System

Abstract

A system is provided.SOLUTION: A system, comprising: sensor means for measuring a viewing range of a user in real time; communication means for transmitting the measured viewing range to a server; AI algorithm means on the server for calculating vision correction information based on the transmitted viewing range information; and lens control means for automatically adjusting a lens based on the received vision correction information.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] In modern society, many people use multiple pairs of glasses to accommodate different viewing distances. This situation arises because different glasses are needed for multiple purposes, such as close-up viewing, distance viewing, and use at different distances for PCs and smartphones. Furthermore, prolonged close-up work strains the ciliary body's accommodation function for extended periods, increasing eye fatigue. Users with such vision problems require a versatile vision correction method that can accommodate a variety of viewing distances. Conventional technology has not fully resolved these issues, and new technical solutions are needed to eliminate user inconvenience. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides a system including a sensor means for measuring a user's visual distance in real time, a communication means for transmitting the measured visual distance data to a server, an AI algorithm means on the server for calculating vision correction data based on the transmitted visual distance data, a data transmission means on the server for transmitting the calculated vision correction data to a user terminal, and a lens control means for automatically adjusting lenses based on the received vision correction data. This system eliminates the need for users to carry multiple pairs of glasses and reduces the burden of vision adjustment. By measuring the visual distance in real time and performing optimal vision correction using an AI algorithm, it is possible to provide a comfortable field of view at different visual distances. As a result, it is possible to reduce eye fatigue caused by long periods of close-up work, improving the user's quality of life.

[0006] "Sensor means" refers to a device or equipment for measuring the user's viewing distance in real time.

[0007] "Communication means" refers to a device or equipment for transmitting measured visual distance data to a server.

[0008] "AI algorithm means on the server" is a function that executes an artificial intelligence algorithm on the server to calculate vision correction data based on the transmitted viewing distance data.

[0009] The "data transmission means" is a device or equipment for transmitting calculated vision correction data to a user terminal.

[0010] The "lens control means" is a device or equipment that has the function of automatically adjusting the lens based on the received vision correction data.

[0011] A "user terminal" is a device or equipment for collecting and transmitting visual distance data to a server, or a device or equipment for adjusting lenses based on received vision correction data.

[0012] "Viewing distance data" is data that indicates the distance to an object that the user is looking at.

[0013] The "vision correction data" is data indicating the optimum diopter correction value calculated based on the viewing distance data.

[0014] A "lens" is an optical component for correcting vision and has an adjustable focal length.

[0015] "Real-time" means that the processing occurs immediately, without delay. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

[0024] [First embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0037] This invention is an AI eyeglass system that automatically performs optimal vision correction according to the user's viewing distance. Specific embodiments for implementing this system will be described below.

[0038] overview

[0039] This system consists of a user terminal (eyeglasses device), a server, and a sensor device. Its purpose is to correct vision in real time based on the user's viewing distance when looking at different distances (close to home, PC, long distance, medium distance, etc.).

[0040] User terminal operation

[0041] The system starts operating when the user puts on the glasses. The user device has a built-in sensor for measuring visual distance, which detects the user's line of sight and focal length in real time. The detected visual distance data is sent to the server via the communication means in the user device.

[0042] Server Processing

[0043] The server receives the viewing distance data transmitted from the user terminal. The received data is analyzed by an AI algorithm on the server, and vision correction data is calculated. This calculation is performed to provide appropriate vision correction in real time according to the user's viewing distance. The calculated vision correction data is then transmitted back to the user terminal by the server's data transmission means.

[0044] Automatic lens adjustment

[0045] The user terminal receives the vision correction data sent from the server. Based on the received data, the lens control means built into the glasses operates and automatically adjusts the lenses to the appropriate focal length. This allows the user to comfortably see close-up and long-distance objects.

[0046] Specific examples

[0047] Example 1: When looking at your hands

[0048] User: When reading a newspaper, keep your eyes on the screen.

[0049] Terminal: The sensor detects that the viewing distance is close (approximately 30 cm) and sends that data to the server.

[0050] Server: Receives the visual distance data and calculates the appropriate near-distance vision correction data using an AI algorithm. Then, resends the data to the user device.

[0051] Device: Automatically adjusts the lens for close distances based on the received correction data.

[0052] Example 2: When looking into the distance

[0053] User: When looking at a distant scene, look into the distance.

[0054] Terminal: The sensor detects that the viewing distance is long (approximately 5m or more) and sends that data to the server.

[0055] Server: Receives the visual distance data and calculates the appropriate long-distance vision correction data using an AI algorithm. Then, resends the data to the user device.

[0056] Terminal: Automatically adjusts the lens for long distances based on the received correction data.

[0057] In this way, the system can automatically provide appropriate vision correction in real time according to the user's viewing distance, eliminating the need for multiple pairs of glasses and ensuring that the user always has a comfortable field of vision.

[0058] Instructions for use

[0059] 1. The user puts on the glasses.

[0060] 2. The sensor measures the viewing distance.

[0061] 3. The viewing distance data is sent to the server.

[0062] 4. The server calculates the vision correction data and sends it to the user's device.

[0063] 5. The user device adjusts the lens.

[0064] 6. Make sure the user looks comfortable.

[0065] By using this system, users can always receive optimal vision correction and reduce eye strain caused by long periods of close-up work.

[0066] The processing flow will be explained below.

[0067] Step 1:

[0068] The moment the user puts on the glasses, the sensor device activates and begins measuring the user's gaze direction and focal length in real time.

[0069] Step 2:

[0070] The device collects viewing distance data from sensors, which includes gaze direction and focal length, providing an accurate measurement of the distance to the object the user is looking at.

[0071] Step 3:

[0072] The device sends the collected visual distance data to the server using a communication method, and the data arrives immediately without delay.

[0073] Step 4:

[0074] The server receives the visual distance data sent from the user terminal. This data is information indicating the distance at which the line of sight is focused.

[0075] Step 5:

[0076] The server then analyzes the received visual distance data using an AI algorithm, which takes into account past data and usage patterns to calculate optimal vision correction data.

[0077] Step 6:

[0078] The server transmits the calculated vision correction data to the user terminal using the data transmission means, which indicates how the lenses should be adjusted.

[0079] Step 7:

[0080] The device receives vision correction data sent from the server, and based on this data, the lens is automatically adjusted to the appropriate focal length instantly.

[0081] Step 8:

[0082] Users can comfortably view objects close up and at a distance, and because vision correction occurs in real time, users can always maintain optimal vision for different viewing distances.

[0083] Step 9:

[0084] When the user changes their line of sight again, for example, moving their gaze away from the object in front of them, the entire process returns to step 1 and is carried out automatically. This allows the user to maintain a comfortable field of vision at all times without having to adjust their glasses themselves.

[0085] Example 1

[0086] 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."

[0087] Conventional eyeglass systems have the problem of being inconvenient, as users must wear different glasses for each different viewing distance, such as for something close to them, a PC, long-distance viewing, or medium-distance viewing.In addition, there is also the problem of eyestrain caused by prolonged close-up work, as vision correction is not performed appropriately according to the viewing distance.

[0088] 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.

[0089] In this invention, the server includes a sensor for measuring the user's visual distance in real time, a communication unit for transmitting the measured visual distance data to the server, an AI algorithm for calculating vision correction data based on the transmitted visual distance data, a data transmission unit on the server for transmitting the calculated vision correction data to the user terminal, a lens control unit for automatically adjusting the lenses based on the received vision correction data, a system initialization unit for managing the initialization process, a detection unit for detecting the line of sight and focal length in real time, and an encryption unit for securely transmitting the vision correction data to the server. This allows the user to automatically perform vision correction for different visual distances in real time, eliminating the need for multiple glasses. Furthermore, appropriate vision correction can reduce eye fatigue.

[0090] "Sensor means" is a device for measuring the user's viewing distance in real time.

[0091] "Communication means" refers to a method or device for transmitting measured viewing distance data to a server.

[0092] The "AI algorithm means on the server" is an artificial intelligence algorithm executed on the server to calculate vision correction data based on the transmitted viewing distance data.

[0093] The "server data transmission means" refers to a device or method for transmitting calculated vision correction data to a user terminal.

[0094] The "lens control means" is a mechanism or device for automatically adjusting the lenses based on the received vision correction data.

[0095] The "system initialization means" is a mechanism or device that performs initial settings to start the operation of the system.

[0096] "Detection means" refers to a device or method for detecting the line of sight and focal length in real time.

[0097] The "encryption means" is a data encryption technique for securely transmitting vision correction data to the server.

[0098] MODE FOR CARRYING OUT THE INVENTION

[0099] The present invention is an AI eyeglass system that automatically performs optimal vision correction according to the user's viewing distance. Specific embodiments for carrying out the present invention will be described below.

[0100] User terminal operation

[0101] The system begins operation when the user puts on the glasses. The user device is equipped with a built-in sensor for measuring visual distance, which detects the user's line of sight and focal length in real time. Specifically, it uses ToF (Time-of-Flight) technology to obtain the focal length of the line of sight in milliseconds. The detected visual distance data is sent to a server via a built-in communication method (e.g., Bluetooth or Wi-Fi). This communication is kept secure by encrypting the data.

[0102] Server Processing

[0103] The server receives the visual distance data sent from the user device. The received data is analyzed by an AI algorithm (for example, a deep learning model using TensorFlow or PyTorch) running on the server. The AI ​​algorithm uses a pre-trained vision correction model to calculate the optimal lens focal length in real time. The calculated vision correction data is then retransmitted to the user device via the server's data transmission means. This transmission is also encrypted and carried out via secure communication.

[0104] Automatic lens adjustment

[0105] The user terminal receives the vision correction data sent from the server. Based on the received data, the built-in lens control means (e.g., an electrically adjustable liquid crystal lens) operates and automatically adjusts the lens to the appropriate focal length. This allows the user to comfortably view close-up and distant objects.

[0106] Specific examples

[0107] Example 1: When looking at your hands

[0108] When a user reads a newspaper, they look directly at the screen.

[0109] The device's sensor detects that the viewing distance is 30 cm.

[0110] The sensor measures the focal length of the gaze and instantly stores the data in the device's memory.

[0111] The terminal transmits the data to the server.

[0112] The data is sent to a server via Bluetooth.

[0113] The server receives the visual distance data and uses an AI algorithm to calculate vision correction data for close distances.

[0114] The AI ​​model on the server calculates the optimal lens settings for viewing 30 cm ahead.

[0115] The server retransmits the correction data to the user terminal.

[0116] The correction data is encrypted and sent to the device over a secure connection.

[0117] The device automatically adjusts the lens for close distances based on the received correction data.

[0118] A lens control means adjusts the voltage to cause the lens to deform to a specified focal length.

[0119] Example 2: When looking into the distance

[0120] When a user views a distant scene, the user directs his or her gaze into the distance.

[0121] The device's sensor detects that the viewing distance is 5m or more.

[0122] The sensor measures the focal length of the gaze and instantly stores the data in the device's memory.

[0123] The terminal transmits the data to the server.

[0124] The data is sent to a server via Wi-Fi.

[0125] The server receives the viewing distance data and uses an AI algorithm to calculate vision correction data for long distances.

[0126] The AI ​​model on the server calculates the optimal lens settings for seeing more than 5m ahead.

[0127] The server retransmits the correction data to the user terminal.

[0128] The correction data is encrypted and sent to the device over a secure connection.

[0129] The device automatically adjusts the lens for long distances based on the received correction data.

[0130] A lens control means adjusts the voltage to cause the lens to deform to a specified focal length.

[0131] Example prompts for generative AI models

[0132] "Calculate the vision correction required for a user to read a newspaper 30 cm away."

[0133] "Calculate the visual acuity correction required when the user views a scene 5 meters away."

[0134] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0135] System program processing flow

[0136] Step 1: Initialize the system

[0137] Specific behavior:

[0138] The user puts on the glasses.

[0139] The terminal is powered on and the system initialization means starts operating. It checks whether the sensors are working properly and the communication module establishes a connection with the server. This initialization includes the initial setting data and calibration process for the system to operate.

[0140] Input: Eyeglasses wearing information

[0141] Output: System initialization complete signal

[0142] Step 2: Measure the viewing distance

[0143] Specific behavior:

[0144] The sensor means detects the user's gaze direction and focal length in real time.

[0145] The device uses ToF technology to capture the focal length of the line of sight, and the sensor collects data every millisecond and stores it in the device's memory.

[0146] Input: User gaze data

[0147] Output: View distance data

[0148] Step 3: Sending viewing distance data

[0149] Specific behavior:

[0150] The terminal transmits the acquired viewing distance data to the server using a communication means (for example, Bluetooth or Wi-Fi).

[0151] The device encrypts the data before sending it to ensure security. Specifically, the viewing distance data is sent using a specific protocol (e.g., HTTP / HTTPS).

[0152] Input: View distance data

[0153] Output: View distance data sent to the server

[0154] Step 4: Calculate the vision correction data

[0155] Specific behavior:

[0156] The server analyzes the received visual distance data using an AI algorithm.

[0157] Based on the received visual distance data, the server calculates the optimal vision correction data using a pre-trained vision correction model (using, for example, TensorFlow or PyTorch).

[0158] Input: Received sight distance data

[0159] Output: Vision correction data

[0160] Step 5: Submit vision correction data

[0161] Specific behavior:

[0162] The server retransmits the calculated vision correction data to the user terminal.

[0163] The server encrypts the data and sends it to the user's device over a secure connection, using a protocol (e.g. HTTP / HTTPS).

[0164] Input: Vision correction data

[0165] Output: Vision correction data sent to the device

[0166] Step 6: Automatic lens adjustment

[0167] Specific behavior:

[0168] The terminal automatically adjusts the lenses based on the received vision correction data.

[0169] The terminal operates a built-in lens control means (for example, an electrically adjustable liquid crystal lens), which adjusts the voltage to deform the lens to the specified focal length.

[0170] Input: Received vision correction data

[0171] Output: Adjusted lens focal length

[0172] Exemplary Processing Steps

[0173] Example 1: Processing flow when looking at your hands

[0174] When a user reads a newspaper, they tend to look at the screen.

[0175] The device's sensor detects a viewing distance of 30 cm.

[0176] The terminal transmits the data to the server.

[0177] The server analyzes the visual distance data using an AI algorithm and calculates vision correction data.

[0178] The server transmits the correction data to the terminal.

[0179] The device automatically adjusts the lens for close distances based on the received correction data.

[0180] Example 2: Processing flow when looking into the distance

[0181] When a user views a distant scene, the user directs his or her gaze into the distance.

[0182] The device's sensor detects a viewing distance of 5m or more.

[0183] The terminal transmits the data to the server.

[0184] The server analyzes the visual distance data using an AI algorithm and calculates vision correction data.

[0185] The server transmits the correction data to the terminal.

[0186] The device automatically adjusts the lens for long distances based on the received correction data.

[0187] (Application example 1)

[0188] 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."

[0189] Robot operators working in factories often have to work at multiple different viewing distances, making it difficult to maintain proper vision. In this regard, inadequate vision correction can make precision work difficult and potentially compromise efficiency and safety. In particular, in jobs that require frequent shifts of gaze between precision components close at hand and distant equipment, inadequate vision correction can lead to reduced work quality and eye fatigue.

[0190] 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.

[0191] In this invention, the server includes a sensor means for measuring the user's visual distance in real time, a communication means for transmitting the measured visual distance data to the server, an AI algorithm means on the server for calculating vision correction data based on the transmitted visual distance data, a data transmission means on the server for transmitting the calculated vision correction data to the user terminal, a lens control means for automatically adjusting the lens based on the received vision correction data, and a vision correction assist means for providing work assistance in a factory based on the user's visual distance measurement data. This enables robot operators working in a factory to receive optimal vision correction in real time according to their visual distance, improving the efficiency and quality of precision work and reducing eye fatigue.

[0192] "Sensor means" is a device for measuring the user's viewing distance in real time.

[0193] "Communication means" is a system for transmitting measured viewing distance data to a server.

[0194] The "AI algorithm means" is an algorithm that runs on the server and calculates vision correction data based on the transmitted viewing distance data.

[0195] The "data transmission means of the server" is a function of the server for transmitting calculated vision correction data to the user terminal.

[0196] The "lens control means" is a mechanism for automatically adjusting the lenses based on the received vision correction data.

[0197] The "vision correction assistance means" is a function for providing work assistance in a factory based on the user's visual distance measurement data.

[0198] This invention provides a system that enables operators working in a factory to receive optimal vision correction in real time according to their viewing distance. A specific embodiment of this system will be described in detail below.

[0199] System configuration

[0200] This system consists of a user terminal (smart glasses device), a server, and a sensor device.

[0201] User terminal operation

[0202] The system starts operation when the user puts on the smart glasses. The user device has a built-in sensor for measuring visual distance, which detects the user's line of sight and focal length in real time. The detected visual distance data is sent to the server via the communication means in the user device.

[0203] Server Processing

[0204] The server receives the viewing distance data transmitted from the user terminal. The received data is analyzed by an AI algorithm on the server, and vision correction data is calculated. This calculation is performed to provide appropriate vision correction in real time according to the user's viewing distance. The calculated vision correction data is then transmitted back to the user terminal by the server's data transmission means.

[0205] Automatic lens adjustment

[0206] The user terminal receives the vision correction data sent from the server. Based on the received data, the lens control means built into the glasses operates and automatically adjusts the lenses to the appropriate focal length. This allows the user to comfortably see close-up and long-distance objects.

[0207] Techniques and equipment used

[0208] Sensors (ToF sensors, etc.): Primarily used to measure line-of-sight distance.

[0209] Communication protocol: Data is sent and received using HTTP POST, etc.

[0210] AI Algorithm: A machine learning model for calculating vision correction data. For example, TensorFlow or PyTorch are used.

[0211] Smart glasses lens control system: Electronically controls lens focus adjustment.

[0212] Specific examples

[0213] As a concrete example, let's say a robot operator working in a smart factory uses the system in the following scenario:

[0214] Example 1: Task at hand

[0215] When an operator inspects a precision part in his or her hand, he or she focuses his or her gaze on the part.

[0216] The gaze sensor measures the visual distance of the hand and sends the data to the server.

[0217] The server-side AI quickly calculates vision correction data based on the viewing distance and sends it to the smart glasses.

[0218] Smart glasses automatically adjust vision, allowing operators to comfortably inspect precision parts at hand.

[0219] Example 2: Long-distance observation

[0220] When operators view distant equipment, they turn their gaze into the distance.

[0221] The gaze sensor measures the long-distance viewing distance and transmits the data to the server.

[0222] The server-side AI quickly calculates vision correction data based on long-distance viewing distance and sends it to the smart glasses.

[0223] Smart glasses automatically adjust vision, allowing operators to clearly see distant equipment.

[0224] Prompt Sentence Examples

[0225] The smart glasses are worn and the visual distance at hand is measured. The visual distance data is acquired by the sensor and sent to the server via an HTTP POST request. A machine learning model (TensorFlow) is used on the server side to calculate vision correction data. The calculation results are sent back to the smart glasses, which automatically adjust the visual acuity. As a result, the robot operator can comfortably inspect precision parts.

[0226] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0227] Step 1:

[0228] The user puts on the smart glasses and turns them on.

[0229] This action activates the smart glasses' built-in sensors, which measure the user's gaze direction and focal length in real time.

[0230] Input: User's gaze direction and focal length

[0231] Output: Real-time visual distance data

[0232] Step 2:

[0233] The communication module inside the smart glasses receives the visual distance data measured by the built-in sensor and sends it to the server.

[0234] This data is sent using an HTTP POST request.

[0235] Input: Real-time visual distance data

[0236] Output: View distance data sent to the server

[0237] Step 3:

[0238] The server receives the viewing distance data transmitted from the user terminal.

[0239] The server filters the received data to remove unwanted noise.

[0240] Input: View distance data sent to the server

[0241] Output: Noise-removed visual distance data

[0242] Step 4:

[0243] A server-side AI algorithm analyzes the filtered viewing distance data and calculates the optimal vision correction data.

[0244] This calculation uses a generative AI model (e.g., TensorFlow).

[0245] Input: filtered viewing distance data

[0246] Output: Vision correction data

[0247] Step 5:

[0248] The data transmitting means of the server transmits the calculated vision correction data to the smart glasses.

[0249] This process is also done using an HTTP POST request.

[0250] Input: Vision correction data

[0251] Output: Vision correction data sent to smart glasses

[0252] Step 6:

[0253] The lens control means of the smart glasses automatically adjusts the lenses based on the received vision correction data.

[0254] Specifically, the focal length of the lens is adjusted in real time to provide the user with the optimal field of view.

[0255] Input: Vision correction data sent to smart glasses

[0256] Output: Optimal vision with automatically adjusted lenses

[0257] Step 7:

[0258] The user checks the corrected vision and continues working as necessary.

[0259] This step provides feedback to confirm that the user has indeed achieved a comfortable field of view.

[0260] Input: Optimal vision with auto-adjusted lenses

[0261] Output: Improving user visual comfort and work efficiency

[0262] 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.

[0263] This invention is an AI glasses system that automatically performs optimal vision correction according to the user's viewing distance and also recognizes the user's emotions to provide an optimal field of view. Specific embodiments for implementing this system are described below.

[0264] overview

[0265] This system consists of a user terminal (eyeglasses device), a server, a sensor device, and an emotion engine. It aims to not only correct vision in real time based on the user's viewing distance when looking at something at different viewing distances, but also to suggest optimal vision correction according to the user's emotions.

[0266] User terminal operation

[0267] The system begins operation when the user puts on the glasses. The user device is equipped with a sensor that measures visual distance and an emotion engine that recognizes the user's emotions. The system detects the user's gaze direction and focal length, as well as facial expressions, voice, and heart rate, and collects visual distance and emotion data in real time.

[0268] Sending data

[0269] The user device sends the collected visual distance data and emotion data to the server using a communication method, and the data arrives immediately without delay.

[0270] Server Processing

[0271] The server receives the viewing distance data and emotion data transmitted from the user terminal, where the viewing distance data indicates the distance to an object the user is looking at, and the emotion data indicates the user's current emotional state.

[0272] Analysis by AI algorithm

[0273] The AI ​​algorithm on the server analyzes the received viewing distance data and emotional data and calculates vision correction data. The AI ​​algorithm not only performs appropriate vision correction based on the user's viewing distance, but also takes emotional data into account to suggest vision correction that the user finds most comfortable.

[0274] Sending correction data

[0275] The server sends the calculated vision correction data to the user terminal, which indicates how the lenses should be adjusted.

[0276] Automatic lens adjustment

[0277] The user terminal receives the vision correction data sent from the server, and the built-in lens control means of the glasses immediately operates to automatically adjust the lenses to the appropriate focal length, allowing the user to obtain a comfortable field of vision.

[0278] Specific examples

[0279] Example 1: When looking at your hands

[0280] User: I feel a little stressed while reading a book.

[0281] Terminal: Detects the viewing distance as close (approximately 30 cm) and senses the stress felt by the user from their facial expression.

[0282] Server: Receives visual distance data and "stress" emotion data, and uses an AI algorithm to calculate vision correction data for close distances and with an emphasis on stress reduction.

[0283] Terminal: Based on the received correction data, the lens is adjusted for close distances and vision correction is performed to reduce stress.

[0284] Example 2: When looking into the distance

[0285] User: I want to see the scenery in the distance, but I'm a little tired.

[0286] Terminal: Detects the viewing distance as long (approximately 5m or more) and senses "fatigue" from the user's facial expression and heart rate.

[0287] Server: Receives visual distance data and "fatigue" emotion data, and uses an AI algorithm to calculate vision correction data for long distances and to reduce fatigue.

[0288] Terminal: Based on the received correction data, the lenses are adjusted for long distances and vision correction is performed to reduce fatigue.

[0289] In this way, this system automatically performs appropriate vision correction in real time according to the user's viewing distance and can also optimize the correction taking into account the user's emotions, allowing the user to always maintain a comfortable field of vision and reduce eye and mental strain.

[0290] Instructions for use

[0291] 1. The user puts on the glasses.

[0292] 2. Sensors and emotion engines measure visual distance and emotion data.

[0293] 3. The viewing distance data and emotion data are sent to the server.

[0294] 4. The server calculates the vision correction data and sends it to the user's device.

[0295] 5. The user device adjusts the lens.

[0296] 6. Make sure the user looks comfortable.

[0297] By using this system, users can always receive optimal vision correction and maintain a comfortable field of vision that even takes their emotions into consideration.

[0298] The processing flow will be explained below.

[0299] Step 1:

[0300] The user puts on the glasses. This triggers the system to start up, and the sensor device and emotion engine begin to operate.

[0301] Step 2:

[0302] The device uses built-in sensors to measure gaze direction and focal length, allowing it to detect the distance of the object the user is looking at in real time.

[0303] Step 3:

[0304] The device recognizes the user's emotions using an emotion engine, which collects data from multiple sensors, including facial expressions, voice, and heart rate, to analyze the user's emotional state.

[0305] Step 4:

[0306] The device transmits the collected visual distance data and emotion data to the server using a communication method. These data are integrated into a single packet and are delivered to the server immediately.

[0307] Step 5:

[0308] The server receives the viewing distance data and emotion data sent from the user terminal. The received data indicates the gaze direction, focal length, and the user's emotional state.

[0309] Step 6:

[0310] The AI ​​algorithm on the server analyzes the received viewing distance data and emotional data, calculates appropriate vision correction data based on the user's viewing distance, and then adjusts the optimal vision correction value taking into account the emotional data.

[0311] Step 7:

[0312] The server transmits the calculated vision correction data to the user terminal using the data transmission means. The vision correction data is information indicating how the lens should be adjusted.

[0313] Step 8:

[0314] The terminal receives the vision correction data sent from the server. Based on the received data, the lens control means starts operation and automatically adjusts the lens to the appropriate focal length.

[0315] Step 9:

[0316] The system ensures that users can see objects close to them and at a distance for comfortable viewing. Vision correction is performed in real time, ensuring users always have optimal vision for different viewing distances. Furthermore, vision correction adjusts to the user's emotional state, reducing stress and fatigue.

[0317] Step 10:

[0318] If the user changes their gaze again, the change in gaze direction and emotional state is detected, and the whole process starts again from step 2. This allows the user to dynamically and continuously receive optimal vision correction.

[0319] Example 2

[0320] 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."

[0321] While conventional vision correction systems can correct a user's vision based on their viewing distance, they are unable to provide optimal vision correction by taking into account the user's emotional state. As a result, when a user is stressed or tired, optimal vision correction is not provided, resulting in an inability to achieve comfortable vision. Furthermore, conventional systems suffer from delays in the entire process from measuring viewing distance data to adjusting lenses, making it difficult to provide real-time vision correction.

[0322] 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.

[0323] In this invention, the server includes a sensor means for measuring the user's viewing distance in real time, an emotion recognition means for recognizing emotion data along with the viewing distance, a communication means for transmitting the measured viewing distance data and emotion data to the server, an AI algorithm means on the server for calculating vision correction data based on the transmitted viewing distance data and emotion data, a data transmission means on the server for transmitting the calculated vision correction data to the user terminal, and a lens control means for automatically adjusting the lens based on the received vision correction data. This enables real-time vision correction that simultaneously takes into account the user's viewing distance and emotional state.

[0324] "Sensor means" is a device for measuring the user's viewing distance in real time.

[0325] The "emotion recognition means" is a device for analyzing the user's facial expressions, voice, heart rate, etc. to obtain emotional data.

[0326] The "communication means" is a device for transmitting the measured viewing distance data and emotion data to the server.

[0327] The "AI algorithm means" is software for calculating vision correction data based on visual distance data and emotional data on a server.

[0328] The "data transmission means of the server" is a device for transmitting calculated vision correction data to the user terminal.

[0329] The "lens control means" is a device for automatically adjusting the lenses based on the received vision correction data.

[0330] A "user terminal" is a glasses-type device worn by a user.

[0331] This invention is an AI glasses system that automatically performs optimal vision correction according to the user's viewing distance and also recognizes the user's emotions to provide an optimal field of view. Next, specific embodiments for implementing this system will be described.

[0332] overview

[0333] This system consists of a user terminal (eyeglasses device), a server, a sensor device, and an emotion recognition engine. It aims to not only correct vision in real time based on the user's viewing distance when looking at something at different viewing distances, but also to suggest optimal vision correction according to the user's emotions.

[0334] User terminal operation

[0335] The system starts when the user puts on the glasses. The user device is equipped with a sensor that measures visual distance and an emotion recognition unit that recognizes the user's emotions. These sensors detect the user's gaze direction and focal length, as well as facial expressions, voice, and heart rate, and collect visual distance and emotion data in real time.

[0336] Sending data

[0337] The user device sends the collected visual distance data and emotion data to the server using a communication method such as Wi-Fi or Bluetooth. This data arrives at the server immediately and without delay.

[0338] Server Processing

[0339] The server receives the viewing distance data and emotion data transmitted from the user terminal, where the viewing distance data indicates the distance of an object the user is looking at, and the emotion data indicates the user's current emotional state.

[0340] Analysis by AI algorithm

[0341] The AI ​​algorithm installed on the server analyzes the received viewing distance data and emotional data and calculates vision correction data. This AI algorithm not only performs appropriate vision correction based on the user's viewing distance, but also takes emotional data into account to suggest vision correction that the user finds comfortable.

[0342] Sending correction data

[0343] The server sends the calculated vision correction data to the user terminal, which indicates how the lenses should be adjusted.

[0344] Automatic lens adjustment

[0345] The user terminal receives the vision correction data sent from the server, and the built-in lens control means of the glasses immediately operates to automatically adjust the lenses to the appropriate focal length, allowing the user to obtain a comfortable field of vision.

[0346] Specific examples

[0347] Example 1: When looking at your hands

[0348] User: I feel a little stressed while reading a book.

[0349] Terminal: Detects the viewing distance as close (approximately 30 cm) and senses the stress felt by the user from their facial expression.

[0350] Server: Receives visual distance data and "stress" emotion data, and uses an AI algorithm to calculate vision correction data for close distances and with an emphasis on stress reduction.

[0351] Terminal: Based on the received correction data, the lens is adjusted for close distances and vision correction is performed to reduce stress.

[0352] Example 2: When looking into the distance

[0353] User: I want to see the scenery in the distance, but I'm a little tired.

[0354] Terminal: Detects the viewing distance as long (approximately 5m or more) and senses "fatigue" from the user's facial expression and heart rate.

[0355] Server: Receives visual distance data and "fatigue" emotion data, and uses an AI algorithm to calculate vision correction data for long distances and to reduce fatigue.

[0356] Terminal: Based on the received correction data, the lenses are adjusted for long distances and vision correction is performed to reduce fatigue.

[0357] Prompt Sentence Examples

[0358] "Please suggest vision correction for users who experience stress at close range."

[0359] "Provide optimal vision correction for users who experience fatigue from looking at distant objects."

[0360] keyword

[0361] Generative AI Models

[0362] Prompt statement

[0363] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0364] Step 1:

[0365] The user puts on the glasses.

[0366] Input: User action (wearing glasses)

[0367] Output: The glasses' system activates.

[0368] How it works: When a user puts on the glasses, the sensor and emotion engine are automatically activated, which starts the process of visual distance measurement and emotion recognition.

[0369] Step 2:

[0370] The device collects viewing distance data and emotion data.

[0371] Input: User's gaze direction, facial expression, voice, heart rate

[0372] Output: Viewing distance data and emotion data are generated.

[0373] Specific operation: The device's built-in visual distance sensor measures the user's gaze direction and focal length, and the emotion recognition means analyzes the user's facial expressions, voice, heart rate, etc. to obtain emotional data. This data is updated in real time.

[0374] Step 3:

[0375] The device transmits the collected viewing distance data and emotion data to the server.

[0376] Input: Viewing distance data, emotion data

[0377] Output: Data is sent to the server.

[0378] Specific operation: The device transmits the acquired visual distance data and emotion data to the server via Wi-Fi or Bluetooth. The data is designed to reach the server immediately.

[0379] Step 4:

[0380] The server receives the viewing distance data and the emotion data.

[0381] Input: Viewing distance data, emotion data

[0382] Output: The data is stored in the server.

[0383] Specific operation: The server receives the viewing distance data and emotion data sent from the device and temporarily stores them in a database. This data is used for subsequent analysis.

[0384] Step 5:

[0385] The server analyzes the data using an AI algorithm and calculates vision correction data.

[0386] Input: Viewing distance data, emotion data

[0387] Output: Vision correction data

[0388] How it works: The AI ​​algorithm installed on the server analyzes the received visual distance data and emotional data. It uses the visual distance data to determine the distance of the object the user is looking at, and uses the emotional data to understand the user's psychological state. Based on this, it generates optimal vision correction data.

[0389] Step 6:

[0390] The server transmits the calculated vision correction data to the terminal.

[0391] Input: Vision correction data

[0392] Output: Vision correction data is sent to the device.

[0393] Specific operation: The server sends vision correction data to the device, including lens adjustment instructions. This data is sent accurately and without delay.

[0394] Step 7:

[0395] The device automatically adjusts the lenses based on vision correction data.

[0396] Input: Vision correction data

[0397] Output: Lens adjusted

[0398] Specific operation: The device's lens control mechanism adjusts the focal length of the lens based on the vision correction data to optimize the user's field of vision, thereby providing a comfortable field of vision for the user.

[0399] Step 8:

[0400] The user checks the field of view after adjustment and confirms that the vision correction is comfortable.

[0401] Input: Adjusted lens field of view

[0402] Output: Ensure comfortable visibility

[0403] What it does: The user puts on the glasses and checks if their vision improves. If it's not comfortable, the system may collect data again and make adjustments.

[0404] (Application example 2)

[0405] 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."

[0406] The present invention relates to a system that automatically provides optimal vision correction by measuring a driver's visual distance and emotions in real time. However, conventional vision correction systems lack the ability to detect driver stress and fatigue and respond immediately, which hinders safe driving. There is a need to solve this problem and ensure that drivers always receive optimal vision correction and safety warnings.

[0407] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a sensor means for measuring the user's visual distance in real time, a communication means for transmitting the measured visual distance data and emotion data to the server, an AI algorithm means on the server for calculating vision correction data based on the transmitted visual distance data and emotion data, a data transmission means on the server for transmitting the calculated vision correction data to the user terminal, a lens control means for automatically adjusting the lens based on the received vision correction data, and a warning means for detecting driver stress or fatigue in an autonomous vehicle and issuing a warning. This enables the driver to not only receive automatic vision correction according to the visual distance but also receive warnings according to stress or fatigue to increase safety while driving.

[0408] "User's viewing distance" is a real-time measurement of the distance to an object that the user is looking at.

[0409] "Sensor means" is a device for measuring the user's viewing distance in real time.

[0410] "Emotion data" is data that indicates the user's current emotional state, including stress, fatigue, and the like.

[0411] The "communication means" is a means for transmitting the measured viewing distance data and emotion data to the server.

[0412] "AI algorithm means on a server" refers to a server equipped with an artificial intelligence algorithm for calculating vision correction data based on visual distance data and emotion data.

[0413] The "data transmission means of the server" is a means for transmitting calculated vision correction data to the user terminal.

[0414] The "lens control means" is a means for automatically adjusting the lens based on the received vision correction data.

[0415] An "autonomous vehicle" is a vehicle that can drive itself using artificial intelligence and sensor technology.

[0416] "Warning means" refers to a means for detecting driver stress or fatigue in an autonomous vehicle and issuing a warning.

[0417] The present invention is a system for measuring the driver's visual distance and emotional data in real time in an autonomous vehicle, and providing optimal vision correction and warnings for fatigue and stress. The system includes the following means:

[0418] Operation of the sensor means

[0419] The system starts working when the user puts on the smart glasses. The smart glasses are equipped with sensors that measure visual distance in real time, as well as sensors that detect heart rate and facial expressions to obtain emotional data. This allows the system to collect information on the user's visual distance and emotions in real time.

[0420] Communication method operation

[0421] The smart glasses, which are the user's terminal, collect visual distance data and emotion data and immediately transmit them to a server. The data is sent securely and quickly using an internet connection.

[0422] AI algorithm means operation on the server

[0423] The server analyzes the received visual distance data and emotion data. An AI algorithm (e.g., TensorFlow, PyTorch) calculates optimal vision correction data based on this data. Based on the emotion data, corrections are made according to the user's stress and fatigue level, providing a comfortable field of vision. It also issues warnings as necessary.

[0424] Operation of data transmission means

[0425] The calculated vision correction data is transmitted to the user terminal through the server's data transmission means, and includes details on how to adjust the lenses.

[0426] Operation of the lens control means

[0427] The user terminal operates the lens control means to automatically adjust the lenses based on the received vision correction data. This adjustment allows the user to always receive optimal vision correction and maintain clear vision.

[0428] Warning mechanism operation

[0429] The system of an autonomous vehicle is equipped with a means to issue a warning via voice or display notification if it determines that the user is experiencing high levels of stress or fatigue, thereby assisting the driver in driving safely.

[0430] Specific examples

[0431] Example of visual distance and emotion data collection

[0432] When the user is wearing the smart glasses, the visual distance is detected to be approximately 0.35m, the heart rate is detected to be 85, and the emotion is detected to be "stressed."

[0433] Vision correction and warning examples

[0434] The server receives this data and generates vision correction data and a warning to "take a break." This data is sent to the user's terminal, and the user is notified to take a break and the lenses are adjusted.

[0435] Prompt Sentence Examples

[0436] "If the user is tired, generate an alert to relax with vision correction: Analyze the data of visual distance 0.35m, heart rate 85, and emotion 'stressed' to suggest the necessary vision correction and display recommended actions to reduce fatigue."

[0437] This system will enable drivers in self-driving vehicles to accurately correct their vision while detecting stress and fatigue, supporting safe driving.

[0438] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0439] Step 1:

[0440] The system starts working when the user puts on the smart glasses. The glasses' built-in visual distance sensor and emotion sensors (heart rate, facial expression recognition) collect data as input. This results in visual distance data and emotion data. The output is the collected visual distance data and emotion data.

[0441] Step 2:

[0442] The device sends the collected viewing distance data and emotion data to the server using a communication method. The viewing distance data and emotion data obtained in step 1 are used as input. The data is sent to the server in real time via a secure protocol (e.g., HTTPS). The output is the viewing distance data and emotion data sent to the server.

[0443] Step 3:

[0444] The server analyzes the received viewing distance data and emotion data. The inputs are the transmitted viewing distance data and emotion data. An AI algorithm (e.g., TensorFlow, PyTorch) on the server calculates vision correction data based on these data. The AI ​​algorithm performs vision correction appropriate for the user's viewing distance and generates correction data that reduces stress and fatigue based on the emotion data. The output is the calculated vision correction data.

[0445] Step 4:

[0446] The server sends the calculated vision correction data to the user terminal. The input is the vision correction data generated in step 3. The data is sent via the Internet as a transmission method. The output is the vision correction data sent to the user terminal.

[0447] Step 5:

[0448] The user terminal operates the lens control means based on the vision correction data received from the server to automatically adjust the lens. The input is the vision correction data received from the server. The focal length of the lens is automatically adjusted based on the vision correction data. The output is the adjusted lens.

[0449] Step 6:

[0450] The server also takes into account the user's emotional state (stress, fatigue) and activates a means to issue a warning if necessary. Emotional data is used as input. If a certain threshold is exceeded, an audio or visual warning is given to the user. The output is a warning notification.

[0451] This process flow allows the user to always receive optimal vision correction while also receiving warnings to ensure safe driving.

[0452] 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.

[0453] 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.

[0454] 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.

[0455] [Second embodiment]

[0456] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0457] 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.

[0458] 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).

[0459] 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.

[0460] 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.

[0461] 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).

[0462] 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.

[0463] 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.

[0464] 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.

[0465] 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.

[0466] 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.

[0467] 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."

[0468] This invention is an AI eyeglass system that automatically performs optimal vision correction according to the user's viewing distance. Specific embodiments for implementing this system will be described below.

[0469] overview

[0470] This system consists of a user terminal (eyeglasses device), a server, and a sensor device. Its purpose is to correct vision in real time based on the user's viewing distance when looking at different distances (close to home, PC, long distance, medium distance, etc.).

[0471] User terminal operation

[0472] The system starts operating when the user puts on the glasses. The user device has a built-in sensor for measuring visual distance, which detects the user's line of sight and focal length in real time. The detected visual distance data is sent to the server via the communication means in the user device.

[0473] Server Processing

[0474] The server receives the viewing distance data transmitted from the user terminal. The received data is analyzed by an AI algorithm on the server, and vision correction data is calculated. This calculation is performed to provide appropriate vision correction in real time according to the user's viewing distance. The calculated vision correction data is then transmitted back to the user terminal by the server's data transmission means.

[0475] Automatic lens adjustment

[0476] The user terminal receives the vision correction data sent from the server. Based on the received data, the lens control means built into the glasses operates and automatically adjusts the lenses to the appropriate focal length. This allows the user to comfortably see close-up and long-distance objects.

[0477] Specific examples

[0478] Example 1: When looking at your hands

[0479] User: When reading a newspaper, keep your eyes on the screen.

[0480] Terminal: The sensor detects that the viewing distance is close (approximately 30 cm) and sends that data to the server.

[0481] Server: Receives the visual distance data and calculates the appropriate near-distance vision correction data using an AI algorithm. Then, resends the data to the user device.

[0482] Device: Automatically adjusts the lens for close distances based on the received correction data.

[0483] Example 2: When looking into the distance

[0484] User: When looking at a distant scene, look into the distance.

[0485] Terminal: The sensor detects that the viewing distance is long (approximately 5m or more) and sends that data to the server.

[0486] Server: Receives the visual distance data and calculates the appropriate long-distance vision correction data using an AI algorithm. Then, resends the data to the user device.

[0487] Terminal: Automatically adjusts the lens for long distances based on the received correction data.

[0488] In this way, the system can automatically provide appropriate vision correction in real time according to the user's viewing distance, eliminating the need for multiple pairs of glasses and ensuring that the user always has a comfortable field of vision.

[0489] Instructions for use

[0490] 1. The user puts on the glasses.

[0491] 2. The sensor measures the viewing distance.

[0492] 3. The viewing distance data is sent to the server.

[0493] 4. The server calculates the vision correction data and sends it to the user's device.

[0494] 5. The user device adjusts the lens.

[0495] 6. Make sure the user looks comfortable.

[0496] By using this system, users can always receive optimal vision correction and reduce eye strain caused by long periods of close-up work.

[0497] The processing flow will be explained below.

[0498] Step 1:

[0499] The moment the user puts on the glasses, the sensor device activates and begins measuring the user's gaze direction and focal length in real time.

[0500] Step 2:

[0501] The device collects viewing distance data from sensors, which includes gaze direction and focal length, providing an accurate measurement of the distance to the object the user is looking at.

[0502] Step 3:

[0503] The device sends the collected visual distance data to the server using a communication method, and the data arrives immediately without delay.

[0504] Step 4:

[0505] The server receives the visual distance data sent from the user terminal. This data is information indicating the distance at which the line of sight is focused.

[0506] Step 5:

[0507] The server then analyzes the received visual distance data using an AI algorithm, which takes into account past data and usage patterns to calculate optimal vision correction data.

[0508] Step 6:

[0509] The server transmits the calculated vision correction data to the user terminal using the data transmission means, which indicates how the lenses should be adjusted.

[0510] Step 7:

[0511] The device receives vision correction data sent from the server, and based on this data, the lens is automatically adjusted to the appropriate focal length instantly.

[0512] Step 8:

[0513] Users can comfortably view objects close up and at a distance, and because vision correction occurs in real time, users can always maintain optimal vision for different viewing distances.

[0514] Step 9:

[0515] When the user changes their line of sight again, for example, moving their gaze away from the object in front of them, the entire process returns to step 1 and is carried out automatically. This allows the user to maintain a comfortable field of vision at all times without having to adjust their glasses themselves.

[0516] Example 1

[0517] 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."

[0518] Conventional eyeglass systems have the problem of being inconvenient, as users must wear different glasses for each different viewing distance, such as for something close to them, a PC, long-distance viewing, or medium-distance viewing.In addition, there is also the problem of eyestrain caused by prolonged close-up work, as vision correction is not performed appropriately according to the viewing distance.

[0519] 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.

[0520] In this invention, the server includes a sensor for measuring the user's visual distance in real time, a communication unit for transmitting the measured visual distance data to the server, an AI algorithm for calculating vision correction data based on the transmitted visual distance data, a data transmission unit on the server for transmitting the calculated vision correction data to the user terminal, a lens control unit for automatically adjusting the lenses based on the received vision correction data, a system initialization unit for managing the initialization process, a detection unit for detecting the line of sight and focal length in real time, and an encryption unit for securely transmitting the vision correction data to the server. This allows the user to automatically perform vision correction for different visual distances in real time, eliminating the need for multiple glasses. Furthermore, appropriate vision correction can reduce eye fatigue.

[0521] "Sensor means" is a device for measuring the user's viewing distance in real time.

[0522] "Communication means" refers to a method or device for transmitting measured viewing distance data to a server.

[0523] The "AI algorithm means on the server" is an artificial intelligence algorithm executed on the server to calculate vision correction data based on the transmitted viewing distance data.

[0524] The "server data transmission means" refers to a device or method for transmitting calculated vision correction data to a user terminal.

[0525] The "lens control means" is a mechanism or device for automatically adjusting the lenses based on the received vision correction data.

[0526] The "system initialization means" is a mechanism or device that performs initial settings to start the operation of the system.

[0527] "Detection means" refers to a device or method for detecting the line of sight and focal length in real time.

[0528] The "encryption means" is a data encryption technique for securely transmitting vision correction data to the server.

[0529] MODE FOR CARRYING OUT THE INVENTION

[0530] The present invention is an AI eyeglass system that automatically performs optimal vision correction according to the user's viewing distance. Specific embodiments for carrying out the present invention will be described below.

[0531] User terminal operation

[0532] The system begins operation when the user puts on the glasses. The user device is equipped with a built-in sensor for measuring visual distance, which detects the user's line of sight and focal length in real time. Specifically, it uses ToF (Time-of-Flight) technology to obtain the focal length of the line of sight in milliseconds. The detected visual distance data is sent to a server via a built-in communication method (e.g., Bluetooth or Wi-Fi). This communication is kept secure by encrypting the data.

[0533] Server Processing

[0534] The server receives the visual distance data sent from the user device. The received data is analyzed by an AI algorithm (for example, a deep learning model using TensorFlow or PyTorch) running on the server. The AI ​​algorithm uses a pre-trained vision correction model to calculate the optimal lens focal length in real time. The calculated vision correction data is then retransmitted to the user device via the server's data transmission means. This transmission is also encrypted and carried out via secure communication.

[0535] Automatic lens adjustment

[0536] The user terminal receives the vision correction data sent from the server. Based on the received data, the built-in lens control means (e.g., an electrically adjustable liquid crystal lens) operates and automatically adjusts the lens to the appropriate focal length. This allows the user to comfortably view close-up and distant objects.

[0537] Specific examples

[0538] Example 1: When looking at your hands

[0539] When a user reads a newspaper, they look directly at the screen.

[0540] The device's sensor detects that the viewing distance is 30 cm.

[0541] The sensor measures the focal length of the gaze and instantly stores the data in the device's memory.

[0542] The terminal transmits the data to the server.

[0543] The data is sent to a server via Bluetooth.

[0544] The server receives the visual distance data and uses an AI algorithm to calculate vision correction data for close distances.

[0545] The AI ​​model on the server calculates the optimal lens settings for viewing 30 cm ahead.

[0546] The server retransmits the correction data to the user terminal.

[0547] The correction data is encrypted and sent to the device over a secure connection.

[0548] The device automatically adjusts the lens for close distances based on the received correction data.

[0549] A lens control means adjusts the voltage to cause the lens to deform to a specified focal length.

[0550] Example 2: When looking into the distance

[0551] When a user views a distant scene, the user directs his or her gaze into the distance.

[0552] The device's sensor detects that the viewing distance is 5m or more.

[0553] The sensor measures the focal length of the gaze and instantly stores the data in the device's memory.

[0554] The terminal transmits the data to the server.

[0555] The data is sent to a server via Wi-Fi.

[0556] The server receives the viewing distance data and uses an AI algorithm to calculate vision correction data for long distances.

[0557] The AI ​​model on the server calculates the optimal lens settings for seeing more than 5m ahead.

[0558] The server retransmits the correction data to the user terminal.

[0559] The correction data is encrypted and sent to the device over a secure connection.

[0560] The device automatically adjusts the lens for long distances based on the received correction data.

[0561] A lens control means adjusts the voltage to cause the lens to deform to a specified focal length.

[0562] Example prompts for generative AI models

[0563] "Calculate the vision correction required for a user to read a newspaper 30 cm away."

[0564] "Calculate the visual acuity correction required when the user views a scene 5 meters away."

[0565] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0566] System program processing flow

[0567] Step 1: Initialize the system

[0568] Specific behavior:

[0569] The user puts on the glasses.

[0570] The terminal is powered on and the system initialization means starts operating. It checks whether the sensors are working properly and the communication module establishes a connection with the server. This initialization includes the initial setting data and calibration process for the system to operate.

[0571] Input: Eyeglasses wearing information

[0572] Output: System initialization complete signal

[0573] Step 2: Measure the viewing distance

[0574] Specific behavior:

[0575] The sensor means detects the user's gaze direction and focal length in real time.

[0576] The device uses ToF technology to capture the focal length of the line of sight, and the sensor collects data every millisecond and stores it in the device's memory.

[0577] Input: User gaze data

[0578] Output: View distance data

[0579] Step 3: Sending viewing distance data

[0580] Specific behavior:

[0581] The terminal transmits the acquired viewing distance data to the server using a communication means (for example, Bluetooth or Wi-Fi).

[0582] The device encrypts the data before sending it to ensure security. Specifically, the viewing distance data is sent using a specific protocol (e.g., HTTP / HTTPS).

[0583] Input: View distance data

[0584] Output: View distance data sent to the server

[0585] Step 4: Calculate the vision correction data

[0586] Specific behavior:

[0587] The server analyzes the received visual distance data using an AI algorithm.

[0588] Based on the received visual distance data, the server calculates the optimal vision correction data using a pre-trained vision correction model (using, for example, TensorFlow or PyTorch).

[0589] Input: Received sight distance data

[0590] Output: Vision correction data

[0591] Step 5: Submit vision correction data

[0592] Specific behavior:

[0593] The server retransmits the calculated vision correction data to the user terminal.

[0594] The server encrypts the data and sends it to the user's device over a secure connection, using a protocol (e.g. HTTP / HTTPS).

[0595] Input: Vision correction data

[0596] Output: Vision correction data sent to the device

[0597] Step 6: Automatic lens adjustment

[0598] Specific behavior:

[0599] The terminal automatically adjusts the lenses based on the received vision correction data.

[0600] The terminal operates a built-in lens control means (for example, an electrically adjustable liquid crystal lens), which adjusts the voltage to deform the lens to the specified focal length.

[0601] Input: Received vision correction data

[0602] Output: Adjusted lens focal length

[0603] Exemplary Processing Steps

[0604] Example 1: Processing flow when looking at your hands

[0605] When a user reads a newspaper, they tend to look at the screen.

[0606] The device's sensor detects a viewing distance of 30 cm.

[0607] The terminal transmits the data to the server.

[0608] The server analyzes the visual distance data using an AI algorithm and calculates vision correction data.

[0609] The server transmits the correction data to the terminal.

[0610] The device automatically adjusts the lens for close distances based on the received correction data.

[0611] Example 2: Processing flow when looking into the distance

[0612] When a user views a distant scene, the user directs his or her gaze into the distance.

[0613] The device's sensor detects a viewing distance of 5m or more.

[0614] The terminal transmits the data to the server.

[0615] The server analyzes the visual distance data using an AI algorithm and calculates vision correction data.

[0616] The server transmits the correction data to the terminal.

[0617] The device automatically adjusts the lens for long distances based on the received correction data.

[0618] (Application example 1)

[0619] 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."

[0620] Robot operators working in factories often have to work at multiple different viewing distances, making it difficult to maintain proper vision. In this regard, inadequate vision correction can make precision work difficult and potentially compromise efficiency and safety. In particular, in jobs that require frequent shifts of gaze between precision components close at hand and distant equipment, inadequate vision correction can lead to reduced work quality and eye fatigue.

[0621] 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.

[0622] In this invention, the server includes a sensor means for measuring the user's visual distance in real time, a communication means for transmitting the measured visual distance data to the server, an AI algorithm means on the server for calculating vision correction data based on the transmitted visual distance data, a data transmission means on the server for transmitting the calculated vision correction data to the user terminal, a lens control means for automatically adjusting the lens based on the received vision correction data, and a vision correction assist means for providing work assistance in a factory based on the user's visual distance measurement data. This enables robot operators working in a factory to receive optimal vision correction in real time according to their visual distance, improving the efficiency and quality of precision work and reducing eye fatigue.

[0623] "Sensor means" is a device for measuring the user's viewing distance in real time.

[0624] "Communication means" is a system for transmitting measured viewing distance data to a server.

[0625] The "AI algorithm means" is an algorithm that runs on the server and calculates vision correction data based on the transmitted viewing distance data.

[0626] The "data transmission means of the server" is a function of the server for transmitting calculated vision correction data to the user terminal.

[0627] The "lens control means" is a mechanism for automatically adjusting the lenses based on the received vision correction data.

[0628] The "vision correction assistance means" is a function for providing work assistance in a factory based on the user's visual distance measurement data.

[0629] This invention provides a system that enables operators working in a factory to receive optimal vision correction in real time according to their viewing distance. A specific embodiment of this system will be described in detail below.

[0630] System configuration

[0631] This system consists of a user terminal (smart glasses device), a server, and a sensor device.

[0632] User terminal operation

[0633] The system starts operation when the user puts on the smart glasses. The user device has a built-in sensor for measuring visual distance, which detects the user's line of sight and focal length in real time. The detected visual distance data is sent to the server via the communication means in the user device.

[0634] Server Processing

[0635] The server receives the viewing distance data transmitted from the user terminal. The received data is analyzed by an AI algorithm on the server, and vision correction data is calculated. This calculation is performed to provide appropriate vision correction in real time according to the user's viewing distance. The calculated vision correction data is then transmitted back to the user terminal by the server's data transmission means.

[0636] Automatic lens adjustment

[0637] The user terminal receives the vision correction data sent from the server. Based on the received data, the lens control means built into the glasses operates and automatically adjusts the lenses to the appropriate focal length. This allows the user to comfortably see close-up and long-distance objects.

[0638] Techniques and equipment used

[0639] Sensors (ToF sensors, etc.): Primarily used to measure line-of-sight distance.

[0640] Communication protocol: Data is sent and received using HTTP POST, etc.

[0641] AI Algorithm: A machine learning model for calculating vision correction data. For example, TensorFlow or PyTorch are used.

[0642] Smart glasses lens control system: Electronically controls lens focus adjustment.

[0643] Specific examples

[0644] As a concrete example, let's say a robot operator working in a smart factory uses the system in the following scenario:

[0645] Example 1: Task at hand

[0646] When an operator inspects a precision part in his or her hand, he or she focuses his or her gaze on the part.

[0647] The gaze sensor measures the visual distance of the hand and sends the data to the server.

[0648] The server-side AI quickly calculates vision correction data based on the viewing distance and sends it to the smart glasses.

[0649] Smart glasses automatically adjust vision, allowing operators to comfortably inspect precision parts at hand.

[0650] Example 2: Long-distance observation

[0651] When operators view distant equipment, they turn their gaze into the distance.

[0652] The gaze sensor measures the long-distance viewing distance and transmits the data to the server.

[0653] The server-side AI quickly calculates vision correction data based on long-distance viewing distance and sends it to the smart glasses.

[0654] Smart glasses automatically adjust vision, allowing operators to clearly see distant equipment.

[0655] Prompt Sentence Examples

[0656] The smart glasses are worn and the visual distance at hand is measured. The visual distance data is acquired by the sensor and sent to the server via an HTTP POST request. A machine learning model (TensorFlow) is used on the server side to calculate vision correction data. The calculation results are sent back to the smart glasses, which automatically adjust the visual acuity. As a result, the robot operator can comfortably inspect precision parts.

[0657] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0658] Step 1:

[0659] The user puts on the smart glasses and turns them on.

[0660] This action activates the smart glasses' built-in sensors, which measure the user's gaze direction and focal length in real time.

[0661] Input: User's gaze direction and focal length

[0662] Output: Real-time visual distance data

[0663] Step 2:

[0664] The communication module inside the smart glasses receives the visual distance data measured by the built-in sensor and sends it to the server.

[0665] This data is sent using an HTTP POST request.

[0666] Input: Real-time visual distance data

[0667] Output: View distance data sent to the server

[0668] Step 3:

[0669] The server receives the viewing distance data transmitted from the user terminal.

[0670] The server filters the received data to remove unwanted noise.

[0671] Input: View distance data sent to the server

[0672] Output: Noise-removed visual distance data

[0673] Step 4:

[0674] A server-side AI algorithm analyzes the filtered viewing distance data and calculates the optimal vision correction data.

[0675] This calculation uses a generative AI model (e.g., TensorFlow).

[0676] Input: filtered viewing distance data

[0677] Output: Vision correction data

[0678] Step 5:

[0679] The data transmitting means of the server transmits the calculated vision correction data to the smart glasses.

[0680] This process is also done using an HTTP POST request.

[0681] Input: Vision correction data

[0682] Output: Vision correction data sent to smart glasses

[0683] Step 6:

[0684] The lens control means of the smart glasses automatically adjusts the lenses based on the received vision correction data.

[0685] Specifically, the focal length of the lens is adjusted in real time to provide the user with the optimal field of view.

[0686] Input: Vision correction data sent to smart glasses

[0687] Output: Optimal vision with automatically adjusted lenses

[0688] Step 7:

[0689] The user checks the corrected vision and continues working as necessary.

[0690] This step provides feedback to confirm that the user has indeed achieved a comfortable field of view.

[0691] Input: Optimal vision with auto-adjusted lenses

[0692] Output: Improving user visual comfort and work efficiency

[0693] 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.

[0694] This invention is an AI glasses system that automatically performs optimal vision correction according to the user's viewing distance and also recognizes the user's emotions to provide an optimal field of view. Specific embodiments for implementing this system are described below.

[0695] overview

[0696] This system consists of a user terminal (eyeglasses device), a server, a sensor device, and an emotion engine. It aims to not only correct vision in real time based on the user's viewing distance when looking at something at different viewing distances, but also to suggest optimal vision correction according to the user's emotions.

[0697] User terminal operation

[0698] The system begins operation when the user puts on the glasses. The user device is equipped with a sensor that measures visual distance and an emotion engine that recognizes the user's emotions. The system detects the user's gaze direction and focal length, as well as facial expressions, voice, and heart rate, and collects visual distance and emotion data in real time.

[0699] Sending data

[0700] The user device sends the collected visual distance data and emotion data to the server using a communication method, and the data arrives immediately without delay.

[0701] Server Processing

[0702] The server receives the viewing distance data and emotion data transmitted from the user terminal, where the viewing distance data indicates the distance to an object the user is looking at, and the emotion data indicates the user's current emotional state.

[0703] Analysis by AI algorithm

[0704] The AI ​​algorithm on the server analyzes the received viewing distance data and emotional data and calculates vision correction data. The AI ​​algorithm not only performs appropriate vision correction based on the user's viewing distance, but also takes emotional data into account to suggest vision correction that the user finds most comfortable.

[0705] Sending correction data

[0706] The server sends the calculated vision correction data to the user terminal, which indicates how the lenses should be adjusted.

[0707] Automatic lens adjustment

[0708] The user terminal receives the vision correction data sent from the server, and the built-in lens control means of the glasses immediately operates to automatically adjust the lenses to the appropriate focal length, allowing the user to obtain a comfortable field of vision.

[0709] Specific examples

[0710] Example 1: When looking at your hands

[0711] User: I feel a little stressed while reading a book.

[0712] Terminal: Detects the viewing distance as close (approximately 30 cm) and senses the stress felt by the user from their facial expression.

[0713] Server: Receives visual distance data and "stress" emotion data, and uses an AI algorithm to calculate vision correction data for close distances and with an emphasis on stress reduction.

[0714] Terminal: Based on the received correction data, the lens is adjusted for close distances and vision correction is performed to reduce stress.

[0715] Example 2: When looking into the distance

[0716] User: I want to see the scenery in the distance, but I'm a little tired.

[0717] Terminal: Detects the viewing distance as long (approximately 5m or more) and senses "fatigue" from the user's facial expression and heart rate.

[0718] Server: Receives visual distance data and "fatigue" emotion data, and uses an AI algorithm to calculate vision correction data for long distances and to reduce fatigue.

[0719] Terminal: Based on the received correction data, the lenses are adjusted for long distances and vision correction is performed to reduce fatigue.

[0720] In this way, this system automatically performs appropriate vision correction in real time according to the user's viewing distance and can also optimize the correction taking into account the user's emotions, allowing the user to always maintain a comfortable field of vision and reduce eye and mental strain.

[0721] Instructions for use

[0722] 1. The user puts on the glasses.

[0723] 2. Sensors and emotion engines measure visual distance and emotion data.

[0724] 3. The viewing distance data and emotion data are sent to the server.

[0725] 4. The server calculates the vision correction data and sends it to the user's device.

[0726] 5. The user device adjusts the lens.

[0727] 6. Make sure the user looks comfortable.

[0728] By using this system, users can always receive optimal vision correction and maintain a comfortable field of vision that even takes their emotions into consideration.

[0729] The processing flow will be explained below.

[0730] Step 1:

[0731] The user puts on the glasses. This triggers the system to start up, and the sensor device and emotion engine begin to operate.

[0732] Step 2:

[0733] The device uses built-in sensors to measure gaze direction and focal length, allowing it to detect the distance of the object the user is looking at in real time.

[0734] Step 3:

[0735] The device recognizes the user's emotions using an emotion engine, which collects data from multiple sensors, including facial expressions, voice, and heart rate, to analyze the user's emotional state.

[0736] Step 4:

[0737] The device transmits the collected visual distance data and emotion data to the server using a communication method. These data are integrated into a single packet and are delivered to the server immediately.

[0738] Step 5:

[0739] The server receives the viewing distance data and emotion data sent from the user terminal. The received data indicates the gaze direction, focal length, and the user's emotional state.

[0740] Step 6:

[0741] The AI ​​algorithm on the server analyzes the received viewing distance data and emotional data, calculates appropriate vision correction data based on the user's viewing distance, and then adjusts the optimal vision correction value taking into account the emotional data.

[0742] Step 7:

[0743] The server transmits the calculated vision correction data to the user terminal using the data transmission means. The vision correction data is information indicating how the lens should be adjusted.

[0744] Step 8:

[0745] The terminal receives the vision correction data sent from the server. Based on the received data, the lens control means starts operation and automatically adjusts the lens to the appropriate focal length.

[0746] Step 9:

[0747] The system ensures that users can see objects close to them and at a distance for comfortable viewing. Vision correction is performed in real time, ensuring users always have optimal vision for different viewing distances. Furthermore, vision correction adjusts to the user's emotional state, reducing stress and fatigue.

[0748] Step 10:

[0749] If the user changes their gaze again, the change in gaze direction and emotional state is detected, and the whole process starts again from step 2. This allows the user to dynamically and continuously receive optimal vision correction.

[0750] Example 2

[0751] 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."

[0752] While conventional vision correction systems can correct a user's vision based on their viewing distance, they are unable to provide optimal vision correction by taking into account the user's emotional state. As a result, when a user is stressed or tired, optimal vision correction is not provided, resulting in an inability to achieve comfortable vision. Furthermore, conventional systems suffer from delays in the entire process from measuring viewing distance data to adjusting lenses, making it difficult to provide real-time vision correction.

[0753] 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.

[0754] In this invention, the server includes a sensor means for measuring the user's viewing distance in real time, an emotion recognition means for recognizing emotion data along with the viewing distance, a communication means for transmitting the measured viewing distance data and emotion data to the server, an AI algorithm means on the server for calculating vision correction data based on the transmitted viewing distance data and emotion data, a data transmission means on the server for transmitting the calculated vision correction data to the user terminal, and a lens control means for automatically adjusting the lens based on the received vision correction data. This enables real-time vision correction that simultaneously takes into account the user's viewing distance and emotional state.

[0755] "Sensor means" is a device for measuring the user's viewing distance in real time.

[0756] The "emotion recognition means" is a device for analyzing the user's facial expressions, voice, heart rate, etc. to obtain emotional data.

[0757] The "communication means" is a device for transmitting the measured viewing distance data and emotion data to the server.

[0758] The "AI algorithm means" is software for calculating vision correction data based on visual distance data and emotional data on a server.

[0759] The "data transmission means of the server" is a device for transmitting calculated vision correction data to the user terminal.

[0760] The "lens control means" is a device for automatically adjusting the lenses based on the received vision correction data.

[0761] A "user terminal" is a glasses-type device worn by a user.

[0762] This invention is an AI glasses system that automatically performs optimal vision correction according to the user's viewing distance and also recognizes the user's emotions to provide an optimal field of view. Next, specific embodiments for implementing this system will be described.

[0763] overview

[0764] This system consists of a user terminal (eyeglasses device), a server, a sensor device, and an emotion recognition engine. It aims to not only correct vision in real time based on the user's viewing distance when looking at something at different viewing distances, but also to suggest optimal vision correction according to the user's emotions.

[0765] User terminal operation

[0766] The system starts when the user puts on the glasses. The user device is equipped with a sensor that measures visual distance and an emotion recognition unit that recognizes the user's emotions. These sensors detect the user's gaze direction and focal length, as well as facial expressions, voice, and heart rate, and collect visual distance and emotion data in real time.

[0767] Sending data

[0768] The user device sends the collected visual distance data and emotion data to the server using a communication method such as Wi-Fi or Bluetooth. This data arrives at the server immediately and without delay.

[0769] Server Processing

[0770] The server receives the viewing distance data and emotion data transmitted from the user terminal, where the viewing distance data indicates the distance of an object the user is looking at, and the emotion data indicates the user's current emotional state.

[0771] Analysis by AI algorithm

[0772] The AI ​​algorithm installed on the server analyzes the received viewing distance data and emotional data and calculates vision correction data. This AI algorithm not only performs appropriate vision correction based on the user's viewing distance, but also takes emotional data into account to suggest vision correction that the user finds comfortable.

[0773] Sending correction data

[0774] The server sends the calculated vision correction data to the user terminal, which indicates how the lenses should be adjusted.

[0775] Automatic lens adjustment

[0776] The user terminal receives the vision correction data sent from the server, and the built-in lens control means of the glasses immediately operates to automatically adjust the lenses to the appropriate focal length, allowing the user to obtain a comfortable field of vision.

[0777] Specific examples

[0778] Example 1: When looking at your hands

[0779] User: I feel a little stressed while reading a book.

[0780] Terminal: Detects the viewing distance as close (approximately 30 cm) and senses the stress felt by the user from their facial expression.

[0781] Server: Receives visual distance data and "stress" emotion data, and uses an AI algorithm to calculate vision correction data for close distances and with an emphasis on stress reduction.

[0782] Terminal: Based on the received correction data, the lens is adjusted for close distances and vision correction is performed to reduce stress.

[0783] Example 2: When looking into the distance

[0784] User: I want to see the scenery in the distance, but I'm a little tired.

[0785] Terminal: Detects the viewing distance as long (approximately 5m or more) and senses "fatigue" from the user's facial expression and heart rate.

[0786] Server: Receives visual distance data and "fatigue" emotion data, and uses an AI algorithm to calculate vision correction data for long distances and to reduce fatigue.

[0787] Terminal: Based on the received correction data, the lenses are adjusted for long distances and vision correction is performed to reduce fatigue.

[0788] Prompt Sentence Examples

[0789] "Please suggest vision correction for users who experience stress at close range."

[0790] "Provide optimal vision correction for users who experience fatigue from looking at distant objects."

[0791] keyword

[0792] Generative AI Models

[0793] Prompt statement

[0794] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0795] Step 1:

[0796] The user puts on the glasses.

[0797] Input: User action (wearing glasses)

[0798] Output: The glasses' system activates.

[0799] How it works: When a user puts on the glasses, the sensor and emotion engine are automatically activated, which starts the process of visual distance measurement and emotion recognition.

[0800] Step 2:

[0801] The device collects viewing distance data and emotion data.

[0802] Input: User's gaze direction, facial expression, voice, heart rate

[0803] Output: Viewing distance data and emotion data are generated.

[0804] Specific operation: The device's built-in visual distance sensor measures the user's gaze direction and focal length, and the emotion recognition means analyzes the user's facial expressions, voice, heart rate, etc. to obtain emotional data. This data is updated in real time.

[0805] Step 3:

[0806] The device transmits the collected viewing distance data and emotion data to the server.

[0807] Input: Viewing distance data, emotion data

[0808] Output: Data is sent to the server.

[0809] Specific operation: The device transmits the acquired visual distance data and emotion data to the server via Wi-Fi or Bluetooth. The data is designed to reach the server immediately.

[0810] Step 4:

[0811] The server receives the viewing distance data and the emotion data.

[0812] Input: Viewing distance data, emotion data

[0813] Output: The data is stored in the server.

[0814] Specific operation: The server receives the viewing distance data and emotion data sent from the device and temporarily stores them in a database. This data is used for subsequent analysis.

[0815] Step 5:

[0816] The server analyzes the data using an AI algorithm and calculates vision correction data.

[0817] Input: Viewing distance data, emotion data

[0818] Output: Vision correction data

[0819] How it works: The AI ​​algorithm installed on the server analyzes the received visual distance data and emotional data. It uses the visual distance data to determine the distance of the object the user is looking at, and uses the emotional data to understand the user's psychological state. Based on this, it generates optimal vision correction data.

[0820] Step 6:

[0821] The server transmits the calculated vision correction data to the terminal.

[0822] Input: Vision correction data

[0823] Output: Vision correction data is sent to the device.

[0824] Specific operation: The server sends vision correction data to the device, including lens adjustment instructions. This data is sent accurately and without delay.

[0825] Step 7:

[0826] The device automatically adjusts the lenses based on vision correction data.

[0827] Input: Vision correction data

[0828] Output: Lens adjusted

[0829] Specific operation: The device's lens control mechanism adjusts the focal length of the lens based on the vision correction data to optimize the user's field of vision, thereby providing a comfortable field of vision for the user.

[0830] Step 8:

[0831] The user checks the field of view after adjustment and confirms that the vision correction is comfortable.

[0832] Input: Adjusted lens field of view

[0833] Output: Ensure comfortable visibility

[0834] What it does: The user puts on the glasses and checks if their vision improves. If it's not comfortable, the system may collect data again and make adjustments.

[0835] (Application example 2)

[0836] 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."

[0837] The present invention relates to a system that automatically provides optimal vision correction by measuring a driver's visual distance and emotions in real time. However, conventional vision correction systems lack the ability to detect driver stress and fatigue and respond immediately, which hinders safe driving. There is a need to solve this problem and ensure that drivers always receive optimal vision correction and safety warnings.

[0838] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a sensor means for measuring the user's visual distance in real time, a communication means for transmitting the measured visual distance data and emotion data to the server, an AI algorithm means on the server for calculating vision correction data based on the transmitted visual distance data and emotion data, a data transmission means on the server for transmitting the calculated vision correction data to the user terminal, a lens control means for automatically adjusting the lens based on the received vision correction data, and a warning means for detecting driver stress or fatigue in an autonomous vehicle and issuing a warning. This enables the driver to not only receive automatic vision correction according to the visual distance but also receive warnings according to stress or fatigue to increase safety while driving.

[0839] "User's viewing distance" is a real-time measurement of the distance to an object that the user is looking at.

[0840] "Sensor means" is a device for measuring the user's viewing distance in real time.

[0841] "Emotion data" is data that indicates the user's current emotional state, including stress, fatigue, and the like.

[0842] The "communication means" is a means for transmitting the measured viewing distance data and emotion data to the server.

[0843] "AI algorithm means on a server" refers to a server equipped with an artificial intelligence algorithm for calculating vision correction data based on visual distance data and emotion data.

[0844] The "data transmission means of the server" is a means for transmitting calculated vision correction data to the user terminal.

[0845] The "lens control means" is a means for automatically adjusting the lens based on the received vision correction data.

[0846] An "autonomous vehicle" is a vehicle that can drive itself using artificial intelligence and sensor technology.

[0847] "Warning means" refers to a means for detecting driver stress or fatigue in an autonomous vehicle and issuing a warning.

[0848] The present invention is a system for measuring the driver's visual distance and emotional data in real time in an autonomous vehicle, and providing optimal vision correction and warnings for fatigue and stress. The system includes the following means:

[0849] Operation of the sensor means

[0850] The system starts working when the user puts on the smart glasses. The smart glasses are equipped with sensors that measure visual distance in real time, as well as sensors that detect heart rate and facial expressions to obtain emotional data. This allows the system to collect information on the user's visual distance and emotions in real time.

[0851] Communication method operation

[0852] The smart glasses, which are the user's terminal, collect visual distance data and emotion data and immediately transmit them to a server. The data is sent securely and quickly using an internet connection.

[0853] AI algorithm means operation on the server

[0854] The server analyzes the received visual distance data and emotion data. An AI algorithm (e.g., TensorFlow, PyTorch) calculates optimal vision correction data based on this data. Based on the emotion data, corrections are made according to the user's stress and fatigue level, providing a comfortable field of vision. It also issues warnings as necessary.

[0855] Operation of data transmission means

[0856] The calculated vision correction data is transmitted to the user terminal through the server's data transmission means, and includes details on how to adjust the lenses.

[0857] Operation of the lens control means

[0858] The user terminal operates the lens control means to automatically adjust the lenses based on the received vision correction data. This adjustment allows the user to always receive optimal vision correction and maintain clear vision.

[0859] Warning mechanism operation

[0860] The system of an autonomous vehicle is equipped with a means to issue a warning via voice or display notification if it determines that the user is experiencing high levels of stress or fatigue, thereby assisting the driver in driving safely.

[0861] Specific examples

[0862] Example of visual distance and emotion data collection

[0863] When the user is wearing the smart glasses, the visual distance is detected as approximately 0.35m, the heart rate is detected as 85, and the emotion is detected as "stressed."

[0864] Vision correction and warning examples

[0865] The server receives this data and generates vision correction data and a warning to "take a break." This data is sent to the user's terminal, and the user is notified to take a break and the lenses are adjusted.

[0866] Prompt Sentence Examples

[0867] "If the user is tired, generate an alert to relax with vision correction: Analyze the data of visual distance 0.35m, heart rate 85, and emotion 'stressed' to suggest the necessary vision correction and display recommended actions to reduce fatigue."

[0868] This system will enable drivers in self-driving vehicles to accurately correct their vision while detecting stress and fatigue, supporting safe driving.

[0869] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0870] Step 1:

[0871] The system starts working when the user puts on the smart glasses. The glasses' built-in visual distance sensor and emotion sensors (heart rate, facial expression recognition) collect data as input. This results in visual distance data and emotion data. The output is the collected visual distance data and emotion data.

[0872] Step 2:

[0873] The device sends the collected viewing distance data and emotion data to the server using a communication method. The viewing distance data and emotion data obtained in step 1 are used as input. The data is sent to the server in real time via a secure protocol (e.g., HTTPS). The output is the viewing distance data and emotion data sent to the server.

[0874] Step 3:

[0875] The server analyzes the received viewing distance data and emotion data. The inputs are the transmitted viewing distance data and emotion data. An AI algorithm (e.g., TensorFlow, PyTorch) on the server calculates vision correction data based on these data. The AI ​​algorithm performs vision correction appropriate for the user's viewing distance and generates correction data that reduces stress and fatigue based on the emotion data. The output is the calculated vision correction data.

[0876] Step 4:

[0877] The server sends the calculated vision correction data to the user terminal. The input is the vision correction data generated in step 3. The data is sent via the Internet as a transmission method. The output is the vision correction data sent to the user terminal.

[0878] Step 5:

[0879] The user terminal operates the lens control means based on the vision correction data received from the server to automatically adjust the lens. The input is the vision correction data received from the server. The focal length of the lens is automatically adjusted based on the vision correction data. The output is the adjusted lens.

[0880] Step 6:

[0881] The server also takes into account the user's emotional state (stress, fatigue) and activates a means to issue a warning if necessary. Emotional data is used as input. If a certain threshold is exceeded, an audio or visual warning is given to the user. The output is a warning notification.

[0882] This process flow allows the user to always receive optimal vision correction while also receiving warnings to ensure safe driving.

[0883] 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.

[0884] 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.

[0885] 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.

[0886] [Third embodiment]

[0887] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0888] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0889] 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).

[0890] 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.

[0891] 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.

[0892] 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).

[0893] 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.

[0894] 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.

[0895] 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.

[0896] 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.

[0897] 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.

[0898] 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."

[0899] This invention is an AI eyeglass system that automatically performs optimal vision correction according to the user's viewing distance. Specific embodiments for implementing this system will be described below.

[0900] overview

[0901] This system consists of a user terminal (eyeglasses device), a server, and a sensor device. Its purpose is to correct vision in real time based on the user's viewing distance when looking at different distances (close to home, PC, long distance, medium distance, etc.).

[0902] User terminal operation

[0903] The system starts operating when the user puts on the glasses. The user device has a built-in sensor for measuring visual distance, which detects the user's line of sight and focal length in real time. The detected visual distance data is sent to the server via the communication means in the user device.

[0904] Server Processing

[0905] The server receives the viewing distance data transmitted from the user terminal. The received data is analyzed by an AI algorithm on the server, and vision correction data is calculated. This calculation is performed to provide appropriate vision correction in real time according to the user's viewing distance. The calculated vision correction data is then transmitted back to the user terminal by the server's data transmission means.

[0906] Automatic lens adjustment

[0907] The user terminal receives the vision correction data sent from the server. Based on the received data, the lens control means built into the glasses operates and automatically adjusts the lenses to the appropriate focal length. This allows the user to comfortably see close-up and long-distance objects.

[0908] Specific examples

[0909] Example 1: When looking at your hands

[0910] User: When reading a newspaper, keep your eyes on the screen.

[0911] Terminal: The sensor detects that the viewing distance is close (approximately 30 cm) and sends that data to the server.

[0912] Server: Receives the visual distance data and calculates the appropriate near-distance vision correction data using an AI algorithm. Then, resends the data to the user device.

[0913] Device: Automatically adjusts the lens for close distances based on the received correction data.

[0914] Example 2: When looking into the distance

[0915] User: When looking at a distant scene, look into the distance.

[0916] Terminal: The sensor detects that the viewing distance is long (approximately 5m or more) and sends that data to the server.

[0917] Server: Receives the visual distance data and calculates the appropriate long-distance vision correction data using an AI algorithm. Then, resends the data to the user device.

[0918] Terminal: Automatically adjusts the lens for long distances based on the received correction data.

[0919] In this way, the system can automatically provide appropriate vision correction in real time according to the user's viewing distance, eliminating the need for multiple pairs of glasses and ensuring that the user always has a comfortable field of vision.

[0920] Instructions for use

[0921] 1. The user puts on the glasses.

[0922] 2. The sensor measures the viewing distance.

[0923] 3. The viewing distance data is sent to the server.

[0924] 4. The server calculates the vision correction data and sends it to the user's device.

[0925] 5. The user device adjusts the lens.

[0926] 6. Make sure the user looks comfortable.

[0927] By using this system, users can always receive optimal vision correction and reduce eye strain caused by long periods of close-up work.

[0928] The processing flow will be explained below.

[0929] Step 1:

[0930] The moment the user puts on the glasses, the sensor device activates and begins measuring the user's gaze direction and focal length in real time.

[0931] Step 2:

[0932] The device collects viewing distance data from sensors, which includes gaze direction and focal length, providing an accurate measurement of the distance to the object the user is looking at.

[0933] Step 3:

[0934] The device sends the collected visual distance data to the server using a communication method, and the data arrives immediately without delay.

[0935] Step 4:

[0936] The server receives the visual distance data sent from the user terminal. This data is information indicating the distance at which the line of sight is focused.

[0937] Step 5:

[0938] The server then analyzes the received visual distance data using an AI algorithm, which takes into account past data and usage patterns to calculate optimal vision correction data.

[0939] Step 6:

[0940] The server transmits the calculated vision correction data to the user terminal using the data transmission means, which indicates how the lenses should be adjusted.

[0941] Step 7:

[0942] The device receives vision correction data sent from the server, and based on this data, the lens is automatically adjusted to the appropriate focal length instantly.

[0943] Step 8:

[0944] Users can comfortably view objects close up and at a distance, and because vision correction occurs in real time, users can always maintain optimal vision for different viewing distances.

[0945] Step 9:

[0946] When the user changes their line of sight again, for example, moving their gaze away from the object in front of them, the entire process returns to step 1 and is carried out automatically. This allows the user to maintain a comfortable field of vision at all times without having to adjust their glasses themselves.

[0947] Example 1

[0948] 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."

[0949] Conventional eyeglass systems have the problem of being inconvenient, as users must wear different glasses for each different viewing distance, such as for something close to them, a PC, long-distance viewing, or medium-distance viewing.In addition, there is also the problem of eyestrain caused by prolonged close-up work, as vision correction is not performed appropriately according to the viewing distance.

[0950] 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.

[0951] In this invention, the server includes a sensor for measuring the user's visual distance in real time, a communication unit for transmitting the measured visual distance data to the server, an AI algorithm for calculating vision correction data based on the transmitted visual distance data, a data transmission unit on the server for transmitting the calculated vision correction data to the user terminal, a lens control unit for automatically adjusting the lenses based on the received vision correction data, a system initialization unit for managing the initialization process, a detection unit for detecting the line of sight and focal length in real time, and an encryption unit for securely transmitting the vision correction data to the server. This allows the user to automatically perform vision correction for different visual distances in real time, eliminating the need for multiple glasses. Furthermore, appropriate vision correction can reduce eye fatigue.

[0952] "Sensor means" is a device for measuring the user's viewing distance in real time.

[0953] "Communication means" refers to a method or device for transmitting measured viewing distance data to a server.

[0954] The "AI algorithm means on the server" is an artificial intelligence algorithm executed on the server to calculate vision correction data based on the transmitted viewing distance data.

[0955] The "server data transmission means" refers to a device or method for transmitting calculated vision correction data to a user terminal.

[0956] The "lens control means" is a mechanism or device for automatically adjusting the lenses based on the received vision correction data.

[0957] The "system initialization means" is a mechanism or device that performs initial settings to start the operation of the system.

[0958] "Detection means" refers to a device or method for detecting the line of sight and focal length in real time.

[0959] The "encryption means" is a data encryption technique for securely transmitting vision correction data to the server.

[0960] MODE FOR CARRYING OUT THE INVENTION

[0961] The present invention is an AI eyeglass system that automatically performs optimal vision correction according to the user's viewing distance. Specific embodiments for carrying out the present invention will be described below.

[0962] User terminal operation

[0963] The system begins operation when the user puts on the glasses. The user device is equipped with a built-in sensor for measuring visual distance, which detects the user's line of sight and focal length in real time. Specifically, it uses ToF (Time-of-Flight) technology to obtain the focal length of the line of sight in milliseconds. The detected visual distance data is sent to a server via a built-in communication method (e.g., Bluetooth or Wi-Fi). This communication is kept secure by encrypting the data.

[0964] Server Processing

[0965] The server receives the visual distance data sent from the user device. The received data is analyzed by an AI algorithm (for example, a deep learning model using TensorFlow or PyTorch) running on the server. The AI ​​algorithm uses a pre-trained vision correction model to calculate the optimal lens focal length in real time. The calculated vision correction data is then retransmitted to the user device via the server's data transmission means. This transmission is also encrypted and carried out via secure communication.

[0966] Automatic lens adjustment

[0967] The user terminal receives the vision correction data sent from the server. Based on the received data, the built-in lens control means (e.g., an electrically adjustable liquid crystal lens) operates and automatically adjusts the lens to the appropriate focal length. This allows the user to comfortably view close-up and distant objects.

[0968] Specific examples

[0969] Example 1: When looking at your hands

[0970] When a user reads a newspaper, they look directly at the screen.

[0971] The device's sensor detects that the viewing distance is 30 cm.

[0972] The sensor measures the focal length of the gaze and instantly stores the data in the device's memory.

[0973] The terminal transmits the data to the server.

[0974] The data is sent to a server via Bluetooth.

[0975] The server receives the visual distance data and uses an AI algorithm to calculate vision correction data for close distances.

[0976] The AI ​​model on the server calculates the optimal lens settings for viewing 30 cm ahead.

[0977] The server retransmits the correction data to the user terminal.

[0978] The correction data is encrypted and sent to the device over a secure connection.

[0979] The device automatically adjusts the lens for close distances based on the received correction data.

[0980] A lens control means adjusts the voltage to cause the lens to deform to a specified focal length.

[0981] Example 2: When looking into the distance

[0982] When a user views a distant scene, the user directs his or her gaze into the distance.

[0983] The device's sensor detects that the viewing distance is 5m or more.

[0984] The sensor measures the focal length of the gaze and instantly stores the data in the device's memory.

[0985] The terminal transmits the data to the server.

[0986] The data is sent to a server via Wi-Fi.

[0987] The server receives the viewing distance data and uses an AI algorithm to calculate vision correction data for long distances.

[0988] The AI ​​model on the server calculates the optimal lens settings for seeing more than 5m ahead.

[0989] The server retransmits the correction data to the user terminal.

[0990] The correction data is encrypted and sent to the device over a secure connection.

[0991] The device automatically adjusts the lens for long distances based on the received correction data.

[0992] A lens control means adjusts the voltage to cause the lens to deform to a specified focal length.

[0993] Example prompts for generative AI models

[0994] "Calculate the vision correction required for a user to read a newspaper 30 cm away."

[0995] "Calculate the visual acuity correction required when the user views a scene 5 meters away."

[0996] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0997] System program processing flow

[0998] Step 1: Initialize the system

[0999] Specific behavior:

[1000] The user puts on the glasses.

[1001] The terminal is powered on and the system initialization means starts operating. It checks whether the sensors are working properly and the communication module establishes a connection with the server. This initialization includes the initial setting data and calibration process for the system to operate.

[1002] Input: Eyeglasses wearing information

[1003] Output: System initialization complete signal

[1004] Step 2: Measure the viewing distance

[1005] Specific behavior:

[1006] The sensor means detects the user's gaze direction and focal length in real time.

[1007] The device uses ToF technology to capture the focal length of the line of sight, and the sensor collects data every millisecond and stores it in the device's memory.

[1008] Input: User gaze data

[1009] Output: View distance data

[1010] Step 3: Sending viewing distance data

[1011] Specific behavior:

[1012] The terminal transmits the acquired viewing distance data to the server using a communication means (for example, Bluetooth or Wi-Fi).

[1013] The device encrypts the data before sending it to ensure security. Specifically, the viewing distance data is sent using a specific protocol (e.g., HTTP / HTTPS).

[1014] Input: View distance data

[1015] Output: View distance data sent to the server

[1016] Step 4: Calculate the vision correction data

[1017] Specific behavior:

[1018] The server analyzes the received visual distance data using an AI algorithm.

[1019] Based on the received visual distance data, the server calculates the optimal vision correction data using a pre-trained vision correction model (using, for example, TensorFlow or PyTorch).

[1020] Input: Received sight distance data

[1021] Output: Vision correction data

[1022] Step 5: Submit vision correction data

[1023] Specific behavior:

[1024] The server retransmits the calculated vision correction data to the user terminal.

[1025] The server encrypts the data and sends it to the user's device over a secure connection, using a protocol (e.g. HTTP / HTTPS).

[1026] Input: Vision correction data

[1027] Output: Vision correction data sent to the device

[1028] Step 6: Automatic lens adjustment

[1029] Specific behavior:

[1030] The terminal automatically adjusts the lenses based on the received vision correction data.

[1031] The terminal operates a built-in lens control means (for example, an electrically adjustable liquid crystal lens), which adjusts the voltage to deform the lens to the specified focal length.

[1032] Input: Received vision correction data

[1033] Output: Adjusted lens focal length

[1034] Exemplary Processing Steps

[1035] Example 1: Processing flow when looking at your hands

[1036] When a user reads a newspaper, they tend to look at the screen.

[1037] The device's sensor detects a viewing distance of 30 cm.

[1038] The terminal transmits the data to the server.

[1039] The server analyzes the visual distance data using an AI algorithm and calculates vision correction data.

[1040] The server transmits the correction data to the terminal.

[1041] The device automatically adjusts the lens for close distances based on the received correction data.

[1042] Example 2: Processing flow when looking into the distance

[1043] When a user views a distant scene, the user directs his or her gaze into the distance.

[1044] The device's sensor detects a viewing distance of 5m or more.

[1045] The terminal transmits the data to the server.

[1046] The server analyzes the visual distance data using an AI algorithm and calculates vision correction data.

[1047] The server transmits the correction data to the terminal.

[1048] The device automatically adjusts the lens for long distances based on the received correction data.

[1049] (Application example 1)

[1050] 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."

[1051] Robot operators working in factories often have to work at multiple different viewing distances, making it difficult to maintain proper vision. In this regard, inadequate vision correction can make precision work difficult and potentially compromise efficiency and safety. In particular, in jobs that require frequent shifts of gaze between precision components close at hand and distant equipment, inadequate vision correction can lead to reduced work quality and eye fatigue.

[1052] 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.

[1053] In this invention, the server includes a sensor means for measuring the user's visual distance in real time, a communication means for transmitting the measured visual distance data to the server, an AI algorithm means on the server for calculating vision correction data based on the transmitted visual distance data, a data transmission means on the server for transmitting the calculated vision correction data to the user terminal, a lens control means for automatically adjusting the lens based on the received vision correction data, and a vision correction assist means for providing work assistance in a factory based on the user's visual distance measurement data. This enables robot operators working in a factory to receive optimal vision correction in real time according to their visual distance, improving the efficiency and quality of precision work and reducing eye fatigue.

[1054] "Sensor means" is a device for measuring the user's viewing distance in real time.

[1055] "Communication means" is a system for transmitting measured viewing distance data to a server.

[1056] The "AI algorithm means" is an algorithm that runs on the server and calculates vision correction data based on the transmitted viewing distance data.

[1057] The "data transmission means of the server" is a function of the server for transmitting calculated vision correction data to the user terminal.

[1058] The "lens control means" is a mechanism for automatically adjusting the lenses based on the received vision correction data.

[1059] The "vision correction assistance means" is a function for providing work assistance in a factory based on the user's visual distance measurement data.

[1060] This invention provides a system that enables operators working in a factory to receive optimal vision correction in real time according to their viewing distance. A specific embodiment of this system will be described in detail below.

[1061] System configuration

[1062] This system consists of a user terminal (smart glasses device), a server, and a sensor device.

[1063] User terminal operation

[1064] The system starts operation when the user puts on the smart glasses. The user device has a built-in sensor for measuring visual distance, which detects the user's line of sight and focal length in real time. The detected visual distance data is sent to the server via the communication means in the user device.

[1065] Server Processing

[1066] The server receives the viewing distance data transmitted from the user terminal. The received data is analyzed by an AI algorithm on the server, and vision correction data is calculated. This calculation is performed to provide appropriate vision correction in real time according to the user's viewing distance. The calculated vision correction data is then transmitted back to the user terminal by the server's data transmission means.

[1067] Automatic lens adjustment

[1068] The user terminal receives the vision correction data sent from the server. Based on the received data, the lens control means built into the glasses operates and automatically adjusts the lenses to the appropriate focal length. This allows the user to comfortably see close-up and long-distance objects.

[1069] Techniques and equipment used

[1070] Sensors (ToF sensors, etc.): Primarily used to measure line-of-sight distance.

[1071] Communication protocol: Data is sent and received using HTTP POST, etc.

[1072] AI Algorithm: A machine learning model for calculating vision correction data. For example, TensorFlow or PyTorch are used.

[1073] Smart glasses lens control system: Electronically controls lens focus adjustment.

[1074] Specific examples

[1075] As a concrete example, let's say a robot operator working in a smart factory uses the system in the following scenario:

[1076] Example 1: Task at hand

[1077] When an operator inspects a precision part in his or her hand, he or she focuses his or her gaze on the part.

[1078] The gaze sensor measures the visual distance of the hand and sends the data to the server.

[1079] The server-side AI quickly calculates vision correction data based on the viewing distance and sends it to the smart glasses.

[1080] Smart glasses automatically adjust vision, allowing operators to comfortably inspect precision parts at hand.

[1081] Example 2: Long-distance observation

[1082] When operators view distant equipment, they turn their gaze into the distance.

[1083] The gaze sensor measures the long-distance viewing distance and transmits the data to the server.

[1084] The server-side AI quickly calculates vision correction data based on long-distance viewing distance and sends it to the smart glasses.

[1085] Smart glasses automatically adjust vision, allowing operators to clearly see distant equipment.

[1086] Prompt Sentence Examples

[1087] The smart glasses are worn and the visual distance at hand is measured. The visual distance data is acquired by the sensor and sent to the server via an HTTP POST request. A machine learning model (TensorFlow) is used on the server side to calculate vision correction data. The calculation results are sent back to the smart glasses, which automatically adjust the visual acuity. As a result, the robot operator can comfortably inspect precision parts.

[1088] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1089] Step 1:

[1090] The user puts on the smart glasses and turns them on.

[1091] This action activates the smart glasses' built-in sensors, which measure the user's gaze direction and focal length in real time.

[1092] Input: User's gaze direction and focal length

[1093] Output: Real-time visual distance data

[1094] Step 2:

[1095] The communication module inside the smart glasses receives the visual distance data measured by the built-in sensor and sends it to the server.

[1096] This data is sent using an HTTP POST request.

[1097] Input: Real-time visual distance data

[1098] Output: View distance data sent to the server

[1099] Step 3:

[1100] The server receives the viewing distance data transmitted from the user terminal.

[1101] The server filters the received data to remove unwanted noise.

[1102] Input: View distance data sent to the server

[1103] Output: Noise-removed visual distance data

[1104] Step 4:

[1105] A server-side AI algorithm analyzes the filtered viewing distance data and calculates the optimal vision correction data.

[1106] This calculation uses a generative AI model (e.g., TensorFlow).

[1107] Input: filtered viewing distance data

[1108] Output: Vision correction data

[1109] Step 5:

[1110] The data transmitting means of the server transmits the calculated vision correction data to the smart glasses.

[1111] This process is also done using an HTTP POST request.

[1112] Input: Vision correction data

[1113] Output: Vision correction data sent to smart glasses

[1114] Step 6:

[1115] The lens control means of the smart glasses automatically adjusts the lenses based on the received vision correction data.

[1116] Specifically, the focal length of the lens is adjusted in real time to provide the user with the optimal field of view.

[1117] Input: Vision correction data sent to smart glasses

[1118] Output: Optimal vision with automatically adjusted lenses

[1119] Step 7:

[1120] The user checks the corrected vision and continues working as necessary.

[1121] This step provides feedback to confirm that the user has indeed achieved a comfortable field of view.

[1122] Input: Optimal vision with auto-adjusted lenses

[1123] Output: Improving user visual comfort and work efficiency

[1124] 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.

[1125] This invention is an AI glasses system that automatically performs optimal vision correction according to the user's viewing distance and also recognizes the user's emotions to provide an optimal field of view. Specific embodiments for implementing this system are described below.

[1126] overview

[1127] This system consists of a user terminal (eyeglasses device), a server, a sensor device, and an emotion engine. It aims to not only correct vision in real time based on the user's viewing distance when looking at something at different viewing distances, but also to suggest optimal vision correction according to the user's emotions.

[1128] User terminal operation

[1129] The system begins operation when the user puts on the glasses. The user device is equipped with a sensor that measures visual distance and an emotion engine that recognizes the user's emotions. The system detects the user's gaze direction and focal length, as well as facial expressions, voice, and heart rate, and collects visual distance and emotion data in real time.

[1130] Sending data

[1131] The user device sends the collected visual distance data and emotion data to the server using a communication method, and the data arrives immediately without delay.

[1132] Server Processing

[1133] The server receives the viewing distance data and emotion data transmitted from the user terminal, where the viewing distance data indicates the distance to an object the user is looking at, and the emotion data indicates the user's current emotional state.

[1134] Analysis by AI algorithm

[1135] The AI ​​algorithm on the server analyzes the received viewing distance data and emotional data and calculates vision correction data. The AI ​​algorithm not only performs appropriate vision correction based on the user's viewing distance, but also takes emotional data into account to suggest vision correction that the user finds most comfortable.

[1136] Sending correction data

[1137] The server sends the calculated vision correction data to the user terminal, which indicates how the lenses should be adjusted.

[1138] Automatic lens adjustment

[1139] The user terminal receives the vision correction data sent from the server, and the built-in lens control means of the glasses immediately operates to automatically adjust the lenses to the appropriate focal length, allowing the user to obtain a comfortable field of vision.

[1140] Specific examples

[1141] Example 1: When looking at your hands

[1142] User: I feel a little stressed while reading a book.

[1143] Terminal: Detects the viewing distance as close (approximately 30 cm) and senses the stress felt by the user from their facial expression.

[1144] Server: Receives visual distance data and "stress" emotion data, and uses an AI algorithm to calculate vision correction data for close distances and with an emphasis on stress reduction.

[1145] Terminal: Based on the received correction data, the lens is adjusted for close distances and vision correction is performed to reduce stress.

[1146] Example 2: When looking into the distance

[1147] User: I want to see the scenery in the distance, but I'm a little tired.

[1148] Terminal: Detects the viewing distance as long (approximately 5m or more) and senses "fatigue" from the user's facial expression and heart rate.

[1149] Server: Receives visual distance data and "fatigue" emotion data, and uses an AI algorithm to calculate vision correction data for long distances and to reduce fatigue.

[1150] Terminal: Based on the received correction data, the lenses are adjusted for long distances and vision correction is performed to reduce fatigue.

[1151] In this way, this system automatically performs appropriate vision correction in real time according to the user's viewing distance and can also optimize the correction taking into account the user's emotions, allowing the user to always maintain a comfortable field of vision and reduce eye and mental strain.

[1152] Instructions for use

[1153] 1. The user puts on the glasses.

[1154] 2. Sensors and emotion engines measure visual distance and emotion data.

[1155] 3. The viewing distance data and emotion data are sent to the server.

[1156] 4. The server calculates the vision correction data and sends it to the user's device.

[1157] 5. The user device adjusts the lens.

[1158] 6. Make sure the user looks comfortable.

[1159] By using this system, users can always receive optimal vision correction and maintain a comfortable field of vision that even takes their emotions into consideration.

[1160] The processing flow will be explained below.

[1161] Step 1:

[1162] The user puts on the glasses. This triggers the system to start up, and the sensor device and emotion engine begin to operate.

[1163] Step 2:

[1164] The device uses built-in sensors to measure gaze direction and focal length, allowing it to detect the distance of the object the user is looking at in real time.

[1165] Step 3:

[1166] The device recognizes the user's emotions using an emotion engine, which collects data from multiple sensors, including facial expressions, voice, and heart rate, to analyze the user's emotional state.

[1167] Step 4:

[1168] The device transmits the collected visual distance data and emotion data to the server using a communication method. These data are integrated into a single packet and are delivered to the server immediately.

[1169] Step 5:

[1170] The server receives the viewing distance data and emotion data sent from the user terminal. The received data indicates the gaze direction, focal length, and the user's emotional state.

[1171] Step 6:

[1172] The AI ​​algorithm on the server analyzes the received viewing distance data and emotional data, calculates appropriate vision correction data based on the user's viewing distance, and then adjusts the optimal vision correction value taking into account the emotional data.

[1173] Step 7:

[1174] The server transmits the calculated vision correction data to the user terminal using the data transmission means. The vision correction data is information indicating how the lens should be adjusted.

[1175] Step 8:

[1176] The terminal receives the vision correction data sent from the server. Based on the received data, the lens control means starts operation and automatically adjusts the lens to the appropriate focal length.

[1177] Step 9:

[1178] The system ensures that users can see objects close to them and at a distance for comfortable viewing. Vision correction is performed in real time, ensuring users always have optimal vision for different viewing distances. Furthermore, vision correction adjusts to the user's emotional state, reducing stress and fatigue.

[1179] Step 10:

[1180] If the user changes their gaze again, the change in gaze direction and emotional state is detected, and the whole process starts again from step 2. This allows the user to dynamically and continuously receive optimal vision correction.

[1181] Example 2

[1182] 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."

[1183] While conventional vision correction systems can correct a user's vision based on their viewing distance, they are unable to provide optimal vision correction by taking into account the user's emotional state. As a result, when a user is stressed or tired, optimal vision correction is not provided, resulting in an inability to achieve comfortable vision. Furthermore, conventional systems suffer from delays in the entire process from measuring viewing distance data to adjusting lenses, making it difficult to provide real-time vision correction.

[1184] 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.

[1185] In this invention, the server includes a sensor means for measuring the user's viewing distance in real time, an emotion recognition means for recognizing emotion data along with the viewing distance, a communication means for transmitting the measured viewing distance data and emotion data to the server, an AI algorithm means on the server for calculating vision correction data based on the transmitted viewing distance data and emotion data, a data transmission means on the server for transmitting the calculated vision correction data to the user terminal, and a lens control means for automatically adjusting the lens based on the received vision correction data. This enables real-time vision correction that simultaneously takes into account the user's viewing distance and emotional state.

[1186] "Sensor means" is a device for measuring the user's viewing distance in real time.

[1187] The "emotion recognition means" is a device for analyzing the user's facial expressions, voice, heart rate, etc. to obtain emotional data.

[1188] The "communication means" is a device for transmitting the measured viewing distance data and emotion data to the server.

[1189] The "AI algorithm means" is software for calculating vision correction data based on visual distance data and emotional data on a server.

[1190] The "data transmission means of the server" is a device for transmitting calculated vision correction data to the user terminal.

[1191] The "lens control means" is a device for automatically adjusting the lenses based on the received vision correction data.

[1192] A "user terminal" is a glasses-type device worn by a user.

[1193] This invention is an AI glasses system that automatically performs optimal vision correction according to the user's viewing distance and also recognizes the user's emotions to provide an optimal field of view. Next, specific embodiments for implementing this system will be described.

[1194] overview

[1195] This system consists of a user terminal (eyeglasses device), a server, a sensor device, and an emotion recognition engine. It aims to not only correct vision in real time based on the user's viewing distance when looking at something at different viewing distances, but also to suggest optimal vision correction according to the user's emotions.

[1196] User terminal operation

[1197] The system starts when the user puts on the glasses. The user device is equipped with a sensor that measures visual distance and an emotion recognition unit that recognizes the user's emotions. These sensors detect the user's gaze direction and focal length, as well as facial expressions, voice, and heart rate, and collect visual distance and emotion data in real time.

[1198] Sending data

[1199] The user device sends the collected visual distance data and emotion data to the server using a communication method such as Wi-Fi or Bluetooth. This data arrives at the server immediately and without delay.

[1200] Server Processing

[1201] The server receives the viewing distance data and emotion data transmitted from the user terminal, where the viewing distance data indicates the distance of an object the user is looking at, and the emotion data indicates the user's current emotional state.

[1202] Analysis by AI algorithm

[1203] The AI ​​algorithm installed on the server analyzes the received viewing distance data and emotional data and calculates vision correction data. This AI algorithm not only performs appropriate vision correction based on the user's viewing distance, but also takes emotional data into account to suggest vision correction that the user finds comfortable.

[1204] Sending correction data

[1205] The server sends the calculated vision correction data to the user terminal, which indicates how the lenses should be adjusted.

[1206] Automatic lens adjustment

[1207] The user terminal receives the vision correction data sent from the server, and the built-in lens control means of the glasses immediately operates to automatically adjust the lenses to the appropriate focal length, allowing the user to obtain a comfortable field of vision.

[1208] Specific examples

[1209] Example 1: When looking at your hands

[1210] User: I feel a little stressed while reading a book.

[1211] Terminal: Detects the viewing distance as close (approximately 30 cm) and senses the stress felt by the user from their facial expression.

[1212] Server: Receives visual distance data and "stress" emotion data, and uses an AI algorithm to calculate vision correction data for close distances and with an emphasis on stress reduction.

[1213] Terminal: Based on the received correction data, the lens is adjusted for close distances and vision correction is performed to reduce stress.

[1214] Example 2: When looking into the distance

[1215] User: I want to see the scenery in the distance, but I'm a little tired.

[1216] Terminal: Detects the viewing distance as long (approximately 5m or more) and senses "fatigue" from the user's facial expression and heart rate.

[1217] Server: Receives visual distance data and "fatigue" emotion data, and uses an AI algorithm to calculate vision correction data for long distances and to reduce fatigue.

[1218] Terminal: Based on the received correction data, the lenses are adjusted for long distances and vision correction is performed to reduce fatigue.

[1219] Prompt Sentence Examples

[1220] "Please suggest vision correction for users who experience stress at close range."

[1221] "Provide optimal vision correction for users who experience fatigue from looking at distant objects."

[1222] keyword

[1223] Generative AI Models

[1224] Prompt statement

[1225] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1226] Step 1:

[1227] The user puts on the glasses.

[1228] Input: User action (wearing glasses)

[1229] Output: The glasses' system activates.

[1230] How it works: When a user puts on the glasses, the sensor and emotion engine are automatically activated, which starts the process of visual distance measurement and emotion recognition.

[1231] Step 2:

[1232] The device collects viewing distance data and emotion data.

[1233] Input: User's gaze direction, facial expression, voice, heart rate

[1234] Output: Viewing distance data and emotion data are generated.

[1235] Specific operation: The device's built-in visual distance sensor measures the user's gaze direction and focal length, and the emotion recognition means analyzes the user's facial expressions, voice, heart rate, etc. to obtain emotional data. This data is updated in real time.

[1236] Step 3:

[1237] The device transmits the collected viewing distance data and emotion data to the server.

[1238] Input: Viewing distance data, emotion data

[1239] Output: Data is sent to the server.

[1240] Specific operation: The device transmits the acquired visual distance data and emotion data to the server via Wi-Fi or Bluetooth. The data is designed to reach the server immediately.

[1241] Step 4:

[1242] The server receives the viewing distance data and the emotion data.

[1243] Input: Viewing distance data, emotion data

[1244] Output: The data is stored in the server.

[1245] Specific operation: The server receives the viewing distance data and emotion data sent from the device and temporarily stores them in a database. This data is used for subsequent analysis.

[1246] Step 5:

[1247] The server analyzes the data using an AI algorithm and calculates vision correction data.

[1248] Input: Viewing distance data, emotion data

[1249] Output: Vision correction data

[1250] How it works: The AI ​​algorithm installed on the server analyzes the received visual distance data and emotional data. It uses the visual distance data to determine the distance of the object the user is looking at, and uses the emotional data to understand the user's psychological state. Based on this, it generates optimal vision correction data.

[1251] Step 6:

[1252] The server transmits the calculated vision correction data to the terminal.

[1253] Input: Vision correction data

[1254] Output: Vision correction data is sent to the device.

[1255] Specific operation: The server sends vision correction data to the device, including lens adjustment instructions. This data is sent accurately and without delay.

[1256] Step 7:

[1257] The device automatically adjusts the lenses based on vision correction data.

[1258] Input: Vision correction data

[1259] Output: Lens adjusted

[1260] Specific operation: The device's lens control mechanism adjusts the focal length of the lens based on the vision correction data to optimize the user's field of vision, thereby providing a comfortable field of vision for the user.

[1261] Step 8:

[1262] The user checks the field of view after adjustment and confirms that the vision correction is comfortable.

[1263] Input: Adjusted lens field of view

[1264] Output: Ensure comfortable visibility

[1265] What it does: The user puts on the glasses and checks if their vision improves. If it's not comfortable, the system may collect data again and make adjustments.

[1266] (Application example 2)

[1267] 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."

[1268] The present invention relates to a system that automatically provides optimal vision correction by measuring a driver's visual distance and emotions in real time. However, conventional vision correction systems lack the ability to detect driver stress and fatigue and respond immediately, which hinders safe driving. There is a need to solve this problem and ensure that drivers always receive optimal vision correction and safety warnings.

[1269] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a sensor means for measuring the user's visual distance in real time, a communication means for transmitting the measured visual distance data and emotion data to the server, an AI algorithm means on the server for calculating vision correction data based on the transmitted visual distance data and emotion data, a data transmission means on the server for transmitting the calculated vision correction data to the user terminal, a lens control means for automatically adjusting the lens based on the received vision correction data, and a warning means for detecting driver stress or fatigue in an autonomous vehicle and issuing a warning. This enables the driver to not only receive automatic vision correction according to the visual distance but also receive warnings according to stress or fatigue to increase safety while driving.

[1270] "User's viewing distance" is a real-time measurement of the distance to an object that the user is looking at.

[1271] "Sensor means" is a device for measuring the user's viewing distance in real time.

[1272] "Emotion data" is data that indicates the user's current emotional state, including stress, fatigue, and the like.

[1273] The "communication means" is a means for transmitting the measured viewing distance data and emotion data to the server.

[1274] "AI algorithm means on a server" refers to a server equipped with an artificial intelligence algorithm for calculating vision correction data based on visual distance data and emotion data.

[1275] The "data transmission means of the server" is a means for transmitting calculated vision correction data to the user terminal.

[1276] The "lens control means" is a means for automatically adjusting the lens based on the received vision correction data.

[1277] An "autonomous vehicle" is a vehicle that can drive itself using artificial intelligence and sensor technology.

[1278] "Warning means" refers to a means for detecting driver stress or fatigue in an autonomous vehicle and issuing a warning.

[1279] The present invention is a system for measuring the driver's visual distance and emotional data in real time in an autonomous vehicle, and providing optimal vision correction and warnings for fatigue and stress. The system includes the following means:

[1280] Operation of the sensor means

[1281] The system starts working when the user puts on the smart glasses. The smart glasses are equipped with sensors that measure visual distance in real time, as well as sensors that detect heart rate and facial expressions to obtain emotional data. This allows the system to collect information on the user's visual distance and emotions in real time.

[1282] Communication method operation

[1283] The smart glasses, which are the user's terminal, collect visual distance data and emotion data and immediately transmit them to a server. The data is sent securely and quickly using an internet connection.

[1284] AI algorithm means operation on the server

[1285] The server analyzes the received visual distance data and emotion data. An AI algorithm (e.g., TensorFlow, PyTorch) calculates optimal vision correction data based on this data. Based on the emotion data, corrections are made according to the user's stress and fatigue level, providing a comfortable field of vision. It also issues warnings as necessary.

[1286] Operation of data transmission means

[1287] The calculated vision correction data is transmitted to the user terminal through the server's data transmission means, and includes details on how to adjust the lenses.

[1288] Operation of the lens control means

[1289] The user terminal operates the lens control means to automatically adjust the lenses based on the received vision correction data. This adjustment allows the user to always receive optimal vision correction and maintain clear vision.

[1290] Warning mechanism operation

[1291] The system of an autonomous vehicle is equipped with a means to issue a warning via voice or display notification if it determines that the user is experiencing high levels of stress or fatigue, thereby assisting the driver in driving safely.

[1292] Specific examples

[1293] Example of visual distance and emotion data collection

[1294] When the user is wearing the smart glasses, the visual distance is detected as approximately 0.35m, the heart rate is detected as 85, and the emotion is detected as "stressed."

[1295] Vision correction and warning examples

[1296] The server receives this data and generates vision correction data and a warning to "take a break." This data is sent to the user's terminal, and the user is notified to take a break and the lenses are adjusted.

[1297] Prompt Sentence Examples

[1298] "If the user is tired, generate an alert to relax with vision correction: Analyze the data of visual distance 0.35m, heart rate 85, and emotion 'stressed' to suggest the necessary vision correction and display recommended actions to reduce fatigue."

[1299] This system will enable drivers in self-driving vehicles to accurately correct their vision while detecting stress and fatigue, supporting safe driving.

[1300] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1301] Step 1:

[1302] The system starts working when the user puts on the smart glasses. The glasses' built-in visual distance sensor and emotion sensors (heart rate, facial expression recognition) collect data as input. This results in visual distance data and emotion data. The output is the collected visual distance data and emotion data.

[1303] Step 2:

[1304] The device sends the collected viewing distance data and emotion data to the server using a communication method. The viewing distance data and emotion data obtained in step 1 are used as input. The data is sent to the server in real time via a secure protocol (e.g., HTTPS). The output is the viewing distance data and emotion data sent to the server.

[1305] Step 3:

[1306] The server analyzes the received viewing distance data and emotion data. The inputs are the transmitted viewing distance data and emotion data. An AI algorithm (e.g., TensorFlow, PyTorch) on the server calculates vision correction data based on these data. The AI ​​algorithm performs vision correction appropriate for the user's viewing distance and generates correction data that reduces stress and fatigue based on the emotion data. The output is the calculated vision correction data.

[1307] Step 4:

[1308] The server sends the calculated vision correction data to the user terminal. The input is the vision correction data generated in step 3. The data is sent via the Internet as a transmission method. The output is the vision correction data sent to the user terminal.

[1309] Step 5:

[1310] The user terminal operates the lens control means based on the vision correction data received from the server to automatically adjust the lens. The input is the vision correction data received from the server. The focal length of the lens is automatically adjusted based on the vision correction data. The output is the adjusted lens.

[1311] Step 6:

[1312] The server also takes into account the user's emotional state (stress, fatigue) and activates a means to issue a warning if necessary. Emotional data is used as input. If a certain threshold is exceeded, an audio or visual warning is given to the user. The output is a warning notification.

[1313] This process flow allows the user to always receive optimal vision correction while also receiving warnings to ensure safe driving.

[1314] 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.

[1315] 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.

[1316] 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.

[1317] [Fourth embodiment]

[1318] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1319] 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.

[1320] 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).

[1321] 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.

[1322] 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.

[1323] 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).

[1324] 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.

[1325] 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.

[1326] 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.

[1327] 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.

[1328] 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.

[1329] 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.

[1330] 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."

[1331] This invention is an AI eyeglass system that automatically performs optimal vision correction according to the user's viewing distance. Specific embodiments for implementing this system will be described below.

[1332] overview

[1333] This system consists of a user terminal (eyeglasses device), a server, and a sensor device. Its purpose is to correct vision in real time based on the user's viewing distance when looking at different distances (close to home, PC, long distance, medium distance, etc.).

[1334] User terminal operation

[1335] The system starts operating when the user puts on the glasses. The user device has a built-in sensor for measuring visual distance, which detects the user's line of sight and focal length in real time. The detected visual distance data is sent to the server via the communication means in the user device.

[1336] Server Processing

[1337] The server receives the viewing distance data transmitted from the user terminal. The received data is analyzed by an AI algorithm on the server, and vision correction data is calculated. This calculation is performed to provide appropriate vision correction in real time according to the user's viewing distance. The calculated vision correction data is then transmitted back to the user terminal by the server's data transmission means.

[1338] Automatic lens adjustment

[1339] The user terminal receives the vision correction data sent from the server. Based on the received data, the lens control means built into the glasses operates and automatically adjusts the lenses to the appropriate focal length. This allows the user to comfortably see close-up and long-distance objects.

[1340] Specific examples

[1341] Example 1: When looking at your hands

[1342] User: When reading a newspaper, keep your eyes on the screen.

[1343] Terminal: The sensor detects that the viewing distance is close (approximately 30 cm) and sends that data to the server.

[1344] Server: Receives the visual distance data and calculates the appropriate near-distance vision correction data using an AI algorithm. Then, resends the data to the user device.

[1345] Device: Automatically adjusts the lens for close distances based on the received correction data.

[1346] Example 2: When looking into the distance

[1347] User: When looking at a distant scene, look into the distance.

[1348] Terminal: The sensor detects that the viewing distance is long (approximately 5m or more) and sends that data to the server.

[1349] Server: Receives the visual distance data and calculates the appropriate long-distance vision correction data using an AI algorithm. Then, resends the data to the user device.

[1350] Terminal: Automatically adjusts the lens for long distances based on the received correction data.

[1351] In this way, the system can automatically provide appropriate vision correction in real time according to the user's viewing distance, eliminating the need for multiple pairs of glasses and ensuring that the user always has a comfortable field of vision.

[1352] Instructions for use

[1353] 1. The user puts on the glasses.

[1354] 2. The sensor measures the viewing distance.

[1355] 3. The viewing distance data is sent to the server.

[1356] 4. The server calculates the vision correction data and sends it to the user's device.

[1357] 5. The user device adjusts the lens.

[1358] 6. Make sure the user looks comfortable.

[1359] By using this system, users can always receive optimal vision correction and reduce eye strain caused by long periods of close-up work.

[1360] The processing flow will be explained below.

[1361] Step 1:

[1362] The moment the user puts on the glasses, the sensor device activates and begins measuring the user's gaze direction and focal length in real time.

[1363] Step 2:

[1364] The device collects viewing distance data from sensors, which includes gaze direction and focal length, providing an accurate measurement of the distance to the object the user is looking at.

[1365] Step 3:

[1366] The device sends the collected visual distance data to the server using a communication method, and the data arrives immediately without delay.

[1367] Step 4:

[1368] The server receives the visual distance data sent from the user terminal. This data is information indicating the distance at which the line of sight is focused.

[1369] Step 5:

[1370] The server then analyzes the received visual distance data using an AI algorithm, which takes into account past data and usage patterns to calculate optimal vision correction data.

[1371] Step 6:

[1372] The server transmits the calculated vision correction data to the user terminal using the data transmission means, which indicates how the lenses should be adjusted.

[1373] Step 7:

[1374] The device receives vision correction data sent from the server, and based on this data, the lens is automatically adjusted to the appropriate focal length instantly.

[1375] Step 8:

[1376] Users can comfortably view objects close up and at a distance, and because vision correction occurs in real time, users can always maintain optimal vision for different viewing distances.

[1377] Step 9:

[1378] When the user changes their line of sight again, for example, moving their gaze away from the object in front of them, the entire process returns to step 1 and is carried out automatically. This allows the user to maintain a comfortable field of vision at all times without having to adjust their glasses themselves.

[1379] Example 1

[1380] 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."

[1381] Conventional eyeglass systems have the problem of being inconvenient, as users must wear different glasses for each different viewing distance, such as for something close to them, a PC, long-distance viewing, or medium-distance viewing.In addition, there is also the problem of eyestrain caused by prolonged close-up work, as vision correction is not performed appropriately according to the viewing distance.

[1382] 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.

[1383] In this invention, the server includes a sensor for measuring the user's visual distance in real time, a communication unit for transmitting the measured visual distance data to the server, an AI algorithm for calculating vision correction data based on the transmitted visual distance data, a data transmission unit on the server for transmitting the calculated vision correction data to the user terminal, a lens control unit for automatically adjusting the lenses based on the received vision correction data, a system initialization unit for managing the initialization process, a detection unit for detecting the line of sight and focal length in real time, and an encryption unit for securely transmitting the vision correction data to the server. This allows the user to automatically perform vision correction for different visual distances in real time, eliminating the need for multiple glasses. Furthermore, appropriate vision correction can reduce eye fatigue.

[1384] "Sensor means" is a device for measuring the user's viewing distance in real time.

[1385] "Communication means" refers to a method or device for transmitting measured viewing distance data to a server.

[1386] The "AI algorithm means on the server" is an artificial intelligence algorithm executed on the server to calculate vision correction data based on the transmitted viewing distance data.

[1387] The "server data transmission means" refers to a device or method for transmitting calculated vision correction data to a user terminal.

[1388] The "lens control means" is a mechanism or device for automatically adjusting the lenses based on the received vision correction data.

[1389] The "system initialization means" is a mechanism or device that performs initial settings to start the operation of the system.

[1390] "Detection means" refers to a device or method for detecting the line of sight and focal length in real time.

[1391] The "encryption means" is a data encryption technique for securely transmitting vision correction data to the server.

[1392] MODE FOR CARRYING OUT THE INVENTION

[1393] The present invention is an AI eyeglass system that automatically performs optimal vision correction according to the user's viewing distance. Specific embodiments for carrying out the present invention will be described below.

[1394] User terminal operation

[1395] The system begins operation when the user puts on the glasses. The user device is equipped with a built-in sensor for measuring visual distance, which detects the user's line of sight and focal length in real time. Specifically, it uses ToF (Time-of-Flight) technology to obtain the focal length of the line of sight in milliseconds. The detected visual distance data is sent to a server via a built-in communication method (e.g., Bluetooth or Wi-Fi). This communication is kept secure by encrypting the data.

[1396] Server Processing

[1397] The server receives the visual distance data sent from the user device. The received data is analyzed by an AI algorithm (for example, a deep learning model using TensorFlow or PyTorch) running on the server. The AI ​​algorithm uses a pre-trained vision correction model to calculate the optimal lens focal length in real time. The calculated vision correction data is then retransmitted to the user device via the server's data transmission means. This transmission is also encrypted and carried out via secure communication.

[1398] Automatic lens adjustment

[1399] The user terminal receives the vision correction data sent from the server. Based on the received data, the built-in lens control means (e.g., an electrically adjustable liquid crystal lens) operates and automatically adjusts the lens to the appropriate focal length. This allows the user to comfortably view close-up and distant objects.

[1400] Specific examples

[1401] Example 1: When looking at your hands

[1402] When a user reads a newspaper, they look directly at the screen.

[1403] The device's sensor detects that the viewing distance is 30 cm.

[1404] The sensor measures the focal length of the gaze and instantly stores the data in the device's memory.

[1405] The terminal transmits the data to the server.

[1406] The data is sent to a server via Bluetooth.

[1407] The server receives the visual distance data and uses an AI algorithm to calculate vision correction data for close distances.

[1408] The AI ​​model on the server calculates the optimal lens settings for viewing 30 cm ahead.

[1409] The server retransmits the correction data to the user terminal.

[1410] The correction data is encrypted and sent to the device over a secure connection.

[1411] The device automatically adjusts the lens for close distances based on the received correction data.

[1412] A lens control means adjusts the voltage to cause the lens to deform to a specified focal length.

[1413] Example 2: When looking into the distance

[1414] When a user views a distant scene, the user directs his or her gaze into the distance.

[1415] The device's sensor detects that the viewing distance is 5m or more.

[1416] The sensor measures the focal length of the gaze and instantly stores the data in the device's memory.

[1417] The terminal transmits the data to the server.

[1418] The data is sent to a server via Wi-Fi.

[1419] The server receives the viewing distance data and uses an AI algorithm to calculate vision correction data for long distances.

[1420] The AI ​​model on the server calculates the optimal lens settings for seeing more than 5m ahead.

[1421] The server retransmits the correction data to the user terminal.

[1422] The correction data is encrypted and sent to the device over a secure connection.

[1423] The device automatically adjusts the lens for long distances based on the received correction data.

[1424] A lens control means adjusts the voltage to cause the lens to deform to a specified focal length.

[1425] Example prompts for generative AI models

[1426] "Calculate the vision correction required for a user to read a newspaper 30 cm away."

[1427] "Calculate the visual acuity correction required when the user views a scene 5 meters away."

[1428] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1429] System program processing flow

[1430] Step 1: Initialize the system

[1431] Specific behavior:

[1432] The user puts on the glasses.

[1433] The terminal is powered on and the system initialization means starts operating. It checks whether the sensors are working properly and the communication module establishes a connection with the server. This initialization includes the initial setting data and calibration process for the system to operate.

[1434] Input: Eyeglasses wearing information

[1435] Output: System initialization complete signal

[1436] Step 2: Measure the viewing distance

[1437] Specific behavior:

[1438] The sensor means detects the user's gaze direction and focal length in real time.

[1439] The device uses ToF technology to capture the focal length of the line of sight, and the sensor collects data every millisecond and stores it in the device's memory.

[1440] Input: User gaze data

[1441] Output: View distance data

[1442] Step 3: Sending viewing distance data

[1443] Specific behavior:

[1444] The terminal transmits the acquired viewing distance data to the server using a communication means (for example, Bluetooth or Wi-Fi).

[1445] The device encrypts the data before sending it to ensure security. Specifically, the viewing distance data is sent using a specific protocol (e.g., HTTP / HTTPS).

[1446] Input: View distance data

[1447] Output: View distance data sent to the server

[1448] Step 4: Calculate the vision correction data

[1449] Specific behavior:

[1450] The server analyzes the received visual distance data using an AI algorithm.

[1451] Based on the received visual distance data, the server calculates the optimal vision correction data using a pre-trained vision correction model (using, for example, TensorFlow or PyTorch).

[1452] Input: Received sight distance data

[1453] Output: Vision correction data

[1454] Step 5: Submit vision correction data

[1455] Specific behavior:

[1456] The server retransmits the calculated vision correction data to the user terminal.

[1457] The server encrypts the data and sends it to the user's device over a secure connection, using a protocol (e.g. HTTP / HTTPS).

[1458] Input: Vision correction data

[1459] Output: Vision correction data sent to the device

[1460] Step 6: Automatic lens adjustment

[1461] Specific behavior:

[1462] The terminal automatically adjusts the lenses based on the received vision correction data.

[1463] The terminal operates a built-in lens control means (for example, an electrically adjustable liquid crystal lens), which adjusts the voltage to deform the lens to the specified focal length.

[1464] Input: Received vision correction data

[1465] Output: Adjusted lens focal length

[1466] Exemplary Processing Steps

[1467] Example 1: Processing flow when looking at your hands

[1468] When a user reads a newspaper, they tend to look at the screen.

[1469] The device's sensor detects a viewing distance of 30 cm.

[1470] The terminal transmits the data to the server.

[1471] The server analyzes the visual distance data using an AI algorithm and calculates vision correction data.

[1472] The server transmits the correction data to the terminal.

[1473] The device automatically adjusts the lens for close distances based on the received correction data.

[1474] Example 2: Processing flow when looking into the distance

[1475] When a user views a distant scene, the user directs his or her gaze into the distance.

[1476] The device's sensor detects a viewing distance of 5m or more.

[1477] The terminal transmits the data to the server.

[1478] The server analyzes the visual distance data using an AI algorithm and calculates vision correction data.

[1479] The server transmits the correction data to the terminal.

[1480] The device automatically adjusts the lens for long distances based on the received correction data.

[1481] (Application example 1)

[1482] 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."

[1483] Robot operators working in factories often have to work at multiple different viewing distances, making it difficult to maintain proper vision. In this regard, inadequate vision correction can make precision work difficult and potentially compromise efficiency and safety. In particular, in jobs that require frequent shifts of gaze between precision components close at hand and distant equipment, inadequate vision correction can lead to reduced work quality and eye fatigue.

[1484] 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.

[1485] In this invention, the server includes a sensor means for measuring the user's visual distance in real time, a communication means for transmitting the measured visual distance data to the server, an AI algorithm means on the server for calculating vision correction data based on the transmitted visual distance data, a data transmission means on the server for transmitting the calculated vision correction data to the user terminal, a lens control means for automatically adjusting the lens based on the received vision correction data, and a vision correction assist means for providing work assistance in a factory based on the user's visual distance measurement data. This enables robot operators working in a factory to receive optimal vision correction in real time according to their visual distance, improving the efficiency and quality of precision work and reducing eye fatigue.

[1486] "Sensor means" is a device for measuring the user's viewing distance in real time.

[1487] "Communication means" is a system for transmitting measured viewing distance data to a server.

[1488] The "AI algorithm means" is an algorithm that runs on the server and calculates vision correction data based on the transmitted viewing distance data.

[1489] The "data transmission means of the server" is a function of the server for transmitting calculated vision correction data to the user terminal.

[1490] The "lens control means" is a mechanism for automatically adjusting the lenses based on the received vision correction data.

[1491] The "vision correction assistance means" is a function for providing work assistance in a factory based on the user's visual distance measurement data.

[1492] This invention provides a system that enables operators working in a factory to receive optimal vision correction in real time according to their viewing distance. A specific embodiment of this system will be described in detail below.

[1493] System configuration

[1494] This system consists of a user terminal (smart glasses device), a server, and a sensor device.

[1495] User terminal operation

[1496] The system starts operation when the user puts on the smart glasses. The user device has a built-in sensor for measuring visual distance, which detects the user's line of sight and focal length in real time. The detected visual distance data is sent to the server via the communication means in the user device.

[1497] Server Processing

[1498] The server receives the viewing distance data transmitted from the user terminal. The received data is analyzed by an AI algorithm on the server, and vision correction data is calculated. This calculation is performed to provide appropriate vision correction in real time according to the user's viewing distance. The calculated vision correction data is then transmitted back to the user terminal by the server's data transmission means.

[1499] Automatic lens adjustment

[1500] The user terminal receives the vision correction data sent from the server. Based on the received data, the lens control means built into the glasses operates and automatically adjusts the lenses to the appropriate focal length. This allows the user to comfortably see close-up and long-distance objects.

[1501] Techniques and equipment used

[1502] Sensors (ToF sensors, etc.): Primarily used to measure line-of-sight distance.

[1503] Communication protocol: Data is sent and received using HTTP POST, etc.

[1504] AI Algorithm: A machine learning model for calculating vision correction data. For example, TensorFlow or PyTorch are used.

[1505] Smart glasses lens control system: Electronically controls lens focus adjustment.

[1506] Specific examples

[1507] As a concrete example, let's say a robot operator working in a smart factory uses the system in the following scenario:

[1508] Example 1: Task at hand

[1509] When an operator inspects a precision part in his or her hand, he or she focuses his or her gaze on the part.

[1510] The gaze sensor measures the visual distance of the hand and sends the data to the server.

[1511] The server-side AI quickly calculates vision correction data based on the viewing distance and sends it to the smart glasses.

[1512] Smart glasses automatically adjust vision, allowing operators to comfortably inspect precision parts at hand.

[1513] Example 2: Long-distance observation

[1514] When operators view distant equipment, they turn their gaze into the distance.

[1515] The gaze sensor measures the long-distance viewing distance and transmits the data to the server.

[1516] The server-side AI quickly calculates vision correction data based on long-distance viewing distance and sends it to the smart glasses.

[1517] Smart glasses automatically adjust vision, allowing operators to clearly see distant equipment.

[1518] Prompt Sentence Examples

[1519] The smart glasses are worn and the visual distance at hand is measured. The visual distance data is acquired by the sensor and sent to the server via an HTTP POST request. A machine learning model (TensorFlow) is used on the server side to calculate vision correction data. The calculation results are sent back to the smart glasses, which automatically adjust the visual acuity. As a result, the robot operator can comfortably inspect precision parts.

[1520] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1521] Step 1:

[1522] The user puts on the smart glasses and turns them on.

[1523] This action activates the smart glasses' built-in sensors, which measure the user's gaze direction and focal length in real time.

[1524] Input: User's gaze direction and focal length

[1525] Output: Real-time visual distance data

[1526] Step 2:

[1527] The communication module inside the smart glasses receives the visual distance data measured by the built-in sensor and sends it to the server.

[1528] This data is sent using an HTTP POST request.

[1529] Input: Real-time visual distance data

[1530] Output: View distance data sent to the server

[1531] Step 3:

[1532] The server receives the viewing distance data transmitted from the user terminal.

[1533] The server filters the received data to remove unwanted noise.

[1534] Input: View distance data sent to the server

[1535] Output: Noise-removed visual distance data

[1536] Step 4:

[1537] A server-side AI algorithm analyzes the filtered viewing distance data and calculates the optimal vision correction data.

[1538] This calculation uses a generative AI model (e.g., TensorFlow).

[1539] Input: filtered viewing distance data

[1540] Output: Vision correction data

[1541] Step 5:

[1542] The data transmitting means of the server transmits the calculated vision correction data to the smart glasses.

[1543] This process is also done using an HTTP POST request.

[1544] Input: Vision correction data

[1545] Output: Vision correction data sent to smart glasses

[1546] Step 6:

[1547] The lens control means of the smart glasses automatically adjusts the lenses based on the received vision correction data.

[1548] Specifically, the focal length of the lens is adjusted in real time to provide the user with the optimal field of view.

[1549] Input: Vision correction data sent to smart glasses

[1550] Output: Optimal vision with automatically adjusted lenses

[1551] Step 7:

[1552] The user checks the corrected vision and continues working as necessary.

[1553] This step provides feedback to confirm that the user has indeed achieved a comfortable field of view.

[1554] Input: Optimal vision with auto-adjusted lenses

[1555] Output: Improving user visual comfort and work efficiency

[1556] 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.

[1557] This invention is an AI glasses system that automatically performs optimal vision correction according to the user's viewing distance and also recognizes the user's emotions to provide an optimal field of view. Specific embodiments for implementing this system are described below.

[1558] overview

[1559] This system consists of a user terminal (eyeglasses device), a server, a sensor device, and an emotion engine. It aims to not only correct vision in real time based on the user's viewing distance when looking at something at different viewing distances, but also to suggest optimal vision correction according to the user's emotions.

[1560] User terminal operation

[1561] The system begins operation when the user puts on the glasses. The user device is equipped with a sensor that measures visual distance and an emotion engine that recognizes the user's emotions. The system detects the user's gaze direction and focal length, as well as facial expressions, voice, and heart rate, and collects visual distance and emotion data in real time.

[1562] Sending data

[1563] The user device sends the collected visual distance data and emotion data to the server using a communication method, and the data arrives immediately without delay.

[1564] Server Processing

[1565] The server receives the viewing distance data and emotion data transmitted from the user terminal, where the viewing distance data indicates the distance to an object the user is looking at, and the emotion data indicates the user's current emotional state.

[1566] Analysis by AI algorithm

[1567] The AI ​​algorithm on the server analyzes the received viewing distance data and emotional data and calculates vision correction data. The AI ​​algorithm not only performs appropriate vision correction based on the user's viewing distance, but also takes emotional data into account to suggest vision correction that the user finds most comfortable.

[1568] Sending correction data

[1569] The server sends the calculated vision correction data to the user terminal, which indicates how the lenses should be adjusted.

[1570] Automatic lens adjustment

[1571] The user terminal receives the vision correction data sent from the server, and the built-in lens control means of the glasses immediately operates to automatically adjust the lenses to the appropriate focal length, allowing the user to obtain a comfortable field of vision.

[1572] Specific examples

[1573] Example 1: When looking at your hands

[1574] User: I feel a little stressed while reading a book.

[1575] Terminal: Detects the viewing distance as close (approximately 30 cm) and senses the stress felt by the user from their facial expression.

[1576] Server: Receives visual distance data and "stress" emotion data, and uses an AI algorithm to calculate vision correction data for close distances and with an emphasis on stress reduction.

[1577] Terminal: Based on the received correction data, the lens is adjusted for close distances and vision correction is performed to reduce stress.

[1578] Example 2: When looking into the distance

[1579] User: I want to see the scenery in the distance, but I'm a little tired.

[1580] Terminal: Detects the viewing distance as long (approximately 5m or more) and senses "fatigue" from the user's facial expression and heart rate.

[1581] Server: Receives visual distance data and "fatigue" emotion data, and uses an AI algorithm to calculate vision correction data for long distances and to reduce fatigue.

[1582] Terminal: Based on the received correction data, the lenses are adjusted for long distances and vision correction is performed to reduce fatigue.

[1583] In this way, this system automatically performs appropriate vision correction in real time according to the user's viewing distance and can also optimize the correction taking into account the user's emotions, allowing the user to always maintain a comfortable field of vision and reduce eye and mental strain.

[1584] Instructions for use

[1585] 1. The user puts on the glasses.

[1586] 2. Sensors and emotion engines measure visual distance and emotion data.

[1587] 3. The viewing distance data and emotion data are sent to the server.

[1588] 4. The server calculates the vision correction data and sends it to the user's device.

[1589] 5. The user device adjusts the lens.

[1590] 6. Make sure the user looks comfortable.

[1591] By using this system, users can always receive optimal vision correction and maintain a comfortable field of vision that even takes their emotions into consideration.

[1592] The processing flow will be explained below.

[1593] Step 1:

[1594] The user puts on the glasses. This triggers the system to start up, and the sensor device and emotion engine begin to operate.

[1595] Step 2:

[1596] The device uses built-in sensors to measure gaze direction and focal length, allowing it to detect the distance of the object the user is looking at in real time.

[1597] Step 3:

[1598] The device recognizes the user's emotions using an emotion engine, which collects data from multiple sensors, including facial expressions, voice, and heart rate, to analyze the user's emotional state.

[1599] Step 4:

[1600] The device transmits the collected visual distance data and emotion data to the server using a communication method. These data are integrated into a single packet and are delivered to the server immediately.

[1601] Step 5:

[1602] The server receives the viewing distance data and emotion data sent from the user terminal. The received data indicates the gaze direction, focal length, and the user's emotional state.

[1603] Step 6:

[1604] The AI ​​algorithm on the server analyzes the received viewing distance data and emotional data, calculates appropriate vision correction data based on the user's viewing distance, and then adjusts the optimal vision correction value taking into account the emotional data.

[1605] Step 7:

[1606] The server transmits the calculated vision correction data to the user terminal using the data transmission means. The vision correction data is information indicating how the lens should be adjusted.

[1607] Step 8:

[1608] The terminal receives the vision correction data sent from the server. Based on the received data, the lens control means starts operation and automatically adjusts the lens to the appropriate focal length.

[1609] Step 9:

[1610] The system ensures that users can see objects close to them and at a distance for comfortable viewing. Vision correction is performed in real time, ensuring users always have optimal vision for different viewing distances. Furthermore, vision correction adjusts to the user's emotional state, reducing stress and fatigue.

[1611] Step 10:

[1612] If the user changes their gaze again, the change in gaze direction and emotional state is detected, and the whole process starts again from step 2. This allows the user to dynamically and continuously receive optimal vision correction.

[1613] Example 2

[1614] 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."

[1615] While conventional vision correction systems can correct a user's vision based on their viewing distance, they are unable to provide optimal vision correction by taking into account the user's emotional state. As a result, when a user is stressed or tired, optimal vision correction is not provided, resulting in an inability to achieve comfortable vision. Furthermore, conventional systems suffer from delays in the entire process from measuring viewing distance data to adjusting lenses, making it difficult to provide real-time vision correction.

[1616] 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.

[1617] In this invention, the server includes a sensor means for measuring the user's viewing distance in real time, an emotion recognition means for recognizing emotion data along with the viewing distance, a communication means for transmitting the measured viewing distance data and emotion data to the server, an AI algorithm means on the server for calculating vision correction data based on the transmitted viewing distance data and emotion data, a data transmission means on the server for transmitting the calculated vision correction data to the user terminal, and a lens control means for automatically adjusting the lens based on the received vision correction data. This enables real-time vision correction that simultaneously takes into account the user's viewing distance and emotional state.

[1618] "Sensor means" is a device for measuring the user's viewing distance in real time.

[1619] The "emotion recognition means" is a device for analyzing the user's facial expressions, voice, heart rate, etc. to obtain emotional data.

[1620] The "communication means" is a device for transmitting the measured viewing distance data and emotion data to the server.

[1621] The "AI algorithm means" is software for calculating vision correction data based on visual distance data and emotional data on a server.

[1622] The "data transmission means of the server" is a device for transmitting calculated vision correction data to the user terminal.

[1623] The "lens control means" is a device for automatically adjusting the lenses based on the received vision correction data.

[1624] A "user terminal" is a glasses-type device worn by a user.

[1625] This invention is an AI glasses system that automatically performs optimal vision correction according to the user's viewing distance and also recognizes the user's emotions to provide an optimal field of view. Next, specific embodiments for implementing this system will be described.

[1626] overview

[1627] This system consists of a user terminal (eyeglasses device), a server, a sensor device, and an emotion recognition engine. It aims to not only correct vision in real time based on the user's viewing distance when looking at something at different viewing distances, but also to suggest optimal vision correction according to the user's emotions.

[1628] User terminal operation

[1629] The system starts when the user puts on the glasses. The user device is equipped with a sensor that measures visual distance and an emotion recognition unit that recognizes the user's emotions. These sensors detect the user's gaze direction and focal length, as well as facial expressions, voice, and heart rate, and collect visual distance and emotion data in real time.

[1630] Sending data

[1631] The user device sends the collected visual distance data and emotion data to the server using a communication method such as Wi-Fi or Bluetooth. This data arrives at the server immediately and without delay.

[1632] Server Processing

[1633] The server receives the viewing distance data and emotion data transmitted from the user terminal, where the viewing distance data indicates the distance of an object the user is looking at, and the emotion data indicates the user's current emotional state.

[1634] Analysis by AI algorithm

[1635] The AI ​​algorithm installed on the server analyzes the received viewing distance data and emotional data and calculates vision correction data. This AI algorithm not only performs appropriate vision correction based on the user's viewing distance, but also takes emotional data into account to suggest vision correction that the user finds comfortable.

[1636] Sending correction data

[1637] The server sends the calculated vision correction data to the user terminal, which indicates how the lenses should be adjusted.

[1638] Automatic lens adjustment

[1639] The user terminal receives the vision correction data sent from the server, and the built-in lens control means of the glasses immediately operates to automatically adjust the lenses to the appropriate focal length, allowing the user to obtain a comfortable field of vision.

[1640] Specific examples

[1641] Example 1: When looking at your hands

[1642] User: I feel a little stressed while reading a book.

[1643] Terminal: Detects the viewing distance as close (approximately 30 cm) and senses the stress felt by the user from their facial expression.

[1644] Server: Receives visual distance data and "stress" emotion data, and uses an AI algorithm to calculate vision correction data for close distances and with an emphasis on stress reduction.

[1645] Terminal: Based on the received correction data, the lens is adjusted for close distances and vision correction is performed to reduce stress.

[1646] Example 2: When looking into the distance

[1647] User: I want to see the scenery in the distance, but I'm a little tired.

[1648] Terminal: Detects the viewing distance as long (approximately 5m or more) and senses "fatigue" from the user's facial expression and heart rate.

[1649] Server: Receives visual distance data and "fatigue" emotion data, and uses an AI algorithm to calculate vision correction data for long distances and to reduce fatigue.

[1650] Terminal: Based on the received correction data, the lenses are adjusted for long distances and vision correction is performed to reduce fatigue.

[1651] Prompt Sentence Examples

[1652] "Please suggest vision correction for users who experience stress at close range."

[1653] "Provide optimal vision correction for users who experience fatigue from looking at distant objects."

[1654] keyword

[1655] Generative AI Models

[1656] Prompt statement

[1657] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1658] Step 1:

[1659] The user puts on the glasses.

[1660] Input: User action (wearing glasses)

[1661] Output: The glasses' system activates.

[1662] How it works: When a user puts on the glasses, the sensor and emotion engine are automatically activated, which starts the process of visual distance measurement and emotion recognition.

[1663] Step 2:

[1664] The device collects viewing distance data and emotion data.

[1665] Input: User's gaze direction, facial expression, voice, heart rate

[1666] Output: Viewing distance data and emotion data are generated.

[1667] Specific operation: The device's built-in visual distance sensor measures the user's gaze direction and focal length, and the emotion recognition means analyzes the user's facial expressions, voice, heart rate, etc. to obtain emotional data. This data is updated in real time.

[1668] Step 3:

[1669] The device transmits the collected viewing distance data and emotion data to the server.

[1670] Input: Viewing distance data, emotion data

[1671] Output: Data is sent to the server.

[1672] Specific operation: The device transmits the acquired visual distance data and emotion data to the server via Wi-Fi or Bluetooth. The data is designed to reach the server immediately.

[1673] Step 4:

[1674] The server receives the viewing distance data and the emotion data.

[1675] Input: Viewing distance data, emotion data

[1676] Output: The data is stored in the server.

[1677] Specific operation: The server receives the viewing distance data and emotion data sent from the device and temporarily stores them in a database. This data is used for subsequent analysis.

[1678] Step 5:

[1679] The server analyzes the data using an AI algorithm and calculates vision correction data.

[1680] Input: Viewing distance data, emotion data

[1681] Output: Vision correction data

[1682] How it works: The AI ​​algorithm installed on the server analyzes the received visual distance data and emotional data. It uses the visual distance data to determine the distance of the object the user is looking at, and uses the emotional data to understand the user's psychological state. Based on this, it generates optimal vision correction data.

[1683] Step 6:

[1684] The server transmits the calculated vision correction data to the terminal.

[1685] Input: Vision correction data

[1686] Output: Vision correction data is sent to the device.

[1687] Specific operation: The server sends vision correction data to the device, including lens adjustment instructions. This data is sent accurately and without delay.

[1688] Step 7:

[1689] The device automatically adjusts the lenses based on vision correction data.

[1690] Input: Vision correction data

[1691] Output: Lens adjusted

[1692] Specific operation: The device's lens control mechanism adjusts the focal length of the lens based on the vision correction data to optimize the user's field of vision, thereby providing a comfortable field of vision for the user.

[1693] Step 8:

[1694] The user checks the field of view after adjustment and confirms that the vision correction is comfortable.

[1695] Input: Adjusted lens field of view

[1696] Output: Ensure comfortable visibility

[1697] What it does: The user puts on the glasses and checks if their vision improves. If it's not comfortable, the system may collect data again and make adjustments.

[1698] (Application example 2)

[1699] 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."

[1700] The present invention relates to a system that automatically provides optimal vision correction by measuring a driver's visual distance and emotions in real time. However, conventional vision correction systems lack the ability to detect driver stress and fatigue and respond immediately, which hinders safe driving. There is a need to solve this problem and ensure that drivers always receive optimal vision correction and safety warnings.

[1701] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a sensor means for measuring the user's visual distance in real time, a communication means for transmitting the measured visual distance data and emotion data to the server, an AI algorithm means on the server for calculating vision correction data based on the transmitted visual distance data and emotion data, a data transmission means on the server for transmitting the calculated vision correction data to the user terminal, a lens control means for automatically adjusting the lens based on the received vision correction data, and a warning means for detecting driver stress or fatigue in an autonomous vehicle and issuing a warning. This enables the driver to not only receive automatic vision correction according to the visual distance but also receive warnings according to stress or fatigue to increase safety while driving.

[1702] "User's viewing distance" is a real-time measurement of the distance to an object that the user is looking at.

[1703] "Sensor means" is a device for measuring the user's viewing distance in real time.

[1704] "Emotion data" is data that indicates the user's current emotional state, including stress, fatigue, and the like.

[1705] The "communication means" is a means for transmitting the measured viewing distance data and emotion data to the server.

[1706] "AI algorithm means on a server" refers to a server equipped with an artificial intelligence algorithm for calculating vision correction data based on visual distance data and emotion data.

[1707] The "data transmission means of the server" is a means for transmitting calculated vision correction data to the user terminal.

[1708] The "lens control means" is a means for automatically adjusting the lens based on the received vision correction data.

[1709] An "autonomous vehicle" is a vehicle that can drive itself using artificial intelligence and sensor technology.

[1710] "Warning means" refers to a means for detecting driver stress or fatigue in an autonomous vehicle and issuing a warning.

[1711] The present invention is a system for measuring the driver's visual distance and emotional data in real time in an autonomous vehicle, and providing optimal vision correction and warnings for fatigue and stress. The system includes the following means:

[1712] Operation of the sensor means

[1713] The system starts working when the user puts on the smart glasses. The smart glasses are equipped with sensors that measure visual distance in real time, as well as sensors that detect heart rate and facial expressions to obtain emotional data. This allows the system to collect information on the user's visual distance and emotions in real time.

[1714] Communication method operation

[1715] The smart glasses, which are the user's terminal, collect visual distance data and emotion data and immediately transmit them to a server. The data is sent securely and quickly using an internet connection.

[1716] AI algorithm means operation on the server

[1717] The server analyzes the received visual distance data and emotion data. An AI algorithm (e.g., TensorFlow, PyTorch) calculates optimal vision correction data based on this data. Based on the emotion data, corrections are made according to the user's stress and fatigue level, providing a comfortable field of vision. It also issues warnings as necessary.

[1718] Operation of data transmission means

[1719] The calculated vision correction data is transmitted to the user terminal through the server's data transmission means, and includes details on how to adjust the lenses.

[1720] Operation of the lens control means

[1721] The user terminal operates the lens control means to automatically adjust the lenses based on the received vision correction data. This adjustment allows the user to always receive optimal vision correction and maintain clear vision.

[1722] Warning mechanism operation

[1723] The system of an autonomous vehicle is equipped with a means to issue a warning via voice or display notification if it determines that the user is experiencing high levels of stress or fatigue, thereby assisting the driver in driving safely.

[1724] Specific examples

[1725] Example of visual distance and emotion data collection

[1726] When the user is wearing the smart glasses, the visual distance is detected as approximately 0.35m, the heart rate is detected as 85, and the emotion is detected as "stressed."

[1727] Vision correction and warning examples

[1728] The server receives this data and generates vision correction data and a warning to "take a break." This data is sent to the user's terminal, and the user is notified to take a break and the lenses are adjusted.

[1729] Prompt Sentence Examples

[1730] "If the user is tired, generate an alert to relax with vision correction: Analyze the data of visual distance 0.35m, heart rate 85, and emotion 'stressed' to suggest the necessary vision correction and display recommended actions to reduce fatigue."

[1731] This system will enable drivers in self-driving vehicles to accurately correct their vision while detecting stress and fatigue, supporting safe driving.

[1732] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1733] Step 1:

[1734] The system starts working when the user puts on the smart glasses. The glasses' built-in visual distance sensor and emotion sensors (heart rate, facial expression recognition) collect data as input. This results in visual distance data and emotion data. The output is the collected visual distance data and emotion data.

[1735] Step 2:

[1736] The device sends the collected viewing distance data and emotion data to the server using a communication method. The viewing distance data and emotion data obtained in step 1 are used as input. The data is sent to the server in real time via a secure protocol (e.g., HTTPS). The output is the viewing distance data and emotion data sent to the server.

[1737] Step 3:

[1738] The server analyzes the received viewing distance data and emotion data. The inputs are the transmitted viewing distance data and emotion data. An AI algorithm (e.g., TensorFlow, PyTorch) on the server calculates vision correction data based on these data. The AI ​​algorithm performs vision correction appropriate for the user's viewing distance and generates correction data that reduces stress and fatigue based on the emotion data. The output is the calculated vision correction data.

[1739] Step 4:

[1740] The server sends the calculated vision correction data to the user terminal. The input is the vision correction data generated in step 3. The data is sent via the Internet as a transmission method. The output is the vision correction data sent to the user terminal.

[1741] Step 5:

[1742] The user terminal operates the lens control means based on the vision correction data received from the server to automatically adjust the lens. The input is the vision correction data received from the server. The focal length of the lens is automatically adjusted based on the vision correction data. The output is the adjusted lens.

[1743] Step 6:

[1744] The server also takes into account the user's emotional state (stress, fatigue) and activates a means to issue a warning if necessary. Emotional data is used as input. If a certain threshold is exceeded, an audio or visual warning is given to the user. The output is a warning notification.

[1745] This process flow allows the user to always receive optimal vision correction while also receiving warnings to ensure safe driving.

[1746] 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.

[1747] 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.

[1748] 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.

[1749] 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.

[1750] 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.

[1751] 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.

[1752] 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).

[1753] 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.

[1754] 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."

[1755] 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.

[1756] 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).

[1757] 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.

[1758] 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.

[1759] 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.

[1760] 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.

[1761] 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.

[1762] 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.

[1763] 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.

[1764] 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.

[1765] 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.

[1766] 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.

[1767] The following is further disclosed regarding the above embodiment.

[1768] (Claim 1)

[1769] a sensor means for measuring the user's viewing distance in real time;

[1770] a communication means for transmitting the measured visual distance data to a server;

[1771] An AI algorithm means on a server that calculates vision correction data based on the transmitted visual distance data;

[1772] a data transmission means of the server for transmitting the calculated vision correction data to the user terminal;

[1773] a lens control means for automatically adjusting the lens based on the received vision correction data;

[1774] A system including:

[1775] (Claim 2)

[1776] The system of claim 1, further comprising a server means for receiving a user's viewing distance data and calculating vision correction data, the server means calculating the vision correction data by an AI algorithm.

[1777] (Claim 3)

[1778] The system according to claim 1, further comprising a control means for sensing the user's viewing distance in real time and feeding back vision correction data to automatically adjust the lens as a means for interoperating between the sensor and the lens control.

[1779] "Example 1"

[1780] (Claim 1)

[1781] a sensor means for measuring the user's viewing distance in real time;

[1782] a communication means for transmitting the measured visual distance data to a server;

[1783] An AI algorithm means on a server that calculates vision correction data based on the transmitted visual distance data;

[1784] a data transmission means of the server for transmitting the calculated vision correction data to the user terminal;

[1785] a lens control means for automatically adjusting the lens based on the received vision correction data;

[1786] a system initialization means for managing an initialization process;

[1787] detection means for detecting the line of sight direction and focal length in real time;

[1788] A system including encryption means for securely transmitting vision correction data to a server.

[1789] (Claim 2)

[1790] 10. The system of claim 1, further comprising an AI algorithm means for receiving the user's viewing distance data and calculating the vision correction data, wherein the vision correction data is calculated by an AI model executed on a server.

[1791] (Claim 3)

[1792] The system according to claim 1, further comprising a control means for sensing the user's viewing distance in real time and feeding back vision correction data to automatically adjust the lens as a means for interoperating between the sensor and lens control, and a protocol means for transmitting and receiving data via a communication means.

[1793] "Application Example 1"

[1794] (Claim 1)

[1795] a sensor means for measuring the user's viewing distance in real time;

[1796] a communication means for transmitting the measured visual distance data to a server;

[1797] An AI algorithm means on a server that calculates vision correction data based on the transmitted visual distance data;

[1798] a data transmission means of the server for transmitting the calculated vision correction data to the user terminal;

[1799] a lens control means for automatically adjusting the lens based on the received vision correction data;

[1800] a vision correction assist means for assisting work in a factory based on the visual distance measurement data of the user;

[1801] A system including:

[1802] (Claim 2)

[1803] The system of claim 1 calculates vision correction data using an AI algorithm to optimize the field of vision of a user operating a factory robot in real time.

[1804] (Claim 3)

[1805] 10. The system according to claim 1, further comprising control means for correcting vision based on the user's line of sight and focal length, thereby improving the efficiency of precision work in a factory.

[1806] "Example 2: Combining Emotion Engines"

[1807] (Claim 1)

[1808] a sensor means for measuring the user's viewing distance in real time;

[1809] emotion recognition means for recognizing emotion data along with viewing distance;

[1810] a communication means for transmitting the measured visual distance data and emotion data to a server;

[1811] An AI algorithm means on a server that calculates vision correction data based on the transmitted visual distance data and emotion data;

[1812] a data transmission means of the server for transmitting the calculated vision correction data to the user terminal;

[1813] a lens control means for automatically adjusting the lens based on the received vision correction data;

[1814] A system including:

[1815] (Claim 2)

[1816] 10. The system of claim 1, further comprising an AI algorithm means for receiving the user's viewing distance data and emotion data and calculating the vision correction data.

[1817] (Claim 3)

[1818] The system according to claim 1, further comprising a control means for sensing the user's visual distance and emotions in real time and feeding back vision correction data to automatically adjust the lens as a means for interoperating between the sensor and emotion recognition means and the lens control means.

[1819] "Application example 2 when combining emotion engines"

[1820] (Claim 1)

[1821] a sensor means for measuring the user's viewing distance in real time;

[1822] a communication means for transmitting the measured visual distance data and emotion data to a server;

[1823] An AI algorithm means on a server that calculates vision correction data based on the transmitted visual distance data and emotion data;

[1824] a data transmission means of the server for transmitting the calculated vision correction data to the user terminal;

[1825] a lens control means for automatically adjusting the lens based on the received vision correction data;

[1826] A warning means for detecting driver stress or fatigue in an autonomous vehicle and issuing a warning;

[1827] A system including:

[1828] (Claim 2)

[1829] 10. The system of claim 1, further comprising an AI algorithm means for receiving the user's viewing distance data and emotion data and calculating the vision correction data.

[1830] (Claim 3)

[1831] The system according to claim 1, further comprising a control means for sensing the user's visual distance and emotions in real time, feeding back vision correction data, and automatically adjusting the lens, as a means for interoperating between the sensor and the lens control. [Explanation of symbols]

[1832] 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 sensor means for measuring the user's viewing distance in real time; a communication means for transmitting the measured visual distance data to a server; An AI algorithm means on a server that calculates vision correction data based on the transmitted visual distance data; a data transmission means of the server for transmitting the calculated vision correction data to the user terminal; a lens control means for automatically adjusting the lens based on the received vision correction data; A system including:

2. The system of claim 1, further comprising a server means for receiving a user's viewing distance data and calculating vision correction data, the server means calculating the vision correction data by an AI algorithm.

3. The system according to claim 1, further comprising a control means for sensing the user's viewing distance in real time and feeding back vision correction data to automatically adjust the lens as a means for interoperating between the sensor and the lens control.

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