System

Abstract

A system is provided.SOLUTION: A system comprising: means for acquiring positional information of a user; means for collecting environmental data; means for reading past play data of the user; means for integrating and analyzing the positional information, the environmental data, and the past play data; means for generating optimal play advice based on an analysis result; and means for notifying the user of the play advice.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] Amateur golf players often face challenges such as stagnant scores and the high cost of hiring a human caddie. This hinders proper golf management and makes it difficult to improve their game. Furthermore, lack of experience makes strategic play difficult, forcing players to rely on their own style of play. The present invention aims to resolve these challenges and enable amateur golf players to efficiently improve their scores. [Means for solving the problem]

[0005] In order to solve the above problems, the present invention provides a system having the following configuration: a means for acquiring user location information, a means for collecting environmental data, a means for reading the user's past play data, a means for integrating and analyzing the location information, environmental data, and past play data, a means for generating optimal play advice based on the analysis results, and a means for notifying the user of the play advice. This system uses artificial intelligence to provide appropriate golf management advice in real time, helping to improve the user's score by compensating for their lack of experience.

[0006] "User" refers to an amateur golf player who plays golf.

[0007] "Location information" refers to information about the user's current location obtained using GPS or other location measurement means.

[0008] "Environmental Data" means data relating to external environmental conditions that affect golf play, such as wind speed, wind direction, temperature, and humidity.

[0009] "Past play data" refers to data relating to golf plays the user has played in the past, including historical information such as which club was used and the results of the shot.

[0010] "Means" refers to the devices or technologies used to achieve a specific function.

[0011] "Analysis" refers to the process of integrating acquired data and using algorithms to derive the optimal strategy for the user's play.

[0012] "Playing advice" refers to specific instructions or suggestions provided to a user to help them play golf more effectively.

[0013] "Notification" refers to the act of communicating generated advice to the user, including using a visual display or an audio message.

[0014] The term "system" refers to the entire device or mechanism formed by combining the above means. [Brief explanation of the drawings]

[0015] [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

[0016] 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.

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

[0018] 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).

[0019] 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.

[0020] 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.

[0021] 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.

[0022] 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."

[0023] [First embodiment]

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

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0030] 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.

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

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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."

[0036] This invention is an AI unmanned caddy system that helps amateur golfers improve their scores efficiently. This system analyzes a user's location information, environmental data, and past play data, and provides optimal playing advice in real time.

[0037] System configuration

[0038] The system includes the following components:

[0039] 1. A device with a built-in GPS module that obtains the user's location information.

[0040] 2. A device with sensors that detect wind speed, direction, temperature, and humidity to collect environmental data.

[0041] 3. A server with a database that stores users' past play data.

[0042] 4. A server equipped with an artificial intelligence algorithm that integrates and analyzes collected location information, environmental data, and past play data.

[0043] 5. A server that generates optimal play advice based on the analysis results.

[0044] 6. A device with smart glasses and earphones that notifies the user of play advice.

[0045] Program processing

[0046] 1. Collecting user location information and gameplay data

[0047] The device uses the built-in GPS module to obtain its current location, which is then sent to the server.

[0048] The server identifies the user's current location and recognizes the target hole.

[0049] The server reads the user's past play data from the database and saves it.

[0050] 2. Real-time environmental data collection

[0051] The device collects environmental data using built-in sensors that detect wind speed, wind direction, temperature, and humidity, and transmits this data to a server.

[0052] 3. Data Analysis

[0053] The server combines collected location information, environmental data, and past play data and analyzes the data using artificial intelligence algorithms.

[0054] The server calculates the optimal club selection and shot direction for the user, taking into account factors such as the effects of wind, past shot results, and hole layout.

[0055] 4. Generating Advice

[0056] The server generates specific playing advice based on the analysis, including which club to use, the direction of the shot, and how much force to use.

[0057] 5. Notice to Users

[0058] The device displays the generated play advice as visual information on the smart glasses display.

[0059] The terminal provides audio advice to the user through an earphone.

[0060] Specific examples

[0061] The following example illustrates the process when the user reaches the fifth hole and wants to know the best club and shot direction for the next shot.

[0062] 1. The device acquires the user's current location using its built-in GPS function and sends it to the server.

[0063] 2. The server recognizes that the user is on the fifth hole and reads the past play data for the fifth hole from the database.

[0064] 3. The device uses its built-in sensor to detect that the current wind speed is 10 km / h and blowing north, and sends this information to the server.

[0065] 4. The server combines location information, environmental data, and past play data and analyzes the data using artificial intelligence algorithms.

[0066] 5. The server determines that the advice is for the user to use a 3-iron and to aim the shot slightly to the left.

[0067] 6. The device will display "Use a 3 iron and aim slightly to the left" on the smart glasses display and will give a voice notification through the earphones saying "Wind speed 10 km / h, northbound, use a 3 iron and aim slightly to the left."

[0068] In this way, users can receive optimal golf management advice in real time, making up for lack of experience and efficiently improving their scores.

[0069] The processing flow will be explained below.

[0070] Step 1:

[0071] The device uses a built-in GPS module to obtain the user's current location, which is then immediately sent to the server.

[0072] Step 2:

[0073] The server identifies the user's current location based on the received location information, identifies the corresponding golf hole, and records the information for further processing.

[0074] Step 3:

[0075] The server reads the user's past play data stored in a database, including the clubs previously used, shot results, and scores.

[0076] Step 4:

[0077] The device uses built-in sensors to collect environmental data such as wind speed, wind direction, temperature, and humidity, which is then sent to a server.

[0078] Step 5:

[0079] The server integrates the collected location information, past play data, and current environmental data, and performs analysis using artificial intelligence algorithms based on this data.

[0080] Step 6:

[0081] The server will comprehensively evaluate factors such as the wind's influence, hole layout, and past success rates to calculate the optimal club selection and shot direction. It also takes into account the power of the shot depending on the situation.

[0082] Step 7:

[0083] The server generates specific play advice based on the analysis results, such as "Use a 3-iron and aim slightly to the left."

[0084] Step 8:

[0085] The device receives play advice from the server and displays it on the smart glasses display, providing visual information such as "Use a 3 iron and aim slightly to the left."

[0086] Step 9:

[0087] The device will notify the user through the earphones by voice, "The wind speed is 10 km / h and blowing north. Aim slightly to the left with a 3 iron."

[0088] This series of processes allows users to receive optimal golf management advice in real time, making it possible to compensate for lack of experience and improve scores.

[0089] Example 1

[0090] 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."

[0091] Amateur golf players often find it difficult to improve their scores efficiently due to lack of experience and technical misjudgments. Furthermore, they lack support for improving their play quality due to limited access to appropriate advice in real time while playing. To solve this problem, a system is needed that integrates and analyzes the user's location information, environmental data, and past play data to provide optimal play advice in real time.

[0092] 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.

[0093] In this invention, the server includes means for acquiring user position information, means for collecting environmental data, means for reading the user's past play data, means for integrating and analyzing the position information, environmental data, and past play data, means for generating optimal play advice based on the analysis results, means for notifying the user of the play advice, and means for providing the advice to the user in visual and audio form, thereby enabling the user to receive optimal play advice in real time and efficiently improve their score.

[0094] The "means for acquiring user location information" is a function for identifying the user's current location and acquiring that location information.

[0095] The "means for collecting environmental data" is a function for detecting surrounding environmental information such as wind speed, wind direction, temperature, and humidity, and collecting this data.

[0096] The "means for reading the user's past play data" is a function for reading the user's past play history data from a database in which the history data is recorded.

[0097] "Means for integrating and analyzing" refers to a function that brings together acquired location information, environmental data, and past play data, and performs analysis based on that data.

[0098] The "means for generating optimal play advice based on the analysis results" is a function for generating optimal play advice for the user based on the results obtained by the analysis.

[0099] The "means for notifying the user of play advice" is a function for notifying the user of the generated play advice.

[0100] "Means for providing advice in visual and audio form" refers to a function for providing advice to the user visually and audio using the smart glasses' display and earphones.

[0101] This invention is an AI unmanned caddy system that helps amateur golfers improve their scores efficiently. This system analyzes a user's location information, environmental data, and past play data, and provides optimal playing advice in real time.

[0102] System Components

[0103] 1. A device with a built-in GPS module that obtains the user's location information

[0104] The device uses the built-in GPS module to obtain the user's current location information, which is then sent to the server.

[0105] 2. A device equipped with sensors to detect wind speed, wind direction, temperature, and humidity to collect environmental data.

[0106] The device's built-in sensors detect wind speed, direction, temperature, and humidity, and send this data to a server.

[0107] 3. A server with a database that stores users' past play data

[0108] The server stores the user's past play data in a database and reads it as needed.

[0109] 4. A server equipped with an artificial intelligence algorithm that integrates and analyzes collected location information, environmental data, and past play data.

[0110] The server's artificial intelligence algorithm integrates and analyzes the collected data (location information, environmental data, and past play data).

[0111] 5. Server that generates optimal play advice based on the analysis results

[0112] The server generates optimal play advice based on the analysis results and provides it to the user.

[0113] 6. A device with smart glasses and earphones that provides play advice to the user

[0114] The device displays the generated play advice on the smart glasses display and notifies the player via audio through earphones.

[0115] Specific examples

[0116] For example, if the user reaches the fifth hole and wants to know the best club and shot direction for the next shot, the process is as follows:

[0117] 1. The device acquires the user's current location using its built-in GPS function and sends it to the server.

[0118] 2. The server recognizes that the user is on the fifth hole and reads the past play data for the fifth hole from the database.

[0119] 3. The device uses its built-in sensor to detect that the current wind speed is 10 km / h and blowing north, and sends this information to the server.

[0120] 4. The server combines location information, environmental data, and past play data and analyzes the data using artificial intelligence algorithms.

[0121] 5. The server determines that the advice is for the user to use a 3-iron and to aim the shot slightly to the left.

[0122] 6. The device will display "Use a 3 iron and aim slightly to the left" on the smart glasses display and will give a voice notification through the earphones saying "Wind speed 10 km / h, northbound, use a 3 iron and aim slightly to the left."

[0123] Example prompts for generative AI models

[0124] Below are some example prompts to be input to the generative AI model:

[0125] "The user has reached the 5th hole. The wind is 10km / h and blowing from the north. Based on past play data, a 3-iron is the best option for this hole. Please advise which club to use and in what direction to aim for the next shot."

[0126] Based on this prompt, the generative AI model is expected to generate appropriate advice and provide it to the user.

[0127] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0128] Step 1:

[0129] Obtain the user's location information and send it to the server

[0130] The device uses its built-in GPS module to obtain the user's current location information. Specifically, the device periodically reads GPS data to obtain latitude and longitude information. This location information (input data) is sent from the device to the server (output data). For example, the device obtains location information of "latitude 35.6895, longitude 139.6917" and sends it to the server.

[0131] Step 2:

[0132] The server recognizes the target hole and loads past play data.

[0133] The server identifies the hole the user is currently on based on the acquired location information. It analyzes and recognizes the hole number from the location information (input data) and reads the corresponding past play data from the database (output data). Specifically, the server identifies the "5th hole" and reads the past play data for the 5th hole.

[0134] Step 3:

[0135] The device collects environmental data and sends it to the server.

[0136] The terminal uses its built-in sensors to collect on-site environmental data. Specifically, the sensors detect data such as wind speed, wind direction, temperature, and humidity (input data). This environmental data is sent from the terminal to a server (output data). For example, the terminal collects data such as "wind speed 10 km / h, facing north, temperature 25°C, humidity 60%" and sends it to the server.

[0137] Step 4:

[0138] The server aggregates the data and analyzes it using artificial intelligence algorithms.

[0139] The server integrates the acquired location information, environmental data, and past play data (input data). It then uses an artificial intelligence algorithm to perform analysis based on the integrated data. Specifically, the server's AI calculates the effects of wind and past shot results, and determines the optimal club selection and shot direction (output data). For example, the server may obtain the analysis result, "Use a 3-iron and set the shot direction slightly to the left."

[0140] Step 5:

[0141] The server generates advice and sends it to the device.

[0142] The server generates specific play advice based on the analysis results (input data). This advice is sent from the server to the device (output data). Specifically, the server generates the play advice "Use a 3-iron and aim slightly to the left" and sends it to the device.

[0143] Step 6:

[0144] The device notifies the user of the advice

[0145] The device notifies the user of the received advice (input data). Specifically, the advice is displayed as visual information on the smart glasses display and audio advice is provided through the earphones (output data). For example, the device displays "Use a 3 iron and aim slightly to the left" on the smart glasses, and the earphones provide an audio notification saying, "Wind speed 10 km / h, northbound, use a 3 iron and aim slightly to the left."

[0146] In this way, each processing step is executed sequentially, and the user can receive real-time play advice to efficiently improve their score.

[0147] (Application example 1)

[0148] 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."

[0149] Conventional self-driving vehicles lack the technology to provide optimal driving advice in real time, making it difficult for them to drive efficiently and make appropriate decisions. Ensuring safety and efficiency has been particularly difficult in situations where quick responses to changes in weather and road conditions are required.

[0150] 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.

[0151] In this invention, the server includes means for acquiring location information, means for collecting environmental data, means for reading the user's past operation data, means for integrating and analyzing the location information, environmental data, and past operation data, means for generating optimal operation advice based on the analysis results, and means for notifying the user of the operation advice, thereby making it possible to provide optimal driving advice in real time and improve driving efficiency and safety.

[0152] "Location information" is data that indicates the current geographic location of an object.

[0153] "Environmental data" refers to data that indicates weather conditions and surrounding circumstances, and specifically includes weather data, road condition data, temperature, humidity, and the like.

[0154] "Task data" is data that indicates the history of past operations and actions.

[0155] "Integration" means bringing together multiple different types of data into one system or format.

[0156] "Analysis" refers to the calculation or evaluation of collected data to arrive at a specific conclusion or result.

[0157] "Operation advice" refers to instructions or suggestions provided to help a user take optimal action.

[0158] "Notification" is the act of conveying important information to the user, and various means such as visual and auditory are used.

[0159] An "internal location information acquisition device" is a device that is built into a device to acquire location information, such as a GPS module.

[0160] A "sensor" is a device that detects physical or chemical changes and outputs them as data.

[0161] "Weather data" refers to data indicating weather conditions such as temperature, wind speed, and rainfall.

[0162] "Road condition data" refers to data relating to road conditions, such as traffic flow, whether there have been any accidents, and construction information.

[0163] This invention relates to a driving assistance system for autonomous vehicles. Specifically, this system integrates and analyzes location information, environmental data, and the user's past work data in real time to provide optimal driving advice.

[0164] System Configuration

[0165] The system includes the following components:

[0166] 1. Obtaining location information

[0167] The server acquires location information using the vehicle's built-in location information acquisition device (GPS module) and uses this information for analysis.

[0168] 2. Environmental data collection

[0169] The server uses environmental sensors installed in the vehicle to collect weather data (temperature, wind speed, rainfall, etc.), road condition data (traffic flow, accident information, etc.), temperature, and humidity.

[0170] 3. Loading past work data

[0171] The server reads data such as the user's past driving routes, traffic conditions, and accident information from a database.

[0172] 4. Analysis of Integrated Data

[0173] This location information, environmental data, and past work data are integrated on the server, and data analysis is performed using a generative AI model.

[0174] 5. Driving advice generation

[0175] Based on the analysis results, the server generates optimal driving routes and driving advice.

[0176] 6. Notice to Users

[0177] The generated driving advice is communicated to the user visually and audibly via a head-mounted display and smartphone.

[0178] What the program does

[0179] The server acquires the vehicle's current location from the built-in location acquisition device and collects real-time weather and road condition data from environmental sensors. This data is stored in a database along with past driving history data. The server integrates all collected data and uses a generative AI model to calculate the optimal driving route and advice.

[0180] Detailed processing contents

[0181] Hardware: Built-in location acquisition device (GPS module), environmental sensors, head-mounted display, smartphone, on-board computer.

[0182] Software: Python, AIML (Artificial Intelligence Machine Learning Library), speech synthesis library.

[0183] Specific examples

[0184] If the user is heading to a destination during rainy weather, here is an example of how the system might behave:

[0185] 1. Location and Environmental Data Collection:

[0186] The built-in location information acquisition device acquires the current location and sends it to the server.

[0187] The environmental sensor detects weather conditions and sends the following to the server: rainfall 10mm / h, temperature 18°C, humidity 85%.

[0188] 2. Loading and analyzing historical data:

[0189] The server reads data on similar situations from a database of past driving situations and references past traffic volume and accident information.

[0190] 3. Driving advice generation:

[0191] A generative AI model integrates and analyzes this data and determines that the optimal route is to use major road A and avoid intersection X.

[0192] 4. Notice to Users:

[0193] The head-mounted display displays, "Take main road A and avoid intersection X."

[0194] Your smartphone will give you a voice notification saying, "In rainy weather, use main road A and avoid intersection X."

[0195] Prompt Sentence Examples

[0196] Get the best driving route from your current location based on real-time weather data and past driving history.

[0197] In this way, the system can provide optimal driving advice in real time, improving the user's driving efficiency and safety.

[0198] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0199] Step 1:

[0200] The server acquires the current location information using the vehicle's built-in location acquisition device (GPS module). The acquired location information is sent to the server and used for analysis. The input is the vehicle's current location data, and the output is the current location information stored on the server.

[0201] Step 2:

[0202] The server collects weather data, road condition data, temperature, and humidity from environmental sensors installed in the vehicle. This environmental data is sent to the server in real time. The input is various environmental data sensed by the sensors, and the output is environmental data stored on the server.

[0203] Step 3:

[0204] The server reads the user's past driving history data from the database, which includes past driving routes, traffic conditions, accident information, etc. The input is the driving history data in the database, and the output is the driving history data stored on the server.

[0205] Step 4:

[0206] The server integrates the acquired location information, environmental data, and past driving history data. Data integration generates consistent information from these different data sources. The input is location information, environmental data, and driving history data, and the output is the integrated data.

[0207] Step 5:

[0208] The server analyzes the integrated data using a generative AI model, which takes into account many variables such as weather conditions, road conditions, and past driving results to calculate the optimal driving route and advice. The input is the integrated data, and the output is the optimal driving advice.

[0209] Step 6:

[0210] The server generates optimal driving advice and notifies the user. Notifications are given via a head-mounted display and a smartphone, and the advice is conveyed visually and audibly. The input is the optimal driving advice, and the output is notification information to the user.

[0211] 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.

[0212] This invention is an AI unmanned caddy system that helps amateur golf players improve their scores efficiently, and it also has the ability to recognize the user's emotions and adjust play advice accordingly, thereby providing optimal advice according to the user's psychological state and maximizing the effectiveness of their play.

[0213] System configuration

[0214] The system includes the following components:

[0215] 1. A device with a built-in GPS module that obtains the user's location information.

[0216] 2. A device with sensors that detect wind speed, direction, temperature, and humidity to collect environmental data.

[0217] 3. A server with a database that stores users' past play data.

[0218] 4. A server equipped with an artificial intelligence algorithm that integrates and analyzes collected location information, environmental data, and past play data.

[0219] 5. A server that generates optimal play advice based on the analysis results.

[0220] 6. A device with smart glasses and earphones that notifies the user of play advice.

[0221] 7. A terminal including an emotion engine that recognizes the user's emotions.

[0222] Program processing

[0223] 1. Collecting user location information and gameplay data

[0224] The device uses the built-in GPS module to obtain its current location, which is then immediately sent to the server.

[0225] The server identifies the user's current location and recognizes the corresponding golf hole, and records the information for further processing.

[0226] The server reads the user's past play data from the database and saves it.

[0227] 2. Real-time environmental data collection

[0228] The device collects environmental data using built-in sensors that detect wind speed, direction, temperature, and humidity, and transmits this data to a server.

[0229] 3. Data Analysis

[0230] The server combines collected location information, environmental data, and past play data and analyzes the data using artificial intelligence algorithms.

[0231] The server comprehensively evaluates factors such as the influence of the wind, past success rates, and the layout of the hole to calculate the optimal club selection and shot direction. It also takes into account the strength of the shot depending on the situation.

[0232] 4. Emotional Data Collection and Analysis

[0233] The device analyzes the user's facial expressions, voice, or biometric information to collect emotional data, which is then sent to a server.

[0234] The server analyzes the emotion data to understand the user's psychological state, for example, determining whether the user is tense or relaxed.

[0235] 5. Advice Generation and Adjustment

[0236] The server adjusts the generated play advice based on the emotion data, for example adding advice to relax if the user is nervous.

[0237] The optimal play advice is finally determined based on the analysis results.

[0238] 6. Notice to Users

[0239] The device then displays the generated play advice on the smart glasses display, providing visual information such as "Use a 3 iron, aim slightly to the left, and hit with a relaxed stance."

[0240] The device will notify the user through the earphones with a voice message saying, "The wind speed is 10 km / h and blowing north. Aim slightly to the left with a 3-iron. Relax and remember to take deep breaths."

[0241] Specific examples

[0242] The following example illustrates the process when the user reaches the fifth hole and wants to know the best club and shot direction for the next shot.

[0243] 1. The device acquires the user's current location using its built-in GPS function and sends it to the server.

[0244] 2. The server recognizes that the user is on the fifth hole and reads the past play data for the fifth hole from the database.

[0245] 3. The device uses its built-in sensor to detect that the current wind speed is 10 km / h and blowing north, and sends this information to the server.

[0246] 4. The server combines location information, environmental data, and past play data and analyzes the data using artificial intelligence algorithms.

[0247] 5. Using a facial recognition camera and voice analysis, the device detects that the user is slightly nervous and sends the emotional data to the server.

[0248] 6. The server recognizes that the user is tense and adjusts the generated playing advice to include instructions for relaxing.

[0249] 7. The device will display on the smart glasses' display, "Use a 3 iron, aim slightly to the left, and hit while relaxing," and will provide a voice notification through the earphones saying, "Wind speed 10 km / h, northbound. Use a 3 iron and aim slightly to the left. Relax and remember to take deep breaths."

[0250] In this way, the user can receive optimal golf management advice tailored to their psychological state, making it possible to compensate for lack of experience and efficiently improve their score.

[0251] The processing flow will be explained below.

[0252] Step 1:

[0253] The device uses a built-in GPS module to obtain the user's current location, which is then immediately sent to the server.

[0254] Step 2:

[0255] The server identifies the user's current location based on the received location information, identifies the corresponding golf hole, and records the information for further processing.

[0256] Step 3:

[0257] The server reads the user's past play data stored in a database, including the clubs previously used, shot results, and scores.

[0258] Step 4:

[0259] The device uses built-in sensors to collect environmental data such as wind speed, wind direction, temperature, and humidity, which is then sent to a server.

[0260] Step 5:

[0261] The server integrates the collected location information, past play data, and current environmental data, and performs analysis using artificial intelligence algorithms based on this data.

[0262] Step 6:

[0263] The device uses a built-in camera and voice recognition function to analyze the user's facial expressions and voice to obtain emotional data, which is then sent to a server.

[0264] Step 7:

[0265] The server analyzes the emotion data to understand the user's psychological state, for example, determining whether the user is tense or relaxed.

[0266] Step 8:

[0267] The server adjusts the generated play advice based on the emotion data, for example adding advice to relax if the user is nervous.

[0268] Step 9:

[0269] The server comprehensively evaluates factors such as the influence of the wind, the layout of the hole, and past success rates to calculate the optimal club selection and shot direction. It also adjusts the force of the shot based on the user's emotions.

[0270] Step 10:

[0271] The server generates specific play advice based on the analysis results, such as "Use a 3-iron, aim slightly to the left, and hit the ball in a relaxed manner."

[0272] Step 11:

[0273] The device receives play advice from the server and displays it on the smart glasses display, providing visual information such as "Use a 3 iron, aim slightly to the left, and hit the ball in a relaxed manner."

[0274] Step 12:

[0275] The device will notify the user through the earphones with a voice message saying, "The wind speed is 10 km / h and blowing north. Aim slightly to the left with a 3-iron. Relax and remember to take deep breaths."

[0276] This series of processes allows users to receive optimal golf management advice in real time according to their psychological state, which can help compensate for lack of experience and improve scores efficiently.

[0277] Example 2

[0278] 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."

[0279] Conventional golf management systems provide advice based only on the user's location, environmental data, and past play data, but do not consider the user's psychological state. This has resulted in the problem that optimal advice is not provided depending on the user's psychological state, such as when the user is tense or relaxed. There is a need to provide playing advice that reflects the user's emotions and psychological state, thereby maximizing the effectiveness of the user's play.

[0280] 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.

[0281] In this invention, the server includes means for acquiring user position information, means for collecting environmental data, means for reading the user's past play data, means for integrating and analyzing the position information, environmental data, and past play data, means for generating optimal play advice based on the analysis results, means for notifying the user of the play advice, means for collecting user emotion data, and means for adjusting the play advice based on the emotion data, thereby making it possible to provide optimal golf management advice tailored to the user's psychological state.

[0282] "User location information" is data that indicates the specific location where the user is currently located.

[0283] "Environmental data" refers to data that indicates the surrounding physical conditions that affect golf play, such as wind speed, wind direction, temperature, and humidity.

[0284] "User's past play data" refers to data that indicates records and statistical information of the golf plays that the user has performed up to now.

[0285] The "built-in GPS module" is a device that uses satellite signals to measure the user's current location with high accuracy.

[0286] A "wind speed sensor" is a device for measuring wind speed.

[0287] A "wind direction sensor" is a device for measuring the direction in which the wind is blowing.

[0288] A "temperature sensor" is a device for measuring the temperature of air.

[0289] A "humidity sensor" is a device for measuring the proportion of water vapor in the air.

[0290] "Means for integrating and analyzing" refers to the process and equipment for consolidating collected data into a single piece of information and analyzing it.

[0291] The "means for generating optimal play advice" refers to a process and device for generating the most effective play advice for the user based on the results of data analysis.

[0292] The "means for notifying the user of the playing advice" refers to a device or method for communicating the generated playing advice to the user.

[0293] "User emotion data" is data that indicates the user's current psychological state, and includes facial expressions, voice analysis results, biometric information, and the like.

[0294] The "means for adjusting play advice" refers to a process and device for appropriately changing the content of the generated play advice based on emotion data.

[0295] The present invention is a system for enabling amateur golf players to efficiently improve their scores, and provides optimal playing advice in accordance with the user's psychological state. Specific embodiments of the system will be described below.

[0296] This system is configured using the following hardware and software:

[0297] 1. Devices with a built-in GPS module: Used to obtain location information.

[0298] 2. Devices with sensors that detect wind speed, direction, temperature, and humidity: Used to collect environmental data.

[0299] 3. Server with database: Used to save and load users' past play data.

[0300] 4. Server equipped with artificial intelligence algorithms: Used to integrate and analyze collected location information, environmental data, and past play data.

[0301] 5. Server that generates optimal play advice: Generates play advice based on the analysis results.

[0302] 6. Device with smart glasses and earphones: Used to notify the user of play advice.

[0303] 7. Devices with emotion engines: Used to recognize user emotions.

[0304] The device uses its built-in GPS module to obtain its current location and sends that information to the server. The server then analyzes the location information, identifies the user's current location, and loads past play data from a database. The device also uses its built-in sensors to collect environmental data such as wind speed, wind direction, temperature, and humidity, which it then sends to the server.

[0305] The server uses an AI algorithm to analyze the collected location information, environmental data, and past play data, and then evaluates the effects of wind, hole layout, past success rates, and other factors to calculate the optimal club selection and shot direction.

[0306] Furthermore, the device uses sensors such as a camera and microphone to collect the user's facial expressions and voice, and sends the emotional data to the server. The server analyzes the emotional data to understand the user's psychological state and adjusts the generated advice accordingly. For example, if the user is nervous, it will add advice to help them relax.

[0307] Finally, the device displays the adjusted playing advice on the smart glasses display and provides audio feedback through the earphones, such as "Use a 3 iron, aim slightly to the left, and hit with a relaxed stance."

[0308] Specific examples

[0309] The following example illustrates the process when the user reaches the fifth hole and wants to know the best club and shot direction for the next shot.

[0310] 1. The device uses its built-in GPS to obtain the user's current location and sends it to the server.

[0311] 2. The server recognizes that the user is on the 5th hole and reads the past play data for the 5th hole from the database.

[0312] 3. The device uses its built-in sensor to detect that the current wind speed is 10 km / h and blowing north, and sends this data to the server.

[0313] 4. The server combines location information, environmental data, and past play data and analyzes the data using artificial intelligence algorithms.

[0314] 5. Using a facial recognition camera and voice analysis, the device detects when the user is feeling slightly nervous and sends that emotional data to the server.

[0315] 6. The server recognizes that the user is nervous and adjusts the generated play advice to include instructions for relaxing.

[0316] 7. The device will display on the smart glasses' display, "Use a 3 iron, aim slightly to the left, and hit while relaxed," and will provide a voice notification through the earphones: "Wind speed 10 km / h, northbound. Use a 3 iron and aim slightly to the left. Relax and remember to take deep breaths."

[0317] Prompt Sentence Examples

[0318] 1. "What is the current wind speed and direction on the hole?"

[0319] 2. "What advice should you give to help users relax?"

[0320] In this way, the user can receive optimal golf management advice tailored to their psychological state, making it possible to compensate for lack of experience and efficiently improve their score.

[0321] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0322] Step 1: Get and send the user's current location

[0323] Input: Location information from the GPS module

[0324] The device will activate its built-in GPS module to obtain the user's current location, which includes latitude and longitude.

[0325] The acquired location information is sent to the server in real time.

[0326] Output: Location information sent to the server

[0327] Step 2: Analyze and set the user's current location

[0328] Input: Location information sent from the device

[0329] The server analyzes the received location information to determine the user's current location, which may involve the use of a geographic information system (GIS).

[0330] The server recognizes the identified golf hole number and records it in an internal database.

[0331] Output: Current golf hole number and its location

[0332] Step 3: Obtaining past play data

[0333] Input: Current golf hole number

[0334] The server reads the user's past play data from its internal database and prepares it for analysis, including the success rate of past shots and the clubs used.

[0335] Output: Past play data

[0336] Step 4: Collect environmental data

[0337] Input: Ambient environmental conditions

[0338] The device activates its built-in sensors to measure wind speed, direction, temperature, and humidity, and the data collected by the sensors is collected in real time.

[0339] The collected environmental data is transmitted from the terminal to a server.

[0340] Output: Environment data sent to the server

[0341] Step 5: Data synthesis and analysis

[0342] Input: location information, environmental data, past play data

[0343] The server combines the acquired location information, environmental data, and past play data and analyzes it using artificial intelligence algorithms, including statistical and machine learning models.

[0344] As a result of the analysis, factors such as the influence of wind, hole layout, and past success rate are evaluated to calculate the optimal club selection and shot direction.

[0345] Output: Optimal club selection and shot direction

[0346] Step 6: Collect and send emotion data

[0347] Input: User's facial expression, voice, biometric information

[0348] The device uses sensors such as a camera and microphone to collect data on the user's emotions, and uses facial expression recognition and voice analysis technology to estimate the user's psychological state.

[0349] The collected emotion data is sent to a server in real time.

[0350] Output: Emotion data sent to the server

[0351] Step 7: Analyze emotional data and adjust play advice

[0352] Input: Emotional data, optimal club selection and shot direction

[0353] The server analyzes the received emotional data to understand the user's psychological state, sometimes using machine learning models or rule-based systems.

[0354] If the user is perceived as tense, the advice is adjusted to include instructions for relaxation.

[0355] Output: Adjusted play advice

[0356] Step 8: Advise users

[0357] Input: Adjusted play advice

[0358] The terminal obtains the finalized play advice.

[0359] The device will then display advice on the smart glasses display, such as "Use a 3 iron, aim slightly to the left, and hit with a relaxed stance."

[0360] The device will then notify the user through the earphones with a voice message saying, "Wind speed 10km / h, northbound. Aim slightly to the left with a 3-iron. Relax and remember to take deep breaths."

[0361] Output: Play advice given to the user

[0362] (Application example 2)

[0363] 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."

[0364] Conventional work management systems have had problems in that they were unable to adequately improve the efficiency of workers on production lines or manage their psychological stress. Furthermore, they lacked the functionality to provide advice that took into account environmental data and the emotional state of workers, which led to a risk of reduced work efficiency and the accumulation of worker stress. The present invention aims to solve these problems and provide a system that simultaneously optimizes workers' work efficiency and psychological health.

[0365] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0366] In this invention, the server includes means for acquiring user location information, means for collecting environmental data, means for reading the user's past work data, means for collecting the user's emotion data, means for integrating and analyzing the location information, environmental data, the user's past work data, and the emotion data, means for adjusting advice generated based on the emotion data, means for generating optimal work advice based on the analysis results, and means for notifying the user of the work advice, thereby enabling optimal work advice according to the work environment and stress management for workers.

[0367] "Location information" is data that indicates the user's current location.

[0368] "Environmental data" refers to data that indicates the ambient conditions in which the user is working, such as temperature, humidity, and noise level.

[0369] "Past work data" refers to records and data relating to work that the user has performed in the past.

[0370] "Emotion data" is data that expresses the user's psychological state and emotions.

[0371] "Analysis" is the process of integrating collected location information, environmental data, past work data, and emotional data, and making evaluations and judgments based on that information.

[0372] "Adjusting the advice" means optimizing the generated advice to suit the user's condition and environment.

[0373] "Work advice" is specific instructions and suggestions for the user to work efficiently and healthily.

[0374] "Notification" refers to transmitting the generated work advice to the user.

[0375] This invention relates to an artificial intelligence system that optimizes the work efficiency and psychological stress of factory workers. The system integrates and analyzes the user's location information, environmental data, past work data, and emotional data, and generates and notifies optimal work advice.

[0376] System configuration

[0377] The system consists of the following main components:

[0378] 1. Location information acquisition means

[0379] The built-in GPS module is used to obtain the user's location, allowing the system to accurately determine which working area the user is in.

[0380] 2. Environmental data collection methods

[0381] Environmental data is collected using sensors that detect wind speed, wind direction, temperature, humidity, noise level, etc. This data is used to evaluate the impact of the work environment on work efficiency and psychological stress.

[0382] 3. How to load past work data

[0383] The user's past work data is read from the database, including the user's past work logs and performance data.

[0384] 4. Emotional Data Collection Methods

[0385] Using facial recognition cameras and voice analysis, the user's psychological state and emotions are analyzed and emotional data is collected.

[0386] 5. Data Analysis Methods

[0387] The server integrates the collected location information, environmental data, past activity data, and emotional data, and analyzes the data using artificial intelligence algorithms, taking into account the effectiveness of the activity and the user's psychological state.

[0388] 6. Advice Generation and Adjustment Methods

[0389] The server generates optimal work advice based on the analysis results and adjusts the content based on emotional data. For example, if stress increases while working, the server will provide advice including ways to relax.

[0390] 7. User Notification Methods

[0391] The generated work advice is notified to the user using smart glasses or a head-mounted display, providing detailed advice in real time.

[0392] Program processing

[0393] For example, when a worker is joining parts on a conveyor, the server collects real-time environmental data and past work data, and analyzes this data. Emotion recognition data is also analyzed, so if the worker feels tired, advice is generated to encourage them to take a short break.

[0394] Hardware and software used

[0395] Built-in GPS module: location information acquisition

[0396] Environmental sensors: Collect data on wind speed, wind direction, temperature, humidity, and noise levels

[0397] Facial recognition camera and voice analysis software: Emotion data collection

[0398] Database server: Saving and loading historical data

[0399] AI analysis server: Analysis of integrated data

[0400] Smart Glasses and Head-Mounted Displays: User Advice Notification

[0401] Prompt Sentence Examples

[0402] "Enter the following data into the AI ​​model: environmental data (temperature 28°C, humidity 60%, noise level 70dB), location information (joining section), past data (points to note when joining), and emotional data (mild fatigue). Generate optimal work procedures and advice on stress management."

[0403] In this way, the system of the present invention allows workers to receive work advice suited to the environment, while also managing psychological stress and enabling them to work efficiently.

[0404] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0405] Step 1:

[0406] The device uses the built-in GPS module to obtain the user's current location, which is used to determine which working area the user is in. The obtained location information is then sent to the server and stored.

[0407] Step 2:

[0408] The device uses built-in sensors to collect environmental data such as temperature, humidity, and noise levels. This environmental data is used to evaluate the impact of the work environment on work efficiency and psychological stress. The collected environmental data is then sent to a server and stored.

[0409] Step 3:

[0410] The server reads the user's past work data from the database. This past data includes logs of the user's past work and performance data. The read data is used for analysis.

[0411] Step 4:

[0412] The device uses facial recognition cameras and voice analysis software to collect data on the user's psychological state and emotions. This emotional data is used to evaluate the user's current psychological state and is sent to a server.

[0413] Step 5:

[0414] The server integrates the collected location information, environmental data, past work data, and emotional data, and analyzes them using artificial intelligence algorithms. This analysis process evaluates the worker's work efficiency and psychological stress level. Based on the input data, optimal work procedures and advice are generated.

[0415] Step 6:

[0416] The server generates optimal work advice based on the analysis results. During this generation process, the advice is adjusted based on the emotional data, for example, if the user is tired, the advice may be adjusted to encourage them to take a break.

[0417] Step 7:

[0418] The generated optimal work advice is sent from the server to the device, which then notifies the user using smart glasses or a head-mounted display. Specific advice content is provided as visual information or audio notifications.

[0419] This allows users to receive real-time, optimal work advice suited to their environment, enabling them to work efficiently. Furthermore, by managing psychological stress, work efficiency is improved and worker health is managed.

[0420] 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.

[0421] 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.

[0422] 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.

[0423] [Second embodiment]

[0424] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0425] 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.

[0426] 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).

[0427] 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.

[0428] 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.

[0429] 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).

[0430] 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.

[0431] 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.

[0432] 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.

[0433] 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.

[0434] 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.

[0435] 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."

[0436] This invention is an AI unmanned caddy system that helps amateur golfers improve their scores efficiently. This system analyzes a user's location information, environmental data, and past play data, and provides optimal playing advice in real time.

[0437] System configuration

[0438] The system includes the following components:

[0439] 1. A device with a built-in GPS module that obtains the user's location information.

[0440] 2. A device with sensors that detect wind speed, direction, temperature, and humidity to collect environmental data.

[0441] 3. A server with a database that stores users' past play data.

[0442] 4. A server equipped with an artificial intelligence algorithm that integrates and analyzes collected location information, environmental data, and past play data.

[0443] 5. A server that generates optimal play advice based on the analysis results.

[0444] 6. A device with smart glasses and earphones that notifies the user of play advice.

[0445] Program processing

[0446] 1. Collecting user location information and gameplay data

[0447] The device uses the built-in GPS module to obtain its current location, which is then sent to the server.

[0448] The server identifies the user's current location and recognizes the target hole.

[0449] The server reads the user's past play data from the database and saves it.

[0450] 2. Real-time environmental data collection

[0451] The device collects environmental data using built-in sensors that detect wind speed, wind direction, temperature, and humidity, and transmits this data to a server.

[0452] 3. Data Analysis

[0453] The server combines collected location information, environmental data, and past play data and analyzes the data using artificial intelligence algorithms.

[0454] The server calculates the optimal club selection and shot direction for the user, taking into account factors such as the effects of wind, past shot results, and hole layout.

[0455] 4. Generating Advice

[0456] The server generates specific playing advice based on the analysis, including which club to use, the direction of the shot, and how much force to use.

[0457] 5. Notice to Users

[0458] The device displays the generated play advice as visual information on the smart glasses display.

[0459] The terminal provides audio advice to the user through an earphone.

[0460] Specific examples

[0461] The following example illustrates the process when the user reaches the fifth hole and wants to know the best club and shot direction for the next shot.

[0462] 1. The device acquires the user's current location using its built-in GPS function and sends it to the server.

[0463] 2. The server recognizes that the user is on the fifth hole and reads the past play data for the fifth hole from the database.

[0464] 3. The device uses its built-in sensor to detect that the current wind speed is 10 km / h and blowing north, and sends this information to the server.

[0465] 4. The server combines location information, environmental data, and past play data and analyzes the data using artificial intelligence algorithms.

[0466] 5. The server determines that the advice is for the user to use a 3-iron and to aim the shot slightly to the left.

[0467] 6. The device will display "Use a 3 iron and aim slightly to the left" on the smart glasses display and will give a voice notification through the earphones saying "Wind speed 10 km / h, northbound, use a 3 iron and aim slightly to the left."

[0468] In this way, users can receive optimal golf management advice in real time, making up for lack of experience and efficiently improving their scores.

[0469] The processing flow will be explained below.

[0470] Step 1:

[0471] The device uses a built-in GPS module to obtain the user's current location, which is then immediately sent to the server.

[0472] Step 2:

[0473] The server identifies the user's current location based on the received location information, identifies the corresponding golf hole, and records the information for further processing.

[0474] Step 3:

[0475] The server reads the user's past play data stored in a database, including the clubs previously used, shot results, and scores.

[0476] Step 4:

[0477] The device uses built-in sensors to collect environmental data such as wind speed, wind direction, temperature, and humidity, which is then sent to a server.

[0478] Step 5:

[0479] The server integrates the collected location information, past play data, and current environmental data, and performs analysis using artificial intelligence algorithms based on this data.

[0480] Step 6:

[0481] The server will comprehensively evaluate factors such as the wind's influence, hole layout, and past success rates to calculate the optimal club selection and shot direction. It also takes into account the power of the shot depending on the situation.

[0482] Step 7:

[0483] The server generates specific play advice based on the analysis results, such as "Use a 3-iron and aim slightly to the left."

[0484] Step 8:

[0485] The device receives play advice from the server and displays it on the smart glasses display, providing visual information such as "Use a 3 iron and aim slightly to the left."

[0486] Step 9:

[0487] The device will notify the user through the earphones by voice, "The wind speed is 10 km / h and blowing north. Aim slightly to the left with a 3 iron."

[0488] This series of processes allows users to receive optimal golf management advice in real time, making it possible to compensate for lack of experience and improve scores.

[0489] Example 1

[0490] 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."

[0491] Amateur golf players often find it difficult to improve their scores efficiently due to lack of experience and technical misjudgments. Furthermore, they lack support for improving their play quality due to limited access to appropriate advice in real time while playing. To solve this problem, a system is needed that integrates and analyzes the user's location information, environmental data, and past play data to provide optimal play advice in real time.

[0492] 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.

[0493] In this invention, the server includes means for acquiring user position information, means for collecting environmental data, means for reading the user's past play data, means for integrating and analyzing the position information, environmental data, and past play data, means for generating optimal play advice based on the analysis results, means for notifying the user of the play advice, and means for providing the advice to the user in visual and audio form, thereby enabling the user to receive optimal play advice in real time and efficiently improve their score.

[0494] The "means for acquiring user location information" is a function for identifying the user's current location and acquiring that location information.

[0495] The "means for collecting environmental data" is a function for detecting surrounding environmental information such as wind speed, wind direction, temperature, and humidity, and collecting this data.

[0496] The "means for reading the user's past play data" is a function for reading the user's past play history data from a database in which the history data is recorded.

[0497] "Means for integrating and analyzing" refers to a function that brings together acquired location information, environmental data, and past play data, and performs analysis based on that data.

[0498] The "means for generating optimal play advice based on the analysis results" is a function for generating optimal play advice for the user based on the results obtained by the analysis.

[0499] The "means for notifying the user of play advice" is a function for notifying the user of the generated play advice.

[0500] "Means for providing advice in visual and audio form" refers to a function for providing advice to the user visually and audio using the smart glasses' display and earphones.

[0501] This invention is an AI unmanned caddy system that helps amateur golfers improve their scores efficiently. This system analyzes a user's location information, environmental data, and past play data, and provides optimal playing advice in real time.

[0502] System Components

[0503] 1. A device with a built-in GPS module that obtains the user's location information

[0504] The device uses the built-in GPS module to obtain the user's current location information, which is then sent to the server.

[0505] 2. A device equipped with sensors to detect wind speed, wind direction, temperature, and humidity to collect environmental data.

[0506] The device's built-in sensors detect wind speed, direction, temperature, and humidity, and send this data to a server.

[0507] 3. A server with a database that stores users' past play data

[0508] The server stores the user's past play data in a database and reads it as needed.

[0509] 4. A server equipped with an artificial intelligence algorithm that integrates and analyzes collected location information, environmental data, and past play data.

[0510] The server's artificial intelligence algorithm integrates and analyzes the collected data (location information, environmental data, and past play data).

[0511] 5. Server that generates optimal play advice based on the analysis results

[0512] The server generates optimal play advice based on the analysis results and provides it to the user.

[0513] 6. A device with smart glasses and earphones that provides play advice to the user

[0514] The device displays the generated play advice on the smart glasses display and notifies the player via audio through earphones.

[0515] Specific examples

[0516] For example, if the user reaches the fifth hole and wants to know the best club and shot direction for the next shot, the process is as follows:

[0517] 1. The device acquires the user's current location using its built-in GPS function and sends it to the server.

[0518] 2. The server recognizes that the user is on the fifth hole and reads the past play data for the fifth hole from the database.

[0519] 3. The device uses its built-in sensor to detect that the current wind speed is 10 km / h and blowing north, and sends this information to the server.

[0520] 4. The server combines location information, environmental data, and past play data and analyzes the data using artificial intelligence algorithms.

[0521] 5. The server determines that the advice is for the user to use a 3-iron and to aim the shot slightly to the left.

[0522] 6. The device will display "Use a 3 iron and aim slightly to the left" on the smart glasses display and will give a voice notification through the earphones saying "Wind speed 10 km / h, northbound, use a 3 iron and aim slightly to the left."

[0523] Example prompts for generative AI models

[0524] Below are some example prompts to be input to the generative AI model:

[0525] "The user has reached the 5th hole. The wind is 10km / h and blowing from the north. Based on past play data, a 3-iron is the best option for this hole. Please advise which club to use and in what direction to aim for the next shot."

[0526] Based on this prompt, the generative AI model is expected to generate appropriate advice and provide it to the user.

[0527] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0528] Step 1:

[0529] Obtain the user's location information and send it to the server

[0530] The device uses its built-in GPS module to obtain the user's current location information. Specifically, the device periodically reads GPS data to obtain latitude and longitude information. This location information (input data) is sent from the device to the server (output data). For example, the device obtains location information of "latitude 35.6895, longitude 139.6917" and sends it to the server.

[0531] Step 2:

[0532] The server recognizes the target hole and loads past play data.

[0533] The server identifies the hole the user is currently on based on the acquired location information. It analyzes and recognizes the hole number from the location information (input data) and reads the corresponding past play data from the database (output data). Specifically, the server identifies the "5th hole" and reads the past play data for the 5th hole.

[0534] Step 3:

[0535] The device collects environmental data and sends it to the server.

[0536] The terminal uses its built-in sensors to collect on-site environmental data. Specifically, the sensors detect data such as wind speed, wind direction, temperature, and humidity (input data). This environmental data is sent from the terminal to a server (output data). For example, the terminal collects data such as "wind speed 10 km / h, facing north, temperature 25°C, humidity 60%" and sends it to the server.

[0537] Step 4:

[0538] The server aggregates the data and analyzes it using artificial intelligence algorithms.

[0539] The server integrates the acquired location information, environmental data, and past play data (input data). It then uses an artificial intelligence algorithm to perform analysis based on the integrated data. Specifically, the server's AI calculates the effects of wind and past shot results, and determines the optimal club selection and shot direction (output data). For example, the server may obtain the analysis result, "Use a 3-iron and set the shot direction slightly to the left."

[0540] Step 5:

[0541] The server generates advice and sends it to the device.

[0542] The server generates specific play advice based on the analysis results (input data). This advice is sent from the server to the device (output data). Specifically, the server generates the play advice "Use a 3-iron and aim slightly to the left" and sends it to the device.

[0543] Step 6:

[0544] The device notifies the user of the advice

[0545] The device notifies the user of the received advice (input data). Specifically, the advice is displayed as visual information on the smart glasses display and audio advice is provided through the earphones (output data). For example, the device displays "Use a 3 iron and aim slightly to the left" on the smart glasses, and the earphones provide an audio notification saying, "Wind speed 10 km / h, northbound, use a 3 iron and aim slightly to the left."

[0546] In this way, each processing step is executed sequentially, and the user can receive real-time play advice to efficiently improve their score.

[0547] (Application example 1)

[0548] 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."

[0549] Conventional self-driving vehicles lack the technology to provide optimal driving advice in real time, making it difficult for them to drive efficiently and make appropriate decisions. Ensuring safety and efficiency has been particularly difficult in situations where quick responses to changes in weather and road conditions are required.

[0550] 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.

[0551] In this invention, the server includes means for acquiring location information, means for collecting environmental data, means for reading the user's past operation data, means for integrating and analyzing the location information, environmental data, and past operation data, means for generating optimal operation advice based on the analysis results, and means for notifying the user of the operation advice, thereby making it possible to provide optimal driving advice in real time and improve driving efficiency and safety.

[0552] "Location information" is data that indicates the current geographic location of an object.

[0553] "Environmental data" refers to data that indicates weather conditions and surrounding circumstances, and specifically includes weather data, road condition data, temperature, humidity, and the like.

[0554] "Task data" is data that indicates the history of past operations and actions.

[0555] "Integration" means bringing together multiple different types of data into one system or format.

[0556] "Analysis" refers to the calculation or evaluation of collected data to arrive at a specific conclusion or result.

[0557] "Operation advice" refers to instructions or suggestions provided to help a user take optimal action.

[0558] "Notification" is the act of conveying important information to the user, and various means such as visual and auditory are used.

[0559] An "internal location information acquisition device" is a device that is built into a device to acquire location information, such as a GPS module.

[0560] A "sensor" is a device that detects physical or chemical changes and outputs them as data.

[0561] "Weather data" refers to data indicating weather conditions such as temperature, wind speed, and rainfall.

[0562] "Road condition data" refers to data relating to road conditions, such as traffic flow, whether there have been any accidents, and construction information.

[0563] This invention relates to a driving assistance system for autonomous vehicles. Specifically, this system integrates and analyzes location information, environmental data, and the user's past work data in real time to provide optimal driving advice.

[0564] System Configuration

[0565] The system includes the following components:

[0566] 1. Obtaining location information

[0567] The server acquires location information using the vehicle's built-in location information acquisition device (GPS module) and uses this information for analysis.

[0568] 2. Environmental data collection

[0569] The server uses environmental sensors installed in the vehicle to collect weather data (temperature, wind speed, rainfall, etc.), road condition data (traffic flow, accident information, etc.), temperature, and humidity.

[0570] 3. Loading past work data

[0571] The server reads data such as the user's past driving routes, traffic conditions, and accident information from a database.

[0572] 4. Analysis of Integrated Data

[0573] This location information, environmental data, and past work data are integrated on the server, and data analysis is performed using a generative AI model.

[0574] 5. Driving advice generation

[0575] Based on the analysis results, the server generates optimal driving routes and driving advice.

[0576] 6. Notice to Users

[0577] The generated driving advice is communicated to the user visually and audibly via a head-mounted display and smartphone.

[0578] What the program does

[0579] The server acquires the vehicle's current location from the built-in location acquisition device and collects real-time weather and road condition data from environmental sensors. This data is stored in a database along with past driving history data. The server integrates all collected data and uses a generative AI model to calculate the optimal driving route and advice.

[0580] Detailed processing contents

[0581] Hardware: Built-in location acquisition device (GPS module), environmental sensors, head-mounted display, smartphone, on-board computer.

[0582] Software: Python, AIML (Artificial Intelligence Machine Learning Library), speech synthesis library.

[0583] Specific examples

[0584] If the user is heading to a destination during rainy weather, here is an example of how the system might behave:

[0585] 1. Location and Environmental Data Collection:

[0586] The built-in location information acquisition device acquires the current location and sends it to the server.

[0587] The environmental sensor detects weather conditions and sends the following to the server: rainfall 10mm / h, temperature 18°C, humidity 85%.

[0588] 2. Loading and analyzing historical data:

[0589] The server reads data on similar situations from a database of past driving situations and references past traffic volume and accident information.

[0590] 3. Driving advice generation:

[0591] A generative AI model integrates and analyzes this data and determines that the optimal route is to use major road A and avoid intersection X.

[0592] 4. Notice to Users:

[0593] The head-mounted display displays, "Take main road A and avoid intersection X."

[0594] Your smartphone will give you a voice notification saying, "In rainy weather, use main road A and avoid intersection X."

[0595] Prompt Sentence Examples

[0596] Get the best driving route from your current location based on real-time weather data and past driving history.

[0597] In this way, the system can provide optimal driving advice in real time, improving the user's driving efficiency and safety.

[0598] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0599] Step 1:

[0600] The server acquires the current location information using the vehicle's built-in location acquisition device (GPS module). The acquired location information is sent to the server and used for analysis. The input is the vehicle's current location data, and the output is the current location information stored on the server.

[0601] Step 2:

[0602] The server collects weather data, road condition data, temperature, and humidity from environmental sensors installed in the vehicle. This environmental data is sent to the server in real time. The input is various environmental data sensed by the sensors, and the output is environmental data stored on the server.

[0603] Step 3:

[0604] The server reads the user's past driving history data from the database, which includes past driving routes, traffic conditions, accident information, etc. The input is the driving history data in the database, and the output is the driving history data stored on the server.

[0605] Step 4:

[0606] The server integrates the acquired location information, environmental data, and past driving history data. Data integration generates consistent information from these different data sources. The input is location information, environmental data, and driving history data, and the output is the integrated data.

[0607] Step 5:

[0608] The server analyzes the integrated data using a generative AI model, which takes into account many variables such as weather conditions, road conditions, and past driving results to calculate the optimal driving route and advice. The input is the integrated data, and the output is the optimal driving advice.

[0609] Step 6:

[0610] The server generates optimal driving advice and notifies the user. Notifications are given via a head-mounted display and a smartphone, and the advice is conveyed visually and audibly. The input is the optimal driving advice, and the output is notification information to the user.

[0611] 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.

[0612] This invention is an AI unmanned caddy system that helps amateur golf players improve their scores efficiently, and it also has the ability to recognize the user's emotions and adjust play advice accordingly, thereby providing optimal advice according to the user's psychological state and maximizing the effectiveness of their play.

[0613] System configuration

[0614] The system includes the following components:

[0615] 1. A device with a built-in GPS module that obtains the user's location information.

[0616] 2. A device with sensors that detect wind speed, direction, temperature, and humidity to collect environmental data.

[0617] 3. A server with a database that stores users' past play data.

[0618] 4. A server equipped with an artificial intelligence algorithm that integrates and analyzes collected location information, environmental data, and past play data.

[0619] 5. A server that generates optimal play advice based on the analysis results.

[0620] 6. A device with smart glasses and earphones that notifies the user of play advice.

[0621] 7. A terminal including an emotion engine that recognizes the user's emotions.

[0622] Program processing

[0623] 1. Collecting user location information and gameplay data

[0624] The device uses the built-in GPS module to obtain its current location, which is then immediately sent to the server.

[0625] The server identifies the user's current location and recognizes the corresponding golf hole, and records the information for further processing.

[0626] The server reads the user's past play data from the database and saves it.

[0627] 2. Real-time environmental data collection

[0628] The device collects environmental data using built-in sensors that detect wind speed, direction, temperature, and humidity, and transmits this data to a server.

[0629] 3. Data Analysis

[0630] The server combines collected location information, environmental data, and past play data and analyzes the data using artificial intelligence algorithms.

[0631] The server comprehensively evaluates factors such as the influence of the wind, past success rates, and the layout of the hole to calculate the optimal club selection and shot direction. It also takes into account the strength of the shot depending on the situation.

[0632] 4. Emotional Data Collection and Analysis

[0633] The device analyzes the user's facial expressions, voice, or biometric information to collect emotional data, which is then sent to a server.

[0634] The server analyzes the emotion data to understand the user's psychological state, for example, determining whether the user is tense or relaxed.

[0635] 5. Advice Generation and Adjustment

[0636] The server adjusts the generated play advice based on the emotion data, for example adding advice to relax if the user is nervous.

[0637] The optimal play advice is finally determined based on the analysis results.

[0638] 6. Notice to Users

[0639] The device then displays the generated play advice on the smart glasses display, providing visual information such as "Use a 3 iron, aim slightly to the left, and hit with a relaxed stance."

[0640] The device will notify the user through the earphones with a voice message saying, "The wind speed is 10 km / h and blowing north. Aim slightly to the left with a 3-iron. Relax and remember to take deep breaths."

[0641] Specific examples

[0642] The following example illustrates the process when the user reaches the fifth hole and wants to know the best club and shot direction for the next shot.

[0643] 1. The device acquires the user's current location using its built-in GPS function and sends it to the server.

[0644] 2. The server recognizes that the user is on the fifth hole and reads the past play data for the fifth hole from the database.

[0645] 3. The device uses its built-in sensor to detect that the current wind speed is 10 km / h and blowing north, and sends this information to the server.

[0646] 4. The server combines location information, environmental data, and past play data and analyzes the data using artificial intelligence algorithms.

[0647] 5. Using a facial recognition camera and voice analysis, the device detects that the user is slightly nervous and sends the emotional data to the server.

[0648] 6. The server recognizes that the user is tense and adjusts the generated playing advice to include instructions for relaxing.

[0649] 7. The device will display on the smart glasses' display, "Use a 3 iron, aim slightly to the left, and hit while relaxing," and will provide a voice notification through the earphones saying, "Wind speed 10 km / h, northbound. Use a 3 iron and aim slightly to the left. Relax and remember to take deep breaths."

[0650] In this way, the user can receive optimal golf management advice tailored to their psychological state, making it possible to compensate for lack of experience and efficiently improve their score.

[0651] The processing flow will be explained below.

[0652] Step 1:

[0653] The device uses a built-in GPS module to obtain the user's current location, which is then immediately sent to the server.

[0654] Step 2:

[0655] The server identifies the user's current location based on the received location information, identifies the corresponding golf hole, and records the information for further processing.

[0656] Step 3:

[0657] The server reads the user's past play data stored in a database, including the clubs previously used, shot results, and scores.

[0658] Step 4:

[0659] The device uses built-in sensors to collect environmental data such as wind speed, wind direction, temperature, and humidity, which is then sent to a server.

[0660] Step 5:

[0661] The server integrates the collected location information, past play data, and current environmental data, and performs analysis using artificial intelligence algorithms based on this data.

[0662] Step 6:

[0663] The device uses a built-in camera and voice recognition function to analyze the user's facial expressions and voice to obtain emotional data, which is then sent to a server.

[0664] Step 7:

[0665] The server analyzes the emotion data to understand the user's psychological state, for example, determining whether the user is tense or relaxed.

[0666] Step 8:

[0667] The server adjusts the generated play advice based on the emotion data, for example adding advice to relax if the user is nervous.

[0668] Step 9:

[0669] The server comprehensively evaluates factors such as the influence of the wind, the layout of the hole, and past success rates to calculate the optimal club selection and shot direction. It also adjusts the force of the shot based on the user's emotions.

[0670] Step 10:

[0671] The server generates specific play advice based on the analysis results, such as "Use a 3-iron, aim slightly to the left, and hit the ball in a relaxed manner."

[0672] Step 11:

[0673] The device receives play advice from the server and displays it on the smart glasses display, providing visual information such as "Use a 3 iron, aim slightly to the left, and hit the ball in a relaxed manner."

[0674] Step 12:

[0675] The device will notify the user through the earphones with a voice message saying, "The wind speed is 10 km / h and blowing north. Aim slightly to the left with a 3-iron. Relax and remember to take deep breaths."

[0676] This series of processes allows users to receive optimal golf management advice in real time according to their psychological state, which can help compensate for lack of experience and improve scores efficiently.

[0677] Example 2

[0678] 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."

[0679] Conventional golf management systems provide advice based only on the user's location, environmental data, and past play data, but do not consider the user's psychological state. This has resulted in the problem that optimal advice is not provided depending on the user's psychological state, such as when the user is tense or relaxed. There is a need to provide playing advice that reflects the user's emotions and psychological state, thereby maximizing the effectiveness of the user's play.

[0680] 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.

[0681] In this invention, the server includes means for acquiring user position information, means for collecting environmental data, means for reading the user's past play data, means for integrating and analyzing the position information, environmental data, and past play data, means for generating optimal play advice based on the analysis results, means for notifying the user of the play advice, means for collecting user emotion data, and means for adjusting the play advice based on the emotion data, thereby making it possible to provide optimal golf management advice tailored to the user's psychological state.

[0682] "User location information" is data that indicates the specific location where the user is currently located.

[0683] "Environmental data" refers to data that indicates the surrounding physical conditions that affect golf play, such as wind speed, wind direction, temperature, and humidity.

[0684] "User's past play data" refers to data that indicates records and statistical information of the golf plays that the user has performed up to now.

[0685] The "built-in GPS module" is a device that uses satellite signals to measure the user's current location with high accuracy.

[0686] A "wind speed sensor" is a device for measuring wind speed.

[0687] A "wind direction sensor" is a device for measuring the direction in which the wind is blowing.

[0688] A "temperature sensor" is a device for measuring the temperature of air.

[0689] A "humidity sensor" is a device for measuring the proportion of water vapor in the air.

[0690] "Means for integrating and analyzing" refers to the process and equipment for consolidating collected data into a single piece of information and analyzing it.

[0691] The "means for generating optimal play advice" refers to a process and device for generating the most effective play advice for the user based on the results of data analysis.

[0692] The "means for notifying the user of the playing advice" refers to a device or method for communicating the generated playing advice to the user.

[0693] "User emotion data" is data that indicates the user's current psychological state, and includes facial expressions, voice analysis results, biometric information, and the like.

[0694] The "means for adjusting play advice" refers to a process and device for appropriately changing the content of the generated play advice based on emotion data.

[0695] The present invention is a system for enabling amateur golf players to efficiently improve their scores, and provides optimal playing advice in accordance with the user's psychological state. Specific embodiments of the system will be described below.

[0696] This system is configured using the following hardware and software:

[0697] 1. Devices with a built-in GPS module: Used to obtain location information.

[0698] 2. Devices with sensors that detect wind speed, direction, temperature, and humidity: Used to collect environmental data.

[0699] 3. Server with database: Used to save and load users' past play data.

[0700] 4. Server equipped with artificial intelligence algorithms: Used to integrate and analyze collected location information, environmental data, and past play data.

[0701] 5. Server that generates optimal play advice: Generates play advice based on the analysis results.

[0702] 6. Device with smart glasses and earphones: Used to notify the user of play advice.

[0703] 7. Devices with emotion engines: Used to recognize user emotions.

[0704] The device uses its built-in GPS module to obtain its current location and sends that information to the server. The server then analyzes the location information, identifies the user's current location, and loads past play data from a database. The device also uses its built-in sensors to collect environmental data such as wind speed, wind direction, temperature, and humidity, which it then sends to the server.

[0705] The server uses an AI algorithm to analyze the collected location information, environmental data, and past play data, and then evaluates the effects of wind, hole layout, past success rates, and other factors to calculate the optimal club selection and shot direction.

[0706] Furthermore, the device uses sensors such as a camera and microphone to collect the user's facial expressions and voice, and sends the emotional data to the server. The server analyzes the emotional data to understand the user's psychological state and adjusts the generated advice accordingly. For example, if the user is nervous, it will add advice to help them relax.

[0707] Finally, the device displays the adjusted playing advice on the smart glasses display and provides audio feedback through the earphones, such as "Use a 3 iron, aim slightly to the left, and hit with a relaxed stance."

[0708] Specific examples

[0709] The following example illustrates the process when the user reaches the fifth hole and wants to know the best club and shot direction for the next shot.

[0710] 1. The device uses its built-in GPS to obtain the user's current location and sends it to the server.

[0711] 2. The server recognizes that the user is on the 5th hole and reads the past play data for the 5th hole from the database.

[0712] 3. The device uses its built-in sensor to detect that the current wind speed is 10 km / h and blowing north, and sends this data to the server.

[0713] 4. The server combines location information, environmental data, and past play data and analyzes the data using artificial intelligence algorithms.

[0714] 5. Using a facial recognition camera and voice analysis, the device detects when the user is feeling slightly nervous and sends that emotional data to the server.

[0715] 6. The server recognizes that the user is nervous and adjusts the generated play advice to include instructions for relaxing.

[0716] 7. The device will display on the smart glasses' display, "Use a 3 iron, aim slightly to the left, and hit while relaxed," and will provide a voice notification through the earphones: "Wind speed 10 km / h, northbound. Use a 3 iron and aim slightly to the left. Relax and remember to take deep breaths."

[0717] Prompt Sentence Examples

[0718] 1. "What is the current wind speed and direction on the hole?"

[0719] 2. "What advice should you give to help users relax?"

[0720] In this way, the user can receive optimal golf management advice tailored to their psychological state, making it possible to compensate for lack of experience and efficiently improve their score.

[0721] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0722] Step 1: Get and send the user's current location

[0723] Input: Location information from the GPS module

[0724] The device will activate its built-in GPS module to obtain the user's current location, which includes latitude and longitude.

[0725] The acquired location information is sent to the server in real time.

[0726] Output: Location information sent to the server

[0727] Step 2: Analyze and set the user's current location

[0728] Input: Location information sent from the device

[0729] The server analyzes the received location information to determine the user's current location, which may involve the use of a geographic information system (GIS).

[0730] The server recognizes the identified golf hole number and records it in an internal database.

[0731] Output: Current golf hole number and its location

[0732] Step 3: Obtaining past play data

[0733] Input: Current golf hole number

[0734] The server reads the user's past play data from its internal database and prepares it for analysis, including the success rate of past shots and the clubs used.

[0735] Output: Past play data

[0736] Step 4: Collect environmental data

[0737] Input: Ambient environmental conditions

[0738] The device activates its built-in sensors to measure wind speed, direction, temperature, and humidity, and the data collected by the sensors is collected in real time.

[0739] The collected environmental data is transmitted from the terminal to a server.

[0740] Output: Environment data sent to the server

[0741] Step 5: Data synthesis and analysis

[0742] Input: location information, environmental data, past play data

[0743] The server combines the acquired location information, environmental data, and past play data and analyzes it using artificial intelligence algorithms, including statistical and machine learning models.

[0744] As a result of the analysis, factors such as the influence of wind, hole layout, and past success rate are evaluated to calculate the optimal club selection and shot direction.

[0745] Output: Optimal club selection and shot direction

[0746] Step 6: Collect and send emotion data

[0747] Input: User's facial expression, voice, biometric information

[0748] The device uses sensors such as a camera and microphone to collect data on the user's emotions, and uses facial expression recognition and voice analysis technology to estimate the user's psychological state.

[0749] The collected emotion data is sent to a server in real time.

[0750] Output: Emotion data sent to the server

[0751] Step 7: Analyze emotional data and adjust play advice

[0752] Input: Emotional data, optimal club selection and shot direction

[0753] The server analyzes the received emotional data to understand the user's psychological state, sometimes using machine learning models or rule-based systems.

[0754] If the user is perceived as tense, the advice is adjusted to include instructions for relaxation.

[0755] Output: Adjusted play advice

[0756] Step 8: Advise users

[0757] Input: Adjusted play advice

[0758] The terminal obtains the finalized play advice.

[0759] The device will then display advice on the smart glasses display, such as "Use a 3 iron, aim slightly to the left, and hit with a relaxed stance."

[0760] The device will then notify the user through the earphones with a voice message saying, "Wind speed 10km / h, northbound. Aim slightly to the left with a 3-iron. Relax and remember to take deep breaths."

[0761] Output: Play advice given to the user

[0762] (Application example 2)

[0763] 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."

[0764] Conventional work management systems have had problems in that they were unable to adequately improve the efficiency of workers on production lines or manage their psychological stress. Furthermore, they lacked the functionality to provide advice that took into account environmental data and the emotional state of workers, which led to a risk of reduced work efficiency and the accumulation of worker stress. The present invention aims to solve these problems and provide a system that simultaneously optimizes workers' work efficiency and psychological health.

[0765] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0766] In this invention, the server includes means for acquiring user location information, means for collecting environmental data, means for reading the user's past work data, means for collecting the user's emotion data, means for integrating and analyzing the location information, environmental data, the user's past work data, and the emotion data, means for adjusting advice generated based on the emotion data, means for generating optimal work advice based on the analysis results, and means for notifying the user of the work advice, thereby enabling optimal work advice according to the work environment and stress management for workers.

[0767] "Location information" is data that indicates the user's current location.

[0768] "Environmental data" refers to data that indicates the ambient conditions in which the user is working, such as temperature, humidity, and noise level.

[0769] "Past work data" refers to records and data relating to work that the user has performed in the past.

[0770] "Emotion data" is data that expresses the user's psychological state and emotions.

[0771] "Analysis" is the process of integrating collected location information, environmental data, past work data, and emotional data, and making evaluations and judgments based on that information.

[0772] "Adjusting the advice" means optimizing the generated advice to suit the user's condition and environment.

[0773] "Work advice" is specific instructions and suggestions for the user to work efficiently and healthily.

[0774] "Notification" refers to transmitting the generated work advice to the user.

[0775] This invention relates to an artificial intelligence system that optimizes the work efficiency and psychological stress of factory workers. The system integrates and analyzes the user's location information, environmental data, past work data, and emotional data, and generates and notifies optimal work advice.

[0776] System configuration

[0777] The system consists of the following main components:

[0778] 1. Location information acquisition means

[0779] The built-in GPS module is used to obtain the user's location, allowing the system to accurately determine which working area the user is in.

[0780] 2. Environmental data collection methods

[0781] Environmental data is collected using sensors that detect wind speed, wind direction, temperature, humidity, noise level, etc. This data is used to evaluate the impact of the work environment on work efficiency and psychological stress.

[0782] 3. How to load past work data

[0783] The user's past work data is read from the database, including the user's past work logs and performance data.

[0784] 4. Emotional Data Collection Methods

[0785] Using facial recognition cameras and voice analysis, the user's psychological state and emotions are analyzed and emotional data is collected.

[0786] 5. Data Analysis Methods

[0787] The server integrates the collected location information, environmental data, past activity data, and emotional data, and analyzes the data using artificial intelligence algorithms, taking into account the effectiveness of the activity and the user's psychological state.

[0788] 6. Advice Generation and Adjustment Methods

[0789] The server generates optimal work advice based on the analysis results and adjusts the content based on emotional data. For example, if stress increases while working, the server will provide advice including ways to relax.

[0790] 7. User Notification Methods

[0791] The generated work advice is notified to the user using smart glasses or a head-mounted display, providing detailed advice in real time.

[0792] Program processing

[0793] For example, when a worker is joining parts on a conveyor, the server collects real-time environmental data and past work data, and analyzes this data. Emotion recognition data is also analyzed, so if the worker feels tired, advice is generated to encourage them to take a short break.

[0794] Hardware and software used

[0795] Built-in GPS module: location information acquisition

[0796] Environmental sensors: Collect data on wind speed, wind direction, temperature, humidity, and noise levels

[0797] Facial recognition camera and voice analysis software: Emotion data collection

[0798] Database server: Saving and loading historical data

[0799] AI analysis server: Analysis of integrated data

[0800] Smart Glasses and Head-Mounted Displays: User Advice Notification

[0801] Prompt Sentence Examples

[0802] "Enter the following data into the AI ​​model: environmental data (temperature 28°C, humidity 60%, noise level 70dB), location information (joining section), past data (points to note when joining), and emotional data (mild fatigue). Generate optimal work procedures and advice on stress management."

[0803] In this way, the system of the present invention allows workers to receive work advice suited to the environment, while also managing psychological stress and enabling them to work efficiently.

[0804] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0805] Step 1:

[0806] The device uses the built-in GPS module to obtain the user's current location, which is used to determine which working area the user is in. The obtained location information is then sent to the server and stored.

[0807] Step 2:

[0808] The device uses built-in sensors to collect environmental data such as temperature, humidity, and noise levels. This environmental data is used to evaluate the impact of the work environment on work efficiency and psychological stress. The collected environmental data is then sent to a server and stored.

[0809] Step 3:

[0810] The server reads the user's past work data from the database. This past data includes logs of the user's past work and performance data. The read data is used for analysis.

[0811] Step 4:

[0812] The device uses facial recognition cameras and voice analysis software to collect data on the user's psychological state and emotions. This emotional data is used to evaluate the user's current psychological state and is sent to a server.

[0813] Step 5:

[0814] The server integrates the collected location information, environmental data, past work data, and emotional data, and analyzes them using artificial intelligence algorithms. This analysis process evaluates the worker's work efficiency and psychological stress level. Based on the input data, optimal work procedures and advice are generated.

[0815] Step 6:

[0816] The server generates optimal work advice based on the analysis results. During this generation process, the advice is adjusted based on the emotional data, for example, if the user is tired, the advice may be adjusted to encourage them to take a break.

[0817] Step 7:

[0818] The generated optimal work advice is sent from the server to the device, which then notifies the user using smart glasses or a head-mounted display. Specific advice content is provided as visual information or audio notifications.

[0819] This allows users to receive real-time, optimal work advice suited to their environment, enabling them to work efficiently. Furthermore, by managing psychological stress, work efficiency is improved and worker health is managed.

[0820] 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.

[0821] 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.

[0822] 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.

[0823] [Third embodiment]

[0824] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0825] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0826] 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).

[0827] 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.

[0828] 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.

[0829] 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).

[0830] 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.

[0831] 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.

[0832] 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.

[0833] 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.

[0834] 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.

[0835] 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."

[0836] This invention is an AI unmanned caddy system that helps amateur golfers improve their scores efficiently. This system analyzes a user's location information, environmental data, and past play data, and provides optimal playing advice in real time.

[0837] System configuration

[0838] The system includes the following components:

[0839] 1. A device with a built-in GPS module that obtains the user's location information.

[0840] 2. A device with sensors that detect wind speed, direction, temperature, and humidity to collect environmental data.

[0841] 3. A server with a database that stores users' past play data.

[0842] 4. A server equipped with an artificial intelligence algorithm that integrates and analyzes collected location information, environmental data, and past play data.

[0843] 5. A server that generates optimal play advice based on the analysis results.

[0844] 6. A device with smart glasses and earphones that notifies the user of play advice.

[0845] Program processing

[0846] 1. Collecting user location information and gameplay data

[0847] The device uses the built-in GPS module to obtain its current location, which is then sent to the server.

[0848] The server identifies the user's current location and recognizes the target hole.

[0849] The server reads the user's past play data from the database and saves it.

[0850] 2. Real-time environmental data collection

[0851] The device collects environmental data using built-in sensors that detect wind speed, wind direction, temperature, and humidity, and transmits this data to a server.

[0852] 3. Data Analysis

[0853] The server combines collected location information, environmental data, and past play data and analyzes the data using artificial intelligence algorithms.

[0854] The server calculates the optimal club selection and shot direction for the user, taking into account factors such as the effects of wind, past shot results, and hole layout.

[0855] 4. Generating Advice

[0856] The server generates specific playing advice based on the analysis, including which club to use, the direction of the shot, and how much force to use.

[0857] 5. Notice to Users

[0858] The device displays the generated play advice as visual information on the smart glasses display.

[0859] The terminal provides audio advice to the user through an earphone.

[0860] Specific examples

[0861] The following example illustrates the process when the user reaches the fifth hole and wants to know the best club and shot direction for the next shot.

[0862] 1. The device acquires the user's current location using its built-in GPS function and sends it to the server.

[0863] 2. The server recognizes that the user is on the fifth hole and reads the past play data for the fifth hole from the database.

[0864] 3. The device uses its built-in sensor to detect that the current wind speed is 10 km / h and blowing north, and sends this information to the server.

[0865] 4. The server combines location information, environmental data, and past play data and analyzes the data using artificial intelligence algorithms.

[0866] 5. The server determines that the advice is for the user to use a 3-iron and to aim the shot slightly to the left.

[0867] 6. The device will display "Use a 3 iron and aim slightly to the left" on the smart glasses display and will give a voice notification through the earphones saying "Wind speed 10 km / h, northbound, use a 3 iron and aim slightly to the left."

[0868] In this way, users can receive optimal golf management advice in real time, making up for lack of experience and efficiently improving their scores.

[0869] The processing flow will be explained below.

[0870] Step 1:

[0871] The device uses a built-in GPS module to obtain the user's current location, which is then immediately sent to the server.

[0872] Step 2:

[0873] The server identifies the user's current location based on the received location information, identifies the corresponding golf hole, and records the information for further processing.

[0874] Step 3:

[0875] The server reads the user's past play data stored in a database, including the clubs previously used, shot results, and scores.

[0876] Step 4:

[0877] The device uses built-in sensors to collect environmental data such as wind speed, wind direction, temperature, and humidity, which is then sent to a server.

[0878] Step 5:

[0879] The server integrates the collected location information, past play data, and current environmental data, and performs analysis using artificial intelligence algorithms based on this data.

[0880] Step 6:

[0881] The server will comprehensively evaluate factors such as the wind's influence, hole layout, and past success rates to calculate the optimal club selection and shot direction. It also takes into account the power of the shot depending on the situation.

[0882] Step 7:

[0883] The server generates specific play advice based on the analysis results, such as "Use a 3-iron and aim slightly to the left."

[0884] Step 8:

[0885] The device receives play advice from the server and displays it on the smart glasses display, providing visual information such as "Use a 3 iron and aim slightly to the left."

[0886] Step 9:

[0887] The device will notify the user through the earphones by voice, "The wind speed is 10 km / h and blowing north. Aim slightly to the left with a 3 iron."

[0888] This series of processes allows users to receive optimal golf management advice in real time, making it possible to compensate for lack of experience and improve scores.

[0889] Example 1

[0890] 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."

[0891] Amateur golf players often find it difficult to improve their scores efficiently due to lack of experience and technical misjudgments. Furthermore, they lack support for improving their play quality due to limited access to appropriate advice in real time while playing. To solve this problem, a system is needed that integrates and analyzes the user's location information, environmental data, and past play data to provide optimal play advice in real time.

[0892] 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.

[0893] In this invention, the server includes means for acquiring user position information, means for collecting environmental data, means for reading the user's past play data, means for integrating and analyzing the position information, environmental data, and past play data, means for generating optimal play advice based on the analysis results, means for notifying the user of the play advice, and means for providing the advice to the user in visual and audio form, thereby enabling the user to receive optimal play advice in real time and efficiently improve their score.

[0894] The "means for acquiring user location information" is a function for identifying the user's current location and acquiring that location information.

[0895] The "means for collecting environmental data" is a function for detecting surrounding environmental information such as wind speed, wind direction, temperature, and humidity, and collecting this data.

[0896] The "means for reading the user's past play data" is a function for reading the user's past play history data from a database in which the history data is recorded.

[0897] "Means for integrating and analyzing" refers to a function that brings together acquired location information, environmental data, and past play data, and performs analysis based on that data.

[0898] The "means for generating optimal play advice based on the analysis results" is a function for generating optimal play advice for the user based on the results obtained by the analysis.

[0899] The "means for notifying the user of play advice" is a function for notifying the user of the generated play advice.

[0900] "Means for providing advice in visual and audio form" refers to a function for providing advice to the user visually and audio using the smart glasses' display and earphones.

[0901] This invention is an AI unmanned caddy system that helps amateur golfers improve their scores efficiently. This system analyzes a user's location information, environmental data, and past play data, and provides optimal playing advice in real time.

[0902] System Components

[0903] 1. A device with a built-in GPS module that obtains the user's location information

[0904] The device uses the built-in GPS module to obtain the user's current location information, which is then sent to the server.

[0905] 2. A device equipped with sensors to detect wind speed, wind direction, temperature, and humidity to collect environmental data.

[0906] The device's built-in sensors detect wind speed, direction, temperature, and humidity, and send this data to a server.

[0907] 3. A server with a database that stores users' past play data

[0908] The server stores the user's past play data in a database and reads it as needed.

[0909] 4. A server equipped with an artificial intelligence algorithm that integrates and analyzes collected location information, environmental data, and past play data.

[0910] The server's artificial intelligence algorithm integrates and analyzes the collected data (location information, environmental data, and past play data).

[0911] 5. Server that generates optimal play advice based on the analysis results

[0912] The server generates optimal play advice based on the analysis results and provides it to the user.

[0913] 6. A device with smart glasses and earphones that provides play advice to the user

[0914] The device displays the generated play advice on the smart glasses display and notifies the player via audio through earphones.

[0915] Specific examples

[0916] For example, if the user reaches the fifth hole and wants to know the best club and shot direction for the next shot, the process is as follows:

[0917] 1. The device acquires the user's current location using its built-in GPS function and sends it to the server.

[0918] 2. The server recognizes that the user is on the fifth hole and reads the past play data for the fifth hole from the database.

[0919] 3. The device uses its built-in sensor to detect that the current wind speed is 10 km / h and blowing north, and sends this information to the server.

[0920] 4. The server combines location information, environmental data, and past play data and analyzes the data using artificial intelligence algorithms.

[0921] 5. The server determines that the advice is for the user to use a 3-iron and to aim the shot slightly to the left.

[0922] 6. The device will display "Use a 3 iron and aim slightly to the left" on the smart glasses display and will give a voice notification through the earphones saying "Wind speed 10 km / h, northbound, use a 3 iron and aim slightly to the left."

[0923] Example prompts for generative AI models

[0924] Below are some example prompts to be input to the generative AI model:

[0925] "The user has reached the 5th hole. The wind is 10km / h and blowing from the north. Based on past play data, a 3-iron is the best option for this hole. Please advise which club to use and in what direction to aim for the next shot."

[0926] Based on this prompt, the generative AI model is expected to generate appropriate advice and provide it to the user.

[0927] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0928] Step 1:

[0929] Obtain the user's location information and send it to the server

[0930] The device uses its built-in GPS module to obtain the user's current location information. Specifically, the device periodically reads GPS data to obtain latitude and longitude information. This location information (input data) is sent from the device to the server (output data). For example, the device obtains location information of "latitude 35.6895, longitude 139.6917" and sends it to the server.

[0931] Step 2:

[0932] The server recognizes the target hole and loads past play data.

[0933] The server identifies the hole the user is currently on based on the acquired location information. It analyzes and recognizes the hole number from the location information (input data) and reads the corresponding past play data from the database (output data). Specifically, the server identifies the "5th hole" and reads the past play data for the 5th hole.

[0934] Step 3:

[0935] The device collects environmental data and sends it to the server.

[0936] The terminal uses its built-in sensors to collect on-site environmental data. Specifically, the sensors detect data such as wind speed, wind direction, temperature, and humidity (input data). This environmental data is sent from the terminal to a server (output data). For example, the terminal collects data such as "wind speed 10 km / h, facing north, temperature 25°C, humidity 60%" and sends it to the server.

[0937] Step 4:

[0938] The server aggregates the data and analyzes it using artificial intelligence algorithms.

[0939] The server integrates the acquired location information, environmental data, and past play data (input data). It then uses an artificial intelligence algorithm to perform analysis based on the integrated data. Specifically, the server's AI calculates the effects of wind and past shot results, and determines the optimal club selection and shot direction (output data). For example, the server may obtain the analysis result, "Use a 3-iron and set the shot direction slightly to the left."

[0940] Step 5:

[0941] The server generates advice and sends it to the device.

[0942] The server generates specific play advice based on the analysis results (input data). This advice is sent from the server to the device (output data). Specifically, the server generates the play advice "Use a 3-iron and aim slightly to the left" and sends it to the device.

[0943] Step 6:

[0944] The device notifies the user of the advice

[0945] The device notifies the user of the received advice (input data). Specifically, the advice is displayed as visual information on the smart glasses display and audio advice is provided through the earphones (output data). For example, the device displays "Use a 3 iron and aim slightly to the left" on the smart glasses, and the earphones provide an audio notification saying, "Wind speed 10 km / h, northbound, use a 3 iron and aim slightly to the left."

[0946] In this way, each processing step is executed sequentially, and the user can receive real-time play advice to efficiently improve their score.

[0947] (Application example 1)

[0948] 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."

[0949] Conventional self-driving vehicles lack the technology to provide optimal driving advice in real time, making it difficult for them to drive efficiently and make appropriate decisions. Ensuring safety and efficiency has been particularly difficult in situations where quick responses to changes in weather and road conditions are required.

[0950] 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.

[0951] In this invention, the server includes means for acquiring location information, means for collecting environmental data, means for reading the user's past operation data, means for integrating and analyzing the location information, environmental data, and past operation data, means for generating optimal operation advice based on the analysis results, and means for notifying the user of the operation advice, thereby making it possible to provide optimal driving advice in real time and improve driving efficiency and safety.

[0952] "Location information" is data that indicates the current geographic location of an object.

[0953] "Environmental data" refers to data that indicates weather conditions and surrounding circumstances, and specifically includes weather data, road condition data, temperature, humidity, and the like.

[0954] "Task data" is data that indicates the history of past operations and actions.

[0955] "Integration" means bringing together multiple different types of data into one system or format.

[0956] "Analysis" refers to the calculation or evaluation of collected data to arrive at a specific conclusion or result.

[0957] "Operation advice" refers to instructions or suggestions provided to help a user take optimal action.

[0958] "Notification" is the act of conveying important information to the user, and various means such as visual and auditory are used.

[0959] An "internal location information acquisition device" is a device that is built into a device to acquire location information, such as a GPS module.

[0960] A "sensor" is a device that detects physical or chemical changes and outputs them as data.

[0961] "Weather data" refers to data indicating weather conditions such as temperature, wind speed, and rainfall.

[0962] "Road condition data" refers to data relating to road conditions, such as traffic flow, whether there have been any accidents, and construction information.

[0963] This invention relates to a driving assistance system for autonomous vehicles. Specifically, this system integrates and analyzes location information, environmental data, and the user's past work data in real time to provide optimal driving advice.

[0964] System Configuration

[0965] The system includes the following components:

[0966] 1. Obtaining location information

[0967] The server acquires location information using the vehicle's built-in location information acquisition device (GPS module) and uses this information for analysis.

[0968] 2. Environmental data collection

[0969] The server uses environmental sensors installed in the vehicle to collect weather data (temperature, wind speed, rainfall, etc.), road condition data (traffic flow, accident information, etc.), temperature, and humidity.

[0970] 3. Loading past work data

[0971] The server reads data such as the user's past driving routes, traffic conditions, and accident information from a database.

[0972] 4. Analysis of Integrated Data

[0973] This location information, environmental data, and past work data are integrated on the server, and data analysis is performed using a generative AI model.

[0974] 5. Driving advice generation

[0975] Based on the analysis results, the server generates optimal driving routes and driving advice.

[0976] 6. Notice to Users

[0977] The generated driving advice is communicated to the user visually and audibly via a head-mounted display and smartphone.

[0978] What the program does

[0979] The server acquires the vehicle's current location from the built-in location acquisition device and collects real-time weather and road condition data from environmental sensors. This data is stored in a database along with past driving history data. The server integrates all collected data and uses a generative AI model to calculate the optimal driving route and advice.

[0980] Detailed processing contents

[0981] Hardware: Built-in location acquisition device (GPS module), environmental sensors, head-mounted display, smartphone, on-board computer.

[0982] Software: Python, AIML (Artificial Intelligence Machine Learning Library), speech synthesis library.

[0983] Specific examples

[0984] If the user is heading to a destination during rainy weather, here is an example of how the system might behave:

[0985] 1. Location and Environmental Data Collection:

[0986] The built-in location information acquisition device acquires the current location and sends it to the server.

[0987] The environmental sensor detects weather conditions and sends the following to the server: rainfall 10mm / h, temperature 18°C, humidity 85%.

[0988] 2. Loading and analyzing historical data:

[0989] The server reads data on similar situations from a database of past driving situations and references past traffic volume and accident information.

[0990] 3. Driving advice generation:

[0991] A generative AI model integrates and analyzes this data and determines that the optimal route is to use major road A and avoid intersection X.

[0992] 4. Notice to Users:

[0993] The head-mounted display displays, "Take main road A and avoid intersection X."

[0994] Your smartphone will give you a voice notification saying, "In rainy weather, use main road A and avoid intersection X."

[0995] Prompt Sentence Examples

[0996] Get the best driving route from your current location based on real-time weather data and past driving history.

[0997] In this way, the system can provide optimal driving advice in real time, improving the user's driving efficiency and safety.

[0998] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0999] Step 1:

[1000] The server acquires the current location information using the vehicle's built-in location acquisition device (GPS module). The acquired location information is sent to the server and used for analysis. The input is the vehicle's current location data, and the output is the current location information stored on the server.

[1001] Step 2:

[1002] The server collects weather data, road condition data, temperature, and humidity from environmental sensors installed in the vehicle. This environmental data is sent to the server in real time. The input is various environmental data sensed by the sensors, and the output is environmental data stored on the server.

[1003] Step 3:

[1004] The server reads the user's past driving history data from the database, which includes past driving routes, traffic conditions, accident information, etc. The input is the driving history data in the database, and the output is the driving history data stored on the server.

[1005] Step 4:

[1006] The server integrates the acquired location information, environmental data, and past driving history data. Data integration generates consistent information from these different data sources. The input is location information, environmental data, and driving history data, and the output is the integrated data.

[1007] Step 5:

[1008] The server analyzes the integrated data using a generative AI model, which takes into account many variables such as weather conditions, road conditions, and past driving results to calculate the optimal driving route and advice. The input is the integrated data, and the output is the optimal driving advice.

[1009] Step 6:

[1010] The server generates optimal driving advice and notifies the user. Notifications are given via a head-mounted display and a smartphone, and the advice is conveyed visually and audibly. The input is the optimal driving advice, and the output is notification information to the user.

[1011] 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.

[1012] This invention is an AI unmanned caddy system that helps amateur golf players improve their scores efficiently, and it also has the ability to recognize the user's emotions and adjust play advice accordingly, thereby providing optimal advice according to the user's psychological state and maximizing the effectiveness of their play.

[1013] System configuration

[1014] The system includes the following components:

[1015] 1. A device with a built-in GPS module that obtains the user's location information.

[1016] 2. A device with sensors that detect wind speed, direction, temperature, and humidity to collect environmental data.

[1017] 3. A server with a database that stores users' past play data.

[1018] 4. A server equipped with an artificial intelligence algorithm that integrates and analyzes collected location information, environmental data, and past play data.

[1019] 5. A server that generates optimal play advice based on the analysis results.

[1020] 6. A device with smart glasses and earphones that notifies the user of play advice.

[1021] 7. A terminal including an emotion engine that recognizes the user's emotions.

[1022] Program processing

[1023] 1. Collecting user location information and gameplay data

[1024] The device uses the built-in GPS module to obtain its current location, which is then immediately sent to the server.

[1025] The server identifies the user's current location and recognizes the corresponding golf hole, and records the information for further processing.

[1026] The server reads the user's past play data from the database and saves it.

[1027] 2. Real-time environmental data collection

[1028] The device collects environmental data using built-in sensors that detect wind speed, direction, temperature, and humidity, and transmits this data to a server.

[1029] 3. Data Analysis

[1030] The server combines collected location information, environmental data, and past play data and analyzes the data using artificial intelligence algorithms.

[1031] The server comprehensively evaluates factors such as the influence of the wind, past success rates, and the layout of the hole to calculate the optimal club selection and shot direction. It also takes into account the strength of the shot depending on the situation.

[1032] 4. Emotional Data Collection and Analysis

[1033] The device analyzes the user's facial expressions, voice, or biometric information to collect emotional data, which is then sent to a server.

[1034] The server analyzes the emotion data to understand the user's psychological state, for example, determining whether the user is tense or relaxed.

[1035] 5. Advice Generation and Adjustment

[1036] The server adjusts the generated play advice based on the emotion data, for example adding advice to relax if the user is nervous.

[1037] The optimal play advice is finally determined based on the analysis results.

[1038] 6. Notice to Users

[1039] The device then displays the generated play advice on the smart glasses display, providing visual information such as "Use a 3 iron, aim slightly to the left, and hit with a relaxed stance."

[1040] The device will notify the user through the earphones with a voice message saying, "The wind speed is 10 km / h and blowing north. Aim slightly to the left with a 3-iron. Relax and remember to take deep breaths."

[1041] Specific examples

[1042] The following example illustrates the process when the user reaches the fifth hole and wants to know the best club and shot direction for the next shot.

[1043] 1. The device acquires the user's current location using its built-in GPS function and sends it to the server.

[1044] 2. The server recognizes that the user is on the fifth hole and reads the past play data for the fifth hole from the database.

[1045] 3. The device uses its built-in sensor to detect that the current wind speed is 10 km / h and blowing north, and sends this information to the server.

[1046] 4. The server combines location information, environmental data, and past play data and analyzes the data using artificial intelligence algorithms.

[1047] 5. Using a facial recognition camera and voice analysis, the device detects that the user is slightly nervous and sends the emotional data to the server.

[1048] 6. The server recognizes that the user is tense and adjusts the generated playing advice to include instructions for relaxing.

[1049] 7. The device will display on the smart glasses' display, "Use a 3 iron, aim slightly to the left, and hit while relaxing," and will provide a voice notification through the earphones saying, "Wind speed 10 km / h, northbound. Use a 3 iron and aim slightly to the left. Relax and remember to take deep breaths."

[1050] In this way, the user can receive optimal golf management advice tailored to their psychological state, making it possible to compensate for lack of experience and efficiently improve their score.

[1051] The processing flow will be explained below.

[1052] Step 1:

[1053] The device uses a built-in GPS module to obtain the user's current location, which is then immediately sent to the server.

[1054] Step 2:

[1055] The server identifies the user's current location based on the received location information, identifies the corresponding golf hole, and records the information for further processing.

[1056] Step 3:

[1057] The server reads the user's past play data stored in a database, including the clubs previously used, shot results, and scores.

[1058] Step 4:

[1059] The device uses built-in sensors to collect environmental data such as wind speed, wind direction, temperature, and humidity, which is then sent to a server.

[1060] Step 5:

[1061] The server integrates the collected location information, past play data, and current environmental data, and performs analysis using artificial intelligence algorithms based on this data.

[1062] Step 6:

[1063] The device uses a built-in camera and voice recognition function to analyze the user's facial expressions and voice to obtain emotional data, which is then sent to a server.

[1064] Step 7:

[1065] The server analyzes the emotion data to understand the user's psychological state, for example, determining whether the user is tense or relaxed.

[1066] Step 8:

[1067] The server adjusts the generated play advice based on the emotion data, for example adding advice to relax if the user is nervous.

[1068] Step 9:

[1069] The server comprehensively evaluates factors such as the influence of the wind, the layout of the hole, and past success rates to calculate the optimal club selection and shot direction. It also adjusts the force of the shot based on the user's emotions.

[1070] Step 10:

[1071] The server generates specific play advice based on the analysis results, such as "Use a 3-iron, aim slightly to the left, and hit the ball in a relaxed manner."

[1072] Step 11:

[1073] The device receives play advice from the server and displays it on the smart glasses display, providing visual information such as "Use a 3 iron, aim slightly to the left, and hit the ball in a relaxed manner."

[1074] Step 12:

[1075] The device will notify the user through the earphones with a voice message saying, "The wind speed is 10 km / h and blowing north. Aim slightly to the left with a 3-iron. Relax and remember to take deep breaths."

[1076] This series of processes allows users to receive optimal golf management advice in real time according to their psychological state, which can help compensate for lack of experience and improve scores efficiently.

[1077] Example 2

[1078] 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."

[1079] Conventional golf management systems provide advice based only on the user's location, environmental data, and past play data, but do not consider the user's psychological state. This has resulted in the problem that optimal advice is not provided depending on the user's psychological state, such as when the user is tense or relaxed. There is a need to provide playing advice that reflects the user's emotions and psychological state, thereby maximizing the effectiveness of the user's play.

[1080] 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.

[1081] In this invention, the server includes means for acquiring user position information, means for collecting environmental data, means for reading the user's past play data, means for integrating and analyzing the position information, environmental data, and past play data, means for generating optimal play advice based on the analysis results, means for notifying the user of the play advice, means for collecting user emotion data, and means for adjusting the play advice based on the emotion data, thereby making it possible to provide optimal golf management advice tailored to the user's psychological state.

[1082] "User location information" is data that indicates the specific location where the user is currently located.

[1083] "Environmental data" refers to data that indicates the surrounding physical conditions that affect golf play, such as wind speed, wind direction, temperature, and humidity.

[1084] "User's past play data" refers to data that indicates records and statistical information of the golf plays that the user has performed up to now.

[1085] The "built-in GPS module" is a device that uses satellite signals to measure the user's current location with high accuracy.

[1086] A "wind speed sensor" is a device for measuring wind speed.

[1087] A "wind direction sensor" is a device for measuring the direction in which the wind is blowing.

[1088] A "temperature sensor" is a device for measuring the temperature of air.

[1089] A "humidity sensor" is a device for measuring the proportion of water vapor in the air.

[1090] "Means for integrating and analyzing" refers to the process and equipment for consolidating collected data into a single piece of information and analyzing it.

[1091] The "means for generating optimal play advice" refers to a process and device for generating the most effective play advice for the user based on the results of data analysis.

[1092] The "means for notifying the user of the playing advice" refers to a device or method for communicating the generated playing advice to the user.

[1093] "User emotion data" is data that indicates the user's current psychological state, and includes facial expressions, voice analysis results, biometric information, and the like.

[1094] The "means for adjusting play advice" refers to a process and device for appropriately changing the content of the generated play advice based on emotion data.

[1095] The present invention is a system for enabling amateur golf players to efficiently improve their scores, and provides optimal playing advice in accordance with the user's psychological state. Specific embodiments of the system will be described below.

[1096] This system is configured using the following hardware and software:

[1097] 1. Devices with a built-in GPS module: Used to obtain location information.

[1098] 2. Devices with sensors that detect wind speed, direction, temperature, and humidity: Used to collect environmental data.

[1099] 3. Server with database: Used to save and load users' past play data.

[1100] 4. Server equipped with artificial intelligence algorithms: Used to integrate and analyze collected location information, environmental data, and past play data.

[1101] 5. Server that generates optimal play advice: Generates play advice based on the analysis results.

[1102] 6. Device with smart glasses and earphones: Used to notify the user of play advice.

[1103] 7. Devices with emotion engines: Used to recognize user emotions.

[1104] The device uses its built-in GPS module to obtain its current location and sends that information to the server. The server then analyzes the location information, identifies the user's current location, and loads past play data from a database. The device also uses its built-in sensors to collect environmental data such as wind speed, wind direction, temperature, and humidity, which it then sends to the server.

[1105] The server uses an AI algorithm to analyze the collected location information, environmental data, and past play data, and then evaluates the effects of wind, hole layout, past success rates, and other factors to calculate the optimal club selection and shot direction.

[1106] Furthermore, the device uses sensors such as a camera and microphone to collect the user's facial expressions and voice, and sends the emotional data to the server. The server analyzes the emotional data to understand the user's psychological state and adjusts the generated advice accordingly. For example, if the user is nervous, it will add advice to help them relax.

[1107] Finally, the device displays the adjusted playing advice on the smart glasses display and provides audio feedback through the earphones, such as "Use a 3 iron, aim slightly to the left, and hit with a relaxed stance."

[1108] Specific examples

[1109] The following example illustrates the process when the user reaches the fifth hole and wants to know the best club and shot direction for the next shot.

[1110] 1. The device uses its built-in GPS to obtain the user's current location and sends it to the server.

[1111] 2. The server recognizes that the user is on the 5th hole and reads the past play data for the 5th hole from the database.

[1112] 3. The device uses its built-in sensor to detect that the current wind speed is 10 km / h and blowing north, and sends this data to the server.

[1113] 4. The server combines location information, environmental data, and past play data and analyzes the data using artificial intelligence algorithms.

[1114] 5. Using a facial recognition camera and voice analysis, the device detects when the user is feeling slightly nervous and sends that emotional data to the server.

[1115] 6. The server recognizes that the user is nervous and adjusts the generated play advice to include instructions for relaxing.

[1116] 7. The device will display on the smart glasses' display, "Use a 3 iron, aim slightly to the left, and hit while relaxed," and will provide a voice notification through the earphones: "Wind speed 10 km / h, northbound. Use a 3 iron and aim slightly to the left. Relax and remember to take deep breaths."

[1117] Prompt Sentence Examples

[1118] 1. "What is the current wind speed and direction on the hole?"

[1119] 2. "What advice should you give to help users relax?"

[1120] In this way, the user can receive optimal golf management advice tailored to their psychological state, making it possible to compensate for lack of experience and efficiently improve their score.

[1121] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1122] Step 1: Get and send the user's current location

[1123] Input: Location information from the GPS module

[1124] The device will activate its built-in GPS module to obtain the user's current location, which includes latitude and longitude.

[1125] The acquired location information is sent to the server in real time.

[1126] Output: Location information sent to the server

[1127] Step 2: Analyze and set the user's current location

[1128] Input: Location information sent from the device

[1129] The server analyzes the received location information to determine the user's current location, which may involve the use of a geographic information system (GIS).

[1130] The server recognizes the identified golf hole number and records it in an internal database.

[1131] Output: Current golf hole number and its location

[1132] Step 3: Obtaining past play data

[1133] Input: Current golf hole number

[1134] The server reads the user's past play data from its internal database and prepares it for analysis, including the success rate of past shots and the clubs used.

[1135] Output: Past play data

[1136] Step 4: Collect environmental data

[1137] Input: Ambient environmental conditions

[1138] The device activates its built-in sensors to measure wind speed, direction, temperature, and humidity, and the data collected by the sensors is collected in real time.

[1139] The collected environmental data is transmitted from the terminal to a server.

[1140] Output: Environment data sent to the server

[1141] Step 5: Data synthesis and analysis

[1142] Input: location information, environmental data, past play data

[1143] The server combines the acquired location information, environmental data, and past play data and analyzes it using artificial intelligence algorithms, including statistical and machine learning models.

[1144] As a result of the analysis, factors such as the influence of wind, hole layout, and past success rate are evaluated to calculate the optimal club selection and shot direction.

[1145] Output: Optimal club selection and shot direction

[1146] Step 6: Collect and send emotion data

[1147] Input: User's facial expression, voice, biometric information

[1148] The device uses sensors such as a camera and microphone to collect data on the user's emotions, and uses facial expression recognition and voice analysis technology to estimate the user's psychological state.

[1149] The collected emotion data is sent to a server in real time.

[1150] Output: Emotion data sent to the server

[1151] Step 7: Analyze emotional data and adjust play advice

[1152] Input: Emotional data, optimal club selection and shot direction

[1153] The server analyzes the received emotional data to understand the user's psychological state, sometimes using machine learning models or rule-based systems.

[1154] If the user is perceived as tense, the advice is adjusted to include instructions for relaxation.

[1155] Output: Adjusted play advice

[1156] Step 8: Advise users

[1157] Input: Adjusted play advice

[1158] The terminal obtains the finalized play advice.

[1159] The device will then display advice on the smart glasses display, such as "Use a 3 iron, aim slightly to the left, and hit with a relaxed stance."

[1160] The device will then notify the user through the earphones with a voice message saying, "Wind speed 10km / h, northbound. Aim slightly to the left with a 3-iron. Relax and remember to take deep breaths."

[1161] Output: Play advice given to the user

[1162] (Application example 2)

[1163] 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."

[1164] Conventional work management systems have had problems in that they were unable to adequately improve the efficiency of workers on production lines or manage their psychological stress. Furthermore, they lacked the functionality to provide advice that took into account environmental data and the emotional state of workers, which led to a risk of reduced work efficiency and the accumulation of worker stress. The present invention aims to solve these problems and provide a system that simultaneously optimizes workers' work efficiency and psychological health.

[1165] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1166] In this invention, the server includes means for acquiring user location information, means for collecting environmental data, means for reading the user's past work data, means for collecting the user's emotion data, means for integrating and analyzing the location information, environmental data, the user's past work data, and the emotion data, means for adjusting advice generated based on the emotion data, means for generating optimal work advice based on the analysis results, and means for notifying the user of the work advice, thereby enabling optimal work advice according to the work environment and stress management for workers.

[1167] "Location information" is data that indicates the user's current location.

[1168] "Environmental data" refers to data that indicates the ambient conditions in which the user is working, such as temperature, humidity, and noise level.

[1169] "Past work data" refers to records and data relating to work that the user has performed in the past.

[1170] "Emotion data" is data that expresses the user's psychological state and emotions.

[1171] "Analysis" is the process of integrating collected location information, environmental data, past work data, and emotional data, and making evaluations and judgments based on that information.

[1172] "Adjusting the advice" means optimizing the generated advice to suit the user's condition and environment.

[1173] "Work advice" is specific instructions and suggestions for the user to work efficiently and healthily.

[1174] "Notification" refers to transmitting the generated work advice to the user.

[1175] This invention relates to an artificial intelligence system that optimizes the work efficiency and psychological stress of factory workers. The system integrates and analyzes the user's location information, environmental data, past work data, and emotional data, and generates and notifies optimal work advice.

[1176] System configuration

[1177] The system consists of the following main components:

[1178] 1. Location information acquisition means

[1179] The built-in GPS module is used to obtain the user's location, allowing the system to accurately determine which working area the user is in.

[1180] 2. Environmental data collection methods

[1181] Environmental data is collected using sensors that detect wind speed, wind direction, temperature, humidity, noise level, etc. This data is used to evaluate the impact of the work environment on work efficiency and psychological stress.

[1182] 3. How to load past work data

[1183] The user's past work data is read from the database, including the user's past work logs and performance data.

[1184] 4. Emotional Data Collection Methods

[1185] Using facial recognition cameras and voice analysis, the user's psychological state and emotions are analyzed and emotional data is collected.

[1186] 5. Data Analysis Methods

[1187] The server integrates the collected location information, environmental data, past activity data, and emotional data, and analyzes the data using artificial intelligence algorithms, taking into account the effectiveness of the activity and the user's psychological state.

[1188] 6. Advice Generation and Adjustment Methods

[1189] The server generates optimal work advice based on the analysis results and adjusts the content based on emotional data. For example, if stress increases while working, the server will provide advice including ways to relax.

[1190] 7. User Notification Methods

[1191] The generated work advice is notified to the user using smart glasses or a head-mounted display, providing detailed advice in real time.

[1192] Program processing

[1193] For example, when a worker is joining parts on a conveyor, the server collects real-time environmental data and past work data, and analyzes this data. Emotion recognition data is also analyzed, so if the worker feels tired, advice is generated to encourage them to take a short break.

[1194] Hardware and software used

[1195] Built-in GPS module: location information acquisition

[1196] Environmental sensors: Collect data on wind speed, wind direction, temperature, humidity, and noise levels

[1197] Facial recognition camera and voice analysis software: Emotion data collection

[1198] Database server: Saving and loading historical data

[1199] AI analysis server: Analysis of integrated data

[1200] Smart Glasses and Head-Mounted Displays: User Advice Notification

[1201] Prompt Sentence Examples

[1202] "Enter the following data into the AI ​​model: environmental data (temperature 28°C, humidity 60%, noise level 70dB), location information (joining section), past data (points to note when joining), and emotional data (mild fatigue). Generate optimal work procedures and advice on stress management."

[1203] In this way, the system of the present invention allows workers to receive work advice suited to the environment, while also managing psychological stress and enabling them to work efficiently.

[1204] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1205] Step 1:

[1206] The device uses the built-in GPS module to obtain the user's current location, which is used to determine which working area the user is in. The obtained location information is then sent to the server and stored.

[1207] Step 2:

[1208] The device uses built-in sensors to collect environmental data such as temperature, humidity, and noise levels. This environmental data is used to evaluate the impact of the work environment on work efficiency and psychological stress. The collected environmental data is then sent to a server and stored.

[1209] Step 3:

[1210] The server reads the user's past work data from the database. This past data includes logs of the user's past work and performance data. The read data is used for analysis.

[1211] Step 4:

[1212] The device uses facial recognition cameras and voice analysis software to collect data on the user's psychological state and emotions. This emotional data is used to evaluate the user's current psychological state and is sent to a server.

[1213] Step 5:

[1214] The server integrates the collected location information, environmental data, past work data, and emotional data, and analyzes them using artificial intelligence algorithms. This analysis process evaluates the worker's work efficiency and psychological stress level. Based on the input data, optimal work procedures and advice are generated.

[1215] Step 6:

[1216] The server generates optimal work advice based on the analysis results. During this generation process, the advice is adjusted based on the emotional data, for example, if the user is tired, the advice may be adjusted to encourage them to take a break.

[1217] Step 7:

[1218] The generated optimal work advice is sent from the server to the device, which then notifies the user using smart glasses or a head-mounted display. Specific advice content is provided as visual information or audio notifications.

[1219] This allows users to receive real-time, optimal work advice suited to their environment, enabling them to work efficiently. Furthermore, by managing psychological stress, work efficiency is improved and worker health is managed.

[1220] 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.

[1221] 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.

[1222] 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.

[1223] [Fourth embodiment]

[1224] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1225] 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.

[1226] 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).

[1227] 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.

[1228] 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.

[1229] 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).

[1230] 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.

[1231] 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.

[1232] 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.

[1233] 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.

[1234] 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.

[1235] 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.

[1236] 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."

[1237] This invention is an AI unmanned caddy system that helps amateur golfers improve their scores efficiently. This system analyzes a user's location information, environmental data, and past play data, and provides optimal playing advice in real time.

[1238] System configuration

[1239] The system includes the following components:

[1240] 1. A device with a built-in GPS module that obtains the user's location information.

[1241] 2. A device with sensors that detect wind speed, direction, temperature, and humidity to collect environmental data.

[1242] 3. A server with a database that stores users' past play data.

[1243] 4. A server equipped with an artificial intelligence algorithm that integrates and analyzes collected location information, environmental data, and past play data.

[1244] 5. A server that generates optimal play advice based on the analysis results.

[1245] 6. A device with smart glasses and earphones that notifies the user of play advice.

[1246] Program processing

[1247] 1. Collecting user location information and gameplay data

[1248] The device uses the built-in GPS module to obtain its current location, which is then sent to the server.

[1249] The server identifies the user's current location and recognizes the target hole.

[1250] The server reads the user's past play data from the database and saves it.

[1251] 2. Real-time environmental data collection

[1252] The device collects environmental data using built-in sensors that detect wind speed, wind direction, temperature, and humidity, and transmits this data to a server.

[1253] 3. Data Analysis

[1254] The server combines collected location information, environmental data, and past play data and analyzes the data using artificial intelligence algorithms.

[1255] The server calculates the optimal club selection and shot direction for the user, taking into account factors such as the effects of wind, past shot results, and hole layout.

[1256] 4. Generating Advice

[1257] The server generates specific playing advice based on the analysis, including which club to use, the direction of the shot, and how much force to use.

[1258] 5. Notice to Users

[1259] The device displays the generated play advice as visual information on the smart glasses display.

[1260] The terminal provides audio advice to the user through an earphone.

[1261] Specific examples

[1262] The following example illustrates the process when the user reaches the fifth hole and wants to know the best club and shot direction for the next shot.

[1263] 1. The device acquires the user's current location using its built-in GPS function and sends it to the server.

[1264] 2. The server recognizes that the user is on the fifth hole and reads the past play data for the fifth hole from the database.

[1265] 3. The device uses its built-in sensor to detect that the current wind speed is 10 km / h and blowing north, and sends this information to the server.

[1266] 4. The server combines location information, environmental data, and past play data and analyzes the data using artificial intelligence algorithms.

[1267] 5. The server determines that the advice is for the user to use a 3-iron and to aim the shot slightly to the left.

[1268] 6. The device will display "Use a 3 iron and aim slightly to the left" on the smart glasses display and will give a voice notification through the earphones saying "Wind speed 10 km / h, northbound, use a 3 iron and aim slightly to the left."

[1269] In this way, users can receive optimal golf management advice in real time, making up for lack of experience and efficiently improving their scores.

[1270] The processing flow will be explained below.

[1271] Step 1:

[1272] The device uses a built-in GPS module to obtain the user's current location, which is then immediately sent to the server.

[1273] Step 2:

[1274] The server identifies the user's current location based on the received location information, identifies the corresponding golf hole, and records the information for further processing.

[1275] Step 3:

[1276] The server reads the user's past play data stored in a database, including the clubs previously used, shot results, and scores.

[1277] Step 4:

[1278] The device uses built-in sensors to collect environmental data such as wind speed, wind direction, temperature, and humidity, which is then sent to a server.

[1279] Step 5:

[1280] The server integrates the collected location information, past play data, and current environmental data, and performs analysis using artificial intelligence algorithms based on this data.

[1281] Step 6:

[1282] The server will comprehensively evaluate factors such as the wind's influence, hole layout, and past success rates to calculate the optimal club selection and shot direction. It also takes into account the power of the shot depending on the situation.

[1283] Step 7:

[1284] The server generates specific play advice based on the analysis results, such as "Use a 3-iron and aim slightly to the left."

[1285] Step 8:

[1286] The device receives play advice from the server and displays it on the smart glasses display, providing visual information such as "Use a 3 iron and aim slightly to the left."

[1287] Step 9:

[1288] The device will notify the user through the earphones by voice, "The wind speed is 10 km / h and blowing north. Aim slightly to the left with a 3 iron."

[1289] This series of processes allows users to receive optimal golf management advice in real time, making it possible to compensate for lack of experience and improve scores.

[1290] Example 1

[1291] 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."

[1292] Amateur golf players often find it difficult to improve their scores efficiently due to lack of experience and technical misjudgments. Furthermore, they lack support for improving their play quality due to limited access to appropriate advice in real time while playing. To solve this problem, a system is needed that integrates and analyzes the user's location information, environmental data, and past play data to provide optimal play advice in real time.

[1293] 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.

[1294] In this invention, the server includes means for acquiring user position information, means for collecting environmental data, means for reading the user's past play data, means for integrating and analyzing the position information, environmental data, and past play data, means for generating optimal play advice based on the analysis results, means for notifying the user of the play advice, and means for providing the advice to the user in visual and audio form, thereby enabling the user to receive optimal play advice in real time and efficiently improve their score.

[1295] The "means for acquiring user location information" is a function for identifying the user's current location and acquiring that location information.

[1296] The "means for collecting environmental data" is a function for detecting surrounding environmental information such as wind speed, wind direction, temperature, and humidity, and collecting this data.

[1297] The "means for reading the user's past play data" is a function for reading the user's past play history data from a database in which the history data is recorded.

[1298] "Means for integrating and analyzing" refers to a function that brings together acquired location information, environmental data, and past play data, and performs analysis based on that data.

[1299] The "means for generating optimal play advice based on the analysis results" is a function for generating optimal play advice for the user based on the results obtained by the analysis.

[1300] The "means for notifying the user of play advice" is a function for notifying the user of the generated play advice.

[1301] "Means for providing advice in visual and audio form" refers to a function for providing advice to the user visually and audio using the smart glasses' display and earphones.

[1302] This invention is an AI unmanned caddy system that helps amateur golfers improve their scores efficiently. This system analyzes a user's location information, environmental data, and past play data, and provides optimal playing advice in real time.

[1303] System Components

[1304] 1. A device with a built-in GPS module that obtains the user's location information

[1305] The device uses the built-in GPS module to obtain the user's current location information, which is then sent to the server.

[1306] 2. A device equipped with sensors to detect wind speed, wind direction, temperature, and humidity to collect environmental data.

[1307] The device's built-in sensors detect wind speed, direction, temperature, and humidity, and send this data to a server.

[1308] 3. A server with a database that stores users' past play data

[1309] The server stores the user's past play data in a database and reads it as needed.

[1310] 4. A server equipped with an artificial intelligence algorithm that integrates and analyzes collected location information, environmental data, and past play data.

[1311] The server's artificial intelligence algorithm integrates and analyzes the collected data (location information, environmental data, and past play data).

[1312] 5. Server that generates optimal play advice based on the analysis results

[1313] The server generates optimal play advice based on the analysis results and provides it to the user.

[1314] 6. A device with smart glasses and earphones that provides play advice to the user

[1315] The device displays the generated play advice on the smart glasses display and notifies the player via audio through earphones.

[1316] Specific examples

[1317] For example, if the user reaches the fifth hole and wants to know the best club and shot direction for the next shot, the process is as follows:

[1318] 1. The device acquires the user's current location using its built-in GPS function and sends it to the server.

[1319] 2. The server recognizes that the user is on the fifth hole and reads the past play data for the fifth hole from the database.

[1320] 3. The device uses its built-in sensor to detect that the current wind speed is 10 km / h and blowing north, and sends this information to the server.

[1321] 4. The server combines location information, environmental data, and past play data and analyzes the data using artificial intelligence algorithms.

[1322] 5. The server determines that the advice is for the user to use a 3-iron and to aim the shot slightly to the left.

[1323] 6. The device will display "Use a 3 iron and aim slightly to the left" on the smart glasses display and will give a voice notification through the earphones saying "Wind speed 10 km / h, northbound, use a 3 iron and aim slightly to the left."

[1324] Example prompts for generative AI models

[1325] Below are some example prompts to be input to the generative AI model:

[1326] "The user has reached the 5th hole. The wind is 10km / h and blowing from the north. Based on past play data, a 3-iron is the best option for this hole. Please advise which club to use and in what direction to aim for the next shot."

[1327] Based on this prompt, the generative AI model is expected to generate appropriate advice and provide it to the user.

[1328] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1329] Step 1:

[1330] Obtain the user's location information and send it to the server

[1331] The device uses its built-in GPS module to obtain the user's current location information. Specifically, the device periodically reads GPS data to obtain latitude and longitude information. This location information (input data) is sent from the device to the server (output data). For example, the device obtains location information of "latitude 35.6895, longitude 139.6917" and sends it to the server.

[1332] Step 2:

[1333] The server recognizes the target hole and loads past play data.

[1334] The server identifies the hole the user is currently on based on the acquired location information. It analyzes and recognizes the hole number from the location information (input data) and reads the corresponding past play data from the database (output data). Specifically, the server identifies the "5th hole" and reads the past play data for the 5th hole.

[1335] Step 3:

[1336] The device collects environmental data and sends it to the server.

[1337] The terminal uses its built-in sensors to collect on-site environmental data. Specifically, the sensors detect data such as wind speed, wind direction, temperature, and humidity (input data). This environmental data is sent from the terminal to a server (output data). For example, the terminal collects data such as "wind speed 10 km / h, facing north, temperature 25°C, humidity 60%" and sends it to the server.

[1338] Step 4:

[1339] The server aggregates the data and analyzes it using artificial intelligence algorithms.

[1340] The server integrates the acquired location information, environmental data, and past play data (input data). It then uses an artificial intelligence algorithm to perform analysis based on the integrated data. Specifically, the server's AI calculates the effects of wind and past shot results, and determines the optimal club selection and shot direction (output data). For example, the server may obtain the analysis result, "Use a 3-iron and set the shot direction slightly to the left."

[1341] Step 5:

[1342] The server generates advice and sends it to the device.

[1343] The server generates specific play advice based on the analysis results (input data). This advice is sent from the server to the device (output data). Specifically, the server generates the play advice "Use a 3-iron and aim slightly to the left" and sends it to the device.

[1344] Step 6:

[1345] The device notifies the user of the advice

[1346] The device notifies the user of the received advice (input data). Specifically, the advice is displayed as visual information on the smart glasses display and audio advice is provided through the earphones (output data). For example, the device displays "Use a 3 iron and aim slightly to the left" on the smart glasses, and the earphones provide an audio notification saying, "Wind speed 10 km / h, northbound, use a 3 iron and aim slightly to the left."

[1347] In this way, each processing step is executed sequentially, and the user can receive real-time play advice to efficiently improve their score.

[1348] (Application example 1)

[1349] 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."

[1350] Conventional self-driving vehicles lack the technology to provide optimal driving advice in real time, making it difficult for them to drive efficiently and make appropriate decisions. Ensuring safety and efficiency has been particularly difficult in situations where quick responses to changes in weather and road conditions are required.

[1351] 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.

[1352] In this invention, the server includes means for acquiring location information, means for collecting environmental data, means for reading the user's past operation data, means for integrating and analyzing the location information, environmental data, and past operation data, means for generating optimal operation advice based on the analysis results, and means for notifying the user of the operation advice, thereby making it possible to provide optimal driving advice in real time and improve driving efficiency and safety.

[1353] "Location information" is data that indicates the current geographic location of an object.

[1354] "Environmental data" refers to data that indicates weather conditions and surrounding circumstances, and specifically includes weather data, road condition data, temperature, humidity, and the like.

[1355] "Task data" is data that indicates the history of past operations and actions.

[1356] "Integration" means bringing together multiple different types of data into one system or format.

[1357] "Analysis" refers to the calculation or evaluation of collected data to arrive at a specific conclusion or result.

[1358] "Operation advice" refers to instructions or suggestions provided to help a user take optimal action.

[1359] "Notification" is the act of conveying important information to the user, and various means such as visual and auditory are used.

[1360] An "internal location information acquisition device" is a device that is built into a device to acquire location information, such as a GPS module.

[1361] A "sensor" is a device that detects physical or chemical changes and outputs them as data.

[1362] "Weather data" refers to data indicating weather conditions such as temperature, wind speed, and rainfall.

[1363] "Road condition data" refers to data relating to road conditions, such as traffic flow, whether there have been any accidents, and construction information.

[1364] This invention relates to a driving assistance system for autonomous vehicles. Specifically, this system integrates and analyzes location information, environmental data, and the user's past work data in real time to provide optimal driving advice.

[1365] System Configuration

[1366] The system includes the following components:

[1367] 1. Obtaining location information

[1368] The server acquires location information using the vehicle's built-in location information acquisition device (GPS module) and uses this information for analysis.

[1369] 2. Environmental data collection

[1370] The server uses environmental sensors installed in the vehicle to collect weather data (temperature, wind speed, rainfall, etc.), road condition data (traffic flow, accident information, etc.), temperature, and humidity.

[1371] 3. Loading past work data

[1372] The server reads data such as the user's past driving routes, traffic conditions, and accident information from a database.

[1373] 4. Analysis of Integrated Data

[1374] This location information, environmental data, and past work data are integrated on the server, and data analysis is performed using a generative AI model.

[1375] 5. Driving advice generation

[1376] Based on the analysis results, the server generates optimal driving routes and driving advice.

[1377] 6. Notice to Users

[1378] The generated driving advice is communicated to the user visually and audibly via a head-mounted display and smartphone.

[1379] What the program does

[1380] The server acquires the vehicle's current location from the built-in location acquisition device and collects real-time weather and road condition data from environmental sensors. This data is stored in a database along with past driving history data. The server integrates all collected data and uses a generative AI model to calculate the optimal driving route and advice.

[1381] Detailed processing contents

[1382] Hardware: Built-in location acquisition device (GPS module), environmental sensors, head-mounted display, smartphone, on-board computer.

[1383] Software: Python, AIML (Artificial Intelligence Machine Learning Library), speech synthesis library.

[1384] Specific examples

[1385] If the user is heading to a destination during rainy weather, here is an example of how the system might behave:

[1386] 1. Location and Environmental Data Collection:

[1387] The built-in location information acquisition device acquires the current location and sends it to the server.

[1388] The environmental sensor detects weather conditions and sends the following to the server: rainfall 10mm / h, temperature 18°C, humidity 85%.

[1389] 2. Loading and analyzing historical data:

[1390] The server reads data on similar situations from a database of past driving situations and references past traffic volume and accident information.

[1391] 3. Driving advice generation:

[1392] A generative AI model integrates and analyzes this data and determines that the optimal route is to use major road A and avoid intersection X.

[1393] 4. Notice to Users:

[1394] The head-mounted display displays, "Take main road A and avoid intersection X."

[1395] Your smartphone will give you a voice notification saying, "In rainy weather, use main road A and avoid intersection X."

[1396] Prompt Sentence Examples

[1397] Get the best driving route from your current location based on real-time weather data and past driving history.

[1398] In this way, the system can provide optimal driving advice in real time, improving the user's driving efficiency and safety.

[1399] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1400] Step 1:

[1401] The server acquires the current location information using the vehicle's built-in location acquisition device (GPS module). The acquired location information is sent to the server and used for analysis. The input is the vehicle's current location data, and the output is the current location information stored on the server.

[1402] Step 2:

[1403] The server collects weather data, road condition data, temperature, and humidity from environmental sensors installed in the vehicle. This environmental data is sent to the server in real time. The input is various environmental data sensed by the sensors, and the output is environmental data stored on the server.

[1404] Step 3:

[1405] The server reads the user's past driving history data from the database, which includes past driving routes, traffic conditions, accident information, etc. The input is the driving history data in the database, and the output is the driving history data stored on the server.

[1406] Step 4:

[1407] The server integrates the acquired location information, environmental data, and past driving history data. Data integration generates consistent information from these different data sources. The input is location information, environmental data, and driving history data, and the output is the integrated data.

[1408] Step 5:

[1409] The server analyzes the integrated data using a generative AI model, which takes into account many variables such as weather conditions, road conditions, and past driving results to calculate the optimal driving route and advice. The input is the integrated data, and the output is the optimal driving advice.

[1410] Step 6:

[1411] The server generates optimal driving advice and notifies the user. Notifications are given via a head-mounted display and a smartphone, and the advice is conveyed visually and audibly. The input is the optimal driving advice, and the output is notification information to the user.

[1412] 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.

[1413] This invention is an AI unmanned caddy system that helps amateur golf players improve their scores efficiently, and it also has the ability to recognize the user's emotions and adjust play advice accordingly, thereby providing optimal advice according to the user's psychological state and maximizing the effectiveness of their play.

[1414] System configuration

[1415] The system includes the following components:

[1416] 1. A device with a built-in GPS module that obtains the user's location information.

[1417] 2. A device with sensors that detect wind speed, direction, temperature, and humidity to collect environmental data.

[1418] 3. A server with a database that stores users' past play data.

[1419] 4. A server equipped with an artificial intelligence algorithm that integrates and analyzes collected location information, environmental data, and past play data.

[1420] 5. A server that generates optimal play advice based on the analysis results.

[1421] 6. A device with smart glasses and earphones that notifies the user of play advice.

[1422] 7. A terminal including an emotion engine that recognizes the user's emotions.

[1423] Program processing

[1424] 1. Collecting user location information and gameplay data

[1425] The device uses the built-in GPS module to obtain its current location, which is then immediately sent to the server.

[1426] The server identifies the user's current location and recognizes the corresponding golf hole, and records the information for further processing.

[1427] The server reads the user's past play data from the database and saves it.

[1428] 2. Real-time environmental data collection

[1429] The device collects environmental data using built-in sensors that detect wind speed, direction, temperature, and humidity, and transmits this data to a server.

[1430] 3. Data Analysis

[1431] The server combines collected location information, environmental data, and past play data and analyzes the data using artificial intelligence algorithms.

[1432] The server comprehensively evaluates factors such as the influence of the wind, past success rates, and the layout of the hole to calculate the optimal club selection and shot direction. It also takes into account the strength of the shot depending on the situation.

[1433] 4. Emotional Data Collection and Analysis

[1434] The device analyzes the user's facial expressions, voice, or biometric information to collect emotional data, which is then sent to a server.

[1435] The server analyzes the emotion data to understand the user's psychological state, for example, determining whether the user is tense or relaxed.

[1436] 5. Advice Generation and Adjustment

[1437] The server adjusts the generated play advice based on the emotion data, for example adding advice to relax if the user is nervous.

[1438] The optimal play advice is finally determined based on the analysis results.

[1439] 6. Notice to Users

[1440] The device then displays the generated play advice on the smart glasses display, providing visual information such as "Use a 3 iron, aim slightly to the left, and hit with a relaxed stance."

[1441] The device will notify the user through the earphones with a voice message saying, "The wind speed is 10 km / h and blowing north. Aim slightly to the left with a 3-iron. Relax and remember to take deep breaths."

[1442] Specific examples

[1443] The following example illustrates the process when the user reaches the fifth hole and wants to know the best club and shot direction for the next shot.

[1444] 1. The device acquires the user's current location using its built-in GPS function and sends it to the server.

[1445] 2. The server recognizes that the user is on the fifth hole and reads the past play data for the fifth hole from the database.

[1446] 3. The device uses its built-in sensor to detect that the current wind speed is 10 km / h and blowing north, and sends this information to the server.

[1447] 4. The server combines location information, environmental data, and past play data and analyzes the data using artificial intelligence algorithms.

[1448] 5. Using a facial recognition camera and voice analysis, the device detects that the user is slightly nervous and sends the emotional data to the server.

[1449] 6. The server recognizes that the user is tense and adjusts the generated playing advice to include instructions for relaxing.

[1450] 7. The device will display on the smart glasses' display, "Use a 3 iron, aim slightly to the left, and hit while relaxing," and will provide a voice notification through the earphones saying, "Wind speed 10 km / h, northbound. Use a 3 iron and aim slightly to the left. Relax and remember to take deep breaths."

[1451] In this way, the user can receive optimal golf management advice tailored to their psychological state, making it possible to compensate for lack of experience and efficiently improve their score.

[1452] The processing flow will be explained below.

[1453] Step 1:

[1454] The device uses a built-in GPS module to obtain the user's current location, which is then immediately sent to the server.

[1455] Step 2:

[1456] The server identifies the user's current location based on the received location information, identifies the corresponding golf hole, and records the information for further processing.

[1457] Step 3:

[1458] The server reads the user's past play data stored in a database, including the clubs previously used, shot results, and scores.

[1459] Step 4:

[1460] The device uses built-in sensors to collect environmental data such as wind speed, wind direction, temperature, and humidity, which is then sent to a server.

[1461] Step 5:

[1462] The server integrates the collected location information, past play data, and current environmental data, and performs analysis using artificial intelligence algorithms based on this data.

[1463] Step 6:

[1464] The device uses a built-in camera and voice recognition function to analyze the user's facial expressions and voice to obtain emotional data, which is then sent to a server.

[1465] Step 7:

[1466] The server analyzes the emotion data to understand the user's psychological state, for example, determining whether the user is tense or relaxed.

[1467] Step 8:

[1468] The server adjusts the generated play advice based on the emotion data, for example adding advice to relax if the user is nervous.

[1469] Step 9:

[1470] The server comprehensively evaluates factors such as the influence of the wind, the layout of the hole, and past success rates to calculate the optimal club selection and shot direction. It also adjusts the force of the shot based on the user's emotions.

[1471] Step 10:

[1472] The server generates specific play advice based on the analysis results, such as "Use a 3-iron, aim slightly to the left, and hit the ball in a relaxed manner."

[1473] Step 11:

[1474] The device receives play advice from the server and displays it on the smart glasses display, providing visual information such as "Use a 3 iron, aim slightly to the left, and hit the ball in a relaxed manner."

[1475] Step 12:

[1476] The device will notify the user through the earphones with a voice message saying, "The wind speed is 10 km / h and blowing north. Aim slightly to the left with a 3-iron. Relax and remember to take deep breaths."

[1477] This series of processes allows users to receive optimal golf management advice in real time according to their psychological state, which can help compensate for lack of experience and improve scores efficiently.

[1478] Example 2

[1479] 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."

[1480] Conventional golf management systems provide advice based only on the user's location, environmental data, and past play data, but do not consider the user's psychological state. This has resulted in the problem that optimal advice is not provided depending on the user's psychological state, such as when the user is tense or relaxed. There is a need to provide playing advice that reflects the user's emotions and psychological state, thereby maximizing the effectiveness of the user's play.

[1481] 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.

[1482] In this invention, the server includes means for acquiring user position information, means for collecting environmental data, means for reading the user's past play data, means for integrating and analyzing the position information, environmental data, and past play data, means for generating optimal play advice based on the analysis results, means for notifying the user of the play advice, means for collecting user emotion data, and means for adjusting the play advice based on the emotion data, thereby making it possible to provide optimal golf management advice tailored to the user's psychological state.

[1483] "User location information" is data that indicates the specific location where the user is currently located.

[1484] "Environmental data" refers to data that indicates the surrounding physical conditions that affect golf play, such as wind speed, wind direction, temperature, and humidity.

[1485] "User's past play data" refers to data that indicates records and statistical information of the golf plays that the user has performed up to now.

[1486] The "built-in GPS module" is a device that uses satellite signals to measure the user's current location with high accuracy.

[1487] A "wind speed sensor" is a device for measuring wind speed.

[1488] A "wind direction sensor" is a device for measuring the direction in which the wind is blowing.

[1489] A "temperature sensor" is a device for measuring the temperature of air.

[1490] A "humidity sensor" is a device for measuring the proportion of water vapor in the air.

[1491] "Means for integrating and analyzing" refers to the process and equipment for consolidating collected data into a single piece of information and analyzing it.

[1492] The "means for generating optimal play advice" refers to a process and device for generating the most effective play advice for the user based on the results of data analysis.

[1493] The "means for notifying the user of the playing advice" refers to a device or method for communicating the generated playing advice to the user.

[1494] "User emotion data" is data that indicates the user's current psychological state, and includes facial expressions, voice analysis results, biometric information, and the like.

[1495] The "means for adjusting play advice" refers to a process and device for appropriately changing the content of the generated play advice based on emotion data.

[1496] The present invention is a system for enabling amateur golf players to efficiently improve their scores, and provides optimal playing advice in accordance with the user's psychological state. Specific embodiments of the system will be described below.

[1497] This system is configured using the following hardware and software:

[1498] 1. Devices with a built-in GPS module: Used to obtain location information.

[1499] 2. Devices with sensors that detect wind speed, direction, temperature, and humidity: Used to collect environmental data.

[1500] 3. Server with database: Used to save and load users' past play data.

[1501] 4. Server equipped with artificial intelligence algorithms: Used to integrate and analyze collected location information, environmental data, and past play data.

[1502] 5. Server that generates optimal play advice: Generates play advice based on the analysis results.

[1503] 6. Device with smart glasses and earphones: Used to notify the user of play advice.

[1504] 7. Devices with emotion engines: Used to recognize user emotions.

[1505] The device uses its built-in GPS module to obtain its current location and sends that information to the server. The server then analyzes the location information, identifies the user's current location, and loads past play data from a database. The device also uses its built-in sensors to collect environmental data such as wind speed, wind direction, temperature, and humidity, which it then sends to the server.

[1506] The server uses an AI algorithm to analyze the collected location information, environmental data, and past play data, and then evaluates the effects of wind, hole layout, past success rates, and other factors to calculate the optimal club selection and shot direction.

[1507] Furthermore, the device uses sensors such as a camera and microphone to collect the user's facial expressions and voice, and sends the emotional data to the server. The server analyzes the emotional data to understand the user's psychological state and adjusts the generated advice accordingly. For example, if the user is nervous, it will add advice to help them relax.

[1508] Finally, the device displays the adjusted playing advice on the smart glasses display and provides audio feedback through the earphones, such as "Use a 3 iron, aim slightly to the left, and hit with a relaxed stance."

[1509] Specific examples

[1510] The following example illustrates the process when the user reaches the fifth hole and wants to know the best club and shot direction for the next shot.

[1511] 1. The device uses its built-in GPS to obtain the user's current location and sends it to the server.

[1512] 2. The server recognizes that the user is on the 5th hole and reads the past play data for the 5th hole from the database.

[1513] 3. The device uses its built-in sensor to detect that the current wind speed is 10 km / h and blowing north, and sends this data to the server.

[1514] 4. The server combines location information, environmental data, and past play data and analyzes the data using artificial intelligence algorithms.

[1515] 5. Using a facial recognition camera and voice analysis, the device detects when the user is feeling slightly nervous and sends that emotional data to the server.

[1516] 6. The server recognizes that the user is nervous and adjusts the generated play advice to include instructions for relaxing.

[1517] 7. The device will display on the smart glasses' display, "Use a 3 iron, aim slightly to the left, and hit while relaxed," and will provide a voice notification through the earphones: "Wind speed 10 km / h, northbound. Use a 3 iron and aim slightly to the left. Relax and remember to take deep breaths."

[1518] Prompt Sentence Examples

[1519] 1. "What is the current wind speed and direction on the hole?"

[1520] 2. "What advice should you give to help users relax?"

[1521] In this way, the user can receive optimal golf management advice tailored to their psychological state, making it possible to compensate for lack of experience and efficiently improve their score.

[1522] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1523] Step 1: Get and send the user's current location

[1524] Input: Location information from the GPS module

[1525] The device will activate its built-in GPS module to obtain the user's current location, which includes latitude and longitude.

[1526] The acquired location information is sent to the server in real time.

[1527] Output: Location information sent to the server

[1528] Step 2: Analyze and set the user's current location

[1529] Input: Location information sent from the device

[1530] The server analyzes the received location information to determine the user's current location, which may involve the use of a geographic information system (GIS).

[1531] The server recognizes the identified golf hole number and records it in an internal database.

[1532] Output: Current golf hole number and its location

[1533] Step 3: Obtaining past play data

[1534] Input: Current golf hole number

[1535] The server reads the user's past play data from its internal database and prepares it for analysis, including the success rate of past shots and the clubs used.

[1536] Output: Past play data

[1537] Step 4: Collect environmental data

[1538] Input: Ambient environmental conditions

[1539] The device activates its built-in sensors to measure wind speed, direction, temperature, and humidity, and the data collected by the sensors is collected in real time.

[1540] The collected environmental data is transmitted from the terminal to a server.

[1541] Output: Environment data sent to the server

[1542] Step 5: Data synthesis and analysis

[1543] Input: location information, environmental data, past play data

[1544] The server combines the acquired location information, environmental data, and past play data and analyzes it using artificial intelligence algorithms, including statistical and machine learning models.

[1545] As a result of the analysis, factors such as the influence of wind, hole layout, and past success rate are evaluated to calculate the optimal club selection and shot direction.

[1546] Output: Optimal club selection and shot direction

[1547] Step 6: Collect and send emotion data

[1548] Input: User's facial expression, voice, biometric information

[1549] The device uses sensors such as a camera and microphone to collect data on the user's emotions, and uses facial expression recognition and voice analysis technology to estimate the user's psychological state.

[1550] The collected emotion data is sent to a server in real time.

[1551] Output: Emotion data sent to the server

[1552] Step 7: Analyze emotional data and adjust play advice

[1553] Input: Emotional data, optimal club selection and shot direction

[1554] The server analyzes the received emotional data to understand the user's psychological state, sometimes using machine learning models or rule-based systems.

[1555] If the user is perceived as tense, the advice is adjusted to include instructions for relaxation.

[1556] Output: Adjusted play advice

[1557] Step 8: Advise users

[1558] Input: Adjusted play advice

[1559] The terminal obtains the finalized play advice.

[1560] The device will then display advice on the smart glasses display, such as "Use a 3 iron, aim slightly to the left, and hit with a relaxed stance."

[1561] The device will then notify the user through the earphones with a voice message saying, "Wind speed 10km / h, northbound. Aim slightly to the left with a 3-iron. Relax and remember to take deep breaths."

[1562] Output: Play advice given to the user

[1563] (Application example 2)

[1564] 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."

[1565] Conventional work management systems have had problems in that they were unable to adequately improve the efficiency of workers on production lines or manage their psychological stress. Furthermore, they lacked the functionality to provide advice that took into account environmental data and the emotional state of workers, which led to a risk of reduced work efficiency and the accumulation of worker stress. The present invention aims to solve these problems and provide a system that simultaneously optimizes workers' work efficiency and psychological health.

[1566] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1567] In this invention, the server includes means for acquiring user location information, means for collecting environmental data, means for reading the user's past work data, means for collecting the user's emotion data, means for integrating and analyzing the location information, environmental data, the user's past work data, and the emotion data, means for adjusting advice generated based on the emotion data, means for generating optimal work advice based on the analysis results, and means for notifying the user of the work advice, thereby enabling optimal work advice according to the work environment and stress management for workers.

[1568] "Location information" is data that indicates the user's current location.

[1569] "Environmental data" refers to data that indicates the ambient conditions in which the user is working, such as temperature, humidity, and noise level.

[1570] "Past work data" refers to records and data relating to work that the user has performed in the past.

[1571] "Emotion data" is data that expresses the user's psychological state and emotions.

[1572] "Analysis" is the process of integrating collected location information, environmental data, past work data, and emotional data, and making evaluations and judgments based on that information.

[1573] "Adjusting the advice" means optimizing the generated advice to suit the user's condition and environment.

[1574] "Work advice" is specific instructions and suggestions for the user to work efficiently and healthily.

[1575] "Notification" refers to transmitting the generated work advice to the user.

[1576] This invention relates to an artificial intelligence system that optimizes the work efficiency and psychological stress of factory workers. The system integrates and analyzes the user's location information, environmental data, past work data, and emotional data, and generates and notifies optimal work advice.

[1577] System configuration

[1578] The system consists of the following main components:

[1579] 1. Location information acquisition means

[1580] The built-in GPS module is used to obtain the user's location, allowing the system to accurately determine which working area the user is in.

[1581] 2. Environmental data collection methods

[1582] Environmental data is collected using sensors that detect wind speed, wind direction, temperature, humidity, noise level, etc. This data is used to evaluate the impact of the work environment on work efficiency and psychological stress.

[1583] 3. How to load past work data

[1584] The user's past work data is read from the database, including the user's past work logs and performance data.

[1585] 4. Emotional Data Collection Methods

[1586] Using facial recognition cameras and voice analysis, the user's psychological state and emotions are analyzed and emotional data is collected.

[1587] 5. Data Analysis Methods

[1588] The server integrates the collected location information, environmental data, past activity data, and emotional data, and analyzes the data using artificial intelligence algorithms, taking into account the effectiveness of the activity and the user's psychological state.

[1589] 6. Advice Generation and Adjustment Methods

[1590] The server generates optimal work advice based on the analysis results and adjusts the content based on emotional data. For example, if stress increases while working, the server will provide advice including ways to relax.

[1591] 7. User Notification Methods

[1592] The generated work advice is notified to the user using smart glasses or a head-mounted display, providing detailed advice in real time.

[1593] Program processing

[1594] For example, when a worker is joining parts on a conveyor, the server collects real-time environmental data and past work data, and analyzes this data. Emotion recognition data is also analyzed, so if the worker feels tired, advice is generated to encourage them to take a short break.

[1595] Hardware and software used

[1596] Built-in GPS module: location information acquisition

[1597] Environmental sensors: Collect data on wind speed, wind direction, temperature, humidity, and noise levels

[1598] Facial recognition camera and voice analysis software: Emotion data collection

[1599] Database server: Saving and loading historical data

[1600] AI analysis server: Analysis of integrated data

[1601] Smart Glasses and Head-Mounted Displays: User Advice Notification

[1602] Prompt Sentence Examples

[1603] "Enter the following data into the AI ​​model: environmental data (temperature 28°C, humidity 60%, noise level 70dB), location information (joining section), past data (points to note when joining), and emotional data (mild fatigue). Generate optimal work procedures and advice on stress management."

[1604] In this way, the system of the present invention allows workers to receive work advice suited to the environment, while also managing psychological stress and enabling them to work efficiently.

[1605] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1606] Step 1:

[1607] The device uses the built-in GPS module to obtain the user's current location, which is used to determine which working area the user is in. The obtained location information is then sent to the server and stored.

[1608] Step 2:

[1609] The device uses built-in sensors to collect environmental data such as temperature, humidity, and noise levels. This environmental data is used to evaluate the impact of the work environment on work efficiency and psychological stress. The collected environmental data is then sent to a server and stored.

[1610] Step 3:

[1611] The server reads the user's past work data from the database. This past data includes logs of the user's past work and performance data. The read data is used for analysis.

[1612] Step 4:

[1613] The device uses facial recognition cameras and voice analysis software to collect data on the user's psychological state and emotions. This emotional data is used to evaluate the user's current psychological state and is sent to a server.

[1614] Step 5:

[1615] The server integrates the collected location information, environmental data, past work data, and emotional data, and analyzes them using artificial intelligence algorithms. This analysis process evaluates the worker's work efficiency and psychological stress level. Based on the input data, optimal work procedures and advice are generated.

[1616] Step 6:

[1617] The server generates optimal work advice based on the analysis results. During this generation process, the advice is adjusted based on the emotional data, for example, if the user is tired, the advice may be adjusted to encourage them to take a break.

[1618] Step 7:

[1619] The generated optimal work advice is sent from the server to the device, which then notifies the user using smart glasses or a head-mounted display. Specific advice content is provided as visual information or audio notifications.

[1620] This allows users to receive real-time, optimal work advice suited to their environment, enabling them to work efficiently. Furthermore, by managing psychological stress, work efficiency is improved and worker health is managed.

[1621] 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.

[1622] 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.

[1623] 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.

[1624] 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.

[1625] 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.

[1626] 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.

[1627] 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).

[1628] 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.

[1629] 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."

[1630] 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.

[1631] 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).

[1632] 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.

[1633] 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.

[1634] 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.

[1635] 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.

[1636] 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.

[1637] 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.

[1638] 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.

[1639] 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.

[1640] 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.

[1641] 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.

[1642] The following is further disclosed regarding the above embodiment.

[1643] (Claim 1)

[1644] A means for acquiring user location information;

[1645] a means for collecting environmental data;

[1646] A means for reading the user's past play data;

[1647] means for integrating and analyzing the position information, environmental data, and past play data;

[1648] A means for generating optimal play advice based on the analysis results;

[1649] means for notifying a user of the play advice;

[1650] A system including:

[1651] (Claim 2)

[1652] 2. The system of claim 1, wherein the means for obtaining location information uses an internal GPS module.

[1653] (Claim 3)

[1654] 2. The system of claim 1, wherein the means for collecting environmental data includes sensors for detecting wind speed, wind direction, temperature, and humidity.

[1655] "Example 1"

[1656] (Claim 1)

[1657] A means for acquiring user location information;

[1658] a means for collecting environmental data;

[1659] A means for reading the user's past play data;

[1660] means for integrating and analyzing the position information, environmental data, and past play data;

[1661] A means for generating optimal play advice based on the analysis results;

[1662] means for notifying a user of the play advice;

[1663] means for providing visual and audio advice to the user;

[1664] A system including:

[1665] (Claim 2)

[1666] 2. The system according to claim 1, wherein the means for acquiring the location information uses an internal GPS module, and further comprising means for transmitting the acquired location information to a server.

[1667] (Claim 3)

[1668] 2. The system according to claim 1, wherein the means for collecting environmental data includes sensors for detecting wind speed, wind direction, temperature, and humidity, and the system further includes means for transmitting the obtained environmental data to a server.

[1669] "Application Example 1"

[1670] (Claim 1)

[1671] A means for acquiring user location information;

[1672] a means for collecting environmental data;

[1673] A means for reading past work data of a user;

[1674] a means for integrating and analyzing the location information, environmental data, and past work data;

[1675] A means for generating optimal operation advice based on the analysis results;

[1676] means for notifying a user of the operation advice;

[1677] A system including:

[1678] (Claim 2)

[1679] 10. The system of claim 1, wherein the means for obtaining location information uses an internal location information obtaining device.

[1680] (Claim 3)

[1681] 2. The system of claim 1, wherein the means for collecting environmental data includes sensors for detecting weather data, road condition data, temperature, and humidity.

[1682] "Example 2: Combining Emotion Engines"

[1683] (Claim 1)

[1684] A means for acquiring user location information;

[1685] a means for collecting environmental data;

[1686] A means for reading the user's past play data;

[1687] means for integrating and analyzing the position information, environmental data, and past play data;

[1688] A means for generating optimal play advice based on the analysis results;

[1689] means for notifying a user of the play advice;

[1690] means for collecting user emotion data;

[1691] means for adjusting play advice based on the emotion data;

[1692] A system including:

[1693] (Claim 2)

[1694] 2. The system of claim 1, wherein the means for obtaining location information uses an internal GPS module.

[1695] (Claim 3)

[1696] 2. The system of claim 1, wherein the means for collecting environmental data includes sensors for detecting wind speed, wind direction, temperature, and humidity.

[1697] "Application example 2 when combining emotion engines"

[1698] (Claim 1)

[1699] A means for acquiring user location information;

[1700] a means for collecting environmental data;

[1701] A means for reading past work data of a user;

[1702] a means for integrating and analyzing the location information, environmental data, and past work data;

[1703] means for collecting user emotion data;

[1704] means for adjusting the generated advice based on the emotion data;

[1705] A means for generating optimal work advice based on the analysis results;

[1706] means for notifying a user of the work advice;

[1707] A system including:

[1708] (Claim 2)

[1709] 2. The system of claim 1, wherein the means for obtaining location information uses an internal GPS module.

[1710] (Claim 3)

[1711] 2. The system of claim 1, wherein the means for collecting environmental data includes sensors for detecting temperature, humidity, and noise level. [Explanation of symbols]

[1712] 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 for collecting environmental data; A means for reading the user's past play data; means for integrating and analyzing the position information, environmental data, and past play data; A means for generating optimal play advice based on the analysis results; means for notifying a user of the play advice; A system including:

2. 2. The system of claim 1, wherein the means for obtaining location information uses an internal GPS module.

3. 2. The system of claim 1, wherein the means for collecting environmental data includes sensors for detecting wind speed, wind direction, temperature, and humidity.

Images