engine analyzes the user's emotions. The server analyzes the received data and generates optimal advice, which is then provided to the user via the terminal and emotion engine.

[0204] Initial Setup

[0205] Users download and install the dedicated application onto their smartphone. Next, they register an account and enter their playing profile (such as their handicap, favorite clubs, and playing style). After that, they put on the smart glasses and earphones and pair them with the app using Bluetooth or other means. The emotion engine is also installed at the same time, and the device is ready for use.

[0206] Data collection and transmission

[0207] The device (smart glasses) uses its built-in GPS to obtain the user's current location in real time. It also uses built-in sensors to measure environmental data such as wind strength, direction, and temperature. At the same time, an emotion engine analyzes the user's facial expressions and tone of voice to obtain emotional data. This data is then sent to a server via the smartphone.

[0208] Data analysis and advice generation

[0209] The server receives the transmitted location information, environmental data, and emotional data. It also considers the user's past playing data (e.g., previous scores and shot success rates) and analyzes them using a machine learning algorithm. Based on the analysis results, golf play advice appropriate for the situation and the user's emotions at the time (specifically, recommended clubs, shot direction, strength, and sometimes words of encouragement or relaxation) is generated.

[0210] Providing advice

[0211] The generated advice is sent to the device in text and audio formats. Visual information is displayed on the smart glasses' display, and audio advice is provided through earphones. In addition, an emotion engine adjusts the tone and content of the advice according to the user's emotions. This allows the user to receive appropriate playing strategies in real time, taking their emotions into consideration.

[0212] Specific examples

[0213] For example, suppose a user is standing on the tee box of the first hole. The device (smart glasses) acquires the user's location, wind strength, and direction, and the emotion engine analyzes the user's facial expressions and tone of voice. This data is sent to the server, which analyzes the information and past play history. The server generates advice such as "Use a 3-wood and aim for the left side of the fairway." This advice is displayed on the smart glasses' display as "3-wood recommended, aim for the left side of the fairway," and is communicated to the user through the earphones by voice: "The wind is blowing from the right at 5 meters per second. Aim for the left side of the fairway." Furthermore, if the emotion engine determines that the user is nervous, it will provide additional encouraging words such as "Relax and hit the ball as you normally would."

[0214] This aspect of the invention allows users to receive optimal advice tailored to their situation in real time, and also provides support that takes emotional well-being into consideration, which is expected to help even beginners improve their scores in a short period of time.

[0215] The processing flow will be explained below.

[0216] Step 1: User registration and initial setup

[0217] Users download and install a dedicated application onto their smartphone.

[0218] Users create an account and enter their playing profile, including their handicap, preferred clubs, and playing style.

[0219] Users wear smart glasses, earphones, and the emotion engine, and pair them with the app using Bluetooth.

[0220] Step 2: Obtaining location and environmental data

[0221] The device (smart glasses) uses its built-in GPS function to obtain the user's current location in real time.

[0222] The device (smart glasses) uses built-in sensors to measure environmental data such as wind strength, direction, and temperature.

[0223] Step 3: Obtaining emotion data

[0224] The device (emotion engine) captures the user's facial expressions and tone of voice using a camera and microphone.

[0225] The device (emotion engine) analyzes the acquired data and recognizes the user's emotional state.

[0226] Step 4: Sending data

[0227] The devices (smart glasses and emotion engine) transmit the acquired location information, environmental data, and emotion data to a server via a smartphone.

[0228] Step 5: Receiving and consolidating data

[0229] The server receives the location information, environmental data, and emotion data transmitted from the terminal.

[0230] The server retrieves the user's past playing data (e.g., previous scores and shot success rates) from a database and consolidates all the data.

[0231] Step 6: Analyze the data

[0232] The server analyzes the real-time environment and the user's past play history based on the integrated data.

[0233] The server uses an analytical algorithm to generate optimal advice (recommended club, shot direction, strength, etc.).

[0234] Step 7: Generating and preparing advice

[0235] The server converts the generated advice into text and audio formats.

[0236] The server prepares to send text information to the smart glasses and audio information to the earphones.

[0237] Step 8: Providing advice

[0238] The device (smart glasses) displays the text advice received from the server on the display.

[0239] Example: "3 wood recommended, aim for the left side of the fairway."

[0240] The terminal (earphone) provides the audio advice received from the server to the user.

[0241] Example: "The wind is blowing from the right at 5 meters per second. Aim to the left side of the fairway."

[0242] Step 9: Adjust your advice to your emotions

[0243] The terminal (emotion engine) keeps monitoring the user's emotional state.

[0244] The server receives data from the emotion engine and adjusts the tone and content of the advice.

[0245] For example, if the user is nervous, add encouraging words like "Relax and type normally."

[0246] Step 10: Real-time updates

[0247] The devices (smart glasses and emotion engine) continuously monitor the user's movements and changes in environmental data, and send new data to the server.

[0248] Step 11: Generate and serve update advice

[0249] The server reanalyzes the data and updates the advice as needed.

[0250] The server regenerates the updated advice in text and audio form.

[0251] The devices (smart glasses and earphones, emotion engine) provide updated advice to the user.

[0252] This is the specific flow of the process. This process allows the user to always receive the best golf play advice in real time according to the situation, and also enjoys support that takes emotional well-being into consideration.

[0253] Example 2

[0254] 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."

[0255] Conventional golf play support systems provide advice based only on the user's location and environmental data, but do not take into account the user's emotional state. As a result, they often fail to provide appropriate advice based on the user's mental state, resulting in poor performance. Furthermore, the lack of systems that can flexibly respond to real-time movements and environmental changes makes it difficult to provide advice based on the latest information.

[0256] 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.

[0257] In this invention, the server includes: means for acquiring user location information; means for acquiring environmental data such as wind strength and direction and temperature; means for acquiring user emotion data; means for transmitting the location information, environmental data, and emotion data; means for receiving and analyzing the location information, environmental data, and emotion data; means for generating optimal golf play advice based on the analysis results; means for providing the advice to the user; means for integrating and analyzing the user's past play data; means for monitoring the user's movements and environmental changes in real time and updating the advice; and means for adjusting the tone and content of the advice in response to the user's emotion. This enables real-time and appropriate advice that takes into account not only the user's location and environment, but also their emotional state. As a result, even beginners can improve their scores and play quality in a short period of time.

[0258] A "user" is a person who uses the system to receive golf playing advice.

[0259] "Location information" is data indicating the user's current location obtained using a GPS function or the like.

[0260] "Environmental Data" refers to data that indicates external environmental conditions that affect golf play, such as wind strength and direction, and temperature.

[0261] "Emotional data" is data that indicates the user's psychological state, analyzed from the user's facial expressions, tone of voice, etc.

[0262] "Transmission means" is a function for transmitting acquired location information, environmental data, and emotion data to a server.

[0263] The "receiving means" is a function that allows the server to receive the transmitted location information, environmental data, and emotion data.

[0264] "Analysis means" is a function that analyzes data based on received data using machine learning algorithms, etc.

[0265] The "advice generating means" is a function that generates optimal golf playing advice based on the analysis results.

[0266] The "provision means" is a function that provides the generated advice to the user in text and audio formats.

[0267] "Past play data" refers to data that indicates the user's past golf play history data, shot success rate, and the like.

[0268] "Real-time monitoring means" is a function for monitoring user movements and changes in the environment in real time and updating advice.

[0269] The "tone adjustment means" is a function that adjusts the tone and content of the advice voice according to the user's emotions.

[0270] An embodiment of the present invention will be described below. This system includes a user, a terminal (smart glasses and earphones), a server, and an emotion engine. The terminal is responsible for acquiring location information and environmental data, and the emotion engine analyzes the user's emotions. The server analyzes the received data and generates optimal advice, which is then provided to the user via the terminal and the emotion engine.

[0271] Users download and install the dedicated application onto their smartphone. Next, they register an account and enter their playing profile (handicap, favorite club, playing style, etc.). After that, they put on the smart glasses and earphones and pair them with the app via Bluetooth. The emotion engine is also installed at the same time, and the device is ready for use.

[0272] The device (smart glasses) uses its built-in GPS to obtain the user's current location in real time. It also uses built-in sensors to measure environmental data such as wind strength, direction, and temperature. At the same time, an emotion engine analyzes the user's facial expressions and tone of voice to obtain emotional data. This data is then sent to a server via the smartphone.

[0273] The server receives and analyzes the transmitted location information, environmental data, and emotional data using AWS AI services and machine learning algorithms (e.g., TensorFlow and PyTorch). It also takes into account the user's past playing data (e.g., previous scores and shot success rates) and generates golf play advice appropriate to the situation and the user's emotions at the time based on the analysis results. For example, it generates advice such as "Use a 3-wood and aim for the left side of the fairway."

[0274] The generated advice is sent to the device in text and audio formats. The smart glasses display visual information such as "3-wood recommended, aim for the left side of the fairway," and the earphones provide a voice message saying, "The wind is blowing from the right at 5 meters per second. Aim for the left side of the fairway." Furthermore, the emotion engine adjusts the tone and content of the advice according to the user's emotions. For example, if it determines that the user is nervous, it will provide encouraging words such as, "Relax and hit the ball as you normally would."

[0275] As a concrete example, consider a user standing on the tee box of the first hole. The device (smart glasses) acquires the user's location, wind strength, and direction, and the emotion engine analyzes the user's facial expressions and tone of voice. This data is sent to the server, which analyzes it based on this information and past play history. The server then generates advice such as "Use a 3-wood and aim for the left side of the fairway." This advice is displayed on the smart glasses' display as "3-wood recommended, aim for the left side of the fairway," and is communicated to the user through the earphones by voice: "The wind is blowing from the right at 5 meters per second. Aim for the left side of the fairway." Furthermore, if the emotion engine determines that the user is nervous, it provides encouraging words such as "Relax and hit the ball as usual."

[0276] Examples of prompts include, "I'm standing on the tee box. Please capture my location and environmental data to provide advice on the best club and shot." or "I'm playing. Please consider my past data and current emotions to generate advice for my next shot."

[0277] This invention allows users to receive optimal advice tailored to their situation in real time, and also provides support that takes emotional well-being into consideration. As a result, even beginners can expect to improve their scores in a short period of time.

[0278] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0279] Step 1: Initial Setup

[0280] The user downloads and installs the dedicated application onto their smartphone. Next, the user registers an account and enters their playing profile (e.g., handicap, preferred club, playing style, etc.). Finally, the user puts on the smart glasses and earphones and pairs them with the app via Bluetooth. The user's basic information and device pairing status are entered, completing the initial setup.

[0281] Step 2: Data collection

[0282] The device (smart glasses) uses its built-in GPS to obtain the user's current location (location information) in real time. It also uses built-in sensors to measure environmental data such as wind strength and direction and temperature. At the same time, the emotion engine uses the smart glasses' camera and earphone microphone to analyze the user's facial expressions and tone of voice to obtain emotional data. The input is the user's location information, environmental data, and emotional data, which are obtained in real time and sent to the server.

[0283] Step 3: Send data

[0284] The device sends the collected location information, environmental data, and emotional data to a server via a smartphone. The input is the three types of data acquired from the device, and the output is the status of data transmission to the server.

[0285] Step 4: Data analysis

[0286] The server receives and analyzes the transmitted location information, environmental data, and emotional data using AWS AI services and machine learning algorithms (e.g., TensorFlow and PyTorch). The inputs are location information, environmental data, and emotional data, and the output is the analysis results. This analysis includes the user's past play data (e.g., previous scores and success rates) and takes this into account to generate optimal advice.

[0287] Step 5: Advice Generation

[0288] Based on the results of the data analysis, the server generates golf play advice appropriate to the situation and the user's emotions at the time. For example, specific advice such as "Use a 3-wood and aim for the left fairway" may be generated. The input is the results of the data analysis, and the output is the generated advice.

[0289] Step 6: Providing advice

[0290] The generated advice is sent to the device (smart glasses and earphones) in text and audio format. The device displays "3-wood recommended, aim for the left side of the fairway" on the smart glasses display and announces through the earphones, "The wind is blowing from the right at 5 meters per second. Aim for the left side of the fairway." Furthermore, the emotion engine adjusts the tone and content of the advice according to the user's emotions, adding encouraging words such as "Relax and hit the ball as normal" if the user is nervous. The input is the generated advice and the results of reanalysis of emotion data, and the output is specific feedback to the user.

[0291] (Application example 2)

[0292] 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."

[0293] Modern security services lack real-time advice tailored to the psychological state of security guards and their surrounding environments. In particular, situations in which security guards feel tense or stressed can make it difficult for them to respond, potentially resulting in a decline in the quality of security. Furthermore, real-time data collection and analysis are required to quickly respond to on-site situations. A system that can solve these problems and provide effective support for security guards is needed.

[0294] The identification processing 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 location information, means for acquiring environmental data such as wind strength and direction and temperature, means for recognizing the user's emotions, means for transmitting the location information, environmental data, and emotional data, means for receiving and analyzing the location information, environmental data, and emotional data, means for generating optimal security advice based on the analysis results, and means for providing the advice to the user. This allows security guards to receive optimal advice tailored to the situation in real time, which also contributes to reducing tension and stress, thereby improving the quality of security.

[0295] "Location information" is data that indicates the user's current geographical location.

[0296] "Environmental data" refers to data about the surrounding environment, such as wind strength, direction, and temperature.

[0297] "Emotion data" refers to data relating to the user's psychological state that can be obtained from facial expressions, tone of voice, and the like.

[0298] The "data transmission means" is a means for transmitting location information, environmental data, and emotion data from the terminal to the server.

[0299] The "data receiving and analyzing means" is a means by which the server receives and analyzes location information, environmental data, and emotion data.

[0300] The "security advice generating means" is a means for generating optimal security advice based on the analysis results.

[0301] The "advice providing means" is a means for providing the generated advice to the user.

[0302] "Past behavioral data" refers to data relating to the user's behavioral history.

[0303] The "real-time monitoring means" is a means for monitoring the user's movements and changes in the environment in real time and updating advice as necessary.

[0304] To implement this invention, a system including a user, a terminal (smart glasses and earphones), a server, and an emotion engine is required. The terminal acquires the user's location information and environmental data, and the emotion engine analyzes the user's emotions. The server receives this data, generates optimal security advice, and provides it to the user via the terminal and the emotion engine.

[0305] System Configuration

[0306] First, the user must download and install a dedicated application onto their smartphone. Next, they register an account and enter their user profile. After that, they put on the smart glasses and earphones and pair them with the app using Bluetooth or other means. The emotion engine is also installed at this stage, and the device is ready to use.

[0307] Data collection and transmission

[0308] The device (smart glasses) uses its built-in GPS to obtain the user's current location in real time. It also uses built-in sensors to measure environmental data such as wind strength, direction, and temperature. At the same time, an emotion engine analyzes the user's facial expressions and tone of voice to obtain emotional data. This data is then sent to a server via the smartphone.

[0309] Data analysis and advice generation

[0310] The server receives the transmitted location information, environmental data, and emotional data. It also takes into account the user's past behavioral data and performs analysis using a machine learning algorithm. Based on the analysis results, security advice appropriate to the situation and the user's emotions at the time (specifically, recommendations for strengthening security activities and vigilant areas) is generated.

[0311] Providing advice

[0312] The generated advice is sent to the terminal in text and audio formats. Visual information is displayed on the smart glasses' display, and audio advice is provided through earphones. In addition, an emotion engine adjusts the tone and content of the advice according to the user's emotions. This allows security guards to take appropriate security actions in real time, taking their emotions into consideration.

[0313] Specific examples

[0314] For example, a security guard guarding a large shopping mall at night sends location information and environmental data acquired by his device (smart glasses) along with emotional data analyzed by an emotion engine to a server. The server analyzes this information, and if it determines that the security guard is feeling nervous or stressed, it generates security advice such as, "Caution is required around current location X. Look around and ensure safety." This advice is displayed on the smart glasses and communicated to the security guard via audible audio through earphones.

[0315] Prompt Sentence Examples

[0316] Input:

[0317] Position: Point X

[0318] Environmental data: Dark, quiet

[0319] Emotional data: Tension, high alertness

[0320] Output:

[0321] Advice: "Caution is advised around location X. Please look around and make sure it is safe."

[0322] In this way, security personnel receive real-time advice adapted to the situation on the ground, enabling them to carry out effective security operations.

[0323] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0324] Step 1:

[0325] The user downloads and installs the dedicated application on their smartphone. Next, the user registers an account and enters their user profile, which sends the user's basic information to the server.

[0326] Input: Smartphone operation, user information.

[0327] Output: User profile registration.

[0328] Step 2:

[0329] The user puts on the smart glasses and earphones and pairs them with the app using Bluetooth. The emotion engine is also incorporated at this stage, and the system is ready. If pairing is successful, initialization data is sent to the server.

[0330] Input: Smart glasses, earphones, Bluetooth connection.

[0331] Output: Device paired and initialized successfully.

[0332] Step 3:

[0333] The device (smart glasses) uses its built-in GPS to obtain the user's current location in real time. It also uses built-in sensors to measure environmental data such as wind strength, direction, and temperature. This data is obtained in real time.

[0334] Input: GPS data, environmental sensor data.

[0335] Output: Location and environmental data.

[0336] Step 4:

[0337] The emotion engine analyzes the user's facial expressions and tone of voice to obtain emotional data, which is updated in real time.

[0338] Input: facial expression data, tone of voice.

[0339] Output: User emotion data.

[0340] Step 5:

[0341] The acquired location information, environmental data, and emotional data are sent via the smartphone to a server, which receives and analyzes the data.

[0342] Input: Location, environment data, emotion data.

[0343] Output: Sending data to the server.

[0344] Step 6:

[0345] The server uses machine learning algorithms to analyze the data it receives, integrating location, environmental, emotional, and past behavioral data to generate optimal security advice tailored to each individual situation.

[0346] Input: location, environmental data, emotional data, past behavioral data.

[0347] Output: Analysis results (best security advice).

[0348] Step 7:

[0349] The server sends the generated security advice in text and audio format to the device, where it is displayed visually on the smart glasses display and provided via audio via earphones.

[0350] Input: Analysis result (security advice).

[0351] Output: Providing text and audio advice.

[0352] Step 8:

[0353] An emotion engine adjusts the tone and content of advice based on the user's emotional state, providing emotionally sensitive security advice in real time.

[0354] Input: User emotion data.

[0355] Output: Providing tailored advice.

[0356] 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.

[0357] 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.

[0358] 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.

[0359] [Second embodiment]

[0360] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0361] 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.

[0362] 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).

[0363] 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.

[0364] 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.

[0365] 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).

[0366] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0367] 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.

[0368] 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.

[0369] 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.

[0370] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0371] 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."

[0372] DETAILED DESCRIPTION OF THE INVENTION The following describes a mode for carrying out the invention based on the claims.

[0373] System Configuration

[0374] This system consists of a user, a device (smart glasses and earphones), and a server. The device is responsible for acquiring location and environmental data, and the server analyzes the received data to generate optimal advice, which is then provided to the user via the device.

[0375] Initial Setup

[0376] Users download and install the dedicated application onto their smartphone, then register an account and enter their playing profile (such as handicap, favorite club, playing style, etc.), then put on the smart glasses and earphones and pair them with the app using Bluetooth or other means.

[0377] Data collection and transmission

[0378] The device (smart glasses) uses its built-in GPS to obtain the user's current location in real time. It also uses built-in sensors to measure environmental data such as wind strength, direction, and temperature. The obtained data is sent to a server via the smartphone.

[0379] Data analysis and advice generation

[0380] The server receives the transmitted location information and environmental data. It also takes into account the user's past playing data (e.g., previous scores and shot success rates) and analyzes them using a machine learning algorithm. Based on the analysis results, golf play advice appropriate for the current situation (specifically, recommended clubs, shot direction, strength, etc.) is generated.

[0381] Providing advice

[0382] The generated advice is sent to the device in text and audio formats, and visual information is displayed on the smart glasses display, while audio advice is provided through earphones, allowing users to receive appropriate playing strategies in real time.

[0383] Specific examples

[0384] Let's say a user is standing on the tee box of the first hole. The device (smart glasses) acquires their position, wind strength, and direction, and sends them to the server. The server analyzes this data and past play history to generate advice such as "Use a 3-wood and aim for the left side of the fairway." This advice is displayed on the smart glasses' display as "3-wood recommended, aim for the left side of the fairway," and is communicated to the user through the earphones by voice: "The wind is blowing from the right at 5 meters per second. Aim for the left side of the fairway."

[0385] This embodiment of the present invention allows users to receive optimal advice in real time, enabling even beginners to improve their scores in a short period of time.

[0386] The processing flow will be explained below.

[0387] Step 1: User registration and initial setup

[0388] Users install a dedicated application on their smartphone and create an account.

[0389] The user enters their playing profile (handicap, preferred club, playing style, etc.).

[0390] Users wear smart glasses and earphones and pair them with the app via Bluetooth or other means.

[0391] Step 2: Obtaining location information

[0392] The device (smart glasses) uses its built-in GPS function to obtain the user's current location in real time.

[0393] The device (smart glasses) transmits the acquired location information to a server via a smartphone.

[0394] Step 3: Get environment data

[0395] The device (smart glasses) uses built-in sensors to measure environmental data such as wind strength, direction, and temperature.

[0396] The device (smart glasses) sends the measured environmental data to a server via a smartphone.

[0397] Step 4: Receiving and consolidating data

[0398] The server receives the location information and environmental data transmitted from the terminal.

[0399] The server retrieves and integrates the user's past playing data (e.g., previous scores and shot success rates) from a database.

[0400] Step 5: Analyze the data

[0401] The server analyzes the real-time environment and the user's past play history based on the received and integrated data.

[0402] The server uses machine learning algorithms to generate optimal advice (recommended club, shot direction, strength, etc.).

[0403] Step 6: Generating and preparing advice

[0404] The server converts the generated advice into text and audio formats.

[0405] The server prepares the text information to be sent to the smart glasses and the audio information to be sent to the earphones.

[0406] Step 7: Providing advice

[0407] The device (smart glasses) displays the text advice received from the server on the display.

[0408] Example: "3 wood recommended, aim for the left side of the fairway."

[0409] The terminal (earphone) provides the user with the audio advice received from the server.

[0410] Example: "The wind is blowing from the right at 5 meters per second. Aim to the left side of the fairway."

[0411] Step 8: Real-time updates

[0412] The device (smart glasses) monitors changes in the user's location and environmental data in real time.

[0413] The device (smart glasses) sends new data to the server.

[0414] Step 9: Generate and serve update advice

[0415] The server reanalyzes the data and updates the advice as needed.

[0416] The server regenerates the updated advice in text and audio form.

[0417] The devices (smart glasses and earphones) will then provide the updated advice to the user again.

[0418] This is the specific flow of processing. This process allows the user to always receive the most appropriate golf playing advice in real time according to the situation.

[0419] Example 1

[0420] 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."

[0421] When playing golf, it is extremely difficult for users to accurately assess the current playing situation and environmental conditions and develop an optimal strategy. Furthermore, without a way to obtain appropriate advice in real time, the quality of play declines, especially for beginners and inexperienced players. Furthermore, it is difficult to effectively utilize past play data to improve.

[0422] 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.

[0423] In this invention, the server includes means for acquiring user location information, means for acquiring environmental data such as wind strength and direction and temperature, means for transmitting the location information and environmental data, means for receiving and analyzing the location information and environmental data, means for generating optimal sports play advice based on the analysis results, means for providing the advice to the user, means for analyzing the data taking into account the user's past play data, and means for updating the advice in real time based on the analyzed data. This allows the user to receive optimal play advice in real time, thereby improving the quality of their play. Furthermore, using past play data also contributes to improving the user's skills.

[0424] "Means for obtaining user location information" refers to a device that uses the Global Positioning System (GPS) or equivalent technology to determine the user's current location in real time.

[0425] "Means for acquiring environmental data such as wind strength, direction, and temperature" refers to devices that measure the surrounding environmental conditions using environmental sensors such as anemometers, temperature sensors, and wind vanes.

[0426] "Means for transmitting the location information and environmental data" refers to a device or function that transmits this data to a server via wireless communication technology (e.g., Bluetooth, Wi-Fi).

[0427] "Means for receiving and analyzing the location information and environmental data" refers to a series of processes in which the server processes the data received and analyzes it using statistical analysis and machine learning algorithms.

[0428] "Means for generating optimal sports play advice based on analysis results" refers to a function that generates specific advice such as optimal club selection, shot direction, and strength based on analyzed data.

[0429] The "means for providing the advice to the user" refers to a display device or an audio device for conveying the generated advice to the user in text or audio form.

[0430] "Means for performing analysis taking into account the user's past play data" refers to a function that improves the accuracy of analysis by using data such as the user's previous scores and shot success rates.

[0431] "Means for updating advice in real time based on analyzed data" refers to a function that updates the content of advice in a timely manner in response to changes in the environment and situation during play.

[0432] MODE FOR CARRYING OUT THE INVENTION

[0433] This invention is implemented using a system consisting of a user, a device (smart glasses and earphones), and a server. The device is responsible for acquiring the user's location information and environmental data, and the server analyzes the received data to generate optimal advice and provide it to the user through the device.

[0434] Hardware and Software Configuration

[0435] User

[0436] Users download and install a dedicated application onto their smartphone, which then functions as a central device for sending and receiving data.

[0437] Terminal

[0438] The device consists of smart glasses and earphones. The smart glasses use a built-in GPS to determine the user's current location. They also have built-in environmental sensors, such as an anemometer, temperature sensor, and wind vane, to acquire data such as wind strength and direction and temperature. The earphones are a device that provides audio advice to the user.

[0439] server

[0440] The server uses powerful computing resources and specialized software to analyze the received location and environmental data, using statistical analysis software and machine learning algorithms. Based on the analysis results, optimal play advice is generated.

[0441] Data Flow and Processing

[0442] Initial Setup

[0443] Users download and install the dedicated application onto their smartphone. They launch the application, register an account, and enter their playing profile (handicap, favorite club, playing style, etc.). After that, the user puts on the smart glasses and earphones and pairs them with the smartphone application via Bluetooth.

[0444] Data collection and transmission

[0445] When a user starts playing, the smart glasses on the device use their built-in GPS to obtain their current location in real time, while environmental sensors measure data such as wind strength, direction, and temperature. This data is then sent to a server via the smartphone.

[0446] Data analysis and advice generation

[0447] The server analyzes the received location and environmental data using statistical analysis and machine learning algorithms. The server also takes into account the user's past play data (e.g., score, shot success rate). Based on the analysis results, the server generates optimal play advice. The advice is provided in text and audio formats.

[0448] Providing advice

[0449] The generated advice is sent to the device, where visual information (e.g., recommended club, shot direction, etc.) is displayed on the smart glasses display, and audio advice is provided through earphones, allowing the user to receive appropriate playing strategies in real time.

[0450] Specific examples

[0451] For example, say a user is standing on the tee box of the first hole. The device's smart glasses use GPS to pinpoint its location, and environmental sensors measure that a wind is blowing from the right at 5 meters per second. This information is sent to a server via the smartphone. The server analyzes the received data and past play data and generates the advice "Use a 3-wood and aim for the left side of the fairway." This advice is displayed on the smart glasses' display as "3-wood recommended, aim for the left side of the fairway," and is communicated to the user via earphones via voice: "The wind is blowing from the right at 5 meters per second. Aim for the left side of the fairway."

[0452] Prompt Sentence Examples

[0453] If you input the following prompt into the generative AI model, it will return the above specific action description:

[0454] Please explain in detail the process of the smart glasses and earphone system that supports golf play. The system collects location and environmental data, sends it to a server for analysis, and then generates and provides appropriate playing advice to the user. Please explain each processing step, including the specific operation.

[0455] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0456] Step 1: User performs initial setup

[0457] Users download and install the dedicated application onto their smartphone. They launch the application, register an account, and enter their own playing profile (handicap, favorite club, playing style, etc.). They then put on the smart glasses and earphones and pair them with the smartphone application via Bluetooth.

[0458] Input: Smartphone, account information, play profile

[0459] Output: Paired smart glasses and earphones

[0460] Step 2: Device collects data

[0461] When a user starts playing, the smart glasses use their built-in GPS to obtain their current location in real time, while environmental sensors measure data such as wind strength, direction, and temperature. The acquired data is then stored in the smart glasses' internal memory.

[0462] Input: current user location, environmental conditions

[0463] Output: Collected location and environmental data

[0464] Step 3: The device sends the data to the server

[0465] The smart glasses collect location and environmental data and transmit it to a server via a smartphone, using Bluetooth and an internet connection.

[0466] Input: Collected location and environmental data

[0467] Output: Data sent to the server

[0468] Step 4: The server parses the data

[0469] The server receives the location and environmental data, and then analyzes it by integrating it with the user's past play data. Statistical analysis software and machine learning algorithms are used for the analysis. The analysis results in advice tailored to the situation at hand.

[0470] Input: location information, environmental data, past play data

[0471] Output: Best Play Advice

[0472] Step 5: Server generates advice

[0473] The server generates optimal play advice based on the analysis results, including recommended clubs, shot direction, and strength. The generated advice is saved in text and audio formats.

[0474] Input: Analysis results

[0475] Output: Play advice in text and audio format

[0476] Step 6: The server sends the advice to the device

[0477] The server generates text and audio advice and sends it to the smart glasses and earphones via an internet connection and Bluetooth.

[0478] Input: Text and audio advice

[0479] Output: Advice sent to terminal

[0480] Step 7: The device provides advice to the user

[0481] The smart glasses display visual information and provide real-time audio advice through earphones, allowing users to instantly receive appropriate playing strategies.

[0482] Input: Advice sent to terminal

[0483] Output: Visual and audio advice provided to the user

[0484] (Application example 1)

[0485] 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."

[0486] In conventional shopping experiences, it has been difficult for users to efficiently obtain necessary product information in stores and make optimal purchasing decisions. Furthermore, there has been no system that analyzes in-store environmental data and users' purchasing history in real time to provide optimal advice to individuals. This has led to users wasting time and sometimes being unable to find the perfect product. A new system is needed to solve these problems.

[0487] 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.

[0488] In this invention, the server includes means for acquiring user location information, means for acquiring environmental data such as wind strength and direction and temperature, means for acquiring product information to support user decision-making, means for transmitting the location information, environmental data and product information, means for receiving and analyzing the location information, environmental data and product information, means for generating optimal shopping advice based on the analysis results, and means for providing the advice to the user. This enables users to efficiently acquire information and make optimal purchasing decisions even in a physical store.

[0489] "User location information" is geographical coordinate data of the user's current location.

[0490] "Environmental data" refers to data relating to the surrounding conditions of the user's current location, such as wind strength and direction, temperature, and humidity.

[0491] "Product information" is data that includes detailed information about products in a store, such as price, stock status, and promotion information.

[0492] The "data transmission means" is a communication means for sending the acquired location information, environmental data, and product information to the server.

[0493] The "analysis means" is a means having a function of analyzing necessary information based on received data and generating optimal advice.

[0494] "Shopping advice" is information that includes recommendations and instructions to help users make optimal purchasing decisions.

[0495] "User movement" is information indicating changes in the user's position as they move around the store.

[0496] The "advice providing means" is a means for conveying the generated advice to the user, and presents the information visually or audibly.

[0497] System Configuration

[0498] This system consists of a user, a device (smart glasses and earphones), and a server. The device is responsible for acquiring location and environmental data as well as product information, and the server analyzes the received data to generate optimal shopping advice and provide it to the user via the device.

[0499] Initial Setup

[0500] Users download and install the dedicated application on their smartphone, then register an account and enter their user profile (such as purchase history, favorite product categories, alert settings, etc.), then put on the smart glasses and earphones and pair them with the application using Bluetooth or other means.

[0501] Data collection and transmission

[0502] The device (smart glasses) uses its built-in GPS to obtain the user's current location in real time. It also uses sensors in the smart glasses to measure environmental data such as wind strength, direction, and temperature. It also obtains product information for the store. This data is then sent to a server via the smartphone.

[0503] Data analysis and advice generation

[0504] The server receives the transmitted location and environmental data, as well as the product information. It also analyzes the data using machine learning algorithms, taking into account the user's past purchase history and preferences. Based on the analysis results, it generates shopping advice tailored to the current situation (specifically, recommended products, promotion information, product locations within the store, etc.).

[0505] Providing advice

[0506] The generated advice is sent to the device in text and audio formats, with visual information displayed on the smart glasses display and audio advice provided through earphones, allowing users to receive appropriate shopping strategies in real time.

[0507] Hardware and software used

[0508] Smart glasses: Equipped with built-in GPS and sensors to collect location and environmental data, and display visual information.

[0509] Earphones: Provides audio advice.

[0510] Server: Analyzes data and generates advice using machine learning algorithms such as TensorFlow.

[0511] Specific examples

[0512] For example, suppose a user arrives at a clothing section of a store. The smart glasses use GPS to pinpoint their location and measure the ambient temperature and humidity. This data is sent to a server, which generates advice such as, "We recommend the new jackets on sale. They're on the rack on the left," based on the user's past purchasing history and preferences. The smart glasses' display will show "New Jackets Sale - Left Rack," and a voice message will be heard through the earphones saying, "There are new jackets on the rack on the left."

[0513] Example prompts for generative AI models

[0514] "The user is in the clothing department. Based on environmental data, what products should you recommend, taking into account their purchasing history and preferences?"

[0515] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0516] Step 1:

[0517] The user downloads and installs a dedicated application onto their smartphone. Next, the user registers for an account and enters their user profile (purchase history, favorite product categories, alert settings, etc.). This information is entered on the user's smartphone and sent to the server. The input data is stored on the server as the user's account information. The output is user profile data securely stored on the server.

[0518] Step 2:

[0519] The user wears the smart glasses and earphones and pairs them with a dedicated application using Bluetooth. At this time, the system checks whether the smart glasses and earphones are working properly. The input is the user's Bluetooth pairing operation, and the output is a message indicating successful pairing.

[0520] Step 3:

[0521] The device (smart glasses) uses its built-in GPS to obtain the user's current location in real time. In addition, the smart glasses' sensors collect environmental data such as wind strength, direction, and temperature. The input is data from the GPS sensor and environmental sensors, and the output is the obtained location information and environmental data.

[0522] Step 4:

[0523] Obtain product information within the store. Smart glasses communicate with the store's sales floor information system to obtain the latest product information (price, stock status, promotion information, etc.). The input is data from the sales floor information system, and the output is the obtained product information.

[0524] Step 5:

[0525] The device transmits the acquired location information, environmental data, and product information to a server via a smartphone. The input is the connection between the smart glasses and the smartphone, and the output is the transmission of data to the server. The server receives this data.

[0526] Step 6:

[0527] The server integrates and analyzes the received location information, environmental data, product information, and the user's past purchasing history and preference data. The server uses TensorFlow to execute machine learning algorithms and generate optimal shopping advice (recommended products, promotion information, product locations in stores, etc.). The input is various data collected on the server, and the output is advice as the result of the analysis.

[0528] Step 7:

[0529] The generated advice is sent to the devices (smart glasses and earphones) in text and audio formats. Visual information is displayed on the smart glasses display, and audio advice is provided through the earphones. The input is advice data sent from the server, and the output is the display of visual information and playback of audio advice.

[0530] Step 8:

[0531] The user selects the most suitable product based on the visual information displayed on the smart glasses display and the audio advice provided through the earphones. At this stage, the user can obtain an appropriate shopping strategy in real time. The input is the advice content, and the output is the user's purchasing decision.

[0532] 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.

[0533] DETAILED DESCRIPTION OF THE INVENTION The following describes a mode for carrying out the invention based on the claims.

[0534] System Configuration

[0535] The system of the present invention includes a user, a terminal (smart glasses and earphones), a server, and an emotion engine that recognizes the user's emotions. The terminal is responsible for acquiring location information and environmental data, and the emotion engine analyzes the user's emotions. The server analyzes the received data and generates optimal advice, which is then provided to the user via the terminal and emotion engine.

[0536] Initial Setup

[0537] Users download and install the dedicated application onto their smartphone. Next, they register an account and enter their playing profile (such as their handicap, favorite clubs, and playing style). After that, they put on the smart glasses and earphones and pair them with the app using Bluetooth or other means. The emotion engine is also installed at the same time, and the device is ready for use.

[0538] Data collection and transmission

[0539] The device (smart glasses) uses its built-in GPS to obtain the user's current location in real time. It also uses built-in sensors to measure environmental data such as wind strength, direction, and temperature. At the same time, an emotion engine analyzes the user's facial expressions and tone of voice to obtain emotional data. This data is then sent to a server via the smartphone.

[0540] Data analysis and advice generation

[0541] The server receives the transmitted location information, environmental data, and emotional data. It also considers the user's past playing data (e.g., previous scores and shot success rates) and analyzes them using a machine learning algorithm. Based on the analysis results, golf play advice appropriate for the situation and the user's emotions at the time (specifically, recommended clubs, shot direction, strength, and sometimes words of encouragement or relaxation) is generated.

[0542] Providing advice

[0543] The generated advice is sent to the device in text and audio formats. Visual information is displayed on the smart glasses' display, and audio advice is provided through earphones. In addition, an emotion engine adjusts the tone and content of the advice according to the user's emotions. This allows the user to receive appropriate playing strategies in real time, taking their emotions into consideration.

[0544] Specific examples

[0545] For example, suppose a user is standing on the tee box of the first hole. The device (smart glasses) acquires the user's location, wind strength, and direction, and the emotion engine analyzes the user's facial expressions and tone of voice. This data is sent to the server, which analyzes the information and past play history. The server generates advice such as "Use a 3-wood and aim for the left side of the fairway." This advice is displayed on the smart glasses' display as "3-wood recommended, aim for the left side of the fairway," and is communicated to the user through the earphones by voice: "The wind is blowing from the right at 5 meters per second. Aim for the left side of the fairway." Furthermore, if the emotion engine determines that the user is nervous, it will provide additional encouraging words such as "Relax and hit the ball as you normally would."

[0546] This aspect of the invention allows users to receive optimal advice tailored to their situation in real time, and also provides support that takes emotional well-being into consideration, which is expected to help even beginners improve their scores in a short period of time.

[0547] The processing flow will be explained below.

[0548] Step 1: User registration and initial setup

[0549] Users download and install a dedicated application onto their smartphone.

[0550] Users create an account and enter their playing profile, including their handicap, preferred clubs, and playing style.

[0551] Users wear smart glasses, earphones, and the emotion engine, and pair them with the app using Bluetooth.

[0552] Step 2: Obtaining location and environmental data

[0553] The device (smart glasses) uses its built-in GPS function to obtain the user's current location in real time.

[0554] The device (smart glasses) uses built-in sensors to measure environmental data such as wind strength, direction, and temperature.

[0555] Step 3: Obtaining emotion data

[0556] The device (emotion engine) captures the user's facial expressions and tone of voice using a camera and microphone.

[0557] The device (emotion engine) analyzes the acquired data and recognizes the user's emotional state.

[0558] Step 4: Sending data

[0559] The devices (smart glasses and emotion engine) transmit the acquired location information, environmental data, and emotion data to a server via a smartphone.

[0560] Step 5: Receiving and consolidating data

[0561] The server receives the location information, environmental data, and emotion data transmitted from the terminal.

[0562] The server retrieves the user's past playing data (e.g., previous scores and shot success rates) from a database and consolidates all the data.

[0563] Step 6: Analyze the data

[0564] The server analyzes the real-time environment and the user's past play history based on the integrated data.

[0565] The server uses an analytical algorithm to generate optimal advice (recommended club, shot direction, strength, etc.).

[0566] Step 7: Generating and preparing advice

[0567] The server converts the generated advice into text and audio formats.

[0568] The server prepares to send text information to the smart glasses and audio information to the earphones.

[0569] Step 8: Providing advice

[0570] The device (smart glasses) displays the text advice received from the server on the display.

[0571] Example: "3 wood recommended, aim for the left side of the fairway."

[0572] The terminal (earphone) provides the audio advice received from the server to the user.

[0573] Example: "The wind is blowing from the right at 5 meters per second. Aim to the left side of the fairway."

[0574] Step 9: Adjust your advice to your emotions

[0575] The terminal (emotion engine) keeps monitoring the user's emotional state.

[0576] The server receives data from the emotion engine and adjusts the tone and content of the advice.

[0577] For example, if the user is nervous, add encouraging words like "Relax and type normally."

[0578] Step 10: Real-time updates

[0579] The devices (smart glasses and emotion engine) continuously monitor the user's movements and changes in environmental data, and send new data to the server.

[0580] Step 11: Generate and serve update advice

[0581] The server reanalyzes the data and updates the advice as needed.

[0582] The server regenerates the updated advice in text and audio form.

[0583] The devices (smart glasses and earphones, emotion engine) provide updated advice to the user.

[0584] This is the specific flow of the process. This process allows the user to always receive the best golf play advice in real time according to the situation, and also enjoys support that takes emotional well-being into consideration.

[0585] Example 2

[0586] 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."

[0587] Conventional golf play support systems provide advice based only on the user's location and environmental data, but do not take into account the user's emotional state. As a result, they often fail to provide appropriate advice based on the user's mental state, resulting in poor performance. Furthermore, the lack of systems that can flexibly respond to real-time movements and environmental changes makes it difficult to provide advice based on the latest information.

[0588] 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.

[0589] In this invention, the server includes: means for acquiring user location information; means for acquiring environmental data such as wind strength and direction and temperature; means for acquiring user emotion data; means for transmitting the location information, environmental data, and emotion data; means for receiving and analyzing the location information, environmental data, and emotion data; means for generating optimal golf play advice based on the analysis results; means for providing the advice to the user; means for integrating and analyzing the user's past play data; means for monitoring the user's movements and environmental changes in real time and updating the advice; and means for adjusting the tone and content of the advice in response to the user's emotion. This enables real-time and appropriate advice that takes into account not only the user's location and environment, but also their emotional state. As a result, even beginners can improve their scores and play quality in a short period of time.

[0590] A "user" is a person who uses the system to receive golf playing advice.

[0591] "Location information" is data indicating the user's current location obtained using a GPS function or the like.

[0592] "Environmental Data" refers to data that indicates external environmental conditions that affect golf play, such as wind strength and direction, and temperature.

[0593] "Emotional data" is data that indicates the user's psychological state, analyzed from the user's facial expressions, tone of voice, etc.

[0594] "Transmission means" is a function for transmitting acquired location information, environmental data, and emotion data to a server.

[0595] The "receiving means" is a function that allows the server to receive the transmitted location information, environmental data, and emotion data.

[0596] "Analysis means" is a function that analyzes data based on received data using machine learning algorithms, etc.

[0597] The "advice generating means" is a function that generates optimal golf playing advice based on the analysis results.

[0598] The "provision means" is a function that provides the generated advice to the user in text and audio formats.

[0599] "Past play data" refers to data that indicates the user's past golf play history data, shot success rate, and the like.

[0600] "Real-time monitoring means" is a function for monitoring user movements and changes in the environment in real time and updating advice.

[0601] The "tone adjustment means" is a function that adjusts the tone and content of the advice voice according to the user's emotions.

[0602] An embodiment of the present invention will be described below. This system includes a user, a terminal (smart glasses and earphones), a server, and an emotion engine. The terminal is responsible for acquiring location information and environmental data, and the emotion engine analyzes the user's emotions. The server analyzes the received data and generates optimal advice, which is then provided to the user via the terminal and the emotion engine.

[0603] Users download and install the dedicated application onto their smartphone. Next, they register an account and enter their playing profile (handicap, favorite club, playing style, etc.). After that, they put on the smart glasses and earphones and pair them with the app via Bluetooth. The emotion engine is also installed at the same time, and the device is ready for use.

[0604] The device (smart glasses) uses its built-in GPS to obtain the user's current location in real time. It also uses built-in sensors to measure environmental data such as wind strength, direction, and temperature. At the same time, an emotion engine analyzes the user's facial expressions and tone of voice to obtain emotional data. This data is then sent to a server via the smartphone.

[0605] The server receives and analyzes the transmitted location information, environmental data, and emotional data using AWS AI services and machine learning algorithms (e.g., TensorFlow and PyTorch). It also takes into account the user's past playing data (e.g., previous scores and shot success rates) and generates golf play advice appropriate to the situation and the user's emotions at the time based on the analysis results. For example, it generates advice such as "Use a 3-wood and aim for the left side of the fairway."

[0606] The generated advice is sent to the device in text and audio formats. The smart glasses display visual information such as "3-wood recommended, aim for the left side of the fairway," and the earphones provide a voice message saying, "The wind is blowing from the right at 5 meters per second. Aim for the left side of the fairway." Furthermore, the emotion engine adjusts the tone and content of the advice according to the user's emotions. For example, if it determines that the user is nervous, it will provide encouraging words such as, "Relax and hit the ball as you normally would."

[0607] As a concrete example, consider a user standing on the tee box of the first hole. The device (smart glasses) acquires the user's location, wind strength, and direction, and the emotion engine analyzes the user's facial expressions and tone of voice. This data is sent to the server, which analyzes it based on this information and past play history. The server then generates advice such as "Use a 3-wood and aim for the left side of the fairway." This advice is displayed on the smart glasses' display as "3-wood recommended, aim for the left side of the fairway," and is communicated to the user through the earphones by voice: "The wind is blowing from the right at 5 meters per second. Aim for the left side of the fairway." Furthermore, if the emotion engine determines that the user is nervous, it provides encouraging words such as "Relax and hit the ball as usual."

[0608] Examples of prompts include, "I'm standing on the tee box. Please capture my location and environmental data to provide advice on the best club and shot." or "I'm playing. Please consider my past data and current emotions to generate advice for my next shot."

[0609] This invention allows users to receive optimal advice tailored to their situation in real time, and also provides support that takes emotional well-being into consideration. As a result, even beginners can expect to improve their scores in a short period of time.

[0610] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0611] Step 1: Initial Setup

[0612] The user downloads and installs the dedicated application onto their smartphone. Next, the user registers an account and enters their playing profile (e.g., handicap, preferred club, playing style, etc.). Finally, the user puts on the smart glasses and earphones and pairs them with the app via Bluetooth. The user's basic information and device pairing status are entered, completing the initial setup.

[0613] Step 2: Data collection

[0614] The device (smart glasses) uses its built-in GPS to obtain the user's current location (location information) in real time. It also uses built-in sensors to measure environmental data such as wind strength and direction and temperature. At the same time, the emotion engine uses the smart glasses' camera and earphone microphone to analyze the user's facial expressions and tone of voice to obtain emotional data. The input is the user's location information, environmental data, and emotional data, which are obtained in real time and sent to the server.

[0615] Step 3: Send data

[0616] The device sends the collected location information, environmental data, and emotional data to a server via a smartphone. The input is the three types of data acquired from the device, and the output is the status of data transmission to the server.

[0617] Step 4: Data analysis

[0618] The server receives and analyzes the transmitted location information, environmental data, and emotional data using AWS AI services and machine learning algorithms (e.g., TensorFlow and PyTorch). The inputs are location information, environmental data, and emotional data, and the output is the analysis results. This analysis includes the user's past play data (e.g., previous scores and success rates) and takes this into account to generate optimal advice.

[0619] Step 5: Advice Generation

[0620] Based on the results of the data analysis, the server generates golf play advice appropriate to the situation and the user's emotions at the time. For example, specific advice such as "Use a 3-wood and aim for the left fairway" may be generated. The input is the results of the data analysis, and the output is the generated advice.

[0621] Step 6: Providing advice

[0622] The generated advice is sent to the device (smart glasses and earphones) in text and audio format. The device displays "3-wood recommended, aim for the left side of the fairway" on the smart glasses display and announces through the earphones, "The wind is blowing from the right at 5 meters per second. Aim for the left side of the fairway." Furthermore, the emotion engine adjusts the tone and content of the advice according to the user's emotions, adding encouraging words such as "Relax and hit the ball as normal" if the user is nervous. The input is the generated advice and the results of reanalysis of emotion data, and the output is specific feedback to the user.

[0623] (Application example 2)

[0624] 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."

[0625] Modern security services lack real-time advice tailored to the psychological state of security guards and their surrounding environments. In particular, situations in which security guards feel tense or stressed can make it difficult for them to respond, potentially resulting in a decline in the quality of security. Furthermore, real-time data collection and analysis are required to quickly respond to on-site situations. A system that can solve these problems and provide effective support for security guards is needed.

[0626] The identification processing 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 location information, means for acquiring environmental data such as wind strength and direction and temperature, means for recognizing the user's emotions, means for transmitting the location information, environmental data, and emotional data, means for receiving and analyzing the location information, environmental data, and emotional data, means for generating optimal security advice based on the analysis results, and means for providing the advice to the user. This allows security guards to receive optimal advice tailored to the situation in real time, which also contributes to reducing tension and stress, thereby improving the quality of security.

[0627] "Location information" is data that indicates the user's current geographical location.

[0628] "Environmental data" refers to data about the surrounding environment, such as wind strength, direction, and temperature.

[0629] "Emotion data" refers to data relating to the user's psychological state that can be obtained from facial expressions, tone of voice, and the like.

[0630] The "data transmission means" is a means for transmitting location information, environmental data, and emotion data from the terminal to the server.

[0631] The "data receiving and analyzing means" is a means by which the server receives and analyzes location information, environmental data, and emotion data.

[0632] The "security advice generating means" is a means for generating optimal security advice based on the analysis results.

[0633] The "advice providing means" is a means for providing the generated advice to the user.

[0634] "Past behavioral data" refers to data relating to the user's behavioral history.

[0635] The "real-time monitoring means" is a means for monitoring the user's movements and changes in the environment in real time and updating advice as necessary.

[0636] To implement this invention, a system including a user, a terminal (smart glasses and earphones), a server, and an emotion engine is required. The terminal acquires the user's location information and environmental data, and the emotion engine analyzes the user's emotions. The server receives this data, generates optimal security advice, and provides it to the user via the terminal and the emotion engine.

[0637] System Configuration

[0638] First, the user must download and install a dedicated application onto their smartphone. Next, they register an account and enter their user profile. After that, they put on the smart glasses and earphones and pair them with the app using Bluetooth or other means. The emotion engine is also installed at this stage, and the device is ready to use.

[0639] Data collection and transmission

[0640] The device (smart glasses) uses its built-in GPS to obtain the user's current location in real time. It also uses built-in sensors to measure environmental data such as wind strength, direction, and temperature. At the same time, an emotion engine analyzes the user's facial expressions and tone of voice to obtain emotional data. This data is then sent to a server via the smartphone.

[0641] Data analysis and advice generation

[0642] The server receives the transmitted location information, environmental data, and emotional data. It also takes into account the user's past behavioral data and performs analysis using a machine learning algorithm. Based on the analysis results, security advice appropriate to the situation and the user's emotions at the time (specifically, recommendations for strengthening security activities and vigilant areas) is generated.

[0643] Providing advice

[0644] The generated advice is sent to the terminal in text and audio formats. Visual information is displayed on the smart glasses' display, and audio advice is provided through earphones. In addition, an emotion engine adjusts the tone and content of the advice according to the user's emotions. This allows security guards to take appropriate security actions in real time, taking their emotions into consideration.

[0645] Specific examples

[0646] For example, a security guard guarding a large shopping mall at night sends location information and environmental data acquired by his device (smart glasses) along with emotional data analyzed by an emotion engine to a server. The server analyzes this information, and if it determines that the security guard is feeling nervous or stressed, it generates security advice such as, "Caution is required around current location X. Look around and ensure safety." This advice is displayed on the smart glasses and communicated to the security guard via audible audio through earphones.

[0647] Prompt Sentence Examples

[0648] Input:

[0649] Position: Point X

[0650] Environmental data: Dark, quiet

[0651] Emotional data: Tension, high alertness

[0652] Output:

[0653] Advice: "Caution is advised around location X. Please look around and make sure it is safe."

[0654] In this way, security personnel receive real-time advice adapted to the situation on the ground, enabling them to carry out effective security operations.

[0655] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0656] Step 1:

[0657] The user downloads and installs the dedicated application on their smartphone. Next, the user registers an account and enters their user profile, which sends the user's basic information to the server.

[0658] Input: Smartphone operation, user information.

[0659] Output: User profile registration.

[0660] Step 2:

[0661] The user puts on the smart glasses and earphones and pairs them with the app using Bluetooth. The emotion engine is also incorporated at this stage, and the system is ready. If pairing is successful, initialization data is sent to the server.

[0662] Input: Smart glasses, earphones, Bluetooth connection.

[0663] Output: Device paired and initialized successfully.

[0664] Step 3:

[0665] The device (smart glasses) uses its built-in GPS to obtain the user's current location in real time. It also uses built-in sensors to measure environmental data such as wind strength, direction, and temperature. This data is obtained in real time.

[0666] Input: GPS data, environmental sensor data.

[0667] Output: Location and environmental data.

[0668] Step 4:

[0669] The emotion engine analyzes the user's facial expressions and tone of voice to obtain emotional data, which is updated in real time.

[0670] Input: facial expression data, tone of voice.

[0671] Output: User emotion data.

[0672] Step 5:

[0673] The acquired location information, environmental data, and emotional data are sent via the smartphone to a server, which receives and analyzes the data.

[0674] Input: Location, environment data, emotion data.

[0675] Output: Sending data to the server.

[0676] Step 6:

[0677] The server uses machine learning algorithms to analyze the data it receives, integrating location, environmental, emotional, and past behavioral data to generate optimal security advice tailored to each individual situation.

[0678] Input: location, environmental data, emotional data, past behavioral data.

[0679] Output: Analysis results (best security advice).

[0680] Step 7:

[0681] The server sends the generated security advice in text and audio format to the device, where it is displayed visually on the smart glasses display and provided via audio via earphones.

[0682] Input: Analysis result (security advice).

[0683] Output: Providing text and audio advice.

[0684] Step 8:

[0685] An emotion engine adjusts the tone and content of advice based on the user's emotional state, providing emotionally sensitive security advice in real time.

[0686] Input: User emotion data.

[0687] Output: Providing tailored advice.

[0688] 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.

[0689] 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.

[0690] 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.

[0691] [Third embodiment]

[0692] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0693] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0694] 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).

[0695] 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.

[0696] 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.

[0697] 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).

[0698] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0699] 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.

[0700] 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.

[0701] 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.

[0702] 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.

[0703] 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."

[0704] DETAILED DESCRIPTION OF THE INVENTION The following describes a mode for carrying out the invention based on the claims.

[0705] System Configuration

[0706] This system consists of a user, a device (smart glasses and earphones), and a server. The device is responsible for acquiring location and environmental data, and the server analyzes the received data to generate optimal advice, which is then provided to the user via the device.

[0707] Initial Setup

[0708] Users download and install the dedicated application onto their smartphone, then register an account and enter their playing profile (such as handicap, favorite club, playing style, etc.), then put on the smart glasses and earphones and pair them with the app using Bluetooth or other means.

[0709] Data collection and transmission

[0710] The device (smart glasses) uses its built-in GPS to obtain the user's current location in real time. It also uses built-in sensors to measure environmental data such as wind strength, direction, and temperature. The obtained data is sent to a server via the smartphone.

[0711] Data analysis and advice generation

[0712] The server receives the transmitted location information and environmental data. It also takes into account the user's past playing data (e.g., previous scores and shot success rates) and analyzes them using a machine learning algorithm. Based on the analysis results, golf play advice appropriate for the current situation (specifically, recommended clubs, shot direction, strength, etc.) is generated.

[0713] Providing advice

[0714] The generated advice is sent to the device in text and audio formats, and visual information is displayed on the smart glasses display, while audio advice is provided through earphones, allowing users to receive appropriate playing strategies in real time.

[0715] Specific examples

[0716] Let's say a user is standing on the tee box of the first hole. The device (smart glasses) acquires their position, wind strength, and direction, and sends them to the server. The server analyzes this data and past play history to generate advice such as "Use a 3-wood and aim for the left side of the fairway." This advice is displayed on the smart glasses' display as "3-wood recommended, aim for the left side of the fairway," and is communicated to the user through the earphones by voice: "The wind is blowing from the right at 5 meters per second. Aim for the left side of the fairway."

[0717] This embodiment of the present invention allows users to receive optimal advice in real time, enabling even beginners to improve their scores in a short period of time.

[0718] The processing flow will be explained below.

[0719] Step 1: User registration and initial setup

[0720] Users install a dedicated application on their smartphone and create an account.

[0721] The user enters their playing profile (handicap, preferred club, playing style, etc.).

[0722] Users wear smart glasses and earphones and pair them with the app via Bluetooth or other means.

[0723] Step 2: Obtaining location information

[0724] The device (smart glasses) uses its built-in GPS function to obtain the user's current location in real time.

[0725] The device (smart glasses) transmits the acquired location information to a server via a smartphone.

[0726] Step 3: Get environment data

[0727] The device (smart glasses) uses built-in sensors to measure environmental data such as wind strength, direction, and temperature.

[0728] The device (smart glasses) sends the measured environmental data to a server via a smartphone.

[0729] Step 4: Receiving and consolidating data

[0730] The server receives the location information and environmental data transmitted from the terminal.

[0731] The server retrieves and integrates the user's past playing data (e.g., previous scores and shot success rates) from a database.

[0732] Step 5: Analyze the data

[0733] The server analyzes the real-time environment and the user's past play history based on the received and integrated data.

[0734] The server uses machine learning algorithms to generate optimal advice (recommended club, shot direction, strength, etc.).

[0735] Step 6: Generating and preparing advice

[0736] The server converts the generated advice into text and audio formats.

[0737] The server prepares the text information to be sent to the smart glasses and the audio information to be sent to the earphones.

[0738] Step 7: Providing advice

[0739] The device (smart glasses) displays the text advice received from the server on the display.

[0740] Example: "3 wood recommended, aim for the left side of the fairway."

[0741] The terminal (earphone) provides the user with the audio advice received from the server.

[0742] Example: "The wind is blowing from the right at 5 meters per second. Aim to the left side of the fairway."

[0743] Step 8: Real-time updates

[0744] The device (smart glasses) monitors changes in the user's location and environmental data in real time.

[0745] The device (smart glasses) sends new data to the server.

[0746] Step 9: Generate and serve update advice

[0747] The server reanalyzes the data and updates the advice as needed.

[0748] The server regenerates the updated advice in text and audio form.

[0749] The devices (smart glasses and earphones) will then provide the updated advice to the user again.

[0750] This is the specific flow of processing. This process allows the user to always receive the most appropriate golf playing advice in real time according to the situation.

[0751] Example 1

[0752] 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."

[0753] When playing golf, it is extremely difficult for users to accurately assess the current playing situation and environmental conditions and develop an optimal strategy. Furthermore, without a way to obtain appropriate advice in real time, the quality of play declines, especially for beginners and inexperienced players. Furthermore, it is difficult to effectively utilize past play data to improve.

[0754] 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.

[0755] In this invention, the server includes means for acquiring user location information, means for acquiring environmental data such as wind strength and direction and temperature, means for transmitting the location information and environmental data, means for receiving and analyzing the location information and environmental data, means for generating optimal sports play advice based on the analysis results, means for providing the advice to the user, means for analyzing the data taking into account the user's past play data, and means for updating the advice in real time based on the analyzed data. This allows the user to receive optimal play advice in real time, thereby improving the quality of their play. Furthermore, using past play data also contributes to improving the user's skills.

[0756] "Means for obtaining user location information" refers to a device that uses the Global Positioning System (GPS) or equivalent technology to determine the user's current location in real time.

[0757] "Means for acquiring environmental data such as wind strength, direction, and temperature" refers to devices that measure the surrounding environmental conditions using environmental sensors such as anemometers, temperature sensors, and wind vanes.

[0758] "Means for transmitting the location information and environmental data" refers to a device or function that transmits this data to a server via wireless communication technology (e.g., Bluetooth, Wi-Fi).

[0759] "Means for receiving and analyzing the location information and environmental data" refers to a series of processes in which the server processes the data received and analyzes it using statistical analysis and machine learning algorithms.

[0760] "Means for generating optimal sports play advice based on analysis results" refers to a function that generates specific advice such as optimal club selection, shot direction, and strength based on analyzed data.

[0761] The "means for providing the advice to the user" refers to a display device or an audio device for conveying the generated advice to the user in text or audio form.

[0762] "Means for performing analysis taking into account the user's past play data" refers to a function that improves the accuracy of analysis by using data such as the user's previous scores and shot success rates.

[0763] "Means for updating advice in real time based on analyzed data" refers to a function that updates the content of advice in a timely manner in response to changes in the environment and situation during play.

[0764] MODE FOR CARRYING OUT THE INVENTION

[0765] This invention is implemented using a system consisting of a user, a device (smart glasses and earphones), and a server. The device is responsible for acquiring the user's location information and environmental data, and the server analyzes the received data to generate optimal advice and provide it to the user through the device.

[0766] Hardware and Software Configuration

[0767] User

[0768] Users download and install a dedicated application onto their smartphone, which then functions as a central device for sending and receiving data.

[0769] Terminal

[0770] The device consists of smart glasses and earphones. The smart glasses use a built-in GPS to determine the user's current location. They also have built-in environmental sensors, such as an anemometer, temperature sensor, and wind vane, to acquire data such as wind strength and direction and temperature. The earphones are a device that provides audio advice to the user.

[0771] server

[0772] The server uses powerful computing resources and specialized software to analyze the received location and environmental data, using statistical analysis software and machine learning algorithms. Based on the analysis results, optimal play advice is generated.

[0773] Data Flow and Processing

[0774] Initial Setup

[0775] Users download and install the dedicated application onto their smartphone. They launch the application, register an account, and enter their playing profile (handicap, favorite club, playing style, etc.). After that, the user puts on the smart glasses and earphones and pairs them with the smartphone application via Bluetooth.

[0776] Data collection and transmission

[0777] When a user starts playing, the smart glasses on the device use their built-in GPS to obtain their current location in real time, while environmental sensors measure data such as wind strength, direction, and temperature. This data is then sent to a server via the smartphone.

[0778] Data analysis and advice generation

[0779] The server analyzes the received location and environmental data using statistical analysis and machine learning algorithms. The server also takes into account the user's past play data (e.g., score, shot success rate). Based on the analysis results, the server generates optimal play advice. The advice is provided in text and audio formats.

[0780] Providing advice

[0781] The generated advice is sent to the device, where visual information (e.g., recommended club, shot direction, etc.) is displayed on the smart glasses display, and audio advice is provided through earphones, allowing the user to receive appropriate playing strategies in real time.

[0782] Specific examples

[0783] For example, say a user is standing on the tee box of the first hole. The device's smart glasses use GPS to pinpoint its location, and environmental sensors measure that a wind is blowing from the right at 5 meters per second. This information is sent to a server via the smartphone. The server analyzes the received data and past play data and generates the advice "Use a 3-wood and aim for the left side of the fairway." This advice is displayed on the smart glasses' display as "3-wood recommended, aim for the left side of the fairway," and is communicated to the user via earphones via voice: "The wind is blowing from the right at 5 meters per second. Aim for the left side of the fairway."

[0784] Prompt Sentence Examples

[0785] If you input the following prompt into the generative AI model, it will return the above specific action description:

[0786] Please explain in detail the process of the smart glasses and earphone system that supports golf play. The system collects location and environmental data, sends it to a server for analysis, and then generates and provides appropriate playing advice to the user. Please explain each processing step, including the specific operation.

[0787] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0788] Step 1: User performs initial setup

[0789] Users download and install the dedicated application onto their smartphone. They launch the application, register an account, and enter their own playing profile (handicap, favorite club, playing style, etc.). They then put on the smart glasses and earphones and pair them with the smartphone application via Bluetooth.

[0790] Input: Smartphone, account information, play profile

[0791] Output: Paired smart glasses and earphones

[0792] Step 2: Device collects data

[0793] When a user starts playing, the smart glasses use their built-in GPS to obtain their current location in real time, while environmental sensors measure data such as wind strength, direction, and temperature. The acquired data is then stored in the smart glasses' internal memory.

[0794] Input: current user location, environmental conditions

[0795] Output: Collected location and environmental data

[0796] Step 3: The device sends the data to the server

[0797] The smart glasses collect location and environmental data and transmit it to a server via a smartphone, using Bluetooth and an internet connection.

[0798] Input: Collected location and environmental data

[0799] Output: Data sent to the server

[0800] Step 4: The server parses the data

[0801] The server receives the location and environmental data, and then analyzes it by integrating it with the user's past play data. Statistical analysis software and machine learning algorithms are used for the analysis. The analysis results in advice tailored to the situation at hand.

[0802] Input: location information, environmental data, past play data

[0803] Output: Best Play Advice

[0804] Step 5: Server generates advice

[0805] The server generates optimal play advice based on the analysis results, including recommended clubs, shot direction, and strength. The generated advice is saved in text and audio formats.

[0806] Input: Analysis results

[0807] Output: Play advice in text and audio format

[0808] Step 6: The server sends the advice to the device

[0809] The server generates text and audio advice and sends it to the smart glasses and earphones via an internet connection and Bluetooth.

[0810] Input: Text and audio advice

[0811] Output: Advice sent to terminal

[0812] Step 7: The device provides advice to the user

[0813] The smart glasses display visual information and provide real-time audio advice through earphones, allowing users to instantly receive appropriate playing strategies.

[0814] Input: Advice sent to terminal

[0815] Output: Visual and audio advice provided to the user

[0816] (Application example 1)

[0817] 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."

[0818] In conventional shopping experiences, it has been difficult for users to efficiently obtain necessary product information in stores and make optimal purchasing decisions. Furthermore, there has been no system that analyzes in-store environmental data and users' purchasing history in real time to provide optimal advice to individuals. This has led to users wasting time and sometimes being unable to find the perfect product. A new system is needed to solve these problems.

[0819] 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.

[0820] In this invention, the server includes means for acquiring user location information, means for acquiring environmental data such as wind strength and direction and temperature, means for acquiring product information to support user decision-making, means for transmitting the location information, environmental data and product information, means for receiving and analyzing the location information, environmental data and product information, means for generating optimal shopping advice based on the analysis results, and means for providing the advice to the user. This enables users to efficiently acquire information and make optimal purchasing decisions even in a physical store.

[0821] "User location information" is geographical coordinate data of the user's current location.

[0822] "Environmental data" refers to data relating to the surrounding conditions of the user's current location, such as wind strength and direction, temperature, and humidity.

[0823] "Product information" is data that includes detailed information about products in a store, such as price, stock status, and promotion information.

[0824] The "data transmission means" is a communication means for sending the acquired location information, environmental data, and product information to the server.

[0825] The "analysis means" is a means having a function of analyzing necessary information based on received data and generating optimal advice.

[0826] "Shopping advice" is information that includes recommendations and instructions to help users make optimal purchasing decisions.

[0827] "User movement" is information indicating changes in the user's position as they move around the store.

[0828] The "advice providing means" is a means for conveying the generated advice to the user, and presents the information visually or audibly.

[0829] System Configuration

[0830] This system consists of a user, a device (smart glasses and earphones), and a server. The device is responsible for acquiring location and environmental data as well as product information, and the server analyzes the received data to generate optimal shopping advice and provide it to the user via the device.

[0831] Initial Setup

[0832] Users download and install the dedicated application on their smartphone, then register an account and enter their user profile (such as purchase history, favorite product categories, alert settings, etc.), then put on the smart glasses and earphones and pair them with the application using Bluetooth or other means.

[0833] Data collection and transmission

[0834] The device (smart glasses) uses its built-in GPS to obtain the user's current location in real time. It also uses sensors in the smart glasses to measure environmental data such as wind strength, direction, and temperature. It also obtains product information for the store. This data is then sent to a server via the smartphone.

[0835] Data analysis and advice generation

[0836] The server receives the transmitted location and environmental data, as well as the product information. It also analyzes the data using machine learning algorithms, taking into account the user's past purchase history and preferences. Based on the analysis results, it generates shopping advice tailored to the current situation (specifically, recommended products, promotion information, product locations within the store, etc.).

[0837] Providing advice

[0838] The generated advice is sent to the device in text and audio formats, with visual information displayed on the smart glasses display and audio advice provided through earphones, allowing users to receive appropriate shopping strategies in real time.

[0839] Hardware and software used

[0840] Smart glasses: Equipped with built-in GPS and sensors to collect location and environmental data, and display visual information.

[0841] Earphones: Provides audio advice.

[0842] Server: Analyzes data and generates advice using machine learning algorithms such as TensorFlow.

[0843] Specific examples

[0844] For example, suppose a user arrives at a clothing section of a store. The smart glasses use GPS to pinpoint their location and measure the ambient temperature and humidity. This data is sent to a server, which generates advice such as, "We recommend the new jackets on sale. They're on the rack on the left," based on the user's past purchasing history and preferences. The smart glasses' display will show "New Jackets Sale - Left Rack," and a voice message will be heard through the earphones saying, "There are new jackets on the rack on the left."

[0845] Example prompts for generative AI models

[0846] "The user is in the clothing department. Based on environmental data, what products should you recommend, taking into account their purchasing history and preferences?"

[0847] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0848] Step 1:

[0849] The user downloads and installs a dedicated application onto their smartphone. Next, the user registers for an account and enters their user profile (purchase history, favorite product categories, alert settings, etc.). This information is entered on the user's smartphone and sent to the server. The input data is stored on the server as the user's account information. The output is user profile data securely stored on the server.

[0850] Step 2:

[0851] The user wears the smart glasses and earphones and pairs them with a dedicated application using Bluetooth. At this time, the system checks whether the smart glasses and earphones are working properly. The input is the user's Bluetooth pairing operation, and the output is a message indicating successful pairing.

[0852] Step 3:

[0853] The device (smart glasses) uses its built-in GPS to obtain the user's current location in real time. In addition, the smart glasses' sensors collect environmental data such as wind strength, direction, and temperature. The input is data from the GPS sensor and environmental sensors, and the output is the obtained location information and environmental data.

[0854] Step 4:

[0855] Obtain product information within the store. Smart glasses communicate with the store's sales floor information system to obtain the latest product information (price, stock status, promotion information, etc.). The input is data from the sales floor information system, and the output is the obtained product information.

[0856] Step 5:

[0857] The device transmits the acquired location information, environmental data, and product information to a server via a smartphone. The input is the connection between the smart glasses and the smartphone, and the output is the transmission of data to the server. The server receives this data.

[0858] Step 6:

[0859] The server integrates and analyzes the received location information, environmental data, product information, and the user's past purchasing history and preference data. The server uses TensorFlow to execute machine learning algorithms and generate optimal shopping advice (recommended products, promotion information, product locations in stores, etc.). The input is various data collected on the server, and the output is advice as the result of the analysis.

[0860] Step 7:

[0861] The generated advice is sent to the devices (smart glasses and earphones) in text and audio formats. Visual information is displayed on the smart glasses display, and audio advice is provided through the earphones. The input is advice data sent from the server, and the output is the display of visual information and playback of audio advice.

[0862] Step 8:

[0863] The user selects the most suitable product based on the visual information displayed on the smart glasses display and the audio advice provided through the earphones. At this stage, the user can obtain an appropriate shopping strategy in real time. The input is the advice content, and the output is the user's purchasing decision.

[0864] 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.

[0865] DETAILED DESCRIPTION OF THE INVENTION The following describes a mode for carrying out the invention based on the claims.

[0866] System Configuration

[0867] The system of the present invention includes a user, a terminal (smart glasses and earphones), a server, and an emotion engine that recognizes the user's emotions. The terminal is responsible for acquiring location information and environmental data, and the emotion engine analyzes the user's emotions. The server analyzes the received data and generates optimal advice, which is then provided to the user via the terminal and emotion engine.

[0868] Initial Setup

[0869] Users download and install the dedicated application onto their smartphone. Next, they register an account and enter their playing profile (such as their handicap, favorite clubs, and playing style). After that, they put on the smart glasses and earphones and pair them with the app using Bluetooth or other means. The emotion engine is also installed at the same time, and the device is ready for use.

[0870] Data collection and transmission

[0871] The device (smart glasses) uses its built-in GPS to obtain the user's current location in real time. It also uses built-in sensors to measure environmental data such as wind strength, direction, and temperature. At the same time, an emotion engine analyzes the user's facial expressions and tone of voice to obtain emotional data. This data is then sent to a server via the smartphone.

[0872] Data analysis and advice generation

[0873] The server receives the transmitted location information, environmental data, and emotional data. It also considers the user's past playing data (e.g., previous scores and shot success rates) and analyzes them using a machine learning algorithm. Based on the analysis results, golf play advice appropriate for the situation and the user's emotions at the time (specifically, recommended clubs, shot direction, strength, and sometimes words of encouragement or relaxation) is generated.

[0874] Providing advice

[0875] The generated advice is sent to the device in text and audio formats. Visual information is displayed on the smart glasses' display, and audio advice is provided through earphones. In addition, an emotion engine adjusts the tone and content of the advice according to the user's emotions. This allows the user to receive appropriate playing strategies in real time, taking their emotions into consideration.

[0876] Specific examples

[0877] For example, suppose a user is standing on the tee box of the first hole. The device (smart glasses) acquires the user's location, wind strength, and direction, and the emotion engine analyzes the user's facial expressions and tone of voice. This data is sent to the server, which analyzes the information and past play history. The server generates advice such as "Use a 3-wood and aim for the left side of the fairway." This advice is displayed on the smart glasses' display as "3-wood recommended, aim for the left side of the fairway," and is communicated to the user through the earphones by voice: "The wind is blowing from the right at 5 meters per second. Aim for the left side of the fairway." Furthermore, if the emotion engine determines that the user is nervous, it will provide additional encouraging words such as "Relax and hit the ball as you normally would."

[0878] This aspect of the invention allows users to receive optimal advice tailored to their situation in real time, and also provides support that takes emotional well-being into consideration, which is expected to help even beginners improve their scores in a short period of time.

[0879] The processing flow will be explained below.

[0880] Step 1: User registration and initial setup

[0881] Users download and install a dedicated application onto their smartphone.

[0882] Users create an account and enter their playing profile, including their handicap, preferred clubs, and playing style.

[0883] Users wear smart glasses, earphones, and the emotion engine, and pair them with the app using Bluetooth.

[0884] Step 2: Obtaining location and environmental data

[0885] The device (smart glasses) uses its built-in GPS function to obtain the user's current location in real time.

[0886] The device (smart glasses) uses built-in sensors to measure environmental data such as wind strength, direction, and temperature.

[0887] Step 3: Obtaining emotion data

[0888] The device (emotion engine) captures the user's facial expressions and tone of voice using a camera and microphone.

[0889] The device (emotion engine) analyzes the acquired data and recognizes the user's emotional state.

[0890] Step 4: Sending data

[0891] The devices (smart glasses and emotion engine) transmit the acquired location information, environmental data, and emotion data to a server via a smartphone.

[0892] Step 5: Receiving and consolidating data

[0893] The server receives the location information, environmental data, and emotion data transmitted from the terminal.

[0894] The server retrieves the user's past playing data (e.g., previous scores and shot success rates) from a database and consolidates all the data.

[0895] Step 6: Analyze the data

[0896] The server analyzes the real-time environment and the user's past play history based on the integrated data.

[0897] The server uses an analytical algorithm to generate optimal advice (recommended club, shot direction, strength, etc.).

[0898] Step 7: Generating and preparing advice

[0899] The server converts the generated advice into text and audio formats.

[0900] The server prepares to send text information to the smart glasses and audio information to the earphones.

[0901] Step 8: Providing advice

[0902] The device (smart glasses) displays the text advice received from the server on the display.

[0903] Example: "3 wood recommended, aim for the left side of the fairway."

[0904] The terminal (earphone) provides the audio advice received from the server to the user.

[0905] Example: "The wind is blowing from the right at 5 meters per second. Aim to the left side of the fairway."

[0906] Step 9: Adjust your advice to your emotions

[0907] The terminal (emotion engine) keeps monitoring the user's emotional state.

[0908] The server receives data from the emotion engine and adjusts the tone and content of the advice.

[0909] For example, if the user is nervous, add encouraging words like "Relax and type normally."

[0910] Step 10: Real-time updates

[0911] The devices (smart glasses and emotion engine) continuously monitor the user's movements and changes in environmental data, and send new data to the server.

[0912] Step 11: Generate and serve update advice

[0913] The server reanalyzes the data and updates the advice as needed.

[0914] The server regenerates the updated advice in text and audio form.

[0915] The devices (smart glasses and earphones, emotion engine) provide updated advice to the user.

[0916] This is the specific flow of the process. This process allows the user to always receive the best golf play advice in real time according to the situation, and also enjoys support that takes emotional well-being into consideration.

[0917] Example 2

[0918] 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."

[0919] Conventional golf play support systems provide advice based only on the user's location and environmental data, but do not take into account the user's emotional state. As a result, they often fail to provide appropriate advice based on the user's mental state, resulting in poor performance. Furthermore, the lack of systems that can flexibly respond to real-time movements and environmental changes makes it difficult to provide advice based on the latest information.

[0920] 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.

[0921] In this invention, the server includes: means for acquiring user location information; means for acquiring environmental data such as wind strength and direction and temperature; means for acquiring user emotion data; means for transmitting the location information, environmental data, and emotion data; means for receiving and analyzing the location information, environmental data, and emotion data; means for generating optimal golf play advice based on the analysis results; means for providing the advice to the user; means for integrating and analyzing the user's past play data; means for monitoring the user's movements and environmental changes in real time and updating the advice; and means for adjusting the tone and content of the advice in response to the user's emotion. This enables real-time and appropriate advice that takes into account not only the user's location and environment, but also their emotional state. As a result, even beginners can improve their scores and play quality in a short period of time.

[0922] A "user" is a person who uses the system to receive golf playing advice.

[0923] "Location information" is data indicating the user's current location obtained using a GPS function or the like.

[0924] "Environmental Data" refers to data that indicates external environmental conditions that affect golf play, such as wind strength and direction, and temperature.

[0925] "Emotional data" is data that indicates the user's psychological state, analyzed from the user's facial expressions, tone of voice, etc.

[0926] "Transmission means" is a function for transmitting acquired location information, environmental data, and emotion data to a server.

[0927] The "receiving means" is a function that allows the server to receive the transmitted location information, environmental data, and emotion data.

[0928] "Analysis means" is a function that analyzes data based on received data using machine learning algorithms, etc.

[0929] The "advice generating means" is a function that generates optimal golf playing advice based on the analysis results.

[0930] The "provision means" is a function that provides the generated advice to the user in text and audio formats.

[0931] "Past play data" refers to data that indicates the user's past golf play history data, shot success rate, and the like.

[0932] "Real-time monitoring means" is a function for monitoring user movements and changes in the environment in real time and updating advice.

[0933] The "tone adjustment means" is a function that adjusts the tone and content of the advice voice according to the user's emotions.

[0934] An embodiment of the present invention will be described below. This system includes a user, a terminal (smart glasses and earphones), a server, and an emotion engine. The terminal is responsible for acquiring location information and environmental data, and the emotion engine analyzes the user's emotions. The server analyzes the received data and generates optimal advice, which is then provided to the user via the terminal and the emotion engine.

[0935] Users download and install the dedicated application onto their smartphone. Next, they register an account and enter their playing profile (handicap, favorite club, playing style, etc.). After that, they put on the smart glasses and earphones and pair them with the app via Bluetooth. The emotion engine is also installed at the same time, and the device is ready for use.

[0936] The device (smart glasses) uses its built-in GPS to obtain the user's current location in real time. It also uses built-in sensors to measure environmental data such as wind strength, direction, and temperature. At the same time, an emotion engine analyzes the user's facial expressions and tone of voice to obtain emotional data. This data is then sent to a server via the smartphone.

[0937] The server receives and analyzes the transmitted location information, environmental data, and emotional data using AWS AI services and machine learning algorithms (e.g., TensorFlow and PyTorch). It also takes into account the user's past playing data (e.g., previous scores and shot success rates) and generates golf play advice appropriate to the situation and the user's emotions at the time based on the analysis results. For example, it generates advice such as "Use a 3-wood and aim for the left side of the fairway."

[0938] The generated advice is sent to the device in text and audio formats. The smart glasses display visual information such as "3-wood recommended, aim for the left side of the fairway," and the earphones provide a voice message saying, "The wind is blowing from the right at 5 meters per second. Aim for the left side of the fairway." Furthermore, the emotion engine adjusts the tone and content of the advice according to the user's emotions. For example, if it determines that the user is nervous, it will provide encouraging words such as, "Relax and hit the ball as you normally would."

[0939] As a concrete example, consider a user standing on the tee box of the first hole. The device (smart glasses) acquires the user's location, wind strength, and direction, and the emotion engine analyzes the user's facial expressions and tone of voice. This data is sent to the server, which analyzes it based on this information and past play history. The server then generates advice such as "Use a 3-wood and aim for the left side of the fairway." This advice is displayed on the smart glasses' display as "3-wood recommended, aim for the left side of the fairway," and is communicated to the user through the earphones by voice: "The wind is blowing from the right at 5 meters per second. Aim for the left side of the fairway." Furthermore, if the emotion engine determines that the user is nervous, it provides encouraging words such as "Relax and hit the ball as usual."

[0940] Examples of prompts include, "I'm standing on the tee box. Please capture my location and environmental data to provide advice on the best club and shot." or "I'm playing. Please consider my past data and current emotions to generate advice for my next shot."

[0941] This invention allows users to receive optimal advice tailored to their situation in real time, and also provides support that takes emotional well-being into consideration. As a result, even beginners can expect to improve their scores in a short period of time.

[0942] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0943] Step 1: Initial Setup

[0944] The user downloads and installs the dedicated application onto their smartphone. Next, the user registers an account and enters their playing profile (e.g., handicap, preferred club, playing style, etc.). Finally, the user puts on the smart glasses and earphones and pairs them with the app via Bluetooth. The user's basic information and device pairing status are entered, completing the initial setup.

[0945] Step 2: Data collection

[0946] The device (smart glasses) uses its built-in GPS to obtain the user's current location (location information) in real time. It also uses built-in sensors to measure environmental data such as wind strength and direction and temperature. At the same time, the emotion engine uses the smart glasses' camera and earphone microphone to analyze the user's facial expressions and tone of voice to obtain emotional data. The input is the user's location information, environmental data, and emotional data, which are obtained in real time and sent to the server.

[0947] Step 3: Send data

[0948] The device sends the collected location information, environmental data, and emotional data to a server via a smartphone. The input is the three types of data acquired from the device, and the output is the status of data transmission to the server.

[0949] Step 4: Data analysis

[0950] The server receives and analyzes the transmitted location information, environmental data, and emotional data using AWS AI services and machine learning algorithms (e.g., TensorFlow and PyTorch). The inputs are location information, environmental data, and emotional data, and the output is the analysis results. This analysis includes the user's past play data (e.g., previous scores and success rates) and takes this into account to generate optimal advice.

[0951] Step 5: Advice Generation

[0952] Based on the results of the data analysis, the server generates golf play advice appropriate to the situation and the user's emotions at the time. For example, specific advice such as "Use a 3-wood and aim for the left fairway" may be generated. The input is the results of the data analysis, and the output is the generated advice.

[0953] Step 6: Providing advice

[0954] The generated advice is sent to the device (smart glasses and earphones) in text and audio format. The device displays "3-wood recommended, aim for the left side of the fairway" on the smart glasses display and announces through the earphones, "The wind is blowing from the right at 5 meters per second. Aim for the left side of the fairway." Furthermore, the emotion engine adjusts the tone and content of the advice according to the user's emotions, adding encouraging words such as "Relax and hit the ball as normal" if the user is nervous. The input is the generated advice and the results of reanalysis of emotion data, and the output is specific feedback to the user.

[0955] (Application example 2)

[0956] 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."

[0957] Modern security services lack real-time advice tailored to the psychological state of security guards and their surrounding environments. In particular, situations in which security guards feel tense or stressed can make it difficult for them to respond, potentially resulting in a decline in the quality of security. Furthermore, real-time data collection and analysis are required to quickly respond to on-site situations. A system that can solve these problems and provide effective support for security guards is needed.

[0958] The identification processing 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 location information, means for acquiring environmental data such as wind strength and direction and temperature, means for recognizing the user's emotions, means for transmitting the location information, environmental data, and emotional data, means for receiving and analyzing the location information, environmental data, and emotional data, means for generating optimal security advice based on the analysis results, and means for providing the advice to the user. This allows security guards to receive optimal advice tailored to the situation in real time, which also contributes to reducing tension and stress, thereby improving the quality of security.

[0959] "Location information" is data that indicates the user's current geographical location.

[0960] "Environmental data" refers to data about the surrounding environment, such as wind strength, direction, and temperature.

[0961] "Emotion data" refers to data relating to the user's psychological state that can be obtained from facial expressions, tone of voice, and the like.

[0962] The "data transmission means" is a means for transmitting location information, environmental data, and emotion data from the terminal to the server.

[0963] The "data receiving and analyzing means" is a means by which the server receives and analyzes location information, environmental data, and emotion data.

[0964] The "security advice generating means" is a means for generating optimal security advice based on the analysis results.

[0965] The "advice providing means" is a means for providing the generated advice to the user.

[0966] "Past behavioral data" refers to data relating to the user's behavioral history.

[0967] The "real-time monitoring means" is a means for monitoring the user's movements and changes in the environment in real time and updating advice as necessary.

[0968] To implement this invention, a system including a user, a terminal (smart glasses and earphones), a server, and an emotion engine is required. The terminal acquires the user's location information and environmental data, and the emotion engine analyzes the user's emotions. The server receives this data, generates optimal security advice, and provides it to the user via the terminal and the emotion engine.

[0969] System Configuration

[0970] First, the user must download and install a dedicated application onto their smartphone. Next, they register an account and enter their user profile. After that, they put on the smart glasses and earphones and pair them with the app using Bluetooth or other means. The emotion engine is also installed at this stage, and the device is ready to use.

[0971] Data collection and transmission

[0972] The device (smart glasses) uses its built-in GPS to obtain the user's current location in real time. It also uses built-in sensors to measure environmental data such as wind strength, direction, and temperature. At the same time, an emotion engine analyzes the user's facial expressions and tone of voice to obtain emotional data. This data is then sent to a server via the smartphone.

[0973] Data analysis and advice generation

[0974] The server receives the transmitted location information, environmental data, and emotional data. It also takes into account the user's past behavioral data and performs analysis using a machine learning algorithm. Based on the analysis results, security advice appropriate to the situation and the user's emotions at the time (specifically, recommendations for strengthening security activities and vigilant areas) is generated.

[0975] Providing advice

[0976] The generated advice is sent to the terminal in text and audio formats. Visual information is displayed on the smart glasses' display, and audio advice is provided through earphones. In addition, an emotion engine adjusts the tone and content of the advice according to the user's emotions. This allows security guards to take appropriate security actions in real time, taking their emotions into consideration.

[0977] Specific examples

[0978] For example, a security guard guarding a large shopping mall at night sends location information and environmental data acquired by his device (smart glasses) along with emotional data analyzed by an emotion engine to a server. The server analyzes this information, and if it determines that the security guard is feeling nervous or stressed, it generates security advice such as, "Caution is required around current location X. Look around and ensure safety." This advice is displayed on the smart glasses and communicated to the security guard via audible audio through earphones.

[0979] Prompt Sentence Examples

[0980] Input:

[0981] Position: Point X

[0982] Environmental data: Dark, quiet

[0983] Emotional data: Tension, high alertness

[0984] Output:

[0985] Advice: "Caution is advised around location X. Please look around and make sure it is safe."

[0986] In this way, security personnel receive real-time advice adapted to the situation on the ground, enabling them to carry out effective security operations.

[0987] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0988] Step 1:

[0989] The user downloads and installs the dedicated application on their smartphone. Next, the user registers an account and enters their user profile, which sends the user's basic information to the server.

[0990] Input: Smartphone operation, user information.

[0991] Output: User profile registration.

[0992] Step 2:

[0993] The user puts on the smart glasses and earphones and pairs them with the app using Bluetooth. The emotion engine is also incorporated at this stage, and the system is ready. If pairing is successful, initialization data is sent to the server.

[0994] Input: Smart glasses, earphones, Bluetooth connection.

[0995] Output: Device paired and initialized successfully.

[0996] Step 3:

[0997] The device (smart glasses) uses its built-in GPS to obtain the user's current location in real time. It also uses built-in sensors to measure environmental data such as wind strength, direction, and temperature. This data is obtained in real time.

[0998] Input: GPS data, environmental sensor data.

[0999] Output: Location and environmental data.

[1000] Step 4:

[1001] The emotion engine analyzes the user's facial expressions and tone of voice to obtain emotional data, which is updated in real time.

[1002] Input: facial expression data, tone of voice.

[1003] Output: User emotion data.

[1004] Step 5:

[1005] The acquired location information, environmental data, and emotional data are sent via the smartphone to a server, which receives and analyzes the data.

[1006] Input: Location, environment data, emotion data.

[1007] Output: Sending data to the server.

[1008] Step 6:

[1009] The server uses machine learning algorithms to analyze the data it receives, integrating location, environmental, emotional, and past behavioral data to generate optimal security advice tailored to each individual situation.

[1010] Input: location, environmental data, emotional data, past behavioral data.

[1011] Output: Analysis results (best security advice).

[1012] Step 7:

[1013] The server sends the generated security advice in text and audio format to the device, where it is displayed visually on the smart glasses display and provided via audio via earphones.

[1014] Input: Analysis result (security advice).

[1015] Output: Providing text and audio advice.

[1016] Step 8:

[1017] An emotion engine adjusts the tone and content of advice based on the user's emotional state, providing emotionally sensitive security advice in real time.

[1018] Input: User emotion data.

[1019] Output: Providing tailored advice.

[1020] 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.

[1021] 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.

[1022] 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.

[1023] [Fourth embodiment]

[1024] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1025] 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.

[1026] 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).

[1027] 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.

[1028] 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.

[1029] 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).

[1030] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1031] 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.

[1032] 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.

[1033] 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.

[1034] 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.

[1035] 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.

[1036] 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."

[1037] DETAILED DESCRIPTION OF THE INVENTION The following describes a mode for carrying out the invention based on the claims.

[1038] System Configuration

[1039] This system consists of a user, a device (smart glasses and earphones), and a server. The device is responsible for acquiring location and environmental data, and the server analyzes the received data to generate optimal advice, which is then provided to the user via the device.

[1040] Initial Setup

[1041] Users download and install the dedicated application onto their smartphone, then register an account and enter their playing profile (such as handicap, favorite club, playing style, etc.), then put on the smart glasses and earphones and pair them with the app using Bluetooth or other means.

[1042] Data collection and transmission

[1043] The device (smart glasses) uses its built-in GPS to obtain the user's current location in real time. It also uses built-in sensors to measure environmental data such as wind strength, direction, and temperature. The obtained data is sent to a server via the smartphone.

[1044] Data analysis and advice generation

[1045] The server receives the transmitted location information and environmental data. It also takes into account the user's past playing data (e.g., previous scores and shot success rates) and analyzes them using a machine learning algorithm. Based on the analysis results, golf play advice appropriate for the current situation (specifically, recommended clubs, shot direction, strength, etc.) is generated.

[1046] Providing advice

[1047] The generated advice is sent to the device in text and audio formats, and visual information is displayed on the smart glasses display, while audio advice is provided through earphones, allowing users to receive appropriate playing strategies in real time.

[1048] Specific examples

[1049] Let's say a user is standing on the tee box of the first hole. The device (smart glasses) acquires their position, wind strength, and direction, and sends them to the server. The server analyzes this data and past play history to generate advice such as "Use a 3-wood and aim for the left side of the fairway." This advice is displayed on the smart glasses' display as "3-wood recommended, aim for the left side of the fairway," and is communicated to the user through the earphones by voice: "The wind is blowing from the right at 5 meters per second. Aim for the left side of the fairway."

[1050] This embodiment of the present invention allows users to receive optimal advice in real time, enabling even beginners to improve their scores in a short period of time.

[1051] The processing flow will be explained below.

[1052] Step 1: User registration and initial setup

[1053] Users install a dedicated application on their smartphone and create an account.

[1054] The user enters their playing profile (handicap, preferred club, playing style, etc.).

[1055] Users wear smart glasses and earphones and pair them with the app via Bluetooth or other means.

[1056] Step 2: Obtaining location information

[1057] The device (smart glasses) uses its built-in GPS function to obtain the user's current location in real time.

[1058] The device (smart glasses) transmits the acquired location information to a server via a smartphone.

[1059] Step 3: Get environment data

[1060] The device (smart glasses) uses built-in sensors to measure environmental data such as wind strength, direction, and temperature.

[1061] The device (smart glasses) sends the measured environmental data to a server via a smartphone.

[1062] Step 4: Receiving and consolidating data

[1063] The server receives the location information and environmental data transmitted from the terminal.

[1064] The server retrieves and integrates the user's past playing data (e.g., previous scores and shot success rates) from a database.

[1065] Step 5: Analyze the data

[1066] The server analyzes the real-time environment and the user's past play history based on the received and integrated data.

[1067] The server uses machine learning algorithms to generate optimal advice (recommended club, shot direction, strength, etc.).

[1068] Step 6: Generating and preparing advice

[1069] The server converts the generated advice into text and audio formats.

[1070] The server prepares the text information to be sent to the smart glasses and the audio information to be sent to the earphones.

[1071] Step 7: Providing advice

[1072] The device (smart glasses) displays the text advice received from the server on the display.

[1073] Example: "3 wood recommended, aim for the left side of the fairway."

[1074] The terminal (earphone) provides the user with the audio advice received from the server.

[1075] Example: "The wind is blowing from the right at 5 meters per second. Aim to the left side of the fairway."

[1076] Step 8: Real-time updates

[1077] The device (smart glasses) monitors changes in the user's location and environmental data in real time.

[1078] The device (smart glasses) sends new data to the server.

[1079] Step 9: Generate and serve update advice

[1080] The server reanalyzes the data and updates the advice as needed.

[1081] The server regenerates the updated advice in text and audio form.

[1082] The devices (smart glasses and earphones) will then provide the updated advice to the user again.

[1083] This is the specific flow of processing. This process allows the user to always receive the most appropriate golf playing advice in real time according to the situation.

[1084] Example 1

[1085] 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."

[1086] When playing golf, it is extremely difficult for users to accurately assess the current playing situation and environmental conditions and develop an optimal strategy. Furthermore, without a way to obtain appropriate advice in real time, the quality of play declines, especially for beginners and inexperienced players. Furthermore, it is difficult to effectively utilize past play data to improve.

[1087] 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.

[1088] In this invention, the server includes means for acquiring user location information, means for acquiring environmental data such as wind strength and direction and temperature, means for transmitting the location information and environmental data, means for receiving and analyzing the location information and environmental data, means for generating optimal sports play advice based on the analysis results, means for providing the advice to the user, means for analyzing the data taking into account the user's past play data, and means for updating the advice in real time based on the analyzed data. This allows the user to receive optimal play advice in real time, thereby improving the quality of their play. Furthermore, using past play data also contributes to improving the user's skills.

[1089] "Means for obtaining user location information" refers to a device that uses the Global Positioning System (GPS) or equivalent technology to determine the user's current location in real time.

[1090] "Means for acquiring environmental data such as wind strength, direction, and temperature" refers to devices that measure the surrounding environmental conditions using environmental sensors such as anemometers, temperature sensors, and wind vanes.

[1091] "Means for transmitting the location information and environmental data" refers to a device or function that transmits this data to a server via wireless communication technology (e.g., Bluetooth, Wi-Fi).

[1092] "Means for receiving and analyzing the location information and environmental data" refers to a series of processes in which the server processes the data received and analyzes it using statistical analysis and machine learning algorithms.

[1093] "Means for generating optimal sports play advice based on analysis results" refers to a function that generates specific advice such as optimal club selection, shot direction, and strength based on analyzed data.

[1094] The "means for providing the advice to the user" refers to a display device or an audio device for conveying the generated advice to the user in text or audio form.

[1095] "Means for performing analysis taking into account the user's past play data" refers to a function that improves the accuracy of analysis by using data such as the user's previous scores and shot success rates.

[1096] "Means for updating advice in real time based on analyzed data" refers to a function that updates the content of advice in a timely manner in response to changes in the environment and situation during play.

[1097] MODE FOR CARRYING OUT THE INVENTION

[1098] This invention is implemented using a system consisting of a user, a device (smart glasses and earphones), and a server. The device is responsible for acquiring the user's location information and environmental data, and the server analyzes the received data to generate optimal advice and provide it to the user through the device.

[1099] Hardware and Software Configuration

[1100] User

[1101] Users download and install a dedicated application onto their smartphone, which then functions as a central device for sending and receiving data.

[1102] Terminal

[1103] The device consists of smart glasses and earphones. The smart glasses use a built-in GPS to determine the user's current location. They also have built-in environmental sensors, such as an anemometer, temperature sensor, and wind vane, to acquire data such as wind strength and direction and temperature. The earphones are a device that provides audio advice to the user.

[1104] server

[1105] The server uses powerful computing resources and specialized software to analyze the received location and environmental data, using statistical analysis software and machine learning algorithms. Based on the analysis results, optimal play advice is generated.

[1106] Data Flow and Processing

[1107] Initial Setup

[1108] Users download and install the dedicated application onto their smartphone. They launch the application, register an account, and enter their playing profile (handicap, favorite club, playing style, etc.). After that, the user puts on the smart glasses and earphones and pairs them with the smartphone application via Bluetooth.

[1109] Data collection and transmission

[1110] When a user starts playing, the smart glasses on the device use their built-in GPS to obtain their current location in real time, while environmental sensors measure data such as wind strength, direction, and temperature. This data is then sent to a server via the smartphone.

[1111] Data analysis and advice generation

[1112] The server analyzes the received location and environmental data using statistical analysis and machine learning algorithms. The server also takes into account the user's past play data (e.g., score, shot success rate). Based on the analysis results, the server generates optimal play advice. The advice is provided in text and audio formats.

[1113] Providing advice

[1114] The generated advice is sent to the device, where visual information (e.g., recommended club, shot direction, etc.) is displayed on the smart glasses display, and audio advice is provided through earphones, allowing the user to receive appropriate playing strategies in real time.

[1115] Specific examples

[1116] For example, say a user is standing on the tee box of the first hole. The device's smart glasses use GPS to pinpoint its location, and environmental sensors measure that a wind is blowing from the right at 5 meters per second. This information is sent to a server via the smartphone. The server analyzes the received data and past play data and generates the advice "Use a 3-wood and aim for the left side of the fairway." This advice is displayed on the smart glasses' display as "3-wood recommended, aim for the left side of the fairway," and is communicated to the user via earphones via voice: "The wind is blowing from the right at 5 meters per second. Aim for the left side of the fairway."

[1117] Prompt Sentence Examples

[1118] If you input the following prompt into the generative AI model, it will return the above specific action description:

[1119] Please explain in detail the process of the smart glasses and earphone system that supports golf play. The system collects location and environmental data, sends it to a server for analysis, and then generates and provides appropriate playing advice to the user. Please explain each processing step, including the specific operation.

[1120] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1121] Step 1: User performs initial setup

[1122] Users download and install the dedicated application onto their smartphone. They launch the application, register an account, and enter their own playing profile (handicap, favorite club, playing style, etc.). They then put on the smart glasses and earphones and pair them with the smartphone application via Bluetooth.

[1123] Input: Smartphone, account information, play profile

[1124] Output: Paired smart glasses and earphones

[1125] Step 2: Device collects data

[1126] When a user starts playing, the smart glasses use their built-in GPS to obtain their current location in real time, while environmental sensors measure data such as wind strength, direction, and temperature. The acquired data is then stored in the smart glasses' internal memory.

[1127] Input: current user location, environmental conditions

[1128] Output: Collected location and environmental data

[1129] Step 3: The device sends the data to the server

[1130] The smart glasses collect location and environmental data and transmit it to a server via a smartphone, using Bluetooth and an internet connection.

[1131] Input: Collected location and environmental data

[1132] Output: Data sent to the server

[1133] Step 4: The server parses the data

[1134] The server receives the location and environmental data, and then analyzes it by integrating it with the user's past play data. Statistical analysis software and machine learning algorithms are used for the analysis. The analysis results in advice tailored to the situation at hand.

[1135] Input: location information, environmental data, past play data

[1136] Output: Best Play Advice

[1137] Step 5: Server generates advice

[1138] The server generates optimal play advice based on the analysis results, including recommended clubs, shot direction, and strength. The generated advice is saved in text and audio formats.

[1139] Input: Analysis results

[1140] Output: Play advice in text and audio format

[1141] Step 6: The server sends the advice to the device

[1142] The server generates text and audio advice and sends it to the smart glasses and earphones via an internet connection and Bluetooth.

[1143] Input: Text and audio advice

[1144] Output: Advice sent to terminal

[1145] Step 7: The device provides advice to the user

[1146] The smart glasses display visual information and provide real-time audio advice through earphones, allowing users to instantly receive appropriate playing strategies.

[1147] Input: Advice sent to terminal

[1148] Output: Visual and audio advice provided to the user

[1149] (Application example 1)

[1150] 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."

[1151] In conventional shopping experiences, it has been difficult for users to efficiently obtain necessary product information in stores and make optimal purchasing decisions. Furthermore, there has been no system that analyzes in-store environmental data and users' purchasing history in real time to provide optimal advice to individuals. This has led to users wasting time and sometimes being unable to find the perfect product. A new system is needed to solve these problems.

[1152] 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.

[1153] In this invention, the server includes means for acquiring user location information, means for acquiring environmental data such as wind strength and direction and temperature, means for acquiring product information to support user decision-making, means for transmitting the location information, environmental data and product information, means for receiving and analyzing the location information, environmental data and product information, means for generating optimal shopping advice based on the analysis results, and means for providing the advice to the user. This enables users to efficiently acquire information and make optimal purchasing decisions even in a physical store.

[1154] "User location information" is geographical coordinate data of the user's current location.

[1155] "Environmental data" refers to data relating to the surrounding conditions of the user's current location, such as wind strength and direction, temperature, and humidity.

[1156] "Product information" is data that includes detailed information about products in a store, such as price, stock status, and promotion information.

[1157] The "data transmission means" is a communication means for sending the acquired location information, environmental data, and product information to the server.

[1158] The "analysis means" is a means having a function of analyzing necessary information based on received data and generating optimal advice.

[1159] "Shopping advice" is information that includes recommendations and instructions to help users make optimal purchasing decisions.

[1160] "User movement" is information indicating changes in the user's position as they move around the store.

[1161] The "advice providing means" is a means for conveying the generated advice to the user, and presents the information visually or audibly.

[1162] System Configuration

[1163] This system consists of a user, a device (smart glasses and earphones), and a server. The device is responsible for acquiring location and environmental data as well as product information, and the server analyzes the received data to generate optimal shopping advice and provide it to the user via the device.

[1164] Initial Setup

[1165] Users download and install the dedicated application on their smartphone, then register an account and enter their user profile (such as purchase history, favorite product categories, alert settings, etc.), then put on the smart glasses and earphones and pair them with the application using Bluetooth or other means.

[1166] Data collection and transmission

[1167] The device (smart glasses) uses its built-in GPS to obtain the user's current location in real time. It also uses sensors in the smart glasses to measure environmental data such as wind strength, direction, and temperature. It also obtains product information for the store. This data is then sent to a server via the smartphone.

[1168] Data analysis and advice generation

[1169] The server receives the transmitted location and environmental data, as well as the product information. It also analyzes the data using machine learning algorithms, taking into account the user's past purchase history and preferences. Based on the analysis results, it generates shopping advice tailored to the current situation (specifically, recommended products, promotion information, product locations within the store, etc.).

[1170] Providing advice

[1171] The generated advice is sent to the device in text and audio formats, with visual information displayed on the smart glasses display and audio advice provided through earphones, allowing users to receive appropriate shopping strategies in real time.

[1172] Hardware and software used

[1173] Smart glasses: Equipped with built-in GPS and sensors to collect location and environmental data, and display visual information.

[1174] Earphones: Provides audio advice.

[1175] Server: Analyzes data and generates advice using machine learning algorithms such as TensorFlow.

[1176] Specific examples

[1177] For example, suppose a user arrives at a clothing section of a store. The smart glasses use GPS to pinpoint their location and measure the ambient temperature and humidity. This data is sent to a server, which generates advice such as, "We recommend the new jackets on sale. They're on the rack on the left," based on the user's past purchasing history and preferences. The smart glasses' display will show "New Jackets Sale - Left Rack," and a voice message will be heard through the earphones saying, "There are new jackets on the rack on the left."

[1178] Example prompts for generative AI models

[1179] "The user is in the clothing department. Based on environmental data, what products should you recommend, taking into account their purchasing history and preferences?"

[1180] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1181] Step 1:

[1182] The user downloads and installs a dedicated application onto their smartphone. Next, the user registers for an account and enters their user profile (purchase history, favorite product categories, alert settings, etc.). This information is entered on the user's smartphone and sent to the server. The input data is stored on the server as the user's account information. The output is user profile data securely stored on the server.

[1183] Step 2:

[1184] The user wears the smart glasses and earphones and pairs them with a dedicated application using Bluetooth. At this time, the system checks whether the smart glasses and earphones are working properly. The input is the user's Bluetooth pairing operation, and the output is a message indicating successful pairing.

[1185] Step 3:

[1186] The device (smart glasses) uses its built-in GPS to obtain the user's current location in real time. In addition, the smart glasses' sensors collect environmental data such as wind strength, direction, and temperature. The input is data from the GPS sensor and environmental sensors, and the output is the obtained location information and environmental data.

[1187] Step 4:

[1188] Obtain product information within the store. Smart glasses communicate with the store's sales floor information system to obtain the latest product information (price, stock status, promotion information, etc.). The input is data from the sales floor information system, and the output is the obtained product information.

[1189] Step 5:

[1190] The device transmits the acquired location information, environmental data, and product information to a server via a smartphone. The input is the connection between the smart glasses and the smartphone, and the output is the transmission of data to the server. The server receives this data.

[1191] Step 6:

[1192] The server integrates and analyzes the received location information, environmental data, product information, and the user's past purchasing history and preference data. The server uses TensorFlow to execute machine learning algorithms and generate optimal shopping advice (recommended products, promotion information, product locations in stores, etc.). The input is various data collected on the server, and the output is advice as the result of the analysis.

[1193] Step 7:

[1194] The generated advice is sent to the devices (smart glasses and earphones) in text and audio formats. Visual information is displayed on the smart glasses display, and audio advice is provided through the earphones. The input is advice data sent from the server, and the output is the display of visual information and playback of audio advice.

[1195] Step 8:

[1196] The user selects the most suitable product based on the visual information displayed on the smart glasses display and the audio advice provided through the earphones. At this stage, the user can obtain an appropriate shopping strategy in real time. The input is the advice content, and the output is the user's purchasing decision.

[1197] 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.

[1198] DETAILED DESCRIPTION OF THE INVENTION The following describes a mode for carrying out the invention based on the claims.

[1199] System Configuration

[1200] The system of the present invention includes a user, a terminal (smart glasses and earphones), a server, and an emotion engine that recognizes the user's emotions. The terminal is responsible for acquiring location information and environmental data, and the emotion engine analyzes the user's emotions. The server analyzes the received data and generates optimal advice, which is then provided to the user via the terminal and emotion engine.

[1201] Initial Setup

[1202] Users download and install the dedicated application onto their smartphone. Next, they register an account and enter their playing profile (such as their handicap, favorite clubs, and playing style). After that, they put on the smart glasses and earphones and pair them with the app using Bluetooth or other means. The emotion engine is also installed at the same time, and the device is ready for use.

[1203] Data collection and transmission

[1204] The device (smart glasses) uses its built-in GPS to obtain the user's current location in real time. It also uses built-in sensors to measure environmental data such as wind strength, direction, and temperature. At the same time, an emotion engine analyzes the user's facial expressions and tone of voice to obtain emotional data. This data is then sent to a server via the smartphone.

[1205] Data analysis and advice generation

[1206] The server receives the transmitted location information, environmental data, and emotional data. It also considers the user's past playing data (e.g., previous scores and shot success rates) and analyzes them using a machine learning algorithm. Based on the analysis results, golf play advice appropriate for the situation and the user's emotions at the time (specifically, recommended clubs, shot direction, strength, and sometimes words of encouragement or relaxation) is generated.

[1207] Providing advice

[1208] The generated advice is sent to the device in text and audio formats. Visual information is displayed on the smart glasses' display, and audio advice is provided through earphones. In addition, an emotion engine adjusts the tone and content of the advice according to the user's emotions. This allows the user to receive appropriate playing strategies in real time, taking their emotions into consideration.

[1209] Specific examples

[1210] For example, suppose a user is standing on the tee box of the first hole. The device (smart glasses) acquires the user's location, wind strength, and direction, and the emotion engine analyzes the user's facial expressions and tone of voice. This data is sent to the server, which analyzes the information and past play history. The server generates advice such as "Use a 3-wood and aim for the left side of the fairway." This advice is displayed on the smart glasses' display as "3-wood recommended, aim for the left side of the fairway," and is communicated to the user through the earphones by voice: "The wind is blowing from the right at 5 meters per second. Aim for the left side of the fairway." Furthermore, if the emotion engine determines that the user is nervous, it will provide additional encouraging words such as "Relax and hit the ball as you normally would."

[1211] This aspect of the invention allows users to receive optimal advice tailored to their situation in real time, and also provides support that takes emotional well-being into consideration, which is expected to help even beginners improve their scores in a short period of time.

[1212] The processing flow will be explained below.

[1213] Step 1: User registration and initial setup

[1214] Users download and install a dedicated application onto their smartphone.

[1215] Users create an account and enter their playing profile, including their handicap, preferred clubs, and playing style.

[1216] Users wear smart glasses, earphones, and the emotion engine, and pair them with the app using Bluetooth.

[1217] Step 2: Obtaining location and environmental data

[1218] The device (smart glasses) uses its built-in GPS function to obtain the user's current location in real time.

[1219] The device (smart glasses) uses built-in sensors to measure environmental data such as wind strength, direction, and temperature.

[1220] Step 3: Obtaining emotion data

[1221] The device (emotion engine) captures the user's facial expressions and tone of voice using a camera and microphone.

[1222] The device (emotion engine) analyzes the acquired data and recognizes the user's emotional state.

[1223] Step 4: Sending data

[1224] The devices (smart glasses and emotion engine) transmit the acquired location information, environmental data, and emotion data to a server via a smartphone.

[1225] Step 5: Receiving and consolidating data

[1226] The server receives the location information, environmental data, and emotion data transmitted from the terminal.

[1227] The server retrieves the user's past playing data (e.g., previous scores and shot success rates) from a database and consolidates all the data.

[1228] Step 6: Analyze the data

[1229] The server analyzes the real-time environment and the user's past play history based on the integrated data.

[1230] The server uses an analytical algorithm to generate optimal advice (recommended club, shot direction, strength, etc.).

[1231] Step 7: Generating and preparing advice

[1232] The server converts the generated advice into text and audio formats.

[1233] The server prepares to send text information to the smart glasses and audio information to the earphones.

[1234] Step 8: Providing advice

[1235] The device (smart glasses) displays the text advice received from the server on the display.

[1236] Example: "3 wood recommended, aim for the left side of the fairway."

[1237] The terminal (earphone) provides the audio advice received from the server to the user.

[1238] Example: "The wind is blowing from the right at 5 meters per second. Aim to the left side of the fairway."

[1239] Step 9: Adjust your advice to your emotions

[1240] The terminal (emotion engine) keeps monitoring the user's emotional state.

[1241] The server receives data from the emotion engine and adjusts the tone and content of the advice.

[1242] For example, if the user is nervous, add encouraging words like "Relax and type normally."

[1243] Step 10: Real-time updates

[1244] The devices (smart glasses and emotion engine) continuously monitor the user's movements and changes in environmental data, and send new data to the server.

[1245] Step 11: Generate and serve update advice

[1246] The server reanalyzes the data and updates the advice as needed.

[1247] The server regenerates the updated advice in text and audio form.

[1248] The devices (smart glasses and earphones, emotion engine) provide updated advice to the user.

[1249] This is the specific flow of the process. This process allows the user to always receive the best golf play advice in real time according to the situation, and also enjoys support that takes emotional well-being into consideration.

[1250] Example 2

[1251] 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."

[1252] Conventional golf play support systems provide advice based only on the user's location and environmental data, but do not take into account the user's emotional state. As a result, they often fail to provide appropriate advice based on the user's mental state, resulting in poor performance. Furthermore, the lack of systems that can flexibly respond to real-time movements and environmental changes makes it difficult to provide advice based on the latest information.

[1253] 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.

[1254] In this invention, the server includes: means for acquiring user location information; means for acquiring environmental data such as wind strength and direction and temperature; means for acquiring user emotion data; means for transmitting the location information, environmental data, and emotion data; means for receiving and analyzing the location information, environmental data, and emotion data; means for generating optimal golf play advice based on the analysis results; means for providing the advice to the user; means for integrating and analyzing the user's past play data; means for monitoring the user's movements and environmental changes in real time and updating the advice; and means for adjusting the tone and content of the advice in response to the user's emotion. This enables real-time and appropriate advice that takes into account not only the user's location and environment, but also their emotional state. As a result, even beginners can improve their scores and play quality in a short period of time.

[1255] A "user" is a person who uses the system to receive golf playing advice.

[1256] "Location information" is data indicating the user's current location obtained using a GPS function or the like.

[1257] "Environmental Data" refers to data that indicates external environmental conditions that affect golf play, such as wind strength and direction, and temperature.

[1258] "Emotional data" is data that indicates the user's psychological state, analyzed from the user's facial expressions, tone of voice, etc.

[1259] "Transmission means" is a function for transmitting acquired location information, environmental data, and emotion data to a server.

[1260] The "receiving means" is a function that allows the server to receive the transmitted location information, environmental data, and emotion data.

[1261] "Analysis means" is a function that analyzes data based on received data using machine learning algorithms, etc.

[1262] The "advice generating means" is a function that generates optimal golf playing advice based on the analysis results.

[1263] The "provision means" is a function that provides the generated advice to the user in text and audio formats.

[1264] "Past play data" refers to data that indicates the user's past golf play history data, shot success rate, and the like.

[1265] "Real-time monitoring means" is a function for monitoring user movements and changes in the environment in real time and updating advice.

[1266] The "tone adjustment means" is a function that adjusts the tone and content of the advice voice according to the user's emotions.

[1267] An embodiment of the present invention will be described below. This system includes a user, a terminal (smart glasses and earphones), a server, and an emotion engine. The terminal is responsible for acquiring location information and environmental data, and the emotion engine analyzes the user's emotions. The server analyzes the received data and generates optimal advice, which is then provided to the user via the terminal and the emotion engine.

[1268] Users download and install the dedicated application onto their smartphone. Next, they register an account and enter their playing profile (handicap, favorite club, playing style, etc.). After that, they put on the smart glasses and earphones and pair them with the app via Bluetooth. The emotion engine is also installed at the same time, and the device is ready for use.

[1269] The device (smart glasses) uses its built-in GPS to obtain the user's current location in real time. It also uses built-in sensors to measure environmental data such as wind strength, direction, and temperature. At the same time, an emotion engine analyzes the user's facial expressions and tone of voice to obtain emotional data. This data is then sent to a server via the smartphone.

[1270] The server receives and analyzes the transmitted location information, environmental data, and emotional data using AWS AI services and machine learning algorithms (e.g., TensorFlow and PyTorch). It also takes into account the user's past playing data (e.g., previous scores and shot success rates) and generates golf play advice appropriate to the situation and the user's emotions at the time based on the analysis results. For example, it generates advice such as "Use a 3-wood and aim for the left side of the fairway."

[1271] The generated advice is sent to the device in text and audio formats. The smart glasses display visual information such as "3-wood recommended, aim for the left side of the fairway," and the earphones provide a voice message saying, "The wind is blowing from the right at 5 meters per second. Aim for the left side of the fairway." Furthermore, the emotion engine adjusts the tone and content of the advice according to the user's emotions. For example, if it determines that the user is nervous, it will provide encouraging words such as, "Relax and hit the ball as you normally would."

[1272] As a concrete example, consider a user standing on the tee box of the first hole. The device (smart glasses) acquires the user's location, wind strength, and direction, and the emotion engine analyzes the user's facial expressions and tone of voice. This data is sent to the server, which analyzes it based on this information and past play history. The server then generates advice such as "Use a 3-wood and aim for the left side of the fairway." This advice is displayed on the smart glasses' display as "3-wood recommended, aim for the left side of the fairway," and is communicated to the user through the earphones by voice: "The wind is blowing from the right at 5 meters per second. Aim for the left side of the fairway." Furthermore, if the emotion engine determines that the user is nervous, it provides encouraging words such as "Relax and hit the ball as usual."

[1273] Examples of prompts include, "I'm standing on the tee box. Please capture my location and environmental data to provide advice on the best club and shot." or "I'm playing. Please consider my past data and current emotions to generate advice for my next shot."

[1274] This invention allows users to receive optimal advice tailored to their situation in real time, and also provides support that takes emotional well-being into consideration. As a result, even beginners can expect to improve their scores in a short period of time.

[1275] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1276] Step 1: Initial Setup

[1277] The user downloads and installs the dedicated application onto their smartphone. Next, the user registers an account and enters their playing profile (e.g., handicap, preferred club, playing style, etc.). Finally, the user puts on the smart glasses and earphones and pairs them with the app via Bluetooth. The user's basic information and device pairing status are entered, completing the initial setup.

[1278] Step 2: Data collection

[1279] The device (smart glasses) uses its built-in GPS to obtain the user's current location (location information) in real time. It also uses built-in sensors to measure environmental data such as wind strength and direction and temperature. At the same time, the emotion engine uses the smart glasses' camera and earphone microphone to analyze the user's facial expressions and tone of voice to obtain emotional data. The input is the user's location information, environmental data, and emotional data, which are obtained in real time and sent to the server.

[1280] Step 3: Send data

[1281] The device sends the collected location information, environmental data, and emotional data to a server via a smartphone. The input is the three types of data acquired from the device, and the output is the status of data transmission to the server.

[1282] Step 4: Data analysis

[1283] The server receives and analyzes the transmitted location information, environmental data, and emotional data using AWS AI services and machine learning algorithms (e.g., TensorFlow and PyTorch). The inputs are location information, environmental data, and emotional data, and the output is the analysis results. This analysis includes the user's past play data (e.g., previous scores and success rates) and takes this into account to generate optimal advice.

[1284] Step 5: Advice Generation

[1285] Based on the results of the data analysis, the server generates golf play advice appropriate to the situation and the user's emotions at the time. For example, specific advice such as "Use a 3-wood and aim for the left fairway" may be generated. The input is the results of the data analysis, and the output is the generated advice.

[1286] Step 6: Providing advice

[1287] The generated advice is sent to the device (smart glasses and earphones) in text and audio format. The device displays "3-wood recommended, aim for the left side of the fairway" on the smart glasses display and announces through the earphones, "The wind is blowing from the right at 5 meters per second. Aim for the left side of the fairway." Furthermore, the emotion engine adjusts the tone and content of the advice according to the user's emotions, adding encouraging words such as "Relax and hit the ball as normal" if the user is nervous. The input is the generated advice and the results of reanalysis of emotion data, and the output is specific feedback to the user.

[1288] (Application example 2)

[1289] 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."

[1290] Modern security services lack real-time advice tailored to the psychological state of security guards and their surrounding environments. In particular, situations in which security guards feel tense or stressed can make it difficult for them to respond, potentially resulting in a decline in the quality of security. Furthermore, real-time data collection and analysis are required to quickly respond to on-site situations. A system that can solve these problems and provide effective support for security guards is needed.

[1291] The identification processing 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 location information, means for acquiring environmental data such as wind strength and direction and temperature, means for recognizing the user's emotions, means for transmitting the location information, environmental data, and emotional data, means for receiving and analyzing the location information, environmental data, and emotional data, means for generating optimal security advice based on the analysis results, and means for providing the advice to the user. This allows security guards to receive optimal advice tailored to the situation in real time, which also contributes to reducing tension and stress, thereby improving the quality of security.

[1292] "Location information" is data that indicates the user's current geographical location.

[1293] "Environmental data" refers to data about the surrounding environment, such as wind strength, direction, and temperature.

[1294] "Emotion data" refers to data relating to the user's psychological state that can be obtained from facial expressions, tone of voice, and the like.

[1295] The "data transmission means" is a means for transmitting location information, environmental data, and emotion data from the terminal to the server.

[1296] The "data receiving and analyzing means" is a means by which the server receives and analyzes location information, environmental data, and emotion data.

[1297] The "security advice generating means" is a means for generating optimal security advice based on the analysis results.

[1298] The "advice providing means" is a means for providing the generated advice to the user.

[1299] "Past behavioral data" refers to data relating to the user's behavioral history.

[1300] The "real-time monitoring means" is a means for monitoring the user's movements and changes in the environment in real time and updating advice as necessary.

[1301] To implement this invention, a system including a user, a terminal (smart glasses and earphones), a server, and an emotion engine is required. The terminal acquires the user's location information and environmental data, and the emotion engine analyzes the user's emotions. The server receives this data, generates optimal security advice, and provides it to the user via the terminal and the emotion engine.

[1302] System Configuration

[1303] First, the user must download and install a dedicated application onto their smartphone. Next, they register an account and enter their user profile. After that, they put on the smart glasses and earphones and pair them with the app using Bluetooth or other means. The emotion engine is also installed at this stage, and the device is ready to use.

[1304] Data collection and transmission

[1305] The device (smart glasses) uses its built-in GPS to obtain the user's current location in real time. It also uses built-in sensors to measure environmental data such as wind strength, direction, and temperature. At the same time, an emotion engine analyzes the user's facial expressions and tone of voice to obtain emotional data. This data is then sent to a server via the smartphone.

[1306] Data analysis and advice generation

[1307] The server receives the transmitted location information, environmental data, and emotional data. It also takes into account the user's past behavioral data and performs analysis using a machine learning algorithm. Based on the analysis results, security advice appropriate to the situation and the user's emotions at the time (specifically, recommendations for strengthening security activities and vigilant areas) is generated.

[1308] Providing advice

[1309] The generated advice is sent to the terminal in text and audio formats. Visual information is displayed on the smart glasses' display, and audio advice is provided through earphones. In addition, an emotion engine adjusts the tone and content of the advice according to the user's emotions. This allows security guards to take appropriate security actions in real time, taking their emotions into consideration.

[1310] Specific examples

[1311] For example, a security guard guarding a large shopping mall at night sends location information and environmental data acquired by his device (smart glasses) along with emotional data analyzed by an emotion engine to a server. The server analyzes this information, and if it determines that the security guard is feeling nervous or stressed, it generates security advice such as, "Caution is required around current location X. Look around and ensure safety." This advice is displayed on the smart glasses and communicated to the security guard via audible audio through earphones.

[1312] Prompt Sentence Examples

[1313] Input:

[1314] Position: Point X

[1315] Environmental data: Dark, quiet

[1316] Emotional data: Tension, high alertness

[1317] Output:

[1318] Advice: "Caution is advised around location X. Please look around and make sure it is safe."

[1319] In this way, security personnel receive real-time advice adapted to the situation on the ground, enabling them to carry out effective security operations.

[1320] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1321] Step 1:

[1322] The user downloads and installs the dedicated application on their smartphone. Next, the user registers an account and enters their user profile, which sends the user's basic information to the server.

[1323] Input: Smartphone operation, user information.

[1324] Output: User profile registration.

[1325] Step 2:

[1326] The user puts on the smart glasses and earphones and pairs them with the app using Bluetooth. The emotion engine is also incorporated at this stage, and the system is ready. If pairing is successful, initialization data is sent to the server.

[1327] Input: Smart glasses, earphones, Bluetooth connection.

[1328] Output: Device paired and initialized successfully.

[1329] Step 3:

[1330] The device (smart glasses) uses its built-in GPS to obtain the user's current location in real time. It also uses built-in sensors to measure environmental data such as wind strength, direction, and temperature. This data is obtained in real time.

[1331] Input: GPS data, environmental sensor data.

[1332] Output: Location and environmental data.

[1333] Step 4:

[1334] The emotion engine analyzes the user's facial expressions and tone of voice to obtain emotional data, which is updated in real time.

[1335] Input: facial expression data, tone of voice.

[1336] Output: User emotion data.

[1337] Step 5:

[1338] The acquired location information, environmental data, and emotional data are sent via the smartphone to a server, which receives and analyzes the data.

[1339] Input: Location, environment data, emotion data.

[1340] Output: Sending data to the server.

[1341] Step 6:

[1342] The server uses machine learning algorithms to analyze the data it receives, integrating location, environmental, emotional, and past behavioral data to generate optimal security advice tailored to each individual situation.

[1343] Input: location, environmental data, emotional data, past behavioral data.

[1344] Output: Analysis results (best security advice).

[1345] Step 7:

[1346] The server sends the generated security advice in text and audio format to the device, where it is displayed visually on the smart glasses display and provided via audio via earphones.

[1347] Input: Analysis result (security advice).

[1348] Output: Providing text and audio advice.

[1349] Step 8:

[1350] An emotion engine adjusts the tone and content of advice based on the user's emotional state, providing emotionally sensitive security advice in real time.

[1351] Input: User emotion data.

[1352] Output: Providing tailored advice.

[1353] 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.

[1354] 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.

[1355] 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.

[1356] 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.

[1357] 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.

[1358] 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.

[1359] 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).

[1360] 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.

[1361] 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."

[1362] 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.

[1363] 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).

[1364] 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.

[1365] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1366] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1367] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1368] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1369] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1370] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1371] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1372] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1373] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1374] The following is further disclosed regarding the above embodiment.

[1375] (Claim 1)

[1376] A means for acquiring user location information;

[1377] A means of obtaining environmental data such as wind strength, direction, and temperature;

[1378] means for transmitting the location information and environmental data;

[1379] means for receiving and analyzing the location information and environmental data;

[1380] means for generating optimal golf playing advice based on the analysis results;

[1381] A system including means for providing said advice to a user.

[1382] (Claim 2)

[1383] 10. The system of claim 1, further comprising means for integrating and analyzing past play data of users.

[1384] (Claim 3)

[1385] 10. The system of claim 1, further comprising means for monitoring user movements and environmental changes in real time and updating the advice.

[1386] "Example 1"

[1387] (Claim 1)

[1388] A means for acquiring user location information;

[1389] A means of obtaining environmental data such as wind strength, direction, and temperature;

[1390] means for transmitting the location information and environmental data;

[1391] means for receiving and analyzing the location information and environmental data;

[1392] A means for generating optimal sports playing advice based on the analysis results;

[1393] means for providing said advice to a user;

[1394] A means for analyzing the user's past play data;

[1395] The system includes a means for updating advice in real time based on the analyzed data.

[1396] (Claim 2)

[1397] 10. The system of claim 1, further comprising means for transmitting the generated advice in text and audio form and providing it to the user through a display and an audio device.

[1398] (Claim 3)

[1399] 10. The system of claim 1, further comprising means for using machine learning algorithms for data analysis.

[1400] "Application Example 1"

[1401] (Claim 1)

[1402] A means for acquiring user location information;

[1403] A means of obtaining environmental data such as wind strength, direction, and temperature;

[1404] A means for acquiring product information to assist a user in making a decision;

[1405] means for transmitting the location information, environmental data, and product information;

[1406] means for receiving and analyzing the location information, environmental data, and product information;

[1407] a means for generating optimal shopping advice based on the analysis results;

[1408] A system including means for providing said advice to a user.

[1409] (Claim 2)

[1410] 10. The system of claim 1, further comprising means for integrating and analyzing past behavioral data of users.

[1411] (Claim 3)

[1412] 10. The system of claim 1, further comprising means for monitoring user movements and environmental changes in real time and updating the advice.

[1413] "Example 2: Combining Emotion Engines"

[1414] (Claim 1)

[1415] A means for acquiring user location information;

[1416] A means of obtaining environmental data such as wind strength, direction, and temperature;

[1417] A means for acquiring user emotion data;

[1418] means for transmitting the location information, environmental data, and emotion data;

[1419] means for receiving and analyzing the location information, environmental data, and emotion data;

[1420] means for generating optimal golf playing advice based on the analysis results;

[1421] A system including means for providing said advice to a user.

[1422] (Claim 2)

[1423] 10. The system of claim 1, further comprising means for integrating and analyzing past play data of users.

[1424] (Claim 3)

[1425] 10. The system of claim 1, further comprising means for monitoring user movements and environmental changes in real time and updating the advice.

[1426] (Claim 4)

[1427] 10. The system of claim 1, further comprising means for adjusting the tone and content of the advice depending on the user's emotions.

[1428] "Application example 2 when combining emotion engines"

[1429] (Claim 1)

[1430] A means for acquiring user location information;

[1431] A means of obtaining environmental data such as wind strength, direction, and temperature;

[1432] means for recognizing a user's emotion;

[1433] means for transmitting the location information, environmental data, and emotion data;

[1434] means for receiving and analyzing the location information, environmental data, and emotion data;

[1435] A means for generating optimal security advice based on the analysis results;

[1436] A system including means for providing said advice to a user.

[1437] (Claim 2)

[1438] 10. The system of claim 1, further comprising means for integrating and analyzing past behavioral data of users.

[1439] (Claim 3)

[1440] 10. The system of claim 1, further comprising means for monitoring user movements and environmental changes in real time and updating the advice. [Explanation of symbols]

[1441] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for acquiring user location information; A means of obtaining environmental data such as wind strength, direction, and temperature; means for transmitting the location information and environmental data; means for receiving and analyzing the location information and environmental data; means for generating optimal golf playing advice based on the analysis results; A system including means for providing said advice to a user.

2. The system according to claim 1 , further comprising means for integrating and analyzing past play data of users.

3. The system of claim 1 , further comprising means for monitoring user movements and environmental changes in real time and updating the advice.

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