System

Abstract

A system is provided.SOLUTION: A system for evaluating a driving behavior of a driver, comprising: means for measuring an inter-vehicle distance and a traveling speed from a device mounted on a vehicle; means for transmitting data of the measured inter-vehicle distance and traveling speed to a server; means for analyzing the transmitted data and calculating an evaluation point; and means for notifying the driver of the calculated evaluation point.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] ---

[0005] Previously, there was no system in place to evaluate the safe driving of drivers on expressways, and dangerous driving often went unnoticed. This increased the risk of accidents and posed a problem in terms of personnel costs for patrols. Furthermore, a lack of feedback to drivers meant there was no incentive to promote safe driving. To solve these issues and realize a safe motorized society, an effective safe driving evaluation and feedback system is needed. [Means for solving the problem]

[0006] The present invention provides a system for evaluating a driver's driving behavior in real time using an AI camera and a GPS device mounted on a vehicle. Specifically, the above-mentioned problems are solved by using the following means.

[0007] 1. A means of measuring vehicle distance and speed from a device installed in a vehicle.

[0008] 2. A means for transmitting the measured inter-vehicle distance and driving speed data to a server.

[0009] 3. A means for analyzing the transmitted data and calculating evaluation points.

[0010] 4. A means of notifying the driver of the calculated evaluation points.

[0011] Furthermore, the present invention includes the following means to provide feedback to the driver and to achieve effective patrol.

[0012] 5. A means of providing rewards to drivers based on rating points.

[0013] 6. A means of sharing assessment points with law enforcement agencies.

[0014] 7. A means of generating and transmitting lists of dangerous drivers to law enforcement agencies.

[0015] Additionally, if the device has GPS functionality, the following methods are also included:

[0016] 8. A means for analyzing the measured position information and evaluating it by comparing it with the speed limit of the road.

[0017] This will enable timely evaluation of driver behavior and provide incentives to promote safe driving, while information sharing with police agencies will enable more efficient patrols and accident prevention.

[0018] ---

[0019] A "device" is a device that is installed in a vehicle and that measures the distance between vehicles, driving speed, location information, and the like.

[0020] "Following distance" refers to the distance between the vehicle ahead and your own vehicle.

[0021] "Traveling speed" refers to the speed at which a vehicle travels on a road.

[0022] "GPS function" refers to the technology that uses the Global Positioning System to identify any location on Earth.

[0023] "Server" refers to a central control device that receives, analyzes, and stores data, and issues various notifications and instructions.

[0024] "Evaluation points" refer to scores calculated based on the driver's driving behavior.

[0025] "Benefits" refers to rewards, discounts, etc. provided based on the driver's evaluation points.

[0026] "Police agency" means a government agency tasked with maintaining public safety and order and enforcing the law.

[0027] A "dangerous driver" is a driver who does not meet safe driving standards and engages in dangerous behavior while driving.

[0028] "Real-time" means that data is processed and analyzed immediately at the moment it is generated. [Brief explanation of the drawings]

[0029] [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

[0030] 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.

[0031] First, the terms used in the following description will be explained.

[0032] 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).

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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."

[0037] [First embodiment]

[0038] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0039] 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.

[0040] 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).

[0041] 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.

[0042] 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.

[0043] 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.

[0044] 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.

[0045] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0046] 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.

[0047] 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.

[0048] 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.

[0049] 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."

[0050] ---

[0051] A system for implementing the present invention comprises a device installed in a vehicle, a server, and a user interface used by the driver.

[0052] Data collection and transmission

[0053] The terminal (AI camera and GPS device installed in the vehicle) performs the following functions while the vehicle is driving.

[0054] The distance between vehicles is measured using an AI camera.

[0055] Driving speed and location information are obtained using a GPS device.

[0056] The collected data is sent to a server at a predetermined timing or at regular intervals.

[0057] For example, a vehicle traveling on a highway automatically measures the distance to the vehicle ahead and acquires real-time speed and location information using a GPS device. This data is then sent to a server via the vehicle's communications equipment.

[0058] Data analysis and evaluation

[0059] The server receives the data sent from the terminal and performs the following analysis and evaluation.

[0060] Analyze data on vehicle distance and speed according to safe driving standards.

[0061] Based on the analysis results, evaluation points are calculated.

[0062] Each driver's rating points are recorded in a database.

[0063] For example, if the following distance meets the safety standard, points are added, while if the following distance is too short and the speed is over the limit, points are subtracted.

[0064] Point notification and management

[0065] The server manages the evaluation points for each driver and performs the following operations:

[0066] When a driver's evaluation points are updated, the results will be notified in real time.

[0067] Drivers can log in to the server and check their rating points and details.

[0068] It also has a function for offering rewards based on points (e.g., discounts on license renewal fees, discounts on car insurance premiums).

[0069] For example, a driver who continues to drive safely will receive a notification from the server saying, "You have been awarded 10 points," and the driver's history can be viewed on the user interface.

[0070] Information sharing with the police

[0071] The server shares information with police agencies.

[0072] Organize data on drivers who have been detected driving recklessly.

[0073] Regularly compile and share lists of dangerous drivers.

[0074] Based on this, the police can carry out focused patrols.

[0075] For example, a list of drivers who frequently engage in dangerous driving could be compiled and sent to the police, who could then use it to efficiently plan patrols and prevent accidents.

[0076] Specific examples

[0077] Data collected by the device:

[0078] Distance between vehicles: Always appropriate (e.g., maintain a distance of at least 2 seconds)

[0079] Driving speed: Within the speed limit (e.g. always adhere to the speed limit of 100km / h)

[0080] Server Action:

[0081] The received data is analyzed and determined to meet all criteria.

[0082] Safe driving points are added to the driver (e.g., 10 points are added).

[0083] User Action:

[0084] Drivers log in to the server and check their evaluation points.

[0085] Apply for a discount on your license renewal fee based on your safe driving points (e.g., 20 points for a 5% discount).

[0086] In this way, the system of the present invention evaluates the driver's driving behavior in real time, promotes safe driving, and supports the efficiency of patrols and accident prevention through effective information sharing with police agencies.

[0087] The processing flow will be explained below.

[0088] ---

[0089] Step 1:

[0090] While the vehicle is moving, the device uses an AI camera to measure the distance to the vehicle ahead, and also obtains driving speed and location information using a GPS device.

[0091] Step 2:

[0092] The terminal formats the data it acquires, including vehicle distance, driving speed, and location information, and sends it to the server via the communication module.

[0093] Step 3:

[0094] The server analyzes the data received from the device, specifically assessing whether the distance between vehicles meets safety standards and whether the driving speed exceeds the speed limit.

[0095] Step 4:

[0096] The server calculates evaluation points based on the analysis results, adding points if safe driving is confirmed and subtracting points if dangerous driving is confirmed.

[0097] Step 5:

[0098] The server records each driver's rating points in a database, and if new points are added, the driver's total points are updated.

[0099] Step 6:

[0100] The server sends notifications based on changes in the driver's rating points, either via the application or email associated with the user's account.

[0101] Step 7:

[0102] The user logs in to the server and checks his / her own rating points and driving rating. If the user wants to apply for a reward, he / she selects a discount or reward based on the points and executes the application.

[0103] Step 8:

[0104] The server receives the reward request from the user, checks the validity of the points, and if the conditions are met, applies the reward and deducts the points.

[0105] Step 9:

[0106] The server compiles data on dangerous drivers and periodically creates a list, which is sent to police agencies and updated as needed.

[0107] Step 10:

[0108] Police can efficiently plan and carry out patrols based on the list of dangerous drivers received from the server, and can also issue direct warnings and take action as necessary.

[0109] ---

[0110] Through the above steps, the system of the present invention evaluates the driver's driving behavior, promotes safe driving, and works to prevent accidents by sharing information with police agencies.

[0111] Example 1

[0112] 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."

[0113] Conventional driving behavior evaluation systems have had problems such as incomplete data collection, such as measurement of vehicle distance and speed, and delayed notification of evaluation results. Furthermore, there were also problems with inefficient rewards based on evaluation points and collaboration with police agencies. As a result, they have not been able to adequately motivate drivers to drive safely or prevent dangerous driving.

[0114] 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.

[0115] In this invention, the server includes a means for measuring the distance and speed from a device mounted on the vehicle, a means for transmitting the measured distance and speed data to a data processing device, a means for analyzing the transmitted data and calculating an evaluation value, and a means for notifying the driver of the calculated evaluation value. This enables multifaceted and real-time evaluation of driving behavior. In addition, rewards based on the evaluation value and information sharing with police agencies can be efficiently carried out, which is expected to promote safe driving and prevent dangerous driving.

[0116] A "driving behavior evaluation system" is a system that uses a device installed in a vehicle to measure and evaluate a driver's driving behavior, and notifies and manages the results.

[0117] "Device" is a general term for measuring instruments and communication equipment attached to a vehicle, and is a device that has the function of collecting data such as vehicle-to-vehicle distance, speed, and location information.

[0118] "Inter-vehicle distance" refers to the distance between a moving vehicle and the vehicle in front of it.

[0119] "Speed" refers to the rate at which a vehicle travels a distance in a given time, and is typically expressed in kilometers per hour (km / h).

[0120] A "data processing device" is a computer system that receives collected data, analyzes it, and calculates evaluation values.

[0121] The "evaluation value" is a value calculated based on the analyzed data to indicate the safety and appropriateness of driving behavior.

[0122] "Notification" is an act of communicating information to the driver about the calculated evaluation value, and is performed in real time.

[0123] "Rewards" refers to incentives and benefits offered to drivers based on their rating figures.

[0124] "Patrol agencies" refer to law enforcement agencies such as the police, which work in conjunction with the driving behavior assessment system to monitor and crack down on dangerous driving.

[0125] The "list" is a report or database format that organizes and lists information on dangerous drivers.

[0126] The system for carrying out the present invention comprises a terminal installed in a vehicle, a server, and a user interface used by the driver. This system has the following technical configuration.

[0127] Data collection and transmission

[0128] The terminal (a device installed in the vehicle) performs the following functions while the vehicle is moving:

[0129] The distance between vehicles is measured using an AI camera.

[0130] Driving speed and location information are obtained using a GPS device.

[0131] The collected data is sent to a server at a predetermined timing or at regular intervals.

[0132] For example, a vehicle traveling on a highway automatically measures the distance to the vehicle ahead and acquires real-time speed and location information using a GPS device. This data is then sent to a server via the vehicle's communications equipment.

[0133] Data analysis and evaluation

[0134] The server receives the data sent from the terminal and performs the following analysis and evaluation.

[0135] Analyze data on vehicle distance and speed according to safe driving standards.

[0136] Based on the analysis results, an evaluation value is calculated.

[0137] Each driver's rating is recorded in a database.

[0138] For example, if the following distance meets the safety standard, points are added, while if the following distance is too short and the speed is over the limit, points are subtracted.

[0139] Point notification and management

[0140] The server manages the evaluation values ​​for each driver and performs the following operations:

[0141] When a driver's rating is updated, the results will be notified in real time.

[0142] Drivers can log in to the server and check their rating numbers and details.

[0143] It also has a function to offer benefits based on the evaluation figures (e.g., discounts on license renewal fees, discounts on car insurance premiums).

[0144] For example, a driver who continues to drive safely will receive a notification from the server saying, "You have been awarded 10 points," and the driver's history can be viewed on the user interface.

[0145] Information sharing with the police

[0146] The server shares information with police agencies.

[0147] Organize data on drivers who have been detected driving recklessly.

[0148] Regularly compile and share lists of dangerous drivers.

[0149] Based on this, the police will carry out intensive patrols.

[0150] For example, a list of drivers who frequently engage in dangerous driving will be compiled and sent to the police, who will then use this information to efficiently plan patrols and work to prevent accidents.

[0151] Specific examples

[0152] Data collected by the device:

[0153] Distance between vehicles: Always appropriate (e.g., maintain a distance of at least 2 seconds)

[0154] Driving speed: Within the speed limit (e.g. always adhere to the speed limit of 100km / h)

[0155] Server Action:

[0156] The received data is analyzed and determined to meet all criteria.

[0157] Safe driving points are added to the driver (e.g., 10 points are added).

[0158] User Action:

[0159] Drivers log in to the server and check their evaluation points.

[0160] Apply for a discount on your license renewal fee based on your safe driving points (e.g., 20 points for a 5% discount).

[0161] The system of this invention evaluates the driving behavior of drivers in real time to promote safe driving. It also supports the efficiency of patrols and accident prevention through effective information sharing with police agencies.

[0162] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0163] Step 1:

[0164] Data collection

[0165] The terminal (an AI camera or GPS device installed inside the vehicle) collects data from the vehicle while it is in motion.

[0166] Input: distance between vehicles, driving speed, location information

[0167] Specific operation: When the vehicle starts moving, the AI ​​camera measures the distance to the vehicle in front, and the GPS device collects the vehicle's speed and location information. For example, the AI ​​camera measures the distance every second, and the GPS device similarly obtains the vehicle's current location and speed every second.

[0168] Output: Inter-vehicle distance data, speed data, location data

[0169] Step 2:

[0170] Data transmission

[0171] The terminal transmits the collected data to the server.

[0172] Input: Inter-vehicle distance data, speed data, location data

[0173] Specific operation: Collected data is packaged at regular intervals (e.g., 1 minute) and sent to a server using the vehicle's communications equipment. The transmission interval can be adjusted, but a short interval is recommended to ensure real-time data transmission.

[0174] Output: Data package received by the server

[0175] Step 3:

[0176] Data analysis

[0177] The server analyzes the data sent from the terminal.

[0178] Input: Received data package (distance data, speed data, location data)

[0179] Specific operation: The server applies an analysis algorithm to the received data and compares it with safe driving standards. For example, if the distance between vehicles is more than 2 seconds and the driving speed is within the speed limit, it is judged as safe driving and points are added to the driver's score. If there is a violation, points are subtracted.

[0180] Output: Rating points

[0181] Step 4:

[0182] Calculation of evaluation points

[0183] The server calculates the evaluation points based on the analysis results.

[0184] Input: Analysis results (distance between vehicles, speed)

[0185] Specific operation: Calculates the evaluation points based on the analysis results. For example, add or subtract points from each analysis data to calculate the overall evaluation points.

[0186] Output: Calculated rating points

[0187] Step 5:

[0188] Point notification

[0189] The server notifies the driver of the calculated evaluation points.

[0190] Input: Rating points

[0191] Specific operation: Once the evaluation points have been calculated, the driver is notified in real time. For example, a notification saying "10 points added" is displayed on a smartphone app or on the in-car display.

[0192] Output: Rating points reported to the driver

[0193] Step 6:

[0194] Check in the user interface

[0195] The user (driver) checks the evaluation points.

[0196] Input: Notifications from the server, login information

[0197] How it works: Drivers can log in to the app on their smartphone or in-car display and check their rating point history and details. For example, it will show "Current points: 50 points," and they can also check the history and data analysis details.

[0198] Output: Driver's rating points information

[0199] Step 7:

[0200] Information sharing with the police

[0201] The server shares information with police agencies.

[0202] Input: Dangerous driving data, evaluation point data

[0203] Specific operation: The server creates a list of drivers who have been detected as driving recklessly and periodically provides it to the police. For example, a list such as "Driver A - Insufficient distance - 3 times, Driver B - Speeding - 2 times" is generated and uploaded to the police database.

[0204] Output: A list of dangerous drivers provided to police agencies

[0205] (Application example 1)

[0206] 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."

[0207] Conventional driving behavior evaluation systems lack sufficient data visualization and real-time feedback, making it difficult to immediately promote safe driving by drivers. In addition, there was a lack of means to provide immediate alerts for dangerous driving behavior, making it difficult to ensure safety.

[0208] 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.

[0209] In this invention, the server includes a means for measuring the inter-vehicle distance and traveling speed from a device mounted on the vehicle, a means for transmitting the measured inter-vehicle distance and traveling speed data to the server, a means for analyzing the transmitted data and calculating an evaluation point, a means for notifying the driver of the calculated evaluation point, a means for visualizing the inter-vehicle distance and traveling speed information in real time, and a means for providing visual and audio alerts as necessary, thereby enabling the driver to immediately understand his / her driving behavior while driving and receive appropriate feedback to maintain safe driving.

[0210] "Following distance" refers to the physical distance between you and the vehicle in front.

[0211] "Traveling speed" refers to the speed at which a vehicle is moving.

[0212] "Server" refers to the system that analyzes collected data, calculates and manages evaluation points.

[0213] "Device" refers to a device installed in a vehicle that measures the distance between vehicles and the driving speed.

[0214] "Evaluation points" refer to points calculated based on the driver's driving behavior.

[0215] "Driver" means a person who drives a vehicle.

[0216] "Real-time" refers to the instantaneous collection and processing of data.

[0217] "Visualization" refers to the visual display of data.

[0218] "Visual alert" refers to a visual warning that alerts the driver.

[0219] "Voice alert" refers to a function that warns the driver by voice.

[0220] "Location information function" refers to technology such as GPS for measuring current location.

[0221] An "unsafe driver" is a driver whose driving behavior does not meet safe driving standards.

[0222] "Benefits" refers to rewards and benefits provided to drivers based on their rating points.

[0223] A system for implementing the present invention comprises a device installed in a vehicle, a server, and a user interface used by the driver.

[0224] Data collection and transmission

[0225] The terminal (such as a camera or GPS device mounted in the vehicle) performs the following functions while the vehicle is traveling:

[0226] The distance between vehicles is measured using a camera.

[0227] Driving speed and location information are obtained using a GPS device.

[0228] This data is transmitted to the server at regular intervals.

[0229] For example, a vehicle traveling on a highway automatically measures the distance to the vehicle ahead, obtains speed and location information in real time using a GPS device, and transmits the collected data to a server via communication equipment inside the vehicle.

[0230] Data analysis and evaluation

[0231] The server receives the data sent from the terminal and performs the following analysis and evaluation.

[0232] Data on vehicle distance and driving speed is analyzed, and evaluation points are calculated according to safe driving standards.

[0233] Each driver's rating points are recorded in a database.

[0234] For example, points are added if the following distance meets safety standards, while points are subtracted if the following distance is too short and the speed is above the limit.

[0235] Point notification and management

[0236] The server manages the evaluation points for each driver and performs the following operations:

[0237] When a driver's evaluation points are updated, the results will be notified in real time.

[0238] Drivers can log in to the server and check their rating points and details.

[0239] It also has the ability to offer rewards based on points (e.g., discounts on license renewal fees, discounts on car insurance premiums).

[0240] For example, a driver who continues to drive safely will receive a notification from the server saying, "You have been awarded 10 points," and the driver's history can be viewed on the user interface.

[0241] Real-time visibility and alerts

[0242] Smart glasses or a head-mounted display (HMD) can be used as a user interface.

[0243] Visualize real-time information on distance and driving speed.

[0244] Provide visual and audio alerts as needed.

[0245] For example, a driver can see through smart glasses that the distance to the vehicle ahead is 15m and the speed is 90km / h, and a visual and audio alert will be issued if the distance becomes too close.

[0246] Information sharing with the police

[0247] The server shares information with police agencies.

[0248] Organize data on drivers who have been detected driving recklessly.

[0249] Regularly compile and share lists of dangerous drivers.

[0250] Based on this, the police can carry out focused patrols.

[0251] For example, a list of drivers who frequently engage in dangerous driving could be created and sent to the police, allowing them to efficiently plan patrols and work to prevent accidents.

[0252] Program processing

[0253] The server uses Python and TensorFlow for remote data analysis, processes data sent from vehicles in real time, calculates evaluation points, and generates safe driving alerts. It also uses the requests library to manage data transmission and reception.

[0254] For example, while driving, drivers can check the information displayed on the smart glasses and, if a safe distance is maintained, receive a notification that "safe driving points have been added." Visual and audio alerts provide immediate warning when unsafe conditions occur.

[0255] Prompt Sentence Examples

[0256] "This application displays real-time driving data on smart glasses, monitors the distance and speed of vehicles in front of the car, and sends an alert when the distance falls below a certain level."

[0257] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0258] Step 1:

[0259] The device collects data on vehicle distance and speed.

[0260] Specific operation: The camera installed on the device uses an AI model to measure the distance to the vehicle ahead, and the GPS device obtains the current driving speed and location information.

[0261] Input: Video data, GPS data.

[0262] Output: Inter-vehicle distance, speed, position information.

[0263] Step 2:

[0264] The terminal transmits the collected data to the server.

[0265] Specific operation: Data is encoded at regular intervals and sent to the server via the terminal's communication equipment.

[0266] Input: distance, speed, location.

[0267] Output: The data sent to the server.

[0268] Step 3:

[0269] The server parses the received data.

[0270] Specific operation: The server uses the TensorFlow model to analyze the transmitted distance and speed data and calculates evaluation points according to safe driving standards.

[0271] Input: distance, speed, location.

[0272] Data processing: analysis, calculation of evaluation points.

[0273] Output: Rating points.

[0274] Step 4:

[0275] The server notifies the driver of the evaluation points.

[0276] How it works: The evaluation points are calculated and displayed in real time on the driver's user interface (smart glasses or HMD). Visual and audio alerts are also provided if necessary.

[0277] Input: Rating points.

[0278] Output: Rating points notified to the driver, visual and audio alerts.

[0279] Step 5:

[0280] The server records the evaluation points in a database and provides rewards.

[0281] Specific operation: The evaluation points are recorded in a database and the driver is given benefits (e.g., a discount on license renewal fees).

[0282] Input: Rating points.

[0283] Output: Reputation points recorded in the database, rewards provided.

[0284] Step 6:

[0285] The server shares information with police agencies and generates a list of dangerous drivers.

[0286] Specific operation: Based on the analysis results, a list of dangerous drivers is created and sent to police agencies on a regular basis.

[0287] Input: Evaluation point data.

[0288] Data processing: List generation.

[0289] Output: A list of dangerous drivers sent to police agencies.

[0290] Step 7:

[0291] Police will conduct targeted patrols based on a list of dangerous drivers.

[0292] Specific actions: Based on the list sent, police will develop patrol plans for areas with high rates of dangerous driving and strengthen safety measures.

[0293] Input: Dangerous Driver List.

[0294] Output: Developing and implementing patrol plans.

[0295] By using the above processing steps, the present invention can evaluate the driver's driving behavior in real time and promote safe driving. In addition, by sharing information with police agencies, a system for preventing dangerous driving can be established.

[0296] 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.

[0297] ---

[0298] The system for implementing the present invention is composed of a device installed in a vehicle, a server, and a user interface used by the driver. In addition, by adding a function to analyze the driver's facial expressions and recognize their emotions, it is possible to evaluate not only the driving behavior but also the driver's emotional state.

[0299] Data collection and transmission

[0300] The terminal (the AI ​​camera, GPS device, and emotion engine installed in the vehicle) performs the following functions while the vehicle is driving:

[0301] The distance between vehicles is measured using an AI camera.

[0302] Driving speed and location information are obtained using a GPS device.

[0303] The emotion engine analyzes the driver's facial expressions and recognizes their emotional state (e.g., fatigue, stress, concentration).

[0304] The collected data (vehicle distance, driving speed, location information, emotion data) is sent to a server at a set time or at regular intervals.

[0305] For example, a vehicle traveling on a highway automatically measures the distance to the vehicle ahead and acquires speed and location information in real time using a GPS device. At the same time, an emotion engine analyzes the driver's facial expressions and obtains their emotional state as data. This data is then sent to a server via the vehicle's communications equipment.

[0306] Data analysis and evaluation

[0307] The server receives the data sent from the terminal and performs the following analysis and evaluation.

[0308] Analyze data on vehicle distance and speed according to safe driving standards.

[0309] Emotional data is analyzed to assess the driver's emotional state.

[0310] Based on the analysis results, evaluation points are calculated. Points are added if safe driving is confirmed, and points are subtracted if dangerous driving or a bad emotional state is confirmed.

[0311] Each driver's rating points are recorded in a database.

[0312] For example, points are added if the following distance meets safety standards and the driver is deemed to be concentrating, while points are subtracted if the following distance is too short, the speed is over the limit, and the driver is deemed to be fatigued.

[0313] Point notification and management

[0314] The server manages the evaluation points for each driver and performs the following operations:

[0315] When a driver's evaluation points are updated, the results will be notified in real time.

[0316] Drivers can log in to the server and check their rating points and details.

[0317] It also has a function for offering rewards based on points (e.g., discounts on license renewal fees, discounts on car insurance premiums).

[0318] Providing feedback and advice based on emotional state.

[0319] For example, if a driver continues to drive safely and maintains a good emotional state, the server will send a notification saying, "You've been awarded 10 points," and the driver's score history can be checked on the user interface. If the driver is deemed to be fatigued, the server will also send a notification saying, "We recommend you take a break."

[0320] Information sharing with the police

[0321] The server shares information with police agencies.

[0322] Organize data on drivers who have been detected driving recklessly.

[0323] Regularly compile and share lists of dangerous drivers.

[0324] Based on this, the police can carry out focused patrols.

[0325] For example, a list of drivers who frequently engage in dangerous driving could be compiled and sent to the police, who could then use it to efficiently plan patrols and prevent accidents.

[0326] Specific examples

[0327] Data collected by the device:

[0328] Distance between vehicles: Always appropriate (e.g., maintain a distance of at least 2 seconds)

[0329] Driving speed: Within the speed limit (e.g. always adhere to the speed limit of 100km / h)

[0330] Emotional state: Focused, relaxed

[0331] Server Action:

[0332] The received data is analyzed and determined to meet all criteria.

[0333] Safe driving points are added to the driver (e.g., 10 points are added).

[0334] User Action:

[0335] Drivers log in to the server and check their evaluation points.

[0336] Apply for a discount on your license renewal fee based on your safe driving points (e.g., 20 points for a 5% discount).

[0337] Receive feedback on staying focused.

[0338] In this way, the system of the present invention not only evaluates the driver's driving behavior but also their emotional state in real time, promoting safe driving. Furthermore, by effectively sharing information with police agencies, it supports the efficiency of patrols and accident prevention.

[0339] The processing flow will be explained below.

[0340] ---

[0341] Step 1:

[0342] While the vehicle is moving, the device uses an AI camera to measure the distance to the vehicle ahead. It also uses a GPS device to acquire driving speed and location information. The emotion engine also analyzes the driver's facial expressions to recognize their emotional state.

[0343] Step 2:

[0344] The device formats the acquired data, such as vehicle distance, driving speed, location information, and emotion data, and transmits the formatted data to the server via the communication module.

[0345] Step 3:

[0346] The server analyzes the data received from the device, assessing whether the following distance meets safety standards, whether the driving speed exceeds the speed limit, and the driver's emotional state.

[0347] Step 4:

[0348] The server calculates evaluation points based on the analysis results. Specifically, points are added if safe driving and a good emotional state are confirmed, and points are subtracted if dangerous driving and a bad emotional state are confirmed.

[0349] Step 5:

[0350] The server records each driver's rating points in a database, and if new points are added, the driver's total points are updated.

[0351] Step 6:

[0352] The server sends notifications based on changes in the driver's rating points, either via the app or email associated with the user's account.

[0353] Step 7:

[0354] The user logs in to the server and checks his / her own rating points and driving rating. If the user wants to apply for a reward, he / she selects a discount or reward based on the points and executes the application.

[0355] Step 8:

[0356] The server receives the reward request from the user, checks the validity of the points, and if the conditions are met, applies the reward and deducts the points.

[0357] Step 9:

[0358] The server evaluates the emotional data and sends a notification to alert you if a particular emotional state (e.g., fatigue or high stress) is detected.

[0359] Step 10:

[0360] The server records emotional data over time and analyzes patterns of the driver's emotional state, generating a long-term emotional assessment report.

[0361] Step 11:

[0362] The server compiles data on dangerous drivers and periodically creates a list, which is sent to police agencies and updated as needed.

[0363] Step 12:

[0364] Police can efficiently plan and carry out patrols based on the list of dangerous drivers received from the server, and can also issue direct warnings and take action as necessary.

[0365] ---

[0366] Through the above steps, the system of the present invention evaluates the driver's driving behavior and emotional state, promotes safe driving, and works to prevent accidents by sharing information with police agencies.

[0367] Example 2

[0368] 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."

[0369] Conventional driver evaluation systems only evaluate driving behavior and do not consider the driver's emotional state, making it difficult to accurately evaluate safe driving. Furthermore, there is a lack of a means to efficiently share information on dangerous drivers with police agencies, limiting their effectiveness in preventing traffic accidents.

[0370] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for analyzing the driver's facial expression and recognizing the emotional state, a means for transmitting data on the emotional state, and a means for analyzing the data on the emotional state and evaluating it based on safe driving standards. This makes it possible to evaluate not only the driver's driving behavior but also their emotional state.

[0371] "Inter-vehicle distance" refers to the distance between your vehicle and the vehicle ahead.

[0372] "Traveling speed" is the distance a vehicle travels in a certain period of time expressed in speed units (e.g., km / h).

[0373] "Device" refers to all equipment installed in a vehicle for measurement and analysis.

[0374] "Server" refers to a computer system for receiving, analyzing, storing, and notifying data.

[0375] "Driver" means a person who drives a vehicle.

[0376] "Emotional state" refers to the psychological state of the driver as judged from their facial expressions and physiological signs.

[0377] "Evaluation points" refer to numerical evaluation indicators calculated based on the driver's driving behavior and emotional state.

[0378] "Notification" refers to informing the driver of certain information.

[0379] "Benefits" refers to rewards and benefits provided to drivers based on their rating points.

[0380] "Police agency" means a government agency tasked with maintaining public safety and order and enforcing the law.

[0381] A "list" refers to a collection of data organized based on specific criteria.

[0382] "GPS function" refers to technology that uses the Global Positioning System to determine the vehicle's location.

[0383] "Feedback" refers to sharing information with the driver about their driving behavior and emotional state, as well as providing advice to encourage improvement.

[0384] The above are definitions of important words included in the claims.

[0385] The system for implementing this invention is composed of a device installed in a vehicle, a server, and a user interface used by the driver. This system aims to prevent traffic accidents and promote safe driving by analyzing the driver's driving behavior and emotional state and evaluating safe driving.

[0386] Hardware and software used

[0387] The terminal (device installed in the vehicle) uses the following hardware and software:

[0388] AI camera: Used to measure the distance between the vehicle and the vehicle ahead.

[0389] GPS device: Used to obtain driving speed and location information.

[0390] Emotion Engine: Used to analyze the driver's facial expressions and recognize their emotional state.

[0391] Communication device: Used to send collected data to the server.

[0392] Data collection

[0393] The device collects data on vehicle distance, speed, location, and emotional state. For example, it uses an AI camera to measure the distance to the vehicle ahead in real time, and a GPS device to record the driver's current speed and location. At the same time, an emotion engine analyzes the driver's facial expressions to identify their level of concentration and fatigue.

[0394] Data transmission

[0395] The data collected by the device (including distance, speed, location, and emotional state) is sent to a server every minute, packaged in JSON format, and uploaded to the server via the vehicle's Wi-Fi or cellular network.

[0396] Data analysis and evaluation

[0397] The server receives the data sent by the device and performs the following analysis and evaluation:

[0398] Data on vehicle distance and driving speed is analyzed and evaluated based on safe driving standards.

[0399] Emotional data is analyzed to assess the driver's emotional state.

[0400] For example, if the distance between vehicles is equal to or greater than a standard value, the speed is within the speed limit, and the driver is concentrating, safe driving points are added.

[0401] Notifications and Feedback

[0402] The server calculates the evaluation points based on the analysis results and notifies the driver of the results. For example, if 10 points are added to the driver's safe driving points, the driver's smartphone will be notified that "10 points have been added."

[0403] Drivers can log in to the server and check their own rating points. Based on the rating points, they can receive certain benefits (e.g., discounts on license renewal fees, discounts on car insurance premiums).

[0404] Information sharing with the police

[0405] The server creates a list of dangerous drivers and sends it to the police. This list is updated monthly and includes information on drivers who frequently engage in dangerous driving. Police can use this list to plan efficient patrols and work to prevent traffic accidents.

[0406] Examples of concrete examples and prompts

[0407] As a concrete example, consider the following scenario:

[0408] Data collected by the device:

[0409] Distance between vehicles: Always appropriate (e.g., maintain a distance of at least 2 seconds)

[0410] Driving speed: Within the speed limit (e.g. always adhere to the speed limit of 100km / h)

[0411] Emotional state: Focused, relaxed

[0412] Server Action:

[0413] The received data is analyzed and determined to meet all criteria.

[0414] Safe driving points are added to the driver (e.g., 10 points are added).

[0415] User Action:

[0416] Drivers log in to the server and check their evaluation points.

[0417] Apply for a discount on your license renewal fee based on your safe driving points (e.g., 20 points for a 5% discount).

[0418] Receive feedback on staying focused.

[0419] Examples of prompts include:

[0420] "Please explain the system in which a vehicle automatically measures the distance to the vehicle ahead and analyzes the driver's facial expressions to evaluate safe driving."

[0421] "Please give a concrete example of a system that calculates evaluation points based on the driver's emotional data and provides rewards based on those points."

[0422] "Please provide the police with a list of dangerous drivers and explain how the system works to support efficient patrols."

[0423] In this way, the system of the present invention comprehensively evaluates the driver's driving behavior and emotional state, promoting safe driving. Furthermore, by providing rewards and feedback based on the evaluation, it is expected to increase driver motivation. Furthermore, it is also characterized by the ability to implement efficient traffic safety measures in cooperation with police agencies.

[0424] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0425] Step 1:

[0426] Data collection

[0427] The device collects data on vehicle distance, driving speed, location, and emotional state.

[0428] Specifically, the AI ​​camera measures the distance to the vehicle ahead in real time, and a GPS device records the current speed and location. At the same time, an emotion engine analyzes the driver's facial expressions to recognize their level of concentration and fatigue.

[0429] It receives camera image data, GPS data, and facial expression data as input.

[0430] As outputs, it generates distance data, speed data, position data, and emotion data.

[0431] Step 2:

[0432] Data transmission

[0433] The terminal transmits the collected data to the server.

[0434] Specifically, data on vehicle distance, speed, location, and emotional state is packaged in JSON format and uploaded to a server via the vehicle's Wi-Fi or cellular network.

[0435] As input, it takes the data generated in step 1.

[0436] As an output, the submitted data is sent to the server.

[0437] Step 3:

[0438] Data reception

[0439] The server receives the data sent from the terminal.

[0440] Specifically, the data is received from the terminal via the data receiving endpoint and stored in the database.

[0441] As input, it receives data sent from the terminal.

[0442] As output, it produces data that is recorded in a database.

[0443] Step 4:

[0444] Data analysis

[0445] The server analyzes the received data.

[0446] Specifically, the system analyzes data on vehicle distance and speed based on safe driving standards, and analyzes emotional data to assess the driver's state, for example, determining whether the vehicle distance is appropriate, the speed is within the speed limit, and whether the driver is maintaining a focused state.

[0447] As input, it uses vehicle distance data, speed data, position data, and emotion data recorded in a database.

[0448] As outputs, safe driving evaluation data and emotional state evaluation data are generated.

[0449] Step 5:

[0450] Rating point calculation

[0451] The server calculates the evaluation points based on the analysis results.

[0452] Specifically, based on the analyzed data, points are added if the criteria are met, and points are subtracted if substandard driving or a bad emotional state is recognized.

[0453] As input, the safe driving evaluation data and emotional state evaluation data generated in step 4 are used.

[0454] As an output, it produces rating points.

[0455] Step 6:

[0456] Notifications and Feedback

[0457] The server notifies the driver of the evaluation results and provides feedback.

[0458] Specifically, when the rating points are updated, a notification is sent to the driver's smartphone in real time, and the driver can log in to the server to check the rating points and receive feedback.

[0459] Uses rating points as input.

[0460] As output, it generates notification messages and feedback data.

[0461] Step 7:

[0462] Offering benefits

[0463] The server provides rewards to drivers based on their evaluation points.

[0464] As a specific operation, benefits based on the evaluation points (e.g., discounts on license renewal fees, discounts on car insurance premiums) are presented.

[0465] Uses rating points as input.

[0466] As an output, it generates bonus information.

[0467] Step 8:

[0468] Information sharing with the police

[0469] The server creates a list of dangerous drivers and sends it to the police.

[0470] Specifically, the system organizes data on drivers who frequently engage in dangerous driving, creates a list, and sends it to police agencies.

[0471] It uses historical and evaluation data as input.

[0472] As an output, a list of risky drivers is generated and sent to police agencies.

[0473] (Application example 2)

[0474] 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."

[0475] Conventional safe driving evaluation systems only evaluate a driver's driving behavior and do not take into account the driver's emotional state. As a result, they are unable to fully assess the risks posed by drivers who are fatigued or stressed. Furthermore, there is a lack of concrete means for utilizing the collected data to improve actual driving safety and for effective monitoring by police agencies. Therefore, there is a need for a system that takes into account a driver's emotional state and provides safe driving evaluation and effective feedback.

[0476] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0477] In this invention, the server includes a means for measuring the inter-vehicle distance and traveling speed from a device mounted on the vehicle, a means for analyzing the driver's facial expression and recognizing the emotional state, a means for transmitting data on the measured inter-vehicle distance and traveling speed and the recognized emotional state to the server, a means for analyzing the transmitted data and calculating an evaluation point, and a means for notifying the driver of feedback based on the calculated evaluation point and the emotional state. This enables safe driving evaluation and individual feedback that takes the driver's emotional state into consideration, making it possible to promote comprehensive safe driving and effectively share information with police agencies.

[0478] "Following distance" refers to the safe distance a vehicle should maintain between itself and the vehicle in front.

[0479] "Traveling speed" refers to the speed at which a vehicle is moving and is expressed in units that measure that speed.

[0480] "Facial expression analysis" refers to a technology that analyzes a driver's facial expressions in real time and identifies their emotional state.

[0481] "Emotional state" refers to the emotional state a driver has while driving, including, for example, fatigue, stress, and concentration.

[0482] "Data transmission" refers to the process of transmitting data detected within the vehicle to a server over a network.

[0483] "Evaluation points" refer to evaluation values ​​for the driver's driving behavior and emotional state calculated based on analyzed data.

[0484] "Feedback" refers to specific instructions or advice provided to the driver based on their calculated rating points and emotional state.

[0485] "Benefits" refers to rewards and privileges provided to drivers based on their rating points.

[0486] "Police agency" means a public agency that maintains law and order and monitors safe driving.

[0487] The "list" refers to a compilation of drivers who engage in dangerous driving.

[0488] "GPS Functionality" refers to technology for measuring geolocation and determining the vehicle's current location and speed.

[0489] A "generative AI model" refers to an algorithm that performs analysis and response automatically generated using artificial intelligence.

[0490] A "prompt sentence" refers to an instruction or query sentence that is input into a generative AI model.

[0491] The system for implementing this invention consists of a device installed in a vehicle, a server, and a user interface used by the driver. The main purpose of the entire system is to improve road traffic safety, but here we focus on analyzing the driver's facial expressions and providing evaluation and feedback based on their emotional state.

[0492] Data collection and transmission

[0493] The terminal performs the following processing.

[0494] The distance between vehicles is measured using an AI camera.

[0495] Driving speed and location information are obtained using a GPS device.

[0496] The emotion engine analyzes the driver's facial expressions and recognizes their emotional state (e.g., fatigue, stress, concentration).

[0497] The collected data (vehicle distance, driving speed, location information, and emotion data) is sent to a server via communication equipment.

[0498] Data analysis and evaluation

[0499] The server performs the following processing:

[0500] The received data (distance between vehicles, driving speed, location information, emotional data) is analyzed and compared with safe driving standards.

[0501] Emotional data is analyzed to assess the driver's emotional state.

[0502] Based on the analysis results, evaluation points are calculated. Points are added if safe driving is confirmed, and points are subtracted if dangerous driving or a bad emotional state is confirmed.

[0503] Each driver's evaluation points are recorded in a database and notified to the driver in real time.

[0504] Feedback and Rewards

[0505] The server performs the following operations based on the evaluation points and the emotional state.

[0506] Provide appropriate feedback to the driver, such as "You're staying focused. Please continue to drive safely."

[0507] If the driver is fatigued or stressed, the system will provide feedback such as, "We recommend taking a short break."

[0508] Offer drivers rewards (e.g., discounts on license renewal fees, discounts on car insurance premiums) based on their evaluation points.

[0509] Information sharing with police agencies

[0510] The server generates a list of dangerous drivers and periodically shares this list with police agencies, allowing them to identify drivers who should be monitored more intensively and build a more efficient monitoring system.

[0511] Hardware and software used

[0512] AI camera: Used to measure the distance between vehicles.

[0513] GPS device: Used to obtain driving speed and location information.

[0514] Emotion Engine: Used to analyze the driver's facial expressions and recognize their emotional state.

[0515] Server: Used to receive and analyze data, calculate reputation points, and generate feedback.

[0516] Software: OpenCV (image processing and facial expression analysis), Dlib (facial feature point detection and emotion analysis), Geopy (location information processing), Requests (data transmission).

[0517] Specific examples

[0518] For example, a vehicle traveling on a highway uses an AI camera to measure the distance to the vehicle ahead, and collects driving speed and location information in real time using acquired GPS data. At the same time, an emotion engine analyzes the driver's facial expressions and recognizes their emotional state, such as "concentrated" or "relaxed." This data is sent to a server via the vehicle's communications device, and based on the analysis results, a notification is sent to the driver, such as "10 points have been added."

[0519] Prompt Sentence Examples

[0520] "The current following distance is 10 metres and the driver's emotional state is focused."

[0521] "Maintaining current speed of 60 km / h while maintaining appropriate following distance."

[0522] "We recommend taking timely rest breaks to reduce stress while driving."

[0523] In this way, this system comprehensively evaluates the driver's driving behavior and emotional state, promoting safe driving and helping to prevent accidents by sharing information with police agencies.

[0524] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0525] Step 1:

[0526] Data collection

[0527] The device measures the distance between vehicles using an AI camera. The acquired distance becomes the input for the next data processing. At the same time, the device uses a GPS device to acquire driving speed and location information. It also uses an emotion engine to analyze the driver's facial expressions and recognize their emotional state (e.g., fatigue, stress, concentration). This data (distance between vehicles, driving speed, location information, emotional state) is temporarily stored in the vehicle's local memory.

[0528] Step 2:

[0529] Data transmission

[0530] The device sends the collected data (distance between vehicles, driving speed, location information, emotional state) to the server. A communication module is used for transmission, and the data is protected by an encrypted protocol. The input of this process is the data collected in step 1, and the output is the data sent to the server.

[0531] Step 3:

[0532] Data reception and analysis

[0533] The server receives data sent from the device. This data includes the following distance, driving speed, location information, and emotional state. It performs data analysis based on the received data and compares it with safe driving standards. For example, it checks whether the following distance meets the safety standard and whether the driving speed exceeds the speed limit. The input of this process is the sent data, and the output is the analysis result.

[0534] Step 4:

[0535] Emotional state assessment

[0536] The server analyzes the received emotion data and evaluates the driver's emotional state. For example, it determines whether the driver is tired or focused based on the results of facial expression analysis. The input of this process is emotion data, and the output is the emotion evaluation result.

[0537] Step 5:

[0538] Calculation of evaluation points

[0539] The server calculates evaluation points based on the data analysis and the evaluation results of the emotional state. Points are added if safe driving is confirmed, and points are subtracted if dangerous driving or a bad emotional state is confirmed. The input of this process is the analysis results and evaluation results, and the output is the evaluation points.

[0540] Step 6:

[0541] Real-time notifications

[0542] The server generates a feedback message for the driver based on the calculated evaluation points and emotional state. For example, if safe driving is confirmed, the server generates feedback such as "You are maintaining concentration. Please continue to drive safely." This feedback is notified to the driver's user interface in real time. The inputs of this process are the evaluation points and emotional state, and the output is a feedback message.

[0543] Step 7:

[0544] Offer

[0545] The server provides rewards to drivers based on their rating points. Each driver's rating points are recorded in a database, and rewards (e.g., discounts on license renewal fees, discounts on car insurance premiums) are offered according to the points. In this process, reward information is sent to the driver. The input of this process is the rating points, and the output is a reward offer message.

[0546] Step 8:

[0547] Information sharing with police agencies

[0548] The server generates a list of dangerous drivers and periodically sends this list to the police, allowing the police to identify drivers who should be monitored more closely. The input of this process is the evaluation data, and the output is the list of dangerous drivers.

[0549] 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.

[0550] 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.

[0551] 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.

[0552] [Second embodiment]

[0553] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0554] 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.

[0555] 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).

[0556] 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.

[0557] 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.

[0558] 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).

[0559] 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.

[0560] 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.

[0561] 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.

[0562] 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.

[0563] 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.

[0564] 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."

[0565] ---

[0566] A system for implementing the present invention comprises a device installed in a vehicle, a server, and a user interface used by the driver.

[0567] Data collection and transmission

[0568] The terminal (AI camera and GPS device installed in the vehicle) performs the following functions while the vehicle is driving.

[0569] The distance between vehicles is measured using an AI camera.

[0570] Driving speed and location information are obtained using a GPS device.

[0571] The collected data is sent to a server at a predetermined timing or at regular intervals.

[0572] For example, a vehicle traveling on a highway automatically measures the distance to the vehicle ahead and acquires real-time speed and location information using a GPS device. This data is then sent to a server via the vehicle's communications equipment.

[0573] Data analysis and evaluation

[0574] The server receives the data sent from the terminal and performs the following analysis and evaluation.

[0575] Analyze data on vehicle distance and speed according to safe driving standards.

[0576] Based on the analysis results, evaluation points are calculated.

[0577] Each driver's rating points are recorded in a database.

[0578] For example, if the following distance meets the safety standard, points are added, while if the following distance is too short and the speed is over the limit, points are subtracted.

[0579] Point notification and management

[0580] The server manages the evaluation points for each driver and performs the following operations:

[0581] When a driver's evaluation points are updated, the results will be notified in real time.

[0582] Drivers can log in to the server and check their rating points and details.

[0583] It also has a function for offering rewards based on points (e.g., discounts on license renewal fees, discounts on car insurance premiums).

[0584] For example, a driver who continues to drive safely will receive a notification from the server saying, "You have been awarded 10 points," and the driver's history can be viewed on the user interface.

[0585] Information sharing with the police

[0586] The server shares information with police agencies.

[0587] Organize data on drivers who have been detected driving recklessly.

[0588] Regularly compile and share lists of dangerous drivers.

[0589] Based on this, the police can carry out focused patrols.

[0590] For example, a list of drivers who frequently engage in dangerous driving could be compiled and sent to the police, who could then use it to efficiently plan patrols and prevent accidents.

[0591] Specific examples

[0592] Data collected by the device:

[0593] Distance between vehicles: Always appropriate (e.g., maintain a distance of at least 2 seconds)

[0594] Driving speed: Within the speed limit (e.g. always adhere to the speed limit of 100km / h)

[0595] Server Action:

[0596] The received data is analyzed and determined to meet all criteria.

[0597] Safe driving points are added to the driver (e.g., 10 points are added).

[0598] User Action:

[0599] Drivers log in to the server and check their evaluation points.

[0600] Apply for a discount on your license renewal fee based on your safe driving points (e.g., 20 points for a 5% discount).

[0601] In this way, the system of the present invention evaluates the driver's driving behavior in real time, promotes safe driving, and supports the efficiency of patrols and accident prevention through effective information sharing with police agencies.

[0602] The processing flow will be explained below.

[0603] ---

[0604] Step 1:

[0605] While the vehicle is moving, the device uses an AI camera to measure the distance to the vehicle ahead, and also obtains driving speed and location information using a GPS device.

[0606] Step 2:

[0607] The terminal formats the data it acquires, including vehicle distance, driving speed, and location information, and sends it to the server via the communication module.

[0608] Step 3:

[0609] The server analyzes the data received from the device, specifically assessing whether the distance between vehicles meets safety standards and whether the driving speed exceeds the speed limit.

[0610] Step 4:

[0611] The server calculates evaluation points based on the analysis results, adding points if safe driving is confirmed and subtracting points if dangerous driving is confirmed.

[0612] Step 5:

[0613] The server records each driver's rating points in a database, and if new points are added, the driver's total points are updated.

[0614] Step 6:

[0615] The server sends notifications based on changes in the driver's rating points, either via the application or email associated with the user's account.

[0616] Step 7:

[0617] The user logs in to the server and checks his / her own rating points and driving rating. If the user wants to apply for a reward, he / she selects a discount or reward based on the points and executes the application.

[0618] Step 8:

[0619] The server receives the reward request from the user, checks the validity of the points, and if the conditions are met, applies the reward and deducts the points.

[0620] Step 9:

[0621] The server compiles data on dangerous drivers and periodically creates a list, which is sent to police agencies and updated as needed.

[0622] Step 10:

[0623] Police can efficiently plan and carry out patrols based on the list of dangerous drivers received from the server, and can also issue direct warnings and take action as necessary.

[0624] ---

[0625] Through the above steps, the system of the present invention evaluates the driver's driving behavior, promotes safe driving, and works to prevent accidents by sharing information with police agencies.

[0626] Example 1

[0627] 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."

[0628] Conventional driving behavior evaluation systems have had problems such as incomplete data collection, such as measurement of vehicle distance and speed, and delayed notification of evaluation results. Furthermore, there were also problems with inefficient rewards based on evaluation points and collaboration with police agencies. As a result, they have not been able to adequately motivate drivers to drive safely or prevent dangerous driving.

[0629] 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.

[0630] In this invention, the server includes a means for measuring the distance and speed from a device mounted on the vehicle, a means for transmitting the measured distance and speed data to a data processing device, a means for analyzing the transmitted data and calculating an evaluation value, and a means for notifying the driver of the calculated evaluation value. This enables multifaceted and real-time evaluation of driving behavior. In addition, rewards based on the evaluation value and information sharing with police agencies can be efficiently carried out, which is expected to promote safe driving and prevent dangerous driving.

[0631] A "driving behavior evaluation system" is a system that uses a device installed in a vehicle to measure and evaluate a driver's driving behavior, and notifies and manages the results.

[0632] "Device" is a general term for measuring instruments and communication equipment attached to a vehicle, and is a device that has the function of collecting data such as vehicle-to-vehicle distance, speed, and location information.

[0633] "Inter-vehicle distance" refers to the distance between a moving vehicle and the vehicle in front of it.

[0634] "Speed" refers to the rate at which a vehicle travels a distance in a given time, and is typically expressed in kilometers per hour (km / h).

[0635] A "data processing device" is a computer system that receives collected data, analyzes it, and calculates evaluation values.

[0636] The "evaluation value" is a value calculated based on the analyzed data to indicate the safety and appropriateness of driving behavior.

[0637] "Notification" is an act of communicating information to the driver about the calculated evaluation value, and is performed in real time.

[0638] "Rewards" refers to incentives and benefits offered to drivers based on their rating figures.

[0639] "Patrol agencies" refer to law enforcement agencies such as the police, which work in conjunction with the driving behavior assessment system to monitor and crack down on dangerous driving.

[0640] The "list" is a report or database format that organizes and lists information on dangerous drivers.

[0641] The system for carrying out the present invention comprises a terminal installed in a vehicle, a server, and a user interface used by the driver. This system has the following technical configuration.

[0642] Data collection and transmission

[0643] The terminal (a device installed in the vehicle) performs the following functions while the vehicle is moving:

[0644] The distance between vehicles is measured using an AI camera.

[0645] Driving speed and location information are obtained using a GPS device.

[0646] The collected data is sent to a server at a predetermined timing or at regular intervals.

[0647] For example, a vehicle traveling on a highway automatically measures the distance to the vehicle ahead and acquires real-time speed and location information using a GPS device. This data is then sent to a server via the vehicle's communications equipment.

[0648] Data analysis and evaluation

[0649] The server receives the data sent from the terminal and performs the following analysis and evaluation.

[0650] Analyze data on vehicle distance and speed according to safe driving standards.

[0651] Based on the analysis results, an evaluation value is calculated.

[0652] Each driver's rating is recorded in a database.

[0653] For example, if the following distance meets the safety standard, points are added, while if the following distance is too short and the speed is over the limit, points are subtracted.

[0654] Point notification and management

[0655] The server manages the evaluation values ​​for each driver and performs the following operations:

[0656] When a driver's rating is updated, the results will be notified in real time.

[0657] Drivers can log in to the server and check their rating numbers and details.

[0658] It also has a function to offer benefits based on the evaluation figures (e.g., discounts on license renewal fees, discounts on car insurance premiums).

[0659] For example, a driver who continues to drive safely will receive a notification from the server saying, "You have been awarded 10 points," and the driver's history can be viewed on the user interface.

[0660] Information sharing with the police

[0661] The server shares information with police agencies.

[0662] Organize data on drivers who have been detected driving recklessly.

[0663] Regularly compile and share lists of dangerous drivers.

[0664] Based on this, the police will carry out intensive patrols.

[0665] For example, a list of drivers who frequently engage in dangerous driving will be compiled and sent to the police, who will then use this information to efficiently plan patrols and work to prevent accidents.

[0666] Specific examples

[0667] Data collected by the device:

[0668] Distance between vehicles: Always appropriate (e.g., maintain a distance of at least 2 seconds)

[0669] Driving speed: Within the speed limit (e.g. always adhere to the speed limit of 100km / h)

[0670] Server Action:

[0671] The received data is analyzed and determined to meet all criteria.

[0672] Safe driving points are added to the driver (e.g., 10 points are added).

[0673] User Action:

[0674] Drivers log in to the server and check their evaluation points.

[0675] Apply for a discount on your license renewal fee based on your safe driving points (e.g., 20 points for a 5% discount).

[0676] The system of this invention evaluates the driving behavior of drivers in real time to promote safe driving. It also supports the efficiency of patrols and accident prevention through effective information sharing with police agencies.

[0677] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0678] Step 1:

[0679] Data collection

[0680] The terminal (an AI camera or GPS device installed inside the vehicle) collects data from the vehicle while it is in motion.

[0681] Input: distance between vehicles, driving speed, location information

[0682] Specific operation: When the vehicle starts moving, the AI ​​camera measures the distance to the vehicle in front, and the GPS device collects the vehicle's speed and location information. For example, the AI ​​camera measures the distance every second, and the GPS device similarly obtains the vehicle's current location and speed every second.

[0683] Output: Inter-vehicle distance data, speed data, location data

[0684] Step 2:

[0685] Data transmission

[0686] The terminal transmits the collected data to the server.

[0687] Input: Inter-vehicle distance data, speed data, location data

[0688] Specific operation: Collected data is packaged at regular intervals (e.g., 1 minute) and sent to a server using the vehicle's communications equipment. The transmission interval can be adjusted, but a short interval is recommended to ensure real-time data transmission.

[0689] Output: Data package received by the server

[0690] Step 3:

[0691] Data analysis

[0692] The server analyzes the data sent from the terminal.

[0693] Input: Received data package (distance data, speed data, location data)

[0694] Specific operation: The server applies an analysis algorithm to the received data and compares it with safe driving standards. For example, if the distance between vehicles is more than 2 seconds and the driving speed is within the speed limit, it is judged as safe driving and points are added to the driver's score. If there is a violation, points are subtracted.

[0695] Output: Rating points

[0696] Step 4:

[0697] Calculation of evaluation points

[0698] The server calculates the evaluation points based on the analysis results.

[0699] Input: Analysis results (distance between vehicles, speed)

[0700] Specific operation: Calculates the evaluation points based on the analysis results. For example, add or subtract points from each analysis data to calculate the overall evaluation points.

[0701] Output: Calculated rating points

[0702] Step 5:

[0703] Point notification

[0704] The server notifies the driver of the calculated evaluation points.

[0705] Input: Rating points

[0706] Specific operation: Once the evaluation points have been calculated, the driver is notified in real time. For example, a notification saying "10 points added" is displayed on a smartphone app or on the in-car display.

[0707] Output: Rating points reported to the driver

[0708] Step 6:

[0709] Check in the user interface

[0710] The user (driver) checks the evaluation points.

[0711] Input: Notifications from the server, login information

[0712] How it works: Drivers can log in to the app on their smartphone or in-car display and check their rating point history and details. For example, it will show "Current points: 50 points," and they can also check the history and data analysis details.

[0713] Output: Driver's rating points information

[0714] Step 7:

[0715] Information sharing with the police

[0716] The server shares information with police agencies.

[0717] Input: Dangerous driving data, evaluation point data

[0718] Specific operation: The server creates a list of drivers who have been detected as driving recklessly and periodically provides it to the police. For example, a list such as "Driver A - Insufficient distance - 3 times, Driver B - Speeding - 2 times" is generated and uploaded to the police database.

[0719] Output: A list of dangerous drivers provided to police agencies

[0720] (Application example 1)

[0721] 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."

[0722] Conventional driving behavior evaluation systems lack sufficient data visualization and real-time feedback, making it difficult to immediately promote safe driving by drivers. In addition, there was a lack of means to provide immediate alerts for dangerous driving behavior, making it difficult to ensure safety.

[0723] 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.

[0724] In this invention, the server includes a means for measuring the inter-vehicle distance and traveling speed from a device mounted on the vehicle, a means for transmitting the measured inter-vehicle distance and traveling speed data to the server, a means for analyzing the transmitted data and calculating an evaluation point, a means for notifying the driver of the calculated evaluation point, a means for visualizing the inter-vehicle distance and traveling speed information in real time, and a means for providing visual and audio alerts as necessary, thereby enabling the driver to immediately understand his / her driving behavior while driving and receive appropriate feedback to maintain safe driving.

[0725] "Following distance" refers to the physical distance between you and the vehicle in front.

[0726] "Traveling speed" refers to the speed at which a vehicle is moving.

[0727] "Server" refers to the system that analyzes collected data, calculates and manages evaluation points.

[0728] "Device" refers to a device installed in a vehicle that measures the distance between vehicles and the driving speed.

[0729] "Evaluation points" refer to points calculated based on the driver's driving behavior.

[0730] "Driver" means a person who drives a vehicle.

[0731] "Real-time" refers to the instantaneous collection and processing of data.

[0732] "Visualization" refers to the visual display of data.

[0733] "Visual alert" refers to a visual warning that alerts the driver.

[0734] "Voice alert" refers to a function that warns the driver by voice.

[0735] "Location information function" refers to technology such as GPS for measuring current location.

[0736] An "unsafe driver" is a driver whose driving behavior does not meet safe driving standards.

[0737] "Benefits" refers to rewards and benefits provided to drivers based on their rating points.

[0738] A system for implementing the present invention comprises a device installed in a vehicle, a server, and a user interface used by the driver.

[0739] Data collection and transmission

[0740] The terminal (such as a camera or GPS device mounted in the vehicle) performs the following functions while the vehicle is traveling:

[0741] The distance between vehicles is measured using a camera.

[0742] Driving speed and location information are obtained using a GPS device.

[0743] This data is transmitted to the server at regular intervals.

[0744] For example, a vehicle traveling on a highway automatically measures the distance to the vehicle ahead, obtains speed and location information in real time using a GPS device, and transmits the collected data to a server via communication equipment inside the vehicle.

[0745] Data analysis and evaluation

[0746] The server receives the data sent from the terminal and performs the following analysis and evaluation.

[0747] Data on vehicle distance and driving speed is analyzed, and evaluation points are calculated according to safe driving standards.

[0748] Each driver's rating points are recorded in a database.

[0749] For example, points are added if the following distance meets safety standards, while points are subtracted if the following distance is too short and the speed is above the limit.

[0750] Point notification and management

[0751] The server manages the evaluation points for each driver and performs the following operations:

[0752] When a driver's evaluation points are updated, the results will be notified in real time.

[0753] Drivers can log in to the server and check their rating points and details.

[0754] It also has the ability to offer rewards based on points (e.g., discounts on license renewal fees, discounts on car insurance premiums).

[0755] For example, a driver who continues to drive safely will receive a notification from the server saying, "You have been awarded 10 points," and the driver's history can be viewed on the user interface.

[0756] Real-time visibility and alerts

[0757] Smart glasses or a head-mounted display (HMD) can be used as a user interface.

[0758] Visualize real-time information on distance and driving speed.

[0759] Provide visual and audio alerts as needed.

[0760] For example, a driver can see through smart glasses that the distance to the vehicle ahead is 15m and the speed is 90km / h, and a visual and audio alert will be issued if the distance becomes too close.

[0761] Information sharing with the police

[0762] The server shares information with police agencies.

[0763] Organize data on drivers who have been detected driving recklessly.

[0764] Regularly compile and share lists of dangerous drivers.

[0765] Based on this, the police can carry out focused patrols.

[0766] For example, a list of drivers who frequently engage in dangerous driving could be created and sent to the police, allowing them to efficiently plan patrols and work to prevent accidents.

[0767] Program processing

[0768] The server uses Python and TensorFlow for remote data analysis, processes data sent from vehicles in real time, calculates evaluation points, and generates safe driving alerts. It also uses the requests library to manage data transmission and reception.

[0769] For example, while driving, drivers can check the information displayed on the smart glasses and, if a safe distance is maintained, receive a notification that "safe driving points have been added." Visual and audio alerts provide immediate warning when unsafe conditions occur.

[0770] Prompt Sentence Examples

[0771] "This application displays real-time driving data on smart glasses, monitors the distance and speed of vehicles in front of the car, and sends an alert when the distance falls below a certain level."

[0772] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0773] Step 1:

[0774] The device collects data on vehicle distance and speed.

[0775] Specific operation: The camera installed on the device uses an AI model to measure the distance to the vehicle ahead, and the GPS device obtains the current driving speed and location information.

[0776] Input: Video data, GPS data.

[0777] Output: Inter-vehicle distance, speed, position information.

[0778] Step 2:

[0779] The terminal transmits the collected data to the server.

[0780] Specific operation: Data is encoded at regular intervals and sent to the server via the terminal's communication equipment.

[0781] Input: distance, speed, location.

[0782] Output: The data sent to the server.

[0783] Step 3:

[0784] The server parses the received data.

[0785] Specific operation: The server uses the TensorFlow model to analyze the transmitted distance and speed data and calculates evaluation points according to safe driving standards.

[0786] Input: distance, speed, location.

[0787] Data processing: analysis, calculation of evaluation points.

[0788] Output: Rating points.

[0789] Step 4:

[0790] The server notifies the driver of the evaluation points.

[0791] How it works: The evaluation points are calculated and displayed in real time on the driver's user interface (smart glasses or HMD). Visual and audio alerts are also provided if necessary.

[0792] Input: Rating points.

[0793] Output: Rating points notified to the driver, visual and audio alerts.

[0794] Step 5:

[0795] The server records the evaluation points in a database and provides rewards.

[0796] Specific operation: The evaluation points are recorded in a database and the driver is given benefits (e.g., a discount on license renewal fees).

[0797] Input: Rating points.

[0798] Output: Reputation points recorded in the database, rewards provided.

[0799] Step 6:

[0800] The server shares information with police agencies and generates a list of dangerous drivers.

[0801] Specific operation: Based on the analysis results, a list of dangerous drivers is created and sent to police agencies on a regular basis.

[0802] Input: Evaluation point data.

[0803] Data processing: List generation.

[0804] Output: A list of dangerous drivers sent to police agencies.

[0805] Step 7:

[0806] Police will conduct targeted patrols based on a list of dangerous drivers.

[0807] Specific actions: Based on the list sent, police will develop patrol plans for areas with high rates of dangerous driving and strengthen safety measures.

[0808] Input: Dangerous Driver List.

[0809] Output: Developing and implementing patrol plans.

[0810] By using the above processing steps, the present invention can evaluate the driver's driving behavior in real time and promote safe driving. In addition, by sharing information with police agencies, a system for preventing dangerous driving can be established.

[0811] 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.

[0812] ---

[0813] The system for implementing the present invention is composed of a device installed in a vehicle, a server, and a user interface used by the driver. In addition, by adding a function to analyze the driver's facial expressions and recognize their emotions, it is possible to evaluate not only the driving behavior but also the driver's emotional state.

[0814] Data collection and transmission

[0815] The terminal (the AI ​​camera, GPS device, and emotion engine installed in the vehicle) performs the following functions while the vehicle is driving:

[0816] The distance between vehicles is measured using an AI camera.

[0817] Driving speed and location information are obtained using a GPS device.

[0818] The emotion engine analyzes the driver's facial expressions and recognizes their emotional state (e.g., fatigue, stress, concentration).

[0819] The collected data (vehicle distance, driving speed, location information, emotion data) is sent to a server at a set time or at regular intervals.

[0820] For example, a vehicle traveling on a highway automatically measures the distance to the vehicle ahead and acquires speed and location information in real time using a GPS device. At the same time, an emotion engine analyzes the driver's facial expressions and obtains their emotional state as data. This data is then sent to a server via the vehicle's communications equipment.

[0821] Data analysis and evaluation

[0822] The server receives the data sent from the terminal and performs the following analysis and evaluation.

[0823] Analyze data on vehicle distance and speed according to safe driving standards.

[0824] Emotional data is analyzed to assess the driver's emotional state.

[0825] Based on the analysis results, evaluation points are calculated. Points are added if safe driving is confirmed, and points are subtracted if dangerous driving or a bad emotional state is confirmed.

[0826] Each driver's rating points are recorded in a database.

[0827] For example, points are added if the following distance meets safety standards and the driver is deemed to be concentrating, while points are subtracted if the following distance is too short, the speed is over the limit, and the driver is deemed to be fatigued.

[0828] Point notification and management

[0829] The server manages the evaluation points for each driver and performs the following operations:

[0830] When a driver's evaluation points are updated, the results will be notified in real time.

[0831] Drivers can log in to the server and check their rating points and details.

[0832] It also has a function for offering rewards based on points (e.g., discounts on license renewal fees, discounts on car insurance premiums).

[0833] Providing feedback and advice based on emotional state.

[0834] For example, if a driver continues to drive safely and maintains a good emotional state, the server will send a notification saying, "You've been awarded 10 points," and the driver's score history can be checked on the user interface. If the driver is deemed to be fatigued, the server will also send a notification saying, "We recommend you take a break."

[0835] Information sharing with the police

[0836] The server shares information with police agencies.

[0837] Organize data on drivers who have been detected driving recklessly.

[0838] Regularly compile and share lists of dangerous drivers.

[0839] Based on this, the police can carry out focused patrols.

[0840] For example, a list of drivers who frequently engage in dangerous driving could be compiled and sent to the police, who could then use it to efficiently plan patrols and prevent accidents.

[0841] Specific examples

[0842] Data collected by the device:

[0843] Distance between vehicles: Always appropriate (e.g., maintain a distance of at least 2 seconds)

[0844] Driving speed: Within the speed limit (e.g. always adhere to the speed limit of 100km / h)

[0845] Emotional state: Focused, relaxed

[0846] Server Action:

[0847] The received data is analyzed and determined to meet all criteria.

[0848] Safe driving points are added to the driver (e.g., 10 points are added).

[0849] User Action:

[0850] Drivers log in to the server and check their evaluation points.

[0851] Apply for a discount on your license renewal fee based on your safe driving points (e.g., 20 points for a 5% discount).

[0852] Receive feedback on staying focused.

[0853] In this way, the system of the present invention not only evaluates the driver's driving behavior but also their emotional state in real time, promoting safe driving. Furthermore, by effectively sharing information with police agencies, it supports the efficiency of patrols and accident prevention.

[0854] The processing flow will be explained below.

[0855] ---

[0856] Step 1:

[0857] While the vehicle is moving, the device uses an AI camera to measure the distance to the vehicle ahead. It also uses a GPS device to acquire driving speed and location information. The emotion engine also analyzes the driver's facial expressions to recognize their emotional state.

[0858] Step 2:

[0859] The device formats the acquired data, such as vehicle distance, driving speed, location information, and emotion data, and transmits the formatted data to the server via the communication module.

[0860] Step 3:

[0861] The server analyzes the data received from the device, assessing whether the following distance meets safety standards, whether the driving speed exceeds the speed limit, and the driver's emotional state.

[0862] Step 4:

[0863] The server calculates evaluation points based on the analysis results. Specifically, points are added if safe driving and a good emotional state are confirmed, and points are subtracted if dangerous driving and a bad emotional state are confirmed.

[0864] Step 5:

[0865] The server records each driver's rating points in a database, and if new points are added, the driver's total points are updated.

[0866] Step 6:

[0867] The server sends notifications based on changes in the driver's rating points, either via the app or email associated with the user's account.

[0868] Step 7:

[0869] The user logs in to the server and checks his / her own rating points and driving rating. If the user wants to apply for a reward, he / she selects a discount or reward based on the points and executes the application.

[0870] Step 8:

[0871] The server receives the reward request from the user, checks the validity of the points, and if the conditions are met, applies the reward and deducts the points.

[0872] Step 9:

[0873] The server evaluates the emotional data and sends a notification to alert you if a particular emotional state (e.g., fatigue or high stress) is detected.

[0874] Step 10:

[0875] The server records emotional data over time and analyzes patterns of the driver's emotional state, generating a long-term emotional assessment report.

[0876] Step 11:

[0877] The server compiles data on dangerous drivers and periodically creates a list, which is sent to police agencies and updated as needed.

[0878] Step 12:

[0879] Police can efficiently plan and carry out patrols based on the list of dangerous drivers received from the server, and can also issue direct warnings and take action as necessary.

[0880] ---

[0881] Through the above steps, the system of the present invention evaluates the driver's driving behavior and emotional state, promotes safe driving, and works to prevent accidents by sharing information with police agencies.

[0882] Example 2

[0883] 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."

[0884] Conventional driver evaluation systems only evaluate driving behavior and do not consider the driver's emotional state, making it difficult to accurately evaluate safe driving. Furthermore, there is a lack of a means to efficiently share information on dangerous drivers with police agencies, limiting their effectiveness in preventing traffic accidents.

[0885] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for analyzing the driver's facial expression and recognizing the emotional state, a means for transmitting data on the emotional state, and a means for analyzing the data on the emotional state and evaluating it based on safe driving standards. This makes it possible to evaluate not only the driver's driving behavior but also their emotional state.

[0886] "Inter-vehicle distance" refers to the distance between your vehicle and the vehicle ahead.

[0887] "Traveling speed" is the distance a vehicle travels in a certain period of time expressed in speed units (e.g., km / h).

[0888] "Device" refers to all equipment installed in a vehicle for measurement and analysis.

[0889] "Server" refers to a computer system for receiving, analyzing, storing, and notifying data.

[0890] "Driver" means a person who drives a vehicle.

[0891] "Emotional state" refers to the psychological state of the driver as judged from their facial expressions and physiological signs.

[0892] "Evaluation points" refer to numerical evaluation indicators calculated based on the driver's driving behavior and emotional state.

[0893] "Notification" refers to informing the driver of certain information.

[0894] "Benefits" refers to rewards and benefits provided to drivers based on their rating points.

[0895] "Police agency" means a government agency tasked with maintaining public safety and order and enforcing the law.

[0896] A "list" refers to a collection of data organized based on specific criteria.

[0897] "GPS function" refers to technology that uses the Global Positioning System to determine the vehicle's location.

[0898] "Feedback" refers to sharing information with the driver about their driving behavior and emotional state, as well as providing advice to encourage improvement.

[0899] The above are definitions of important words included in the claims.

[0900] The system for implementing this invention is composed of a device installed in a vehicle, a server, and a user interface used by the driver. This system aims to prevent traffic accidents and promote safe driving by analyzing the driver's driving behavior and emotional state and evaluating safe driving.

[0901] Hardware and software used

[0902] The terminal (device installed in the vehicle) uses the following hardware and software:

[0903] AI camera: Used to measure the distance between the vehicle and the vehicle ahead.

[0904] GPS device: Used to obtain driving speed and location information.

[0905] Emotion Engine: Used to analyze the driver's facial expressions and recognize their emotional state.

[0906] Communication device: Used to send collected data to the server.

[0907] Data collection

[0908] The device collects data on vehicle distance, speed, location, and emotional state. For example, it uses an AI camera to measure the distance to the vehicle ahead in real time, and a GPS device to record the driver's current speed and location. At the same time, an emotion engine analyzes the driver's facial expressions to identify their level of concentration and fatigue.

[0909] Data transmission

[0910] The data collected by the device (including distance, speed, location, and emotional state) is sent to a server every minute, packaged in JSON format, and uploaded to the server via the vehicle's Wi-Fi or cellular network.

[0911] Data analysis and evaluation

[0912] The server receives the data sent by the device and performs the following analysis and evaluation:

[0913] Data on vehicle distance and driving speed is analyzed and evaluated based on safe driving standards.

[0914] Emotional data is analyzed to assess the driver's emotional state.

[0915] For example, if the distance between vehicles is equal to or greater than a standard value, the speed is within the speed limit, and the driver is concentrating, safe driving points are added.

[0916] Notifications and Feedback

[0917] The server calculates the evaluation points based on the analysis results and notifies the driver of the results. For example, if 10 points are added to the driver's safe driving points, the driver's smartphone will be notified that "10 points have been added."

[0918] Drivers can log in to the server and check their own rating points. Based on the rating points, they can receive certain benefits (e.g., discounts on license renewal fees, discounts on car insurance premiums).

[0919] Information sharing with the police

[0920] The server creates a list of dangerous drivers and sends it to the police. This list is updated monthly and includes information on drivers who frequently engage in dangerous driving. Police can use this list to plan efficient patrols and work to prevent traffic accidents.

[0921] Examples of concrete examples and prompts

[0922] As a concrete example, consider the following scenario:

[0923] Data collected by the device:

[0924] Distance between vehicles: Always appropriate (e.g., maintain a distance of at least 2 seconds)

[0925] Driving speed: Within the speed limit (e.g. always adhere to the speed limit of 100km / h)

[0926] Emotional state: Focused, relaxed

[0927] Server Action:

[0928] The received data is analyzed and determined to meet all criteria.

[0929] Safe driving points are added to the driver (e.g., 10 points are added).

[0930] User Action:

[0931] Drivers log in to the server and check their evaluation points.

[0932] Apply for a discount on your license renewal fee based on your safe driving points (e.g., 20 points for a 5% discount).

[0933] Receive feedback on staying focused.

[0934] Examples of prompts include:

[0935] "Please explain the system in which a vehicle automatically measures the distance to the vehicle ahead and analyzes the driver's facial expressions to evaluate safe driving."

[0936] "Please give a concrete example of a system that calculates evaluation points based on the driver's emotional data and provides rewards based on those points."

[0937] "Please provide the police with a list of dangerous drivers and explain how the system works to support efficient patrols."

[0938] In this way, the system of the present invention comprehensively evaluates the driver's driving behavior and emotional state, promoting safe driving. Furthermore, by providing rewards and feedback based on the evaluation, it is expected to increase driver motivation. Furthermore, it is also characterized by the ability to implement efficient traffic safety measures in cooperation with police agencies.

[0939] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0940] Step 1:

[0941] Data collection

[0942] The device collects data on vehicle distance, driving speed, location, and emotional state.

[0943] Specifically, the AI ​​camera measures the distance to the vehicle ahead in real time, and a GPS device records the current speed and location. At the same time, an emotion engine analyzes the driver's facial expressions to recognize their level of concentration and fatigue.

[0944] It receives camera image data, GPS data, and facial expression data as input.

[0945] As outputs, it generates distance data, speed data, position data, and emotion data.

[0946] Step 2:

[0947] Data transmission

[0948] The terminal transmits the collected data to the server.

[0949] Specifically, data on vehicle distance, speed, location, and emotional state is packaged in JSON format and uploaded to a server via the vehicle's Wi-Fi or cellular network.

[0950] As input, it takes the data generated in step 1.

[0951] As an output, the submitted data is sent to the server.

[0952] Step 3:

[0953] Data reception

[0954] The server receives the data sent from the terminal.

[0955] Specifically, the data is received from the terminal via the data receiving endpoint and stored in the database.

[0956] As input, it receives data sent from the terminal.

[0957] As output, it produces data that is recorded in a database.

[0958] Step 4:

[0959] Data analysis

[0960] The server analyzes the received data.

[0961] Specifically, the system analyzes data on vehicle distance and speed based on safe driving standards, and analyzes emotional data to assess the driver's state, for example, determining whether the vehicle distance is appropriate, the speed is within the speed limit, and whether the driver is maintaining a focused state.

[0962] As input, it uses vehicle distance data, speed data, position data, and emotion data recorded in a database.

[0963] As outputs, safe driving evaluation data and emotional state evaluation data are generated.

[0964] Step 5:

[0965] Rating point calculation

[0966] The server calculates the evaluation points based on the analysis results.

[0967] Specifically, based on the analyzed data, points are added if the criteria are met, and points are subtracted if substandard driving or a bad emotional state is recognized.

[0968] As input, the safe driving evaluation data and emotional state evaluation data generated in step 4 are used.

[0969] As an output, it produces rating points.

[0970] Step 6:

[0971] Notifications and Feedback

[0972] The server notifies the driver of the evaluation results and provides feedback.

[0973] Specifically, when the rating points are updated, a notification is sent to the driver's smartphone in real time, and the driver can log in to the server to check the rating points and receive feedback.

[0974] Uses rating points as input.

[0975] As output, it generates notification messages and feedback data.

[0976] Step 7:

[0977] Offering benefits

[0978] The server provides rewards to drivers based on their evaluation points.

[0979] As a specific operation, benefits based on the evaluation points (e.g., discounts on license renewal fees, discounts on car insurance premiums) are presented.

[0980] Uses rating points as input.

[0981] As an output, it generates bonus information.

[0982] Step 8:

[0983] Information sharing with the police

[0984] The server creates a list of dangerous drivers and sends it to the police.

[0985] Specifically, the system organizes data on drivers who frequently engage in dangerous driving, creates a list, and sends it to police agencies.

[0986] It uses historical and evaluation data as input.

[0987] As an output, a list of risky drivers is generated and sent to police agencies.

[0988] (Application example 2)

[0989] 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."

[0990] Conventional safe driving evaluation systems only evaluate a driver's driving behavior and do not take into account the driver's emotional state. As a result, they are unable to fully assess the risks posed by drivers who are fatigued or stressed. Furthermore, there is a lack of concrete means for utilizing the collected data to improve actual driving safety and for effective monitoring by police agencies. Therefore, there is a need for a system that takes into account a driver's emotional state and provides safe driving evaluation and effective feedback.

[0991] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0992] In this invention, the server includes a means for measuring the inter-vehicle distance and traveling speed from a device mounted on the vehicle, a means for analyzing the driver's facial expression and recognizing the emotional state, a means for transmitting data on the measured inter-vehicle distance and traveling speed and the recognized emotional state to the server, a means for analyzing the transmitted data and calculating an evaluation point, and a means for notifying the driver of feedback based on the calculated evaluation point and the emotional state. This enables safe driving evaluation and individual feedback that takes the driver's emotional state into consideration, making it possible to promote comprehensive safe driving and effectively share information with police agencies.

[0993] "Following distance" refers to the safe distance a vehicle should maintain between itself and the vehicle in front.

[0994] "Traveling speed" refers to the speed at which a vehicle is moving and is expressed in units that measure that speed.

[0995] "Facial expression analysis" refers to a technology that analyzes a driver's facial expressions in real time and identifies their emotional state.

[0996] "Emotional state" refers to the emotional state a driver has while driving, including, for example, fatigue, stress, and concentration.

[0997] "Data transmission" refers to the process of transmitting data detected within the vehicle to a server over a network.

[0998] "Evaluation points" refer to evaluation values ​​for the driver's driving behavior and emotional state calculated based on analyzed data.

[0999] "Feedback" refers to specific instructions or advice provided to the driver based on their calculated rating points and emotional state.

[1000] "Benefits" refers to rewards and privileges provided to drivers based on their rating points.

[1001] "Police agency" means a public agency that maintains law and order and monitors safe driving.

[1002] The "list" refers to a compilation of drivers who engage in dangerous driving.

[1003] "GPS Functionality" refers to technology for measuring geolocation and determining the vehicle's current location and speed.

[1004] A "generative AI model" refers to an algorithm that performs analysis and response automatically generated using artificial intelligence.

[1005] A "prompt sentence" refers to an instruction or query sentence that is input into a generative AI model.

[1006] The system for implementing this invention consists of a device installed in a vehicle, a server, and a user interface used by the driver. The main purpose of the entire system is to improve road traffic safety, but here we focus on analyzing the driver's facial expressions and providing evaluation and feedback based on their emotional state.

[1007] Data collection and transmission

[1008] The terminal performs the following processing.

[1009] The distance between vehicles is measured using an AI camera.

[1010] Driving speed and location information are obtained using a GPS device.

[1011] The emotion engine analyzes the driver's facial expressions and recognizes their emotional state (e.g., fatigue, stress, concentration).

[1012] The collected data (vehicle distance, driving speed, location information, and emotion data) is sent to a server via communication equipment.

[1013] Data analysis and evaluation

[1014] The server performs the following processing:

[1015] The received data (distance between vehicles, driving speed, location information, emotional data) is analyzed and compared with safe driving standards.

[1016] Emotional data is analyzed to assess the driver's emotional state.

[1017] Based on the analysis results, evaluation points are calculated. Points are added if safe driving is confirmed, and points are subtracted if dangerous driving or a bad emotional state is confirmed.

[1018] Each driver's evaluation points are recorded in a database and notified to the driver in real time.

[1019] Feedback and Rewards

[1020] The server performs the following operations based on the evaluation points and the emotional state.

[1021] Provide appropriate feedback to the driver, such as "You're staying focused. Please continue to drive safely."

[1022] If the driver is fatigued or stressed, the system will provide feedback such as, "We recommend taking a short break."

[1023] Offer drivers rewards (e.g., discounts on license renewal fees, discounts on car insurance premiums) based on their evaluation points.

[1024] Information sharing with police agencies

[1025] The server generates a list of dangerous drivers and periodically shares this list with police agencies, allowing them to identify drivers who should be monitored more intensively and build a more efficient monitoring system.

[1026] Hardware and software used

[1027] AI camera: Used to measure the distance between vehicles.

[1028] GPS device: Used to obtain driving speed and location information.

[1029] Emotion Engine: Used to analyze the driver's facial expressions and recognize their emotional state.

[1030] Server: Used to receive and analyze data, calculate reputation points, and generate feedback.

[1031] Software: OpenCV (image processing and facial expression analysis), Dlib (facial feature point detection and emotion analysis), Geopy (location information processing), Requests (data transmission).

[1032] Specific examples

[1033] For example, a vehicle traveling on a highway uses an AI camera to measure the distance to the vehicle ahead, and collects driving speed and location information in real time using acquired GPS data. At the same time, an emotion engine analyzes the driver's facial expressions and recognizes their emotional state, such as "concentrated" or "relaxed." This data is sent to a server via the vehicle's communications device, and based on the analysis results, a notification is sent to the driver, such as "10 points have been added."

[1034] Prompt Sentence Examples

[1035] "The current following distance is 10 metres and the driver's emotional state is focused."

[1036] "Maintaining current speed of 60 km / h while maintaining appropriate following distance."

[1037] "We recommend taking timely rest breaks to reduce stress while driving."

[1038] In this way, this system comprehensively evaluates the driver's driving behavior and emotional state, promoting safe driving and helping to prevent accidents by sharing information with police agencies.

[1039] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1040] Step 1:

[1041] Data collection

[1042] The device measures the distance between vehicles using an AI camera. The acquired distance becomes the input for the next data processing. At the same time, the device uses a GPS device to acquire driving speed and location information. It also uses an emotion engine to analyze the driver's facial expressions and recognize their emotional state (e.g., fatigue, stress, concentration). This data (distance between vehicles, driving speed, location information, emotional state) is temporarily stored in the vehicle's local memory.

[1043] Step 2:

[1044] Data transmission

[1045] The device sends the collected data (distance between vehicles, driving speed, location information, emotional state) to the server. A communication module is used for transmission, and the data is protected by an encrypted protocol. The input of this process is the data collected in step 1, and the output is the data sent to the server.

[1046] Step 3:

[1047] Data reception and analysis

[1048] The server receives data sent from the device. This data includes the following distance, driving speed, location information, and emotional state. It performs data analysis based on the received data and compares it with safe driving standards. For example, it checks whether the following distance meets the safety standard and whether the driving speed exceeds the speed limit. The input of this process is the sent data, and the output is the analysis result.

[1049] Step 4:

[1050] Emotional state assessment

[1051] The server analyzes the received emotion data and evaluates the driver's emotional state. For example, it determines whether the driver is tired or focused based on the results of facial expression analysis. The input of this process is emotion data, and the output is the emotion evaluation result.

[1052] Step 5:

[1053] Calculation of evaluation points

[1054] The server calculates evaluation points based on the data analysis and the evaluation results of the emotional state. Points are added if safe driving is confirmed, and points are subtracted if dangerous driving or a bad emotional state is confirmed. The input of this process is the analysis results and evaluation results, and the output is the evaluation points.

[1055] Step 6:

[1056] Real-time notifications

[1057] The server generates a feedback message for the driver based on the calculated evaluation points and emotional state. For example, if safe driving is confirmed, the server generates feedback such as "You are maintaining concentration. Please continue to drive safely." This feedback is notified to the driver's user interface in real time. The inputs of this process are the evaluation points and emotional state, and the output is a feedback message.

[1058] Step 7:

[1059] Offer

[1060] The server provides rewards to drivers based on their rating points. Each driver's rating points are recorded in a database, and rewards (e.g., discounts on license renewal fees, discounts on car insurance premiums) are offered according to the points. In this process, reward information is sent to the driver. The input of this process is the rating points, and the output is a reward offer message.

[1061] Step 8:

[1062] Information sharing with police agencies

[1063] The server generates a list of dangerous drivers and periodically sends this list to the police, allowing the police to identify drivers who should be monitored more closely. The input of this process is the evaluation data, and the output is the list of dangerous drivers.

[1064] 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.

[1065] 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.

[1066] 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.

[1067] [Third embodiment]

[1068] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1069] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1070] 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).

[1071] 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.

[1072] 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.

[1073] 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).

[1074] 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.

[1075] 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.

[1076] 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.

[1077] 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.

[1078] 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.

[1079] 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."

[1080] ---

[1081] A system for implementing the present invention comprises a device installed in a vehicle, a server, and a user interface used by the driver.

[1082] Data collection and transmission

[1083] The terminal (AI camera and GPS device installed in the vehicle) performs the following functions while the vehicle is driving.

[1084] The distance between vehicles is measured using an AI camera.

[1085] Driving speed and location information are obtained using a GPS device.

[1086] The collected data is sent to a server at a predetermined timing or at regular intervals.

[1087] For example, a vehicle traveling on a highway automatically measures the distance to the vehicle ahead and acquires real-time speed and location information using a GPS device. This data is then sent to a server via the vehicle's communications equipment.

[1088] Data analysis and evaluation

[1089] The server receives the data sent from the terminal and performs the following analysis and evaluation.

[1090] Analyze data on vehicle distance and speed according to safe driving standards.

[1091] Based on the analysis results, evaluation points are calculated.

[1092] Each driver's rating points are recorded in a database.

[1093] For example, if the following distance meets the safety standard, points are added, while if the following distance is too short and the speed is over the limit, points are subtracted.

[1094] Point notification and management

[1095] The server manages the evaluation points for each driver and performs the following operations:

[1096] When a driver's evaluation points are updated, the results will be notified in real time.

[1097] Drivers can log in to the server and check their rating points and details.

[1098] It also has a function for offering rewards based on points (e.g., discounts on license renewal fees, discounts on car insurance premiums).

[1099] For example, a driver who continues to drive safely will receive a notification from the server saying, "You have been awarded 10 points," and the driver's history can be viewed on the user interface.

[1100] Information sharing with the police

[1101] The server shares information with police agencies.

[1102] Organize data on drivers who have been detected driving recklessly.

[1103] Regularly compile and share lists of dangerous drivers.

[1104] Based on this, the police can carry out focused patrols.

[1105] For example, a list of drivers who frequently engage in dangerous driving could be compiled and sent to the police, who could then use it to efficiently plan patrols and prevent accidents.

[1106] Specific examples

[1107] Data collected by the device:

[1108] Distance between vehicles: Always appropriate (e.g., maintain a distance of at least 2 seconds)

[1109] Driving speed: Within the speed limit (e.g. always adhere to the speed limit of 100km / h)

[1110] Server Action:

[1111] The received data is analyzed and determined to meet all criteria.

[1112] Safe driving points are added to the driver (e.g., 10 points are added).

[1113] User Action:

[1114] Drivers log in to the server and check their evaluation points.

[1115] Apply for a discount on your license renewal fee based on your safe driving points (e.g., 20 points for a 5% discount).

[1116] In this way, the system of the present invention evaluates the driver's driving behavior in real time, promotes safe driving, and supports the efficiency of patrols and accident prevention through effective information sharing with police agencies.

[1117] The processing flow will be explained below.

[1118] ---

[1119] Step 1:

[1120] While the vehicle is moving, the device uses an AI camera to measure the distance to the vehicle ahead, and also obtains driving speed and location information using a GPS device.

[1121] Step 2:

[1122] The terminal formats the data it acquires, including vehicle distance, driving speed, and location information, and sends it to the server via the communication module.

[1123] Step 3:

[1124] The server analyzes the data received from the device, specifically assessing whether the distance between vehicles meets safety standards and whether the driving speed exceeds the speed limit.

[1125] Step 4:

[1126] The server calculates evaluation points based on the analysis results, adding points if safe driving is confirmed and subtracting points if dangerous driving is confirmed.

[1127] Step 5:

[1128] The server records each driver's rating points in a database, and if new points are added, the driver's total points are updated.

[1129] Step 6:

[1130] The server sends notifications based on changes in the driver's rating points, either via the application or email associated with the user's account.

[1131] Step 7:

[1132] The user logs in to the server and checks his / her own rating points and driving rating. If the user wants to apply for a reward, he / she selects a discount or reward based on the points and executes the application.

[1133] Step 8:

[1134] The server receives the reward request from the user, checks the validity of the points, and if the conditions are met, applies the reward and deducts the points.

[1135] Step 9:

[1136] The server compiles data on dangerous drivers and periodically creates a list, which is sent to police agencies and updated as needed.

[1137] Step 10:

[1138] Police can efficiently plan and carry out patrols based on the list of dangerous drivers received from the server, and can also issue direct warnings and take action as necessary.

[1139] ---

[1140] Through the above steps, the system of the present invention evaluates the driver's driving behavior, promotes safe driving, and works to prevent accidents by sharing information with police agencies.

[1141] Example 1

[1142] 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."

[1143] Conventional driving behavior evaluation systems have had problems such as incomplete data collection, such as measurement of vehicle distance and speed, and delayed notification of evaluation results. Furthermore, there were also problems with inefficient rewards based on evaluation points and collaboration with police agencies. As a result, they have not been able to adequately motivate drivers to drive safely or prevent dangerous driving.

[1144] 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.

[1145] In this invention, the server includes a means for measuring the distance and speed from a device mounted on the vehicle, a means for transmitting the measured distance and speed data to a data processing device, a means for analyzing the transmitted data and calculating an evaluation value, and a means for notifying the driver of the calculated evaluation value. This enables multifaceted and real-time evaluation of driving behavior. In addition, rewards based on the evaluation value and information sharing with police agencies can be efficiently carried out, which is expected to promote safe driving and prevent dangerous driving.

[1146] A "driving behavior evaluation system" is a system that uses a device installed in a vehicle to measure and evaluate a driver's driving behavior, and notifies and manages the results.

[1147] "Device" is a general term for measuring instruments and communication equipment attached to a vehicle, and is a device that has the function of collecting data such as vehicle-to-vehicle distance, speed, and location information.

[1148] "Inter-vehicle distance" refers to the distance between a moving vehicle and the vehicle in front of it.

[1149] "Speed" refers to the rate at which a vehicle travels a distance in a given time, and is typically expressed in kilometers per hour (km / h).

[1150] A "data processing device" is a computer system that receives collected data, analyzes it, and calculates evaluation values.

[1151] The "evaluation value" is a value calculated based on the analyzed data to indicate the safety and appropriateness of driving behavior.

[1152] "Notification" is an act of communicating information to the driver about the calculated evaluation value, and is performed in real time.

[1153] "Rewards" refers to incentives and benefits offered to drivers based on their rating figures.

[1154] "Patrol agencies" refer to law enforcement agencies such as the police, which work in conjunction with the driving behavior assessment system to monitor and crack down on dangerous driving.

[1155] The "list" is a report or database format that organizes and lists information on dangerous drivers.

[1156] The system for carrying out the present invention comprises a terminal installed in a vehicle, a server, and a user interface used by the driver. This system has the following technical configuration.

[1157] Data collection and transmission

[1158] The terminal (a device installed in the vehicle) performs the following functions while the vehicle is moving:

[1159] The distance between vehicles is measured using an AI camera.

[1160] Driving speed and location information are obtained using a GPS device.

[1161] The collected data is sent to a server at a predetermined timing or at regular intervals.

[1162] For example, a vehicle traveling on a highway automatically measures the distance to the vehicle ahead and acquires real-time speed and location information using a GPS device. This data is then sent to a server via the vehicle's communications equipment.

[1163] Data analysis and evaluation

[1164] The server receives the data sent from the terminal and performs the following analysis and evaluation.

[1165] Analyze data on vehicle distance and speed according to safe driving standards.

[1166] Based on the analysis results, an evaluation value is calculated.

[1167] Each driver's rating is recorded in a database.

[1168] For example, if the following distance meets the safety standard, points are added, while if the following distance is too short and the speed is over the limit, points are subtracted.

[1169] Point notification and management

[1170] The server manages the evaluation values ​​for each driver and performs the following operations:

[1171] When a driver's rating is updated, the results will be notified in real time.

[1172] Drivers can log in to the server and check their rating numbers and details.

[1173] It also has a function to offer benefits based on the evaluation figures (e.g., discounts on license renewal fees, discounts on car insurance premiums).

[1174] For example, a driver who continues to drive safely will receive a notification from the server saying, "You have been awarded 10 points," and the driver's history can be viewed on the user interface.

[1175] Information sharing with the police

[1176] The server shares information with police agencies.

[1177] Organize data on drivers who have been detected driving recklessly.

[1178] Regularly compile and share lists of dangerous drivers.

[1179] Based on this, the police will carry out intensive patrols.

[1180] For example, a list of drivers who frequently engage in dangerous driving will be compiled and sent to the police, who will then use this information to efficiently plan patrols and work to prevent accidents.

[1181] Specific examples

[1182] Data collected by the device:

[1183] Distance between vehicles: Always appropriate (e.g., maintain a distance of at least 2 seconds)

[1184] Driving speed: Within the speed limit (e.g. always adhere to the speed limit of 100km / h)

[1185] Server Action:

[1186] The received data is analyzed and determined to meet all criteria.

[1187] Safe driving points are added to the driver (e.g., 10 points are added).

[1188] User Action:

[1189] Drivers log in to the server and check their evaluation points.

[1190] Apply for a discount on your license renewal fee based on your safe driving points (e.g., 20 points for a 5% discount).

[1191] The system of this invention evaluates the driving behavior of drivers in real time to promote safe driving. It also supports the efficiency of patrols and accident prevention through effective information sharing with police agencies.

[1192] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1193] Step 1:

[1194] Data collection

[1195] The terminal (an AI camera or GPS device installed inside the vehicle) collects data from the vehicle while it is in motion.

[1196] Input: distance between vehicles, driving speed, location information

[1197] Specific operation: When the vehicle starts moving, the AI ​​camera measures the distance to the vehicle in front, and the GPS device collects the vehicle's speed and location information. For example, the AI ​​camera measures the distance every second, and the GPS device similarly obtains the vehicle's current location and speed every second.

[1198] Output: Inter-vehicle distance data, speed data, location data

[1199] Step 2:

[1200] Data transmission

[1201] The terminal transmits the collected data to the server.

[1202] Input: Inter-vehicle distance data, speed data, location data

[1203] Specific operation: Collected data is packaged at regular intervals (e.g., 1 minute) and sent to a server using the vehicle's communications equipment. The transmission interval can be adjusted, but a short interval is recommended to ensure real-time data transmission.

[1204] Output: Data package received by the server

[1205] Step 3:

[1206] Data analysis

[1207] The server analyzes the data sent from the terminal.

[1208] Input: Received data package (distance data, speed data, location data)

[1209] Specific operation: The server applies an analysis algorithm to the received data and compares it with safe driving standards. For example, if the distance between vehicles is more than 2 seconds and the driving speed is within the speed limit, it is judged as safe driving and points are added to the driver's score. If there is a violation, points are subtracted.

[1210] Output: Rating points

[1211] Step 4:

[1212] Calculation of evaluation points

[1213] The server calculates the evaluation points based on the analysis results.

[1214] Input: Analysis results (distance between vehicles, speed)

[1215] Specific operation: Calculates the evaluation points based on the analysis results. For example, add or subtract points from each analysis data to calculate the overall evaluation points.

[1216] Output: Calculated rating points

[1217] Step 5:

[1218] Point notification

[1219] The server notifies the driver of the calculated evaluation points.

[1220] Input: Rating points

[1221] Specific operation: Once the evaluation points have been calculated, the driver is notified in real time. For example, a notification saying "10 points added" is displayed on a smartphone app or on the in-car display.

[1222] Output: Rating points reported to the driver

[1223] Step 6:

[1224] Check in the user interface

[1225] The user (driver) checks the evaluation points.

[1226] Input: Notifications from the server, login information

[1227] How it works: Drivers can log in to the app on their smartphone or in-car display and check their rating point history and details. For example, it will show "Current points: 50 points," and they can also check the history and data analysis details.

[1228] Output: Driver's rating points information

[1229] Step 7:

[1230] Information sharing with the police

[1231] The server shares information with police agencies.

[1232] Input: Dangerous driving data, evaluation point data

[1233] Specific operation: The server creates a list of drivers who have been detected as driving recklessly and periodically provides it to the police. For example, a list such as "Driver A - Insufficient distance - 3 times, Driver B - Speeding - 2 times" is generated and uploaded to the police database.

[1234] Output: A list of dangerous drivers provided to police agencies

[1235] (Application example 1)

[1236] 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."

[1237] Conventional driving behavior evaluation systems lack sufficient data visualization and real-time feedback, making it difficult to immediately promote safe driving by drivers. In addition, there was a lack of means to provide immediate alerts for dangerous driving behavior, making it difficult to ensure safety.

[1238] 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.

[1239] In this invention, the server includes a means for measuring the inter-vehicle distance and traveling speed from a device mounted on the vehicle, a means for transmitting the measured inter-vehicle distance and traveling speed data to the server, a means for analyzing the transmitted data and calculating an evaluation point, a means for notifying the driver of the calculated evaluation point, a means for visualizing the inter-vehicle distance and traveling speed information in real time, and a means for providing visual and audio alerts as necessary, thereby enabling the driver to immediately understand his / her driving behavior while driving and receive appropriate feedback to maintain safe driving.

[1240] "Following distance" refers to the physical distance between you and the vehicle in front.

[1241] "Traveling speed" refers to the speed at which a vehicle is moving.

[1242] "Server" refers to the system that analyzes collected data, calculates and manages evaluation points.

[1243] "Device" refers to a device installed in a vehicle that measures the distance between vehicles and the driving speed.

[1244] "Evaluation points" refer to points calculated based on the driver's driving behavior.

[1245] "Driver" means a person who drives a vehicle.

[1246] "Real-time" refers to the instantaneous collection and processing of data.

[1247] "Visualization" refers to the visual display of data.

[1248] "Visual alert" refers to a visual warning that alerts the driver.

[1249] "Voice alert" refers to a function that warns the driver by voice.

[1250] "Location information function" refers to technology such as GPS for measuring current location.

[1251] An "unsafe driver" is a driver whose driving behavior does not meet safe driving standards.

[1252] "Benefits" refers to rewards and benefits provided to drivers based on their rating points.

[1253] A system for implementing the present invention comprises a device installed in a vehicle, a server, and a user interface used by the driver.

[1254] Data collection and transmission

[1255] The terminal (such as a camera or GPS device mounted in the vehicle) performs the following functions while the vehicle is traveling:

[1256] The distance between vehicles is measured using a camera.

[1257] Driving speed and location information are obtained using a GPS device.

[1258] This data is transmitted to the server at regular intervals.

[1259] For example, a vehicle traveling on a highway automatically measures the distance to the vehicle ahead, obtains speed and location information in real time using a GPS device, and transmits the collected data to a server via communication equipment inside the vehicle.

[1260] Data analysis and evaluation

[1261] The server receives the data sent from the terminal and performs the following analysis and evaluation.

[1262] Data on vehicle distance and driving speed is analyzed, and evaluation points are calculated according to safe driving standards.

[1263] Each driver's rating points are recorded in a database.

[1264] For example, points are added if the following distance meets safety standards, while points are subtracted if the following distance is too short and the speed is above the limit.

[1265] Point notification and management

[1266] The server manages the evaluation points for each driver and performs the following operations:

[1267] When a driver's evaluation points are updated, the results will be notified in real time.

[1268] Drivers can log in to the server and check their rating points and details.

[1269] It also has the ability to offer rewards based on points (e.g., discounts on license renewal fees, discounts on car insurance premiums).

[1270] For example, a driver who continues to drive safely will receive a notification from the server saying, "You have been awarded 10 points," and the driver's history can be viewed on the user interface.

[1271] Real-time visibility and alerts

[1272] Smart glasses or a head-mounted display (HMD) can be used as a user interface.

[1273] Visualize real-time information on distance and driving speed.

[1274] Provide visual and audio alerts as needed.

[1275] For example, a driver can see through smart glasses that the distance to the vehicle ahead is 15m and the speed is 90km / h, and a visual and audio alert will be issued if the distance becomes too close.

[1276] Information sharing with the police

[1277] The server shares information with police agencies.

[1278] Organize data on drivers who have been detected driving recklessly.

[1279] Regularly compile and share lists of dangerous drivers.

[1280] Based on this, the police can carry out focused patrols.

[1281] For example, a list of drivers who frequently engage in dangerous driving could be created and sent to the police, allowing them to efficiently plan patrols and work to prevent accidents.

[1282] Program processing

[1283] The server uses Python and TensorFlow for remote data analysis, processes data sent from vehicles in real time, calculates evaluation points, and generates safe driving alerts. It also uses the requests library to manage data transmission and reception.

[1284] For example, while driving, drivers can check the information displayed on the smart glasses and, if a safe distance is maintained, receive a notification that "safe driving points have been added." Visual and audio alerts provide immediate warning when unsafe conditions occur.

[1285] Prompt Sentence Examples

[1286] "This application displays real-time driving data on smart glasses, monitors the distance and speed of vehicles in front of the car, and sends an alert when the distance falls below a certain level."

[1287] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1288] Step 1:

[1289] The device collects data on vehicle distance and speed.

[1290] Specific operation: The camera installed on the device uses an AI model to measure the distance to the vehicle ahead, and the GPS device obtains the current driving speed and location information.

[1291] Input: Video data, GPS data.

[1292] Output: Inter-vehicle distance, speed, position information.

[1293] Step 2:

[1294] The terminal transmits the collected data to the server.

[1295] Specific operation: Data is encoded at regular intervals and sent to the server via the terminal's communication equipment.

[1296] Input: distance, speed, location.

[1297] Output: The data sent to the server.

[1298] Step 3:

[1299] The server parses the received data.

[1300] Specific operation: The server uses the TensorFlow model to analyze the transmitted distance and speed data and calculates evaluation points according to safe driving standards.

[1301] Input: distance, speed, location.

[1302] Data processing: analysis, calculation of evaluation points.

[1303] Output: Rating points.

[1304] Step 4:

[1305] The server notifies the driver of the evaluation points.

[1306] How it works: The evaluation points are calculated and displayed in real time on the driver's user interface (smart glasses or HMD). Visual and audio alerts are also provided if necessary.

[1307] Input: Rating points.

[1308] Output: Rating points notified to the driver, visual and audio alerts.

[1309] Step 5:

[1310] The server records the evaluation points in a database and provides rewards.

[1311] Specific operation: The evaluation points are recorded in a database and the driver is given benefits (e.g., a discount on license renewal fees).

[1312] Input: Rating points.

[1313] Output: Reputation points recorded in the database, rewards provided.

[1314] Step 6:

[1315] The server shares information with police agencies and generates a list of dangerous drivers.

[1316] Specific operation: Based on the analysis results, a list of dangerous drivers is created and sent to police agencies on a regular basis.

[1317] Input: Evaluation point data.

[1318] Data processing: List generation.

[1319] Output: A list of dangerous drivers sent to police agencies.

[1320] Step 7:

[1321] Police will conduct targeted patrols based on a list of dangerous drivers.

[1322] Specific actions: Based on the list sent, police will develop patrol plans for areas with high rates of dangerous driving and strengthen safety measures.

[1323] Input: Dangerous Driver List.

[1324] Output: Developing and implementing patrol plans.

[1325] By using the above processing steps, the present invention can evaluate the driver's driving behavior in real time and promote safe driving. In addition, by sharing information with police agencies, a system for preventing dangerous driving can be established.

[1326] 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.

[1327] ---

[1328] The system for implementing the present invention is composed of a device installed in a vehicle, a server, and a user interface used by the driver. In addition, by adding a function to analyze the driver's facial expressions and recognize their emotions, it is possible to evaluate not only the driving behavior but also the driver's emotional state.

[1329] Data collection and transmission

[1330] The terminal (the AI ​​camera, GPS device, and emotion engine installed in the vehicle) performs the following functions while the vehicle is driving:

[1331] The distance between vehicles is measured using an AI camera.

[1332] Driving speed and location information are obtained using a GPS device.

[1333] The emotion engine analyzes the driver's facial expressions and recognizes their emotional state (e.g., fatigue, stress, concentration).

[1334] The collected data (vehicle distance, driving speed, location information, emotion data) is sent to a server at a set time or at regular intervals.

[1335] For example, a vehicle traveling on a highway automatically measures the distance to the vehicle ahead and acquires speed and location information in real time using a GPS device. At the same time, an emotion engine analyzes the driver's facial expressions and obtains their emotional state as data. This data is then sent to a server via the vehicle's communications equipment.

[1336] Data analysis and evaluation

[1337] The server receives the data sent from the terminal and performs the following analysis and evaluation.

[1338] Analyze data on vehicle distance and speed according to safe driving standards.

[1339] Emotional data is analyzed to assess the driver's emotional state.

[1340] Based on the analysis results, evaluation points are calculated. Points are added if safe driving is confirmed, and points are subtracted if dangerous driving or a bad emotional state is confirmed.

[1341] Each driver's rating points are recorded in a database.

[1342] For example, points are added if the following distance meets safety standards and the driver is deemed to be concentrating, while points are subtracted if the following distance is too short, the speed is over the limit, and the driver is deemed to be fatigued.

[1343] Point notification and management

[1344] The server manages the evaluation points for each driver and performs the following operations:

[1345] When a driver's evaluation points are updated, the results will be notified in real time.

[1346] Drivers can log in to the server and check their rating points and details.

[1347] It also has a function for offering rewards based on points (e.g., discounts on license renewal fees, discounts on car insurance premiums).

[1348] Providing feedback and advice based on emotional state.

[1349] For example, if a driver continues to drive safely and maintains a good emotional state, the server will send a notification saying, "You've been awarded 10 points," and the driver's score history can be checked on the user interface. If the driver is deemed to be fatigued, the server will also send a notification saying, "We recommend you take a break."

[1350] Information sharing with the police

[1351] The server shares information with police agencies.

[1352] Organize data on drivers who have been detected driving recklessly.

[1353] Regularly compile and share lists of dangerous drivers.

[1354] Based on this, the police can carry out focused patrols.

[1355] For example, a list of drivers who frequently engage in dangerous driving could be compiled and sent to the police, who could then use it to efficiently plan patrols and prevent accidents.

[1356] Specific examples

[1357] Data collected by the device:

[1358] Distance between vehicles: Always appropriate (e.g., maintain a distance of at least 2 seconds)

[1359] Driving speed: Within the speed limit (e.g. always adhere to the speed limit of 100km / h)

[1360] Emotional state: Focused, relaxed

[1361] Server Action:

[1362] The received data is analyzed and determined to meet all criteria.

[1363] Safe driving points are added to the driver (e.g., 10 points are added).

[1364] User Action:

[1365] Drivers log in to the server and check their evaluation points.

[1366] Apply for a discount on your license renewal fee based on your safe driving points (e.g., 20 points for a 5% discount).

[1367] Receive feedback on staying focused.

[1368] In this way, the system of the present invention not only evaluates the driver's driving behavior but also their emotional state in real time, promoting safe driving. Furthermore, by effectively sharing information with police agencies, it supports the efficiency of patrols and accident prevention.

[1369] The processing flow will be explained below.

[1370] ---

[1371] Step 1:

[1372] While the vehicle is moving, the device uses an AI camera to measure the distance to the vehicle ahead. It also uses a GPS device to acquire driving speed and location information. The emotion engine also analyzes the driver's facial expressions to recognize their emotional state.

[1373] Step 2:

[1374] The device formats the acquired data, such as vehicle distance, driving speed, location information, and emotion data, and transmits the formatted data to the server via the communication module.

[1375] Step 3:

[1376] The server analyzes the data received from the device, assessing whether the following distance meets safety standards, whether the driving speed exceeds the speed limit, and the driver's emotional state.

[1377] Step 4:

[1378] The server calculates evaluation points based on the analysis results. Specifically, points are added if safe driving and a good emotional state are confirmed, and points are subtracted if dangerous driving and a bad emotional state are confirmed.

[1379] Step 5:

[1380] The server records each driver's rating points in a database, and if new points are added, the driver's total points are updated.

[1381] Step 6:

[1382] The server sends notifications based on changes in the driver's rating points, either via the app or email associated with the user's account.

[1383] Step 7:

[1384] The user logs in to the server and checks his / her own rating points and driving rating. If the user wants to apply for a reward, he / she selects a discount or reward based on the points and executes the application.

[1385] Step 8:

[1386] The server receives the reward request from the user, checks the validity of the points, and if the conditions are met, applies the reward and deducts the points.

[1387] Step 9:

[1388] The server evaluates the emotional data and sends a notification to alert you if a particular emotional state (e.g., fatigue or high stress) is detected.

[1389] Step 10:

[1390] The server records emotional data over time and analyzes patterns of the driver's emotional state, generating a long-term emotional assessment report.

[1391] Step 11:

[1392] The server compiles data on dangerous drivers and periodically creates a list, which is sent to police agencies and updated as needed.

[1393] Step 12:

[1394] Police can efficiently plan and carry out patrols based on the list of dangerous drivers received from the server, and can also issue direct warnings and take action as necessary.

[1395] ---

[1396] Through the above steps, the system of the present invention evaluates the driver's driving behavior and emotional state, promotes safe driving, and works to prevent accidents by sharing information with police agencies.

[1397] Example 2

[1398] 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."

[1399] Conventional driver evaluation systems only evaluate driving behavior and do not consider the driver's emotional state, making it difficult to accurately evaluate safe driving. Furthermore, there is a lack of a means to efficiently share information on dangerous drivers with police agencies, limiting their effectiveness in preventing traffic accidents.

[1400] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for analyzing the driver's facial expression and recognizing the emotional state, a means for transmitting data on the emotional state, and a means for analyzing the data on the emotional state and evaluating it based on safe driving standards. This makes it possible to evaluate not only the driver's driving behavior but also their emotional state.

[1401] "Inter-vehicle distance" refers to the distance between your vehicle and the vehicle ahead.

[1402] "Traveling speed" is the distance a vehicle travels in a certain period of time expressed in speed units (e.g., km / h).

[1403] "Device" refers to all equipment installed in a vehicle for measurement and analysis.

[1404] "Server" refers to a computer system for receiving, analyzing, storing, and notifying data.

[1405] "Driver" means a person who drives a vehicle.

[1406] "Emotional state" refers to the psychological state of the driver as judged from their facial expressions and physiological signs.

[1407] "Evaluation points" refer to numerical evaluation indicators calculated based on the driver's driving behavior and emotional state.

[1408] "Notification" refers to informing the driver of certain information.

[1409] "Benefits" refers to rewards and benefits provided to drivers based on their rating points.

[1410] "Police agency" means a government agency tasked with maintaining public safety and order and enforcing the law.

[1411] A "list" refers to a collection of data organized based on specific criteria.

[1412] "GPS function" refers to technology that uses the Global Positioning System to determine the vehicle's location.

[1413] "Feedback" refers to sharing information with the driver about their driving behavior and emotional state, as well as providing advice to encourage improvement.

[1414] The above are definitions of important words included in the claims.

[1415] The system for implementing this invention is composed of a device installed in a vehicle, a server, and a user interface used by the driver. This system aims to prevent traffic accidents and promote safe driving by analyzing the driver's driving behavior and emotional state and evaluating safe driving.

[1416] Hardware and software used

[1417] The terminal (device installed in the vehicle) uses the following hardware and software:

[1418] AI camera: Used to measure the distance between the vehicle and the vehicle ahead.

[1419] GPS device: Used to obtain driving speed and location information.

[1420] Emotion Engine: Used to analyze the driver's facial expressions and recognize their emotional state.

[1421] Communication device: Used to send collected data to the server.

[1422] Data collection

[1423] The device collects data on vehicle distance, speed, location, and emotional state. For example, it uses an AI camera to measure the distance to the vehicle ahead in real time, and a GPS device to record the driver's current speed and location. At the same time, an emotion engine analyzes the driver's facial expressions to identify their level of concentration and fatigue.

[1424] Data transmission

[1425] The data collected by the device (including distance, speed, location, and emotional state) is sent to a server every minute, packaged in JSON format, and uploaded to the server via the vehicle's Wi-Fi or cellular network.

[1426] Data analysis and evaluation

[1427] The server receives the data sent by the device and performs the following analysis and evaluation:

[1428] Data on vehicle distance and driving speed is analyzed and evaluated based on safe driving standards.

[1429] Emotional data is analyzed to assess the driver's emotional state.

[1430] For example, if the distance between vehicles is equal to or greater than a standard value, the speed is within the speed limit, and the driver is concentrating, safe driving points are added.

[1431] Notifications and Feedback

[1432] The server calculates the evaluation points based on the analysis results and notifies the driver of the results. For example, if 10 points are added to the driver's safe driving points, the driver's smartphone will be notified that "10 points have been added."

[1433] Drivers can log in to the server and check their own rating points. Based on the rating points, they can receive certain benefits (e.g., discounts on license renewal fees, discounts on car insurance premiums).

[1434] Information sharing with the police

[1435] The server creates a list of dangerous drivers and sends it to the police. This list is updated monthly and includes information on drivers who frequently engage in dangerous driving. Police can use this list to plan efficient patrols and work to prevent traffic accidents.

[1436] Examples of concrete examples and prompts

[1437] As a concrete example, consider the following scenario:

[1438] Data collected by the device:

[1439] Distance between vehicles: Always appropriate (e.g., maintain a distance of at least 2 seconds)

[1440] Driving speed: Within the speed limit (e.g. always adhere to the speed limit of 100km / h)

[1441] Emotional state: Focused, relaxed

[1442] Server Action:

[1443] The received data is analyzed and determined to meet all criteria.

[1444] Safe driving points are added to the driver (e.g., 10 points are added).

[1445] User Action:

[1446] Drivers log in to the server and check their evaluation points.

[1447] Apply for a discount on your license renewal fee based on your safe driving points (e.g., 20 points for a 5% discount).

[1448] Receive feedback on staying focused.

[1449] Examples of prompts include:

[1450] "Please explain the system in which a vehicle automatically measures the distance to the vehicle ahead and analyzes the driver's facial expressions to evaluate safe driving."

[1451] "Please give a concrete example of a system that calculates evaluation points based on the driver's emotional data and provides rewards based on those points."

[1452] "Please provide the police with a list of dangerous drivers and explain how the system works to support efficient patrols."

[1453] In this way, the system of the present invention comprehensively evaluates the driver's driving behavior and emotional state, promoting safe driving. Furthermore, by providing rewards and feedback based on the evaluation, it is expected to increase driver motivation. Furthermore, it is also characterized by the ability to implement efficient traffic safety measures in cooperation with police agencies.

[1454] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1455] Step 1:

[1456] Data collection

[1457] The device collects data on vehicle distance, driving speed, location, and emotional state.

[1458] Specifically, the AI ​​camera measures the distance to the vehicle ahead in real time, and a GPS device records the current speed and location. At the same time, an emotion engine analyzes the driver's facial expressions to recognize their level of concentration and fatigue.

[1459] It receives camera image data, GPS data, and facial expression data as input.

[1460] As outputs, it generates distance data, speed data, position data, and emotion data.

[1461] Step 2:

[1462] Data transmission

[1463] The terminal transmits the collected data to the server.

[1464] Specifically, data on vehicle distance, speed, location, and emotional state is packaged in JSON format and uploaded to a server via the vehicle's Wi-Fi or cellular network.

[1465] As input, it takes the data generated in step 1.

[1466] As an output, the submitted data is sent to the server.

[1467] Step 3:

[1468] Data reception

[1469] The server receives the data sent from the terminal.

[1470] Specifically, the data is received from the terminal via the data receiving endpoint and stored in the database.

[1471] As input, it receives data sent from the terminal.

[1472] As output, it produces data that is recorded in a database.

[1473] Step 4:

[1474] Data analysis

[1475] The server analyzes the received data.

[1476] Specifically, the system analyzes data on vehicle distance and speed based on safe driving standards, and analyzes emotional data to assess the driver's state, for example, determining whether the vehicle distance is appropriate, the speed is within the speed limit, and whether the driver is maintaining a focused state.

[1477] As input, it uses vehicle distance data, speed data, position data, and emotion data recorded in a database.

[1478] As outputs, safe driving evaluation data and emotional state evaluation data are generated.

[1479] Step 5:

[1480] Rating point calculation

[1481] The server calculates the evaluation points based on the analysis results.

[1482] Specifically, based on the analyzed data, points are added if the criteria are met, and points are subtracted if substandard driving or a bad emotional state is recognized.

[1483] As input, the safe driving evaluation data and emotional state evaluation data generated in step 4 are used.

[1484] As an output, it produces rating points.

[1485] Step 6:

[1486] Notifications and Feedback

[1487] The server notifies the driver of the evaluation results and provides feedback.

[1488] Specifically, when the rating points are updated, a notification is sent to the driver's smartphone in real time, and the driver can log in to the server to check the rating points and receive feedback.

[1489] Uses rating points as input.

[1490] As output, it generates notification messages and feedback data.

[1491] Step 7:

[1492] Offering benefits

[1493] The server provides rewards to drivers based on their evaluation points.

[1494] As a specific operation, benefits based on the evaluation points (e.g., discounts on license renewal fees, discounts on car insurance premiums) are presented.

[1495] Uses rating points as input.

[1496] As an output, it generates bonus information.

[1497] Step 8:

[1498] Information sharing with the police

[1499] The server creates a list of dangerous drivers and sends it to the police.

[1500] Specifically, the system organizes data on drivers who frequently engage in dangerous driving, creates a list, and sends it to police agencies.

[1501] It uses historical and evaluation data as input.

[1502] As an output, a list of risky drivers is generated and sent to police agencies.

[1503] (Application example 2)

[1504] 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."

[1505] Conventional safe driving evaluation systems only evaluate a driver's driving behavior and do not take into account the driver's emotional state. As a result, they are unable to fully assess the risks posed by drivers who are fatigued or stressed. Furthermore, there is a lack of concrete means for utilizing the collected data to improve actual driving safety and for effective monitoring by police agencies. Therefore, there is a need for a system that takes into account a driver's emotional state and provides safe driving evaluation and effective feedback.

[1506] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1507] In this invention, the server includes a means for measuring the inter-vehicle distance and traveling speed from a device mounted on the vehicle, a means for analyzing the driver's facial expression and recognizing the emotional state, a means for transmitting data on the measured inter-vehicle distance and traveling speed and the recognized emotional state to the server, a means for analyzing the transmitted data and calculating an evaluation point, and a means for notifying the driver of feedback based on the calculated evaluation point and the emotional state. This enables safe driving evaluation and individual feedback that takes the driver's emotional state into consideration, making it possible to promote comprehensive safe driving and effectively share information with police agencies.

[1508] "Following distance" refers to the safe distance a vehicle should maintain between itself and the vehicle in front.

[1509] "Traveling speed" refers to the speed at which a vehicle is moving and is expressed in units that measure that speed.

[1510] "Facial expression analysis" refers to a technology that analyzes a driver's facial expressions in real time and identifies their emotional state.

[1511] "Emotional state" refers to the emotional state a driver has while driving, including, for example, fatigue, stress, and concentration.

[1512] "Data transmission" refers to the process of transmitting data detected within the vehicle to a server over a network.

[1513] "Evaluation points" refer to evaluation values ​​for the driver's driving behavior and emotional state calculated based on analyzed data.

[1514] "Feedback" refers to specific instructions or advice provided to the driver based on their calculated rating points and emotional state.

[1515] "Benefits" refers to rewards and privileges provided to drivers based on their rating points.

[1516] "Police agency" means a public agency that maintains law and order and monitors safe driving.

[1517] The "list" refers to a compilation of drivers who engage in dangerous driving.

[1518] "GPS Functionality" refers to technology for measuring geolocation and determining the vehicle's current location and speed.

[1519] A "generative AI model" refers to an algorithm that performs analysis and response automatically generated using artificial intelligence.

[1520] A "prompt sentence" refers to an instruction or query sentence that is input into a generative AI model.

[1521] The system for implementing this invention consists of a device installed in a vehicle, a server, and a user interface used by the driver. The main purpose of the entire system is to improve road traffic safety, but here we focus on analyzing the driver's facial expressions and providing evaluation and feedback based on their emotional state.

[1522] Data collection and transmission

[1523] The terminal performs the following processing.

[1524] The distance between vehicles is measured using an AI camera.

[1525] Driving speed and location information are obtained using a GPS device.

[1526] The emotion engine analyzes the driver's facial expressions and recognizes their emotional state (e.g., fatigue, stress, concentration).

[1527] The collected data (vehicle distance, driving speed, location information, and emotion data) is sent to a server via communication equipment.

[1528] Data analysis and evaluation

[1529] The server performs the following processing:

[1530] The received data (distance between vehicles, driving speed, location information, emotional data) is analyzed and compared with safe driving standards.

[1531] Emotional data is analyzed to assess the driver's emotional state.

[1532] Based on the analysis results, evaluation points are calculated. Points are added if safe driving is confirmed, and points are subtracted if dangerous driving or a bad emotional state is confirmed.

[1533] Each driver's evaluation points are recorded in a database and notified to the driver in real time.

[1534] Feedback and Rewards

[1535] The server performs the following operations based on the evaluation points and the emotional state.

[1536] Provide appropriate feedback to the driver, such as "You're staying focused. Please continue to drive safely."

[1537] If the driver is fatigued or stressed, the system will provide feedback such as, "We recommend taking a short break."

[1538] Offer drivers rewards (e.g., discounts on license renewal fees, discounts on car insurance premiums) based on their evaluation points.

[1539] Information sharing with police agencies

[1540] The server generates a list of dangerous drivers and periodically shares this list with police agencies, allowing them to identify drivers who should be monitored more intensively and build a more efficient monitoring system.

[1541] Hardware and software used

[1542] AI camera: Used to measure the distance between vehicles.

[1543] GPS device: Used to obtain driving speed and location information.

[1544] Emotion Engine: Used to analyze the driver's facial expressions and recognize their emotional state.

[1545] Server: Used to receive and analyze data, calculate reputation points, and generate feedback.

[1546] Software: OpenCV (image processing and facial expression analysis), Dlib (facial feature point detection and emotion analysis), Geopy (location information processing), Requests (data transmission).

[1547] Specific examples

[1548] For example, a vehicle traveling on a highway uses an AI camera to measure the distance to the vehicle ahead, and collects driving speed and location information in real time using acquired GPS data. At the same time, an emotion engine analyzes the driver's facial expressions and recognizes their emotional state, such as "concentrated" or "relaxed." This data is sent to a server via the vehicle's communications device, and based on the analysis results, a notification is sent to the driver, such as "10 points have been added."

[1549] Prompt Sentence Examples

[1550] "The current following distance is 10 metres and the driver's emotional state is focused."

[1551] "Maintaining current speed of 60 km / h while maintaining appropriate following distance."

[1552] "We recommend taking timely rest breaks to reduce stress while driving."

[1553] In this way, this system comprehensively evaluates the driver's driving behavior and emotional state, promoting safe driving and helping to prevent accidents by sharing information with police agencies.

[1554] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1555] Step 1:

[1556] Data collection

[1557] The device measures the distance between vehicles using an AI camera. The acquired distance becomes the input for the next data processing. At the same time, the device uses a GPS device to acquire driving speed and location information. It also uses an emotion engine to analyze the driver's facial expressions and recognize their emotional state (e.g., fatigue, stress, concentration). This data (distance between vehicles, driving speed, location information, emotional state) is temporarily stored in the vehicle's local memory.

[1558] Step 2:

[1559] Data transmission

[1560] The device sends the collected data (distance between vehicles, driving speed, location information, emotional state) to the server. A communication module is used for transmission, and the data is protected by an encrypted protocol. The input of this process is the data collected in step 1, and the output is the data sent to the server.

[1561] Step 3:

[1562] Data reception and analysis

[1563] The server receives data sent from the device. This data includes the following distance, driving speed, location information, and emotional state. It performs data analysis based on the received data and compares it with safe driving standards. For example, it checks whether the following distance meets the safety standard and whether the driving speed exceeds the speed limit. The input of this process is the sent data, and the output is the analysis result.

[1564] Step 4:

[1565] Emotional state assessment

[1566] The server analyzes the received emotion data and evaluates the driver's emotional state. For example, it determines whether the driver is tired or focused based on the results of facial expression analysis. The input of this process is emotion data, and the output is the emotion evaluation result.

[1567] Step 5:

[1568] Calculation of evaluation points

[1569] The server calculates evaluation points based on the data analysis and the evaluation results of the emotional state. Points are added if safe driving is confirmed, and points are subtracted if dangerous driving or a bad emotional state is confirmed. The input of this process is the analysis results and evaluation results, and the output is the evaluation points.

[1570] Step 6:

[1571] Real-time notifications

[1572] The server generates a feedback message for the driver based on the calculated evaluation points and emotional state. For example, if safe driving is confirmed, the server generates feedback such as "You are maintaining concentration. Please continue to drive safely." This feedback is notified to the driver's user interface in real time. The inputs of this process are the evaluation points and emotional state, and the output is a feedback message.

[1573] Step 7:

[1574] Offer

[1575] The server provides rewards to drivers based on their rating points. Each driver's rating points are recorded in a database, and rewards (e.g., discounts on license renewal fees, discounts on car insurance premiums) are offered according to the points. In this process, reward information is sent to the driver. The input of this process is the rating points, and the output is a reward offer message.

[1576] Step 8:

[1577] Information sharing with police agencies

[1578] The server generates a list of dangerous drivers and periodically sends this list to the police, allowing the police to identify drivers who should be monitored more closely. The input of this process is the evaluation data, and the output is the list of dangerous drivers.

[1579] 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.

[1580] 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.

[1581] 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.

[1582] [Fourth embodiment]

[1583] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1584] 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.

[1585] 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).

[1586] 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.

[1587] 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.

[1588] 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).

[1589] 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.

[1590] 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.

[1591] 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.

[1592] 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.

[1593] 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.

[1594] 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.

[1595] 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."

[1596] ---

[1597] A system for implementing the present invention comprises a device installed in a vehicle, a server, and a user interface used by the driver.

[1598] Data collection and transmission

[1599] The terminal (AI camera and GPS device installed in the vehicle) performs the following functions while the vehicle is driving.

[1600] The distance between vehicles is measured using an AI camera.

[1601] Driving speed and location information are obtained using a GPS device.

[1602] The collected data is sent to a server at a predetermined timing or at regular intervals.

[1603] For example, a vehicle traveling on a highway automatically measures the distance to the vehicle ahead and acquires real-time speed and location information using a GPS device. This data is then sent to a server via the vehicle's communications equipment.

[1604] Data analysis and evaluation

[1605] The server receives the data sent from the terminal and performs the following analysis and evaluation.

[1606] Analyze data on vehicle distance and speed according to safe driving standards.

[1607] Based on the analysis results, evaluation points are calculated.

[1608] Each driver's rating points are recorded in a database.

[1609] For example, if the following distance meets the safety standard, points are added, while if the following distance is too short and the speed is over the limit, points are subtracted.

[1610] Point notification and management

[1611] The server manages the evaluation points for each driver and performs the following operations:

[1612] When a driver's evaluation points are updated, the results will be notified in real time.

[1613] Drivers can log in to the server and check their rating points and details.

[1614] It also has a function for offering rewards based on points (e.g., discounts on license renewal fees, discounts on car insurance premiums).

[1615] For example, a driver who continues to drive safely will receive a notification from the server saying, "You have been awarded 10 points," and the driver's history can be viewed on the user interface.

[1616] Information sharing with the police

[1617] The server shares information with police agencies.

[1618] Organize data on drivers who have been detected driving recklessly.

[1619] Regularly compile and share lists of dangerous drivers.

[1620] Based on this, the police can carry out focused patrols.

[1621] For example, a list of drivers who frequently engage in dangerous driving could be compiled and sent to the police, who could then use it to efficiently plan patrols and prevent accidents.

[1622] Specific examples

[1623] Data collected by the device:

[1624] Distance between vehicles: Always appropriate (e.g., maintain a distance of at least 2 seconds)

[1625] Driving speed: Within the speed limit (e.g. always adhere to the speed limit of 100km / h)

[1626] Server Action:

[1627] The received data is analyzed and determined to meet all criteria.

[1628] Safe driving points are added to the driver (e.g., 10 points are added).

[1629] User Action:

[1630] Drivers log in to the server and check their evaluation points.

[1631] Apply for a discount on your license renewal fee based on your safe driving points (e.g., 20 points for a 5% discount).

[1632] In this way, the system of the present invention evaluates the driver's driving behavior in real time, promotes safe driving, and supports the efficiency of patrols and accident prevention through effective information sharing with police agencies.

[1633] The processing flow will be explained below.

[1634] ---

[1635] Step 1:

[1636] While the vehicle is moving, the device uses an AI camera to measure the distance to the vehicle ahead, and also obtains driving speed and location information using a GPS device.

[1637] Step 2:

[1638] The terminal formats the data it acquires, including vehicle distance, driving speed, and location information, and sends it to the server via the communication module.

[1639] Step 3:

[1640] The server analyzes the data received from the device, specifically assessing whether the distance between vehicles meets safety standards and whether the driving speed exceeds the speed limit.

[1641] Step 4:

[1642] The server calculates evaluation points based on the analysis results, adding points if safe driving is confirmed and subtracting points if dangerous driving is confirmed.

[1643] Step 5:

[1644] The server records each driver's rating points in a database, and if new points are added, the driver's total points are updated.

[1645] Step 6:

[1646] The server sends notifications based on changes in the driver's rating points, either via the application or email associated with the user's account.

[1647] Step 7:

[1648] The user logs in to the server and checks his / her own rating points and driving rating. If the user wants to apply for a reward, he / she selects a discount or reward based on the points and executes the application.

[1649] Step 8:

[1650] The server receives the reward request from the user, checks the validity of the points, and if the conditions are met, applies the reward and deducts the points.

[1651] Step 9:

[1652] The server compiles data on dangerous drivers and periodically creates a list, which is sent to police agencies and updated as needed.

[1653] Step 10:

[1654] Police can efficiently plan and carry out patrols based on the list of dangerous drivers received from the server, and can also issue direct warnings and take action as necessary.

[1655] ---

[1656] Through the above steps, the system of the present invention evaluates the driver's driving behavior, promotes safe driving, and works to prevent accidents by sharing information with police agencies.

[1657] Example 1

[1658] 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."

[1659] Conventional driving behavior evaluation systems have had problems such as incomplete data collection, such as measurement of vehicle distance and speed, and delayed notification of evaluation results. Furthermore, there were also problems with inefficient rewards based on evaluation points and collaboration with police agencies. As a result, they have not been able to adequately motivate drivers to drive safely or prevent dangerous driving.

[1660] 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.

[1661] In this invention, the server includes a means for measuring the distance and speed from a device mounted on the vehicle, a means for transmitting the measured distance and speed data to a data processing device, a means for analyzing the transmitted data and calculating an evaluation value, and a means for notifying the driver of the calculated evaluation value. This enables multifaceted and real-time evaluation of driving behavior. In addition, rewards based on the evaluation value and information sharing with police agencies can be efficiently carried out, which is expected to promote safe driving and prevent dangerous driving.

[1662] A "driving behavior evaluation system" is a system that uses a device installed in a vehicle to measure and evaluate a driver's driving behavior, and notifies and manages the results.

[1663] "Device" is a general term for measuring instruments and communication equipment attached to a vehicle, and is a device that has the function of collecting data such as vehicle-to-vehicle distance, speed, and location information.

[1664] "Inter-vehicle distance" refers to the distance between a moving vehicle and the vehicle in front of it.

[1665] "Speed" refers to the rate at which a vehicle travels a distance in a given time, and is typically expressed in kilometers per hour (km / h).

[1666] A "data processing device" is a computer system that receives collected data, analyzes it, and calculates evaluation values.

[1667] The "evaluation value" is a value calculated based on the analyzed data to indicate the safety and appropriateness of driving behavior.

[1668] "Notification" is an act of communicating information to the driver about the calculated evaluation value, and is performed in real time.

[1669] "Rewards" refers to incentives and benefits offered to drivers based on their rating figures.

[1670] "Patrol agencies" refer to law enforcement agencies such as the police, which work in conjunction with the driving behavior assessment system to monitor and crack down on dangerous driving.

[1671] The "list" is a report or database format that organizes and lists information on dangerous drivers.

[1672] The system for carrying out the present invention comprises a terminal installed in a vehicle, a server, and a user interface used by the driver. This system has the following technical configuration.

[1673] Data collection and transmission

[1674] The terminal (a device installed in the vehicle) performs the following functions while the vehicle is moving:

[1675] The distance between vehicles is measured using an AI camera.

[1676] Driving speed and location information are obtained using a GPS device.

[1677] The collected data is sent to a server at a predetermined timing or at regular intervals.

[1678] For example, a vehicle traveling on a highway automatically measures the distance to the vehicle ahead and acquires real-time speed and location information using a GPS device. This data is then sent to a server via the vehicle's communications equipment.

[1679] Data analysis and evaluation

[1680] The server receives the data sent from the terminal and performs the following analysis and evaluation.

[1681] Analyze data on vehicle distance and speed according to safe driving standards.

[1682] Based on the analysis results, an evaluation value is calculated.

[1683] Each driver's rating is recorded in a database.

[1684] For example, if the following distance meets the safety standard, points are added, while if the following distance is too short and the speed is over the limit, points are subtracted.

[1685] Point notification and management

[1686] The server manages the evaluation values ​​for each driver and performs the following operations:

[1687] When a driver's rating is updated, the results will be notified in real time.

[1688] Drivers can log in to the server and check their rating numbers and details.

[1689] It also has a function to offer benefits based on the evaluation figures (e.g., discounts on license renewal fees, discounts on car insurance premiums).

[1690] For example, a driver who continues to drive safely will receive a notification from the server saying, "You have been awarded 10 points," and the driver's history can be viewed on the user interface.

[1691] Information sharing with the police

[1692] The server shares information with police agencies.

[1693] Organize data on drivers who have been detected driving recklessly.

[1694] Regularly compile and share lists of dangerous drivers.

[1695] Based on this, the police will carry out intensive patrols.

[1696] For example, a list of drivers who frequently engage in dangerous driving will be compiled and sent to the police, who will then use this information to efficiently plan patrols and work to prevent accidents.

[1697] Specific examples

[1698] Data collected by the device:

[1699] Distance between vehicles: Always appropriate (e.g., maintain a distance of at least 2 seconds)

[1700] Driving speed: Within the speed limit (e.g. always adhere to the speed limit of 100km / h)

[1701] Server Action:

[1702] The received data is analyzed and determined to meet all criteria.

[1703] Safe driving points are added to the driver (e.g., 10 points are added).

[1704] User Action:

[1705] Drivers log in to the server and check their evaluation points.

[1706] Apply for a discount on your license renewal fee based on your safe driving points (e.g., 20 points for a 5% discount).

[1707] The system of this invention evaluates the driving behavior of drivers in real time to promote safe driving. It also supports the efficiency of patrols and accident prevention through effective information sharing with police agencies.

[1708] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1709] Step 1:

[1710] Data collection

[1711] The terminal (an AI camera or GPS device installed inside the vehicle) collects data from the vehicle while it is in motion.

[1712] Input: distance between vehicles, driving speed, location information

[1713] Specific operation: When the vehicle starts moving, the AI ​​camera measures the distance to the vehicle in front, and the GPS device collects the vehicle's speed and location information. For example, the AI ​​camera measures the distance every second, and the GPS device similarly obtains the vehicle's current location and speed every second.

[1714] Output: Inter-vehicle distance data, speed data, location data

[1715] Step 2:

[1716] Data transmission

[1717] The terminal transmits the collected data to the server.

[1718] Input: Inter-vehicle distance data, speed data, location data

[1719] Specific operation: Collected data is packaged at regular intervals (e.g., 1 minute) and sent to a server using the vehicle's communications equipment. The transmission interval can be adjusted, but a short interval is recommended to ensure real-time data transmission.

[1720] Output: Data package received by the server

[1721] Step 3:

[1722] Data analysis

[1723] The server analyzes the data sent from the terminal.

[1724] Input: Received data package (distance data, speed data, location data)

[1725] Specific operation: The server applies an analysis algorithm to the received data and compares it with safe driving standards. For example, if the distance between vehicles is more than 2 seconds and the driving speed is within the speed limit, it is judged as safe driving and points are added to the driver's score. If there is a violation, points are subtracted.

[1726] Output: Rating points

[1727] Step 4:

[1728] Calculation of evaluation points

[1729] The server calculates the evaluation points based on the analysis results.

[1730] Input: Analysis results (distance between vehicles, speed)

[1731] Specific operation: Calculates the evaluation points based on the analysis results. For example, add or subtract points from each analysis data to calculate the overall evaluation points.

[1732] Output: Calculated rating points

[1733] Step 5:

[1734] Point notification

[1735] The server notifies the driver of the calculated evaluation points.

[1736] Input: Rating points

[1737] Specific operation: Once the evaluation points have been calculated, the driver is notified in real time. For example, a notification saying "10 points added" is displayed on a smartphone app or on the in-car display.

[1738] Output: Rating points reported to the driver

[1739] Step 6:

[1740] Check in the user interface

[1741] The user (driver) checks the evaluation points.

[1742] Input: Notifications from the server, login information

[1743] How it works: Drivers can log in to the app on their smartphone or in-car display and check their rating point history and details. For example, it will show "Current points: 50 points," and they can also check the history and data analysis details.

[1744] Output: Driver's rating points information

[1745] Step 7:

[1746] Information sharing with the police

[1747] The server shares information with police agencies.

[1748] Input: Dangerous driving data, evaluation point data

[1749] Specific operation: The server creates a list of drivers who have been detected as driving recklessly and periodically provides it to the police. For example, a list such as "Driver A - Insufficient distance - 3 times, Driver B - Speeding - 2 times" is generated and uploaded to the police database.

[1750] Output: A list of dangerous drivers provided to police agencies

[1751] (Application example 1)

[1752] 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."

[1753] Conventional driving behavior evaluation systems lack sufficient data visualization and real-time feedback, making it difficult to immediately promote safe driving by drivers. In addition, there was a lack of means to provide immediate alerts for dangerous driving behavior, making it difficult to ensure safety.

[1754] 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.

[1755] In this invention, the server includes a means for measuring the inter-vehicle distance and traveling speed from a device mounted on the vehicle, a means for transmitting the measured inter-vehicle distance and traveling speed data to the server, a means for analyzing the transmitted data and calculating an evaluation point, a means for notifying the driver of the calculated evaluation point, a means for visualizing the inter-vehicle distance and traveling speed information in real time, and a means for providing visual and audio alerts as necessary, thereby enabling the driver to immediately understand his / her driving behavior while driving and receive appropriate feedback to maintain safe driving.

[1756] "Following distance" refers to the physical distance between you and the vehicle in front.

[1757] "Traveling speed" refers to the speed at which a vehicle is moving.

[1758] "Server" refers to the system that analyzes collected data, calculates and manages evaluation points.

[1759] "Device" refers to a device installed in a vehicle that measures the distance between vehicles and the driving speed.

[1760] "Evaluation points" refer to points calculated based on the driver's driving behavior.

[1761] "Driver" means a person who drives a vehicle.

[1762] "Real-time" refers to the instantaneous collection and processing of data.

[1763] "Visualization" refers to the visual display of data.

[1764] "Visual alert" refers to a visual warning that alerts the driver.

[1765] "Voice alert" refers to a function that warns the driver by voice.

[1766] "Location information function" refers to technology such as GPS for measuring current location.

[1767] An "unsafe driver" is a driver whose driving behavior does not meet safe driving standards.

[1768] "Benefits" refers to rewards and benefits provided to drivers based on their rating points.

[1769] A system for implementing the present invention comprises a device installed in a vehicle, a server, and a user interface used by the driver.

[1770] Data collection and transmission

[1771] The terminal (such as a camera or GPS device mounted in the vehicle) performs the following functions while the vehicle is traveling:

[1772] The distance between vehicles is measured using a camera.

[1773] Driving speed and location information are obtained using a GPS device.

[1774] This data is transmitted to the server at regular intervals.

[1775] For example, a vehicle traveling on a highway automatically measures the distance to the vehicle ahead, obtains speed and location information in real time using a GPS device, and transmits the collected data to a server via communication equipment inside the vehicle.

[1776] Data analysis and evaluation

[1777] The server receives the data sent from the terminal and performs the following analysis and evaluation.

[1778] Data on vehicle distance and driving speed is analyzed, and evaluation points are calculated according to safe driving standards.

[1779] Each driver's rating points are recorded in a database.

[1780] For example, points are added if the following distance meets safety standards, while points are subtracted if the following distance is too short and the speed is above the limit.

[1781] Point notification and management

[1782] The server manages the evaluation points for each driver and performs the following operations:

[1783] When a driver's evaluation points are updated, the results will be notified in real time.

[1784] Drivers can log in to the server and check their rating points and details.

[1785] It also has the ability to offer rewards based on points (e.g., discounts on license renewal fees, discounts on car insurance premiums).

[1786] For example, a driver who continues to drive safely will receive a notification from the server saying, "You have been awarded 10 points," and the driver's history can be viewed on the user interface.

[1787] Real-time visibility and alerts

[1788] Smart glasses or a head-mounted display (HMD) can be used as a user interface.

[1789] Visualize real-time information on distance and driving speed.

[1790] Provide visual and audio alerts as needed.

[1791] For example, a driver can see through smart glasses that the distance to the vehicle ahead is 15m and the speed is 90km / h, and a visual and audio alert will be issued if the distance becomes too close.

[1792] Information sharing with the police

[1793] The server shares information with police agencies.

[1794] Organize data on drivers who have been detected driving recklessly.

[1795] Regularly compile and share lists of dangerous drivers.

[1796] Based on this, the police can carry out focused patrols.

[1797] For example, a list of drivers who frequently engage in dangerous driving could be created and sent to the police, allowing them to efficiently plan patrols and work to prevent accidents.

[1798] Program processing

[1799] The server uses Python and TensorFlow for remote data analysis, processes data sent from vehicles in real time, calculates evaluation points, and generates safe driving alerts. It also uses the requests library to manage data transmission and reception.

[1800] For example, while driving, drivers can check the information displayed on the smart glasses and, if a safe distance is maintained, receive a notification that "safe driving points have been added." Visual and audio alerts provide immediate warning when unsafe conditions occur.

[1801] Prompt Sentence Examples

[1802] "This application displays real-time driving data on smart glasses, monitors the distance and speed of vehicles in front of the car, and sends an alert when the distance falls below a certain level."

[1803] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1804] Step 1:

[1805] The device collects data on vehicle distance and speed.

[1806] Specific operation: The camera installed on the device uses an AI model to measure the distance to the vehicle ahead, and the GPS device obtains the current driving speed and location information.

[1807] Input: Video data, GPS data.

[1808] Output: Inter-vehicle distance, speed, position information.

[1809] Step 2:

[1810] The terminal transmits the collected data to the server.

[1811] Specific operation: Data is encoded at regular intervals and sent to the server via the terminal's communication equipment.

[1812] Input: distance, speed, location.

[1813] Output: The data sent to the server.

[1814] Step 3:

[1815] The server parses the received data.

[1816] Specific operation: The server uses the TensorFlow model to analyze the transmitted distance and speed data and calculates evaluation points according to safe driving standards.

[1817] Input: distance, speed, location.

[1818] Data processing: analysis, calculation of evaluation points.

[1819] Output: Rating points.

[1820] Step 4:

[1821] The server notifies the driver of the evaluation points.

[1822] How it works: The evaluation points are calculated and displayed in real time on the driver's user interface (smart glasses or HMD). Visual and audio alerts are also provided if necessary.

[1823] Input: Rating points.

[1824] Output: Rating points notified to the driver, visual and audio alerts.

[1825] Step 5:

[1826] The server records the evaluation points in a database and provides rewards.

[1827] Specific operation: The evaluation points are recorded in a database and the driver is given benefits (e.g., a discount on license renewal fees).

[1828] Input: Rating points.

[1829] Output: Reputation points recorded in the database, rewards provided.

[1830] Step 6:

[1831] The server shares information with police agencies and generates a list of dangerous drivers.

[1832] Specific operation: Based on the analysis results, a list of dangerous drivers is created and sent to police agencies on a regular basis.

[1833] Input: Evaluation point data.

[1834] Data processing: List generation.

[1835] Output: A list of dangerous drivers sent to police agencies.

[1836] Step 7:

[1837] Police will conduct targeted patrols based on a list of dangerous drivers.

[1838] Specific actions: Based on the list sent, police will develop patrol plans for areas with high rates of dangerous driving and strengthen safety measures.

[1839] Input: Dangerous Driver List.

[1840] Output: Developing and implementing patrol plans.

[1841] By using the above processing steps, the present invention can evaluate the driver's driving behavior in real time and promote safe driving. In addition, by sharing information with police agencies, a system for preventing dangerous driving can be established.

[1842] 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.

[1843] ---

[1844] The system for implementing the present invention is composed of a device installed in a vehicle, a server, and a user interface used by the driver. In addition, by adding a function to analyze the driver's facial expressions and recognize their emotions, it is possible to evaluate not only the driving behavior but also the driver's emotional state.

[1845] Data collection and transmission

[1846] The terminal (the AI ​​camera, GPS device, and emotion engine installed in the vehicle) performs the following functions while the vehicle is driving:

[1847] The distance between vehicles is measured using an AI camera.

[1848] Driving speed and location information are obtained using a GPS device.

[1849] The emotion engine analyzes the driver's facial expressions and recognizes their emotional state (e.g., fatigue, stress, concentration).

[1850] The collected data (vehicle distance, driving speed, location information, emotion data) is sent to a server at a set time or at regular intervals.

[1851] For example, a vehicle traveling on a highway automatically measures the distance to the vehicle ahead and acquires speed and location information in real time using a GPS device. At the same time, an emotion engine analyzes the driver's facial expressions and obtains their emotional state as data. This data is then sent to a server via the vehicle's communications equipment.

[1852] Data analysis and evaluation

[1853] The server receives the data sent from the terminal and performs the following analysis and evaluation.

[1854] Analyze data on vehicle distance and speed according to safe driving standards.

[1855] Emotional data is analyzed to assess the driver's emotional state.

[1856] Based on the analysis results, evaluation points are calculated. Points are added if safe driving is confirmed, and points are subtracted if dangerous driving or a bad emotional state is confirmed.

[1857] Each driver's rating points are recorded in a database.

[1858] For example, points are added if the following distance meets safety standards and the driver is deemed to be concentrating, while points are subtracted if the following distance is too short, the speed is over the limit, and the driver is deemed to be fatigued.

[1859] Point notification and management

[1860] The server manages the evaluation points for each driver and performs the following operations:

[1861] When a driver's evaluation points are updated, the results will be notified in real time.

[1862] Drivers can log in to the server and check their rating points and details.

[1863] It also has a function for offering rewards based on points (e.g., discounts on license renewal fees, discounts on car insurance premiums).

[1864] Providing feedback and advice based on emotional state.

[1865] For example, if a driver continues to drive safely and maintains a good emotional state, the server will send a notification saying, "You've been awarded 10 points," and the driver's score history can be checked on the user interface. If the driver is deemed to be fatigued, the server will also send a notification saying, "We recommend you take a break."

[1866] Information sharing with the police

[1867] The server shares information with police agencies.

[1868] Organize data on drivers who have been detected driving recklessly.

[1869] Regularly compile and share lists of dangerous drivers.

[1870] Based on this, the police can carry out focused patrols.

[1871] For example, a list of drivers who frequently engage in dangerous driving could be compiled and sent to the police, who could then use it to efficiently plan patrols and prevent accidents.

[1872] Specific examples

[1873] Data collected by the device:

[1874] Distance between vehicles: Always appropriate (e.g., maintain a distance of at least 2 seconds)

[1875] Driving speed: Within the speed limit (e.g. always adhere to the speed limit of 100km / h)

[1876] Emotional state: Focused, relaxed

[1877] Server Action:

[1878] The received data is analyzed and determined to meet all criteria.

[1879] Safe driving points are added to the driver (e.g., 10 points are added).

[1880] User Action:

[1881] Drivers log in to the server and check their evaluation points.

[1882] Apply for a discount on your license renewal fee based on your safe driving points (e.g., 20 points for a 5% discount).

[1883] Receive feedback on staying focused.

[1884] In this way, the system of the present invention not only evaluates the driver's driving behavior but also their emotional state in real time, promoting safe driving. Furthermore, by effectively sharing information with police agencies, it supports the efficiency of patrols and accident prevention.

[1885] The processing flow will be explained below.

[1886] ---

[1887] Step 1:

[1888] While the vehicle is moving, the device uses an AI camera to measure the distance to the vehicle ahead. It also uses a GPS device to acquire driving speed and location information. The emotion engine also analyzes the driver's facial expressions to recognize their emotional state.

[1889] Step 2:

[1890] The device formats the acquired data, such as vehicle distance, driving speed, location information, and emotion data, and transmits the formatted data to the server via the communication module.

[1891] Step 3:

[1892] The server analyzes the data received from the device, assessing whether the following distance meets safety standards, whether the driving speed exceeds the speed limit, and the driver's emotional state.

[1893] Step 4:

[1894] The server calculates evaluation points based on the analysis results. Specifically, points are added if safe driving and a good emotional state are confirmed, and points are subtracted if dangerous driving and a bad emotional state are confirmed.

[1895] Step 5:

[1896] The server records each driver's rating points in a database, and if new points are added, the driver's total points are updated.

[1897] Step 6:

[1898] The server sends notifications based on changes in the driver's rating points, either via the app or email associated with the user's account.

[1899] Step 7:

[1900] The user logs in to the server and checks his / her own rating points and driving rating. If the user wants to apply for a reward, he / she selects a discount or reward based on the points and executes the application.

[1901] Step 8:

[1902] The server receives the reward request from the user, checks the validity of the points, and if the conditions are met, applies the reward and deducts the points.

[1903] Step 9:

[1904] The server evaluates the emotional data and sends a notification to alert you if a particular emotional state (e.g., fatigue or high stress) is detected.

[1905] Step 10:

[1906] The server records emotional data over time and analyzes patterns of the driver's emotional state, generating a long-term emotional assessment report.

[1907] Step 11:

[1908] The server compiles data on dangerous drivers and periodically creates a list, which is sent to police agencies and updated as needed.

[1909] Step 12:

[1910] Police can efficiently plan and carry out patrols based on the list of dangerous drivers received from the server, and can also issue direct warnings and take action as necessary.

[1911] ---

[1912] Through the above steps, the system of the present invention evaluates the driver's driving behavior and emotional state, promotes safe driving, and works to prevent accidents by sharing information with police agencies.

[1913] Example 2

[1914] 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."

[1915] Conventional driver evaluation systems only evaluate driving behavior and do not consider the driver's emotional state, making it difficult to accurately evaluate safe driving. Furthermore, there is a lack of a means to efficiently share information on dangerous drivers with police agencies, limiting their effectiveness in preventing traffic accidents.

[1916] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for analyzing the driver's facial expression and recognizing the emotional state, a means for transmitting data on the emotional state, and a means for analyzing the data on the emotional state and evaluating it based on safe driving standards. This makes it possible to evaluate not only the driver's driving behavior but also their emotional state.

[1917] "Inter-vehicle distance" refers to the distance between your vehicle and the vehicle ahead.

[1918] "Traveling speed" is the distance a vehicle travels in a certain period of time expressed in speed units (e.g., km / h).

[1919] "Device" refers to all equipment installed in a vehicle for measurement and analysis.

[1920] "Server" refers to a computer system for receiving, analyzing, storing, and notifying data.

[1921] "Driver" means a person who drives a vehicle.

[1922] "Emotional state" refers to the psychological state of the driver as judged from their facial expressions and physiological signs.

[1923] "Evaluation points" refer to numerical evaluation indicators calculated based on the driver's driving behavior and emotional state.

[1924] "Notification" refers to informing the driver of certain information.

[1925] "Benefits" refers to rewards and benefits provided to drivers based on their rating points.

[1926] "Police agency" means a government agency tasked with maintaining public safety and order and enforcing the law.

[1927] A "list" refers to a collection of data organized based on specific criteria.

[1928] "GPS function" refers to technology that uses the Global Positioning System to determine the vehicle's location.

[1929] "Feedback" refers to sharing information with the driver about their driving behavior and emotional state, as well as providing advice to encourage improvement.

[1930] The above are definitions of important words included in the claims.

[1931] The system for implementing this invention is composed of a device installed in a vehicle, a server, and a user interface used by the driver. This system aims to prevent traffic accidents and promote safe driving by analyzing the driver's driving behavior and emotional state and evaluating safe driving.

[1932] Hardware and software used

[1933] The terminal (device installed in the vehicle) uses the following hardware and software:

[1934] AI camera: Used to measure the distance between the vehicle and the vehicle ahead.

[1935] GPS device: Used to obtain driving speed and location information.

[1936] Emotion Engine: Used to analyze the driver's facial expressions and recognize their emotional state.

[1937] Communication device: Used to send collected data to the server.

[1938] Data collection

[1939] The device collects data on vehicle distance, speed, location, and emotional state. For example, it uses an AI camera to measure the distance to the vehicle ahead in real time, and a GPS device to record the driver's current speed and location. At the same time, an emotion engine analyzes the driver's facial expressions to identify their level of concentration and fatigue.

[1940] Data transmission

[1941] The data collected by the device (including distance, speed, location, and emotional state) is sent to a server every minute, packaged in JSON format, and uploaded to the server via the vehicle's Wi-Fi or cellular network.

[1942] Data analysis and evaluation

[1943] The server receives the data sent by the device and performs the following analysis and evaluation:

[1944] Data on vehicle distance and driving speed is analyzed and evaluated based on safe driving standards.

[1945] Emotional data is analyzed to assess the driver's emotional state.

[1946] For example, if the distance between vehicles is equal to or greater than a standard value, the speed is within the speed limit, and the driver is concentrating, safe driving points are added.

[1947] Notifications and Feedback

[1948] The server calculates the evaluation points based on the analysis results and notifies the driver of the results. For example, if 10 points are added to the driver's safe driving points, the driver's smartphone will be notified that "10 points have been added."

[1949] Drivers can log in to the server and check their own rating points. Based on the rating points, they can receive certain benefits (e.g., discounts on license renewal fees, discounts on car insurance premiums).

[1950] Information sharing with the police

[1951] The server creates a list of dangerous drivers and sends it to the police. This list is updated monthly and includes information on drivers who frequently engage in dangerous driving. Police can use this list to plan efficient patrols and work to prevent traffic accidents.

[1952] Examples of concrete examples and prompts

[1953] As a concrete example, consider the following scenario:

[1954] Data collected by the device:

[1955] Distance between vehicles: Always appropriate (e.g., maintain a distance of at least 2 seconds)

[1956] Driving speed: Within the speed limit (e.g. always adhere to the speed limit of 100km / h)

[1957] Emotional state: Focused, relaxed

[1958] Server Action:

[1959] The received data is analyzed and determined to meet all criteria.

[1960] Safe driving points are added to the driver (e.g., 10 points are added).

[1961] User Action:

[1962] Drivers log in to the server and check their evaluation points.

[1963] Apply for a discount on your license renewal fee based on your safe driving points (e.g., 20 points for a 5% discount).

[1964] Receive feedback on staying focused.

[1965] Examples of prompts include:

[1966] "Please explain the system in which a vehicle automatically measures the distance to the vehicle ahead and analyzes the driver's facial expressions to evaluate safe driving."

[1967] "Please give a concrete example of a system that calculates evaluation points based on the driver's emotional data and provides rewards based on those points."

[1968] "Please provide the police with a list of dangerous drivers and explain how the system works to support efficient patrols."

[1969] In this way, the system of the present invention comprehensively evaluates the driver's driving behavior and emotional state, promoting safe driving. Furthermore, by providing rewards and feedback based on the evaluation, it is expected to increase driver motivation. Furthermore, it is also characterized by the ability to implement efficient traffic safety measures in cooperation with police agencies.

[1970] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1971] Step 1:

[1972] Data collection

[1973] The device collects data on vehicle distance, driving speed, location, and emotional state.

[1974] Specifically, the AI ​​camera measures the distance to the vehicle ahead in real time, and a GPS device records the current speed and location. At the same time, an emotion engine analyzes the driver's facial expressions to recognize their level of concentration and fatigue.

[1975] It receives camera image data, GPS data, and facial expression data as input.

[1976] As outputs, it generates distance data, speed data, position data, and emotion data.

[1977] Step 2:

[1978] Data transmission

[1979] The terminal transmits the collected data to the server.

[1980] Specifically, data on vehicle distance, speed, location, and emotional state is packaged in JSON format and uploaded to a server via the vehicle's Wi-Fi or cellular network.

[1981] As input, it takes the data generated in step 1.

[1982] As an output, the submitted data is sent to the server.

[1983] Step 3:

[1984] Data reception

[1985] The server receives the data sent from the terminal.

[1986] Specifically, the data is received from the terminal via the data receiving endpoint and stored in the database.

[1987] As input, it receives data sent from the terminal.

[1988] As output, it produces data that is recorded in a database.

[1989] Step 4:

[1990] Data analysis

[1991] The server analyzes the received data.

[1992] Specifically, the system analyzes data on vehicle distance and speed based on safe driving standards, and analyzes emotional data to assess the driver's state, for example, determining whether the vehicle distance is appropriate, the speed is within the speed limit, and whether the driver is maintaining a focused state.

[1993] As input, it uses vehicle distance data, speed data, position data, and emotion data recorded in a database.

[1994] As outputs, safe driving evaluation data and emotional state evaluation data are generated.

[1995] Step 5:

[1996] Rating point calculation

[1997] The server calculates the evaluation points based on the analysis results.

[1998] Specifically, based on the analyzed data, points are added if the criteria are met, and points are subtracted if substandard driving or a bad emotional state is recognized.

[1999] As input, the safe driving evaluation data and emotional state evaluation data generated in step 4 are used.

[2000] As an output, it produces rating points.

[2001] Step 6:

[2002] Notifications and Feedback

[2003] The server notifies the driver of the evaluation results and provides feedback.

[2004] Specifically, when the rating points are updated, a notification is sent to the driver's smartphone in real time, and the driver can log in to the server to check the rating points and receive feedback.

[2005] Uses rating points as input.

[2006] As output, it generates notification messages and feedback data.

[2007] Step 7:

[2008] Offering benefits

[2009] The server provides rewards to drivers based on their evaluation points.

[2010] As a specific operation, benefits based on the evaluation points (e.g., discounts on license renewal fees, discounts on car insurance premiums) are presented.

[2011] Uses rating points as input.

[2012] As an output, it generates bonus information.

[2013] Step 8:

[2014] Information sharing with the police

[2015] The server creates a list of dangerous drivers and sends it to the police.

[2016] Specifically, the system organizes data on drivers who frequently engage in dangerous driving, creates a list, and sends it to police agencies.

[2017] It uses historical and evaluation data as input.

[2018] As an output, a list of risky drivers is generated and sent to police agencies.

[2019] (Application example 2)

[2020] 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."

[2021] Conventional safe driving evaluation systems only evaluate a driver's driving behavior and do not take into account the driver's emotional state. As a result, they are unable to fully assess the risks posed by drivers who are fatigued or stressed. Furthermore, there is a lack of concrete means for utilizing the collected data to improve actual driving safety and for effective monitoring by police agencies. Therefore, there is a need for a system that takes into account a driver's emotional state and provides safe driving evaluation and effective feedback.

[2022] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[2023] In this invention, the server includes a means for measuring the inter-vehicle distance and traveling speed from a device mounted on the vehicle, a means for analyzing the driver's facial expression and recognizing the emotional state, a means for transmitting data on the measured inter-vehicle distance and traveling speed and the recognized emotional state to the server, a means for analyzing the transmitted data and calculating an evaluation point, and a means for notifying the driver of feedback based on the calculated evaluation point and the emotional state. This enables safe driving evaluation and individual feedback that takes the driver's emotional state into consideration, making it possible to promote comprehensive safe driving and effectively share information with police agencies.

[2024] "Following distance" refers to the safe distance a vehicle should maintain between itself and the vehicle in front.

[2025] "Traveling speed" refers to the speed at which a vehicle is moving and is expressed in units that measure that speed.

[2026] "Facial expression analysis" refers to a technology that analyzes a driver's facial expressions in real time and identifies their emotional state.

[2027] "Emotional state" refers to the emotional state a driver has while driving, including, for example, fatigue, stress, and concentration.

[2028] "Data transmission" refers to the process of transmitting data detected within the vehicle to a server over a network.

[2029] "Evaluation points" refer to evaluation values ​​for the driver's driving behavior and emotional state calculated based on analyzed data.

[2030] "Feedback" refers to specific instructions or advice provided to the driver based on their calculated rating points and emotional state.

[2031] "Benefits" refers to rewards and privileges provided to drivers based on their rating points.

[2032] "Police agency" means a public agency that maintains law and order and monitors safe driving.

[2033] The "list" refers to a compilation of drivers who engage in dangerous driving.

[2034] "GPS Functionality" refers to technology for measuring geolocation and determining the vehicle's current location and speed.

[2035] A "generative AI model" refers to an algorithm that performs analysis and response automatically generated using artificial intelligence.

[2036] A "prompt sentence" refers to an instruction or query sentence that is input into a generative AI model.

[2037] The system for implementing this invention consists of a device installed in a vehicle, a server, and a user interface used by the driver. The main purpose of the entire system is to improve road traffic safety, but here we focus on analyzing the driver's facial expressions and providing evaluation and feedback based on their emotional state.

[2038] Data collection and transmission

[2039] The terminal performs the following processing.

[2040] The distance between vehicles is measured using an AI camera.

[2041] Driving speed and location information are obtained using a GPS device.

[2042] The emotion engine analyzes the driver's facial expressions and recognizes their emotional state (e.g., fatigue, stress, concentration).

[2043] The collected data (vehicle distance, driving speed, location information, and emotion data) is sent to a server via communication equipment.

[2044] Data analysis and evaluation

[2045] The server performs the following processing:

[2046] The received data (distance between vehicles, driving speed, location information, emotional data) is analyzed and compared with safe driving standards.

[2047] Emotional data is analyzed to assess the driver's emotional state.

[2048] Based on the analysis results, evaluation points are calculated. Points are added if safe driving is confirmed, and points are subtracted if dangerous driving or a bad emotional state is confirmed.

[2049] Each driver's evaluation points are recorded in a database and notified to the driver in real time.

[2050] Feedback and Rewards

[2051] The server performs the following operations based on the evaluation points and the emotional state.

[2052] Provide appropriate feedback to the driver, such as "You're staying focused. Please continue to drive safely."

[2053] If the driver is fatigued or stressed, the system will provide feedback such as, "We recommend taking a short break."

[2054] Offer drivers rewards (e.g., discounts on license renewal fees, discounts on car insurance premiums) based on their evaluation points.

[2055] Information sharing with police agencies

[2056] The server generates a list of dangerous drivers and periodically shares this list with police agencies, allowing them to identify drivers who should be monitored more intensively and build a more efficient monitoring system.

[2057] Hardware and software used

[2058] AI camera: Used to measure the distance between vehicles.

[2059] GPS device: Used to obtain driving speed and location information.

[2060] Emotion Engine: Used to analyze the driver's facial expressions and recognize their emotional state.

[2061] Server: Used to receive and analyze data, calculate reputation points, and generate feedback.

[2062] Software: OpenCV (image processing and facial expression analysis), Dlib (facial feature point detection and emotion analysis), Geopy (location information processing), Requests (data transmission).

[2063] Specific examples

[2064] For example, a vehicle traveling on a highway uses an AI camera to measure the distance to the vehicle ahead, and collects driving speed and location information in real time using acquired GPS data. At the same time, an emotion engine analyzes the driver's facial expressions and recognizes their emotional state, such as "concentrated" or "relaxed." This data is sent to a server via the vehicle's communications device, and based on the analysis results, a notification is sent to the driver, such as "10 points have been added."

[2065] Prompt Sentence Examples

[2066] "The current following distance is 10 metres and the driver's emotional state is focused."

[2067] "Maintaining current speed of 60 km / h while maintaining appropriate following distance."

[2068] "We recommend taking timely rest breaks to reduce stress while driving."

[2069] In this way, this system comprehensively evaluates the driver's driving behavior and emotional state, promoting safe driving and helping to prevent accidents by sharing information with police agencies.

[2070] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2071] Step 1:

[2072] Data collection

[2073] The device measures the distance between vehicles using an AI camera. The acquired distance becomes the input for the next data processing. At the same time, the device uses a GPS device to acquire driving speed and location information. It also uses an emotion engine to analyze the driver's facial expressions and recognize their emotional state (e.g., fatigue, stress, concentration). This data (distance between vehicles, driving speed, location information, emotional state) is temporarily stored in the vehicle's local memory.

[2074] Step 2:

[2075] Data transmission

[2076] The device sends the collected data (distance between vehicles, driving speed, location information, emotional state) to the server. A communication module is used for transmission, and the data is protected by an encrypted protocol. The input of this process is the data collected in step 1, and the output is the data sent to the server.

[2077] Step 3:

[2078] Data reception and analysis

[2079] The server receives data sent from the device. This data includes the following distance, driving speed, location information, and emotional state. It performs data analysis based on the received data and compares it with safe driving standards. For example, it checks whether the following distance meets the safety standard and whether the driving speed exceeds the speed limit. The input of this process is the sent data, and the output is the analysis result.

[2080] Step 4:

[2081] Emotional state assessment

[2082] The server analyzes the received emotion data and evaluates the driver's emotional state. For example, it determines whether the driver is tired or focused based on the results of facial expression analysis. The input of this process is emotion data, and the output is the emotion evaluation result.

[2083] Step 5:

[2084] Calculation of evaluation points

[2085] The server calculates evaluation points based on the data analysis and the evaluation results of the emotional state. Points are added if safe driving is confirmed, and points are subtracted if dangerous driving or a bad emotional state is confirmed. The input of this process is the analysis results and evaluation results, and the output is the evaluation points.

[2086] Step 6:

[2087] Real-time notifications

[2088] The server generates a feedback message for the driver based on the calculated evaluation points and emotional state. For example, if safe driving is confirmed, the server generates feedback such as "You are maintaining concentration. Please continue to drive safely." This feedback is notified to the driver's user interface in real time. The inputs of this process are the evaluation points and emotional state, and the output is a feedback message.

[2089] Step 7:

[2090] Offer

[2091] The server provides rewards to drivers based on their rating points. Each driver's rating points are recorded in a database, and rewards (e.g., discounts on license renewal fees, discounts on car insurance premiums) are offered according to the points. In this process, reward information is sent to the driver. The input of this process is the rating points, and the output is a reward offer message.

[2092] Step 8:

[2093] Information sharing with police agencies

[2094] The server generates a list of dangerous drivers and periodically sends this list to the police, allowing the police to identify drivers who should be monitored more closely. The input of this process is the evaluation data, and the output is the list of dangerous drivers.

[2095] 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.

[2096] 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.

[2097] 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.

[2098] 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.

[2099] 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.

[2100] 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.

[2101] 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).

[2102] 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.

[2103] 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."

[2104] 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.

[2105] 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).

[2106] 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.

[2107] 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.

[2108] 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.

[2109] 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.

[2110] 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.

[2111] 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.

[2112] 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.

[2113] 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.

[2114] 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.

[2115] 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.

[2116] The following is further disclosed regarding the above embodiment.

[2117] ---

[2118] (Claim 1)

[2119] A system for evaluating a driver's driving behavior, comprising:

[2120] means for measuring a distance and a traveling speed from a device mounted on the vehicle;

[2121] means for transmitting data of the measured inter-vehicle distance and traveling speed to a server;

[2122] A means for analyzing the transmitted data and calculating evaluation points;

[2123] a means for notifying the driver of the calculated evaluation points;

[2124] A system including these means.

[2125] (Claim 2)

[2126] A means of providing rewards to drivers based on their rating points;

[2127] A means of sharing evaluation points with law enforcement agencies;

[2128] further comprising means for generating and transmitting a list of dangerous drivers to a law enforcement agency;

[2129] 10. The system of claim 1.

[2130] (Claim 3)

[2131] The device has a GPS function and a means for determining location information;

[2132] The vehicle further includes a means for analyzing the measured position information and comparing it with the speed limit of the road.

[2133] 10. The system of claim 1.

[2134] ---

[2135] "Example 1"

[2136] (Claim 1)

[2137] 1. A system for evaluating driving behavior of a vehicle, comprising:

[2138] means for measuring vehicle distance and speed from a device mounted on the vehicle;

[2139] means for transmitting the measured inter-vehicle distance and speed data to a data processing device;

[2140] means for analyzing the transmitted data and calculating an evaluation value;

[2141] a means for notifying the driver of the calculated evaluation value;

[2142] A system including these means.

[2143] (Claim 2)

[2144] A means for providing a reward to the driver based on the evaluation value;

[2145] A means of sharing the assessment figures with the patrol agency;

[2146] and means for generating and transmitting a list of reckless drivers to a patrol agency.

[2147] 10. The system of claim 1.

[2148] (Claim 3)

[2149] The device has a location measurement function and a means for measuring location information;

[2150] The vehicle further includes a means for analyzing the measured position information and comparing it with the speed limit of the road for evaluation.

[2151] 10. The system of claim 1.

[2152] "Application Example 1"

[2153] (Claim 1)

[2154] 1. A system for evaluating driving behavior of a vehicle, comprising:

[2155] means for measuring a distance and a traveling speed from a device mounted on the vehicle;

[2156] means for transmitting data of the measured inter-vehicle distance and traveling speed to a server;

[2157] A means for analyzing the transmitted data and calculating evaluation points;

[2158] a means for notifying the driver of the calculated evaluation points;

[2159] A means of visualizing real-time distance and driving speed information;

[2160] A means of providing visual and audio alerts as needed;

[2161] A system including these means.

[2162] (Claim 2)

[2163] A means of providing rewards to drivers based on their rating points;

[2164] A means of sharing evaluation points with law enforcement agencies;

[2165] further comprising means for generating and transmitting a list of dangerous drivers to a law enforcement agency;

[2166] 10. The system of claim 1.

[2167] (Claim 3)

[2168] The device has a location function and means for measuring location information;

[2169] The vehicle further includes a means for analyzing the measured position information and comparing it with the speed limit of the road.

[2170] 10. The system of claim 1.

[2171] "Example 2: Combining Emotion Engines"

[2172] (Claim 1)

[2173] means for measuring a distance and a traveling speed from a device mounted on the vehicle;

[2174] means for transmitting data of the measured inter-vehicle distance and traveling speed to a server;

[2175] A means for analyzing the transmitted data and calculating evaluation points;

[2176] a means for notifying the driver of the calculated evaluation points;

[2177] a means for analyzing the driver's facial expression and recognizing the driver's emotional state;

[2178] means for transmitting emotional state data;

[2179] means for analyzing the emotional state data and making an evaluation based on safe driving standards;

[2180] a means for recording each driver's evaluation points in a database;

[2181] A system including:

[2182] (Claim 2)

[2183] A means of providing rewards to drivers based on their rating points;

[2184] A means of sharing evaluation points with law enforcement agencies;

[2185] further comprising means for generating and transmitting a list of dangerous drivers to a law enforcement agency;

[2186] 10. The system of claim 1.

[2187] (Claim 3)

[2188] The device has a GPS function and a means for determining location information;

[2189] A means for analyzing the measured position information and comparing it with the speed limit of the road on which the vehicle is traveling to perform an evaluation;

[2190] A means of real-time notification when rating points change;

[2191] further including a means to provide feedback and advice;

[2192] 10. The system of claim 1.

[2193] "Application example 2 when combining emotion engines"

[2194] (Claim 1)

[2195] means for measuring a distance and a traveling speed from a device mounted on the vehicle;

[2196] a means for analyzing the driver's facial expression and recognizing the driver's emotional state;

[2197] means for transmitting data of the measured inter-vehicle distance and traveling speed, as well as the recognized emotional state, to a server;

[2198] A means for analyzing the transmitted data and calculating evaluation points;

[2199] a means for notifying the driver of feedback based on the calculated evaluation points and emotional state;

[2200] A system including these means.

[2201] (Claim 2)

[2202] A means of providing rewards to drivers based on their rating points;

[2203] a means for sharing assessment points and emotional state with law enforcement agencies;

[2204] further comprising means for generating and transmitting a list of dangerous drivers to a law enforcement agency;

[2205] 10. The system of claim 1.

[2206] (Claim 3)

[2207] The device has a GPS function and a means for determining location information;

[2208] A means for analyzing the measured position information and comparing it with the speed limit of the road on which the vehicle is traveling to perform an evaluation;

[2209] and further comprising means for automatically generating and providing feedback to the driver based on the facial expression analysis results using the generative AI model.

[2210] 10. The system of claim 1. [Explanation of symbols]

[2211] 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 system for evaluating a driver's driving behavior, comprising: means for measuring a distance and a traveling speed from a device mounted on the vehicle; means for transmitting data of the measured inter-vehicle distance and traveling speed to a server; A means for analyzing the transmitted data and calculating evaluation points; a means for notifying the driver of the calculated evaluation points; A system including these means.

2. A means of providing rewards to drivers based on their rating points; A means of sharing evaluation points with law enforcement agencies; further comprising means for generating and transmitting a list of dangerous drivers to a law enforcement agency; The system of claim 1 .

3. The device has a GPS function and a means for determining location information; The vehicle further includes a means for analyzing the measured position information and comparing it with the speed limit of the road. The system of claim 1 .

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