system

Abstract

We provide the system. [Solution] To monitor the driver's condition, A means for acquiring the driver's biometric information using an image capture means, A means of analyzing acquired biometric information to evaluate the driver's health status, A means for generating and notifying warnings based on evaluation results, A system that includes this.

Description

【Technical Field】 【0001】 The technology of the present disclosure relates to a system. 【Background Art】 【0002】 Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance that responds to the user utterance. 【Prior Art Documents】 【Patent Documents】 【0003】 【Patent Document 1】 Japanese Patent Application Laid-Open No. 2022-180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 Among drivers engaged in long-distance transportation, due to the normalization of long hours of driving, there are problems such as drowsy driving and inattentive driving, and the risk of accidents increases. In the conventional technology, there is a lack of means to quickly and accurately evaluate the driver's immediate health condition and attention and give necessary warnings accurately, so it is difficult to prevent accidents. 【Means for Solving the Problems】 【0005】 This invention provides a system that acquires the driver's biometric information in real time using image capture means and evaluates the driver's health condition and attention level using analysis means. Furthermore, it can generate warnings based on the evaluation results and immediately notify the driver, thereby prompting them to stop driving. In addition, if an abnormal condition is detected, it reports to the administrator, supporting a rapid response by the management. This helps to prevent accidents and contributes to improving safety throughout the transportation industry. 【0006】 "Driver's condition" is a general term for factors that directly affect driving safety, such as the driver's health, attention span, and degree of fatigue. 【0007】 "Image acquisition means" refers to a function that uses cameras and related equipment to acquire the driver's face and body movements as video data in real time. 【0008】 "Biometric information" refers to data that indicates vital activities, such as the driver's body movements, eye opening and closing, and direction of gaze. 【0009】 "Analysis means" refers to methods and devices for processing biological information using machine learning algorithms and other analytical techniques to evaluate the driver's health status and attention span. 【0010】 "Assessing health status" is the process of quantifying or qualitatively determining a driver's current physical and mental health status using analytical tools. 【0011】 "Means for generating and notifying warnings" refers to equipment and processes for generating necessary warning messages and communicating them to the driver based on evaluation results. 【0012】 A "notice urging a driver to stop driving" is a notice that advises the driver to stop driving and take a break or other appropriate action. 【0013】 A "notification to report abnormal conditions to the administrator" is a message designed to quickly and reliably convey information to the administrator when a serious abnormality occurs in the driver's condition. [Brief explanation of the drawing] 【0014】 [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined. 【Embodiments for Carrying Out the Invention】 【0015】 Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings. 【0016】 First, the terms used in the following description will be explained. 【0017】 In the following embodiments, a processor with a reference numeral (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be one type of arithmetic unit or a combination of a plurality of types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like. 【0018】 In the following embodiments, a RAM (Random Access Memory) with a reference numeral is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0019】 In the following embodiments, a storage with a reference numeral is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like. 【0020】 In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark). 【0021】 In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or." 【0022】 [First Embodiment] 【0023】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0024】 As shown in Figure 1, the 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. 【0025】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0026】 The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52. 【0027】 The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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. 【0028】 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor. 【0029】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54. 【0030】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0031】 As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30. 【0032】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0033】 In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0034】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal". 【0035】 The system of the present invention operates on the terminal, server, and user sides to monitor the driver's condition in real time and prevent drowsy driving and inattentive driving. 【0036】 Terminal operation 【0037】 The terminal is a device installed in the driver's seat, such as a smartphone or a dedicated camera. The terminal captures the driver's face with a high-precision camera and captures biometric information. The terminal has the function of periodically sending this data to a server and also plays a role in notifying the user of warning messages received from the server. 【0038】 Server operation 【0039】 The server receives biometric information transmitted from the terminal. The received data is analyzed by an AI model to evaluate the driver's health status and attention level. Based on the analysis results, the server generates necessary warning messages and sends them to the terminal. If the driver's condition is determined to be abnormal, the server also notifies the administrator to prompt a quick response. 【0040】 User actions 【0041】 Users should check warning messages received from their devices and interrupt driving as needed. In particular, if signs of drowsiness are detected, users are advised to take a break in a safe place. Furthermore, abnormal notifications are sent to administrators, allowing them to receive more appropriate instructions and support. 【0042】 Specific example 【0043】 For example, if the device's camera monitors the driver's eye blinking frequency, and the driver blinks infrequently for an extended period, the server will determine that the driver is at risk of falling asleep at the wheel. The server will immediately send a warning to the device stating, "Warning: You may be drowsy. Please take a break." This warning is communicated to the user via voice and on-screen display, allowing them to take prompt action. 【0044】 Thus, the system of the present invention is implemented to continuously evaluate the driver's condition and improve safety. 【0045】 The following describes the processing flow. 【0046】 Step 1: 【0047】 The device activates its camera and takes a picture of the driver's face. The acquired video data is processed in real time to extract biometric information such as eye movements and facial orientation. 【0048】 Step 2: 【0049】 The terminal transmits the extracted biometric information to the server at regular intervals. When transmitting data, it waits for a simple response from the server to confirm the success of the transmission. 【0050】 Step 3: 【0051】 The server receives biometric information transmitted from the terminal. The received data is passed to an AI analysis module to evaluate the driver's health and attention level. 【0052】 Step 4: 【0053】 The server uses an AI model to calculate an anomaly score based on biometric information. If the score exceeds a pre-set threshold, it is determined that the user may be experiencing drowsiness or extreme fatigue. 【0054】 Step 5: 【0055】 If an anomaly is detected, the server will generate a warning message. The warning will include specific action instructions, such as a prompt to stop driving or take a break. 【0056】 Step 6: 【0057】 The server sends the generated warning message to the terminal. It also prepares to send an anomaly notification to the administrator if necessary. 【0058】 Step 7: 【0059】 The terminal receives a warning message from the server and immediately notifies the user. Notification methods can include audio alerts or screen displays. 【0060】 Step 8: 【0061】 Users can check notifications, stop driving as advised, and take a safe break. They can also provide feedback on their status to the server as needed. 【0062】 Step 9: 【0063】 The server receives feedback from the user and confirms that the condition has improved. After the anomaly is resolved, the system state is reset and prepared for the next operating cycle. 【0064】 (Example 1) 【0065】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0066】 To prevent traffic accidents caused by drowsy or inattentive driving, it is necessary to monitor the driver's condition in real time and provide appropriate warnings and countermeasures quickly. However, conventional technology has had difficulty effectively detecting these conditions, limiting its ability to provide accurate alerts to drivers. 【0067】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0068】 In this invention, the server includes means for acquiring the driver's biometric information using an image capture device, means including an artificial intelligence model that analyzes the acquired biometric information to evaluate the driver's attention span, and means for generating a warning based on the evaluation result and notifying a terminal. This enables real-time monitoring of the driver's condition and rapid warning notification. 【0069】 The term "driver" refers to the person who operates a vehicle while it is in motion. 【0070】 "Condition monitoring" refers to the act of observing the driver's physical and psychological state in real time. 【0071】 An "image acquisition device" refers to a device that acquires the driver's posture and facial movements as image data. 【0072】 "Biometric information" refers to information that shows physical or physiological data about the driver. 【0073】 An "artificial intelligence model" refers to a program that uses machine learning or deep learning techniques to analyze the driver's condition. 【0074】 "Attention assessment" refers to the process of measuring and judging a driver's level of concentration and alertness. 【0075】 Generating a "warning" refers to the act of creating necessary alerts and cautionary messages for the driver. 【0076】 "Notifying the device" refers to the process of forwarding the generated warning message to the device operated by the user. 【0077】 A "user" refers to someone who receives warnings and notifications from the system. 【0078】 This invention is a system for supporting safe driving by drivers, and operates in the roles of terminal, server, and user. 【0079】 The terminal uses image capture devices such as smartphones or dedicated camera devices installed in the driver's seat. The terminal's high-precision camera captures the driver's facial expressions and movements in real time, acquiring biometric information. This data is periodically transmitted to a server via a communication network (e.g., 4G / 5G or Wi-Fi). 【0080】 The server analyzes the driver's state using a generative AI model based on biometric information received from the terminal. This artificial intelligence model evaluates the driver's attention level based on factors such as blinking and eye movements. Based on the evaluation results, the server generates a warning message and sends it to the terminal. 【0081】 The terminal notifies the user of warning messages sent from the server. Notifications are made via audio or on-screen display, prompting the user to provide necessary information and warnings. 【0082】 For example, if the terminal's camera monitors the driver's blinking frequency while driving and detects an extremely low blinking rate, the server will interpret this as a sign of drowsiness and generate a warning message such as, "Caution: You may be drowsy. Please take a break." This warning is presented to the user via voice or on the display of the terminal, allowing the user to take prompt action. 【0083】 This system aims to prevent dangerous driving by continuously evaluating the driver's psychological and physiological state. 【0084】 An example of a prompt message is, "Use an AI model to analyze the driver's blinking frequency data and detect signs of drowsiness." 【0085】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0086】 Step 1: 【0087】 The device uses a high-precision camera to capture the driver's face. The input is real-time video of the driver's face. Based on this video data, it extracts facial feature points and calculates biometric information (e.g., blink frequency, gaze direction). Specifically, it uses image processing software within the device to automatically identify feature points and record them as numerical data. 【0088】 Step 2: 【0089】 The terminal transmits the acquired biometric information to the server via the network. The input is the numerical data of the biometric information generated in step 1. This data is compressed periodically (for example, every second) and transmitted to the server with low latency. Specifically, the terminal configures the communication protocol, generates data packets, and transmits them. 【0090】 Step 3: 【0091】 The server analyzes biometric information received from the terminal. The input is a dataset of transmitted biometric data. A generative AI model is used to evaluate the driver's attention using this data. In this process, the AI ​​model learns the driver's behavioral patterns and detects signs of drowsiness or inattention. Specifically, the AI ​​software takes in the data, applies the model, and outputs an evaluation score. 【0092】 Step 4: 【0093】 The server generates a warning message based on the analysis results. The input is the analysis score obtained in step 3. Based on this, it sets the warning level for the driver and creates an appropriate message. Specifically, it selects the wording of the warning message and formats it as a digital message. 【0094】 Step 5: 【0095】 The server sends the generated warning message to the terminal. The input is the generated warning message. The server packets the message and sends it quickly to the terminal via the communication network. Specifically, it sets the destination address and sends the message according to the communication protocol. 【0096】 Step 6: 【0097】 The device notifies the user of warning messages received from the server. The input is the warning message sent from the server. The device immediately alerts the user with audio alerts or screen displays according to the notification priority. Specifically, it controls the device's speaker and display to present the message in a way that is easy for the user to understand. 【0098】 (Application Example 1) 【0099】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0100】 In autonomous vehicles, preventing accidents caused by driver inattention or drowsiness is crucial. However, conventional technology struggles to accurately monitor the driver's condition in real time and provide timely warnings. Furthermore, there are insufficient means to prompt drivers to immediately recognize warnings and take appropriate action. 【0101】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0102】 In this invention, the server includes means for acquiring the driver's biometric information using an image capture device, means for analyzing the acquired biometric information to evaluate the driver's health condition and attention level, and means for providing real-time warnings audibly and visually. This enables rapid and accurate monitoring of the driver's condition, immediate warnings as needed, and allows the driver to take prompt and appropriate action. 【0103】 "Driver's condition" refers to all factors that affect vehicle operation, including the driver's health and attention level. 【0104】 An "image acquisition device" is a device that uses a camera or similar device to acquire the driver's biometric information. 【0105】 "Biometric information" refers to data obtained from the driver's body, such as facial images, eye movements, blinking frequency, and posture. 【0106】 "Health status" refers to the condition of the driver's physical and mental health. 【0107】 "Attention" is the driver's ability to concentrate on and maintain focus on driving operations. 【0108】 "Evaluation" is the process of analyzing acquired biometric information to determine health status and attention span. 【0109】 "Real-time" refers to a state where data acquisition and processing occur almost instantly, with virtually no delay. 【0110】 A "warning" is a notification that informs the driver that there is an imminent danger. 【0111】 "Voice notification" is a method of communicating warnings and instructions to the driver through a speaker using sound. 【0112】 "Visual notification" refers to a method of visually presenting warnings and information to the driver through displays or other means. 【0113】 A system for implementing this invention includes a terminal installed in an autonomous vehicle, a remote server, and a driver. The terminal acquires the driver's biometric information using a smartphone or dedicated video camera inside the autonomous vehicle. The image acquisition device used here includes, for example, a high-performance camera. 【0114】 The device has the function of transmitting acquired biometric information to the server in real time. The server uses an AI model to analyze the received biometric information and evaluate the driver's health status and attention level. The AI ​​model is built using Python and TENSORFLOW® and analyzes the driver's eye movements and facial expressions. Based on the analysis results, the server generates audio and visual warnings and notifies the driver through the device. 【0115】 For example, if the driver's eyes are not opening and closing frequently and their gaze is fixed, the system may determine that they are drowsy and automatically generate a warning message, "Caution: You may be drowsy. Please take a break at a nearby rest stop," which will be displayed on the vehicle's screen. This information will also be communicated to the driver via the in-vehicle audio system. 【0116】 Furthermore, if the driver ignores a warning or fails to respond immediately, the server will consider this an abnormal condition and notify the administrator. The notification function will utilize the in-vehicle network and internet communication. An example of a prompt message is: "Create an AI model that can detect signs of drowsy driving by analyzing the frequency of eye opening and closing and pupil movement while driving." 【0117】 Thus, the present invention provides a system that improves driver safety and helps prevent accidents. 【0118】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0119】 Step 1: 【0120】 The device acquires the driver's biometric information. Using a camera, it captures the driver's face, eye movements, and blinking frequency as video. The input is real-time video data, and the output is digital biometric data. 【0121】 Step 2: 【0122】 The device transmits the acquired biometric information to the server. Real-time performance is maintained by sending the data to a remote server via the internet. The input is digitized biometric information, and the output is data ready for processing on the server side. 【0123】 Step 3: 【0124】 The server analyzes biometric information. It uses an AI model to evaluate the driver's health and attention span. Specifically, it uses TensorFlow to analyze facial expressions and eye movements to detect signs of drowsiness or distraction. The input is biometric information sent to the server, and the output is the analyzed evaluation data. 【0125】 Step 4: 【0126】 The server generates warning messages based on the analysis results. If the evaluation data indicates any signs of impediment to safe driving, it automatically creates the necessary warning messages. The input is the evaluation results, and the output is the digital data of the warning messages. 【0127】 Step 5: 【0128】 The server sends the generated warning message to the terminal. It delivers the message to the terminal to provide audio and visual notifications. The input is the warning message, and the output is the message converted into a notificationable format. 【0129】 Step 6: 【0130】 The terminal notifies the driver of a warning. It conveys the warning message to the driver using an audio output device or a display. The input is a warning message in a notifiable format, and the output is warning information that the driver can see or hear. 【0131】 Step 7: 【0132】 The user receives a warning and chooses a response. If there are signs of drowsiness or distraction, they are prompted to take appropriate action. The input is the warning message received, and the output is the driver's action. 【0133】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0134】 The system of this invention monitors the driver's condition and, in particular, incorporates an emotion engine to recognize the driver's emotional state in real time, thereby providing a higher level of safety. This system exchanges information with each other through terminals, servers, and users, enabling rapid response. 【0135】 Terminal operation 【0136】 The terminal is placed in the driver's seat and captures the driver's face via a camera, acquiring facial expressions along with biometric information. The terminal processes this data with an emotion engine to identify the driver's emotional state, thereby sending more detailed warnings and notifications to the server. 【0137】 Server operation 【0138】 The server receives biometric and emotional data transmitted from the terminal. The emotion engine analyzes this data and evaluates the driver's health and emotional state. Depending on the individual's emotional state, for example, if stress levels are high, it generates a stronger warning than usual to draw attention. It also creates notifications recommending interrupting driving or taking a break based on this emotional data. 【0139】 User actions 【0140】 Users receive audio and visual warnings from their devices and adjust their driving accordingly. If they receive a warning related to their emotional state, they can control their emotions and take measures such as taking a longer break if necessary. 【0141】 Specific example 【0142】 For example, if the emotional engine detects that the driver's stress level is high while driving, the server instantly analyzes this information and sends a message to the device saying, "Warning: Your stress level is high. We recommend taking a deep breath and a break." This notification is displayed to the user in real time, allowing the driver to pay attention to their emotions and drive more safely. 【0143】 Thus, by utilizing an emotion engine and responding not only to the driver's biological state but also to their emotional state, this invention further improves safety in the transportation industry. 【0144】 The following describes the processing flow. 【0145】 Step 1: 【0146】 The device uses a camera to photograph the driver's face, capturing not only biometric information but also facial expression data. This data is processed in real time and prepared to be sent to a server at regular intervals. 【0147】 Step 2: 【0148】 The terminal transmits the acquired biometric information and facial expression data to the server. If the transmission is successful, it receives a confirmation signal. 【0149】 Step 3: 【0150】 Upon receiving the transmitted data, the server uses an emotion engine to analyze the driver's current emotional state. 【0151】 Step 4: 【0152】 Based on the analysis results, the server integrates and evaluates the driver's health and emotional state. In particular, if significant emotional changes (e.g., stress or anger) are detected, it calculates an abnormality score accordingly. 【0153】 Step 5: 【0154】 The server generates customized warnings based on the emotional state assessment results. For example, if stress levels are high, it will create a message such as, "You are feeling stressed. Take a short break." 【0155】 Step 6: 【0156】 The server will send the generated warning to the terminal and will also consider notifying the administrator of the abnormal condition so that they can identify the problem. 【0157】 Step 7: 【0158】 The terminal immediately notifies the user of any warnings sent by the server. Notification methods can include audio alerts and visual messages to ensure the user understands the warning. 【0159】 Step 8: 【0160】 The user checks notifications from their device and takes recommended actions (e.g., deep breathing, short breaks). They take necessary steps to support improvement of their emotional state and maintain safe driving. 【0161】 Step 9: 【0162】 When the server receives emotional feedback from the user, it reviews the data and recognizes that the emotional state has improved. It then resets the system state to prepare for the next analysis cycle. 【0163】 (Example 2) 【0164】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0165】 In modern society, traffic accidents caused by driver fatigue and stress are a major social problem. Conventional systems can only provide warnings based on the driver's basic health status and cannot evaluate or notify based on emotional state, resulting in insufficient detection and appropriate countermeasures when a driver is in a potentially dangerous state. Therefore, there is a need for the development of a driver monitoring system capable of more advanced analysis. 【0166】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0167】 In this invention, the server includes means for acquiring the driver's biometric information and facial expression information using image capture means, means for analyzing the acquired biometric information and facial expression information to evaluate the driver's health and emotional state, and means for generating warnings and notifications based on the evaluation results and communicating them to the driver in real time. This enables more detailed monitoring based on the driver's emotional state and prompt countermeasures. 【0168】 "Image capture means" refers to a device installed to photograph the driver's face and facial expressions, and includes means such as cameras and sensors. 【0169】 "Biometric information" refers to data indicating the driver's physical condition, such as heart rate, skin temperature, and respiratory rate. 【0170】 "Facial expression information" refers to information obtained from the driver's facial expressions and includes basic data for analyzing their emotional state. 【0171】 "Emotional state" refers to the driver's psychological state and includes emotions such as joy, anger, sadness, surprise, and fear. 【0172】 "Analysis means" refers to a device or software that uses acquired biometric information and facial expression information to evaluate the driver's health and emotional state. 【0173】 "Warnings and notifications" are messages generated based on analysis results to support safe driving by the driver, and are displayed either audibly or visually. 【0174】 "Real-time" refers to providing processing results immediately without delay, enabling drivers to take immediate action. 【0175】 This invention is a system that promotes safe driving by analyzing the driver's emotional state and health condition in real time. The embodiments thereof are described below. 【0176】 Device Overview 【0177】 The terminal is installed in the driver's seat and primarily consists of a camera and biometric sensors. The camera captures the driver's face and acquires facial expression information. The biometric sensors collect data such as heart rate and skin temperature. This biometric and facial information is processed by software called an emotion engine within the terminal. The emotion engine primarily uses a generative AI model based on deep learning technology to analyze the driver's emotional state. The analysis results are sent to a server as data packets. 【0178】 Server Overview 【0179】 The server is responsible for receiving data packets sent from the terminal and performing detailed analysis. Using a high-performance processor, the server can process the received data quickly in real time. The emotion engine on the server comprehensively evaluates the driver's emotional and physical state. For example, if a high stress level is detected, the server generates a specific notification such as, "We recommend you take a break." This notification is sent to the terminal in audio or visual format and communicated to the user (driver). 【0180】 User Overview 【0181】 Users can receive notifications from their devices and adjust their driving accordingly. For example, a user who receives a notification that their stress levels are rising can choose to take deep breaths or take a break. By following specific advice based on their emotional state, they can drive safely and comfortably. 【0182】 Examples of specific cases and prompt statements 【0183】 For example, if the emotional engine detects that the driver's stress level is high while driving, the server generates a message based on the analysis results, stating, "Warning: Your stress level is high. We recommend taking a deep breath and a break," and sends it to the device. This notification allows the user to respond immediately and maintain safe driving. 【0184】 An example of a prompt would be, "Write a program that acquires the driver's facial expression data and analyzes their stress level. Also, add logic to generate a warning message based on the results." Based on this prompt, the generating AI model constructs the specific operational logic for the emotion engine. 【0185】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0186】 Step 1: 【0187】 The terminal captures the driver's face with a camera and collects facial expression information. It receives image data from the camera as input and generates image information to be processed as output. In this process, preprocessing is performed to reduce noise and adjust the resolution of the image to be used. 【0188】 Step 2: 【0189】 The terminal uses biometric sensors to acquire biometric information such as the driver's heart rate and skin temperature. It receives data from the biometric sensors as input and generates biometric data as output. The acquired data undergoes a smoothing process to remove outliers. 【0190】 Step 3: 【0191】 The emotion engine installed in the terminal receives pre-processed facial and biometric information as input and analyzes the driver's emotional state. As output, it generates an index indicating the driver's emotional state. In this process, an algorithm is applied that uses a generative AI model to determine emotions from the driver's facial expressions. 【0192】 Step 4: 【0193】 The terminal sends the analysis results to the server as data packets. It receives indicators of emotional state as input and generates data packets for transmission to the server as output. These packets include details of the driver's stress level and emotions. 【0194】 Step 5: 【0195】 The server analyzes data packets received from the terminal. Using the received data packets as input, it generates warnings and notifications corresponding to the driver's emotional state as output. In this process, a detailed evaluation is conducted, taking into account the intensity and changes in emotions, to determine the necessary actions. 【0196】 Step 6: 【0197】 The server sends the generated warnings and notifications to the terminal. Using the analyzed evaluation results as input, it generates voice and visual notification messages for the user as output. Specifically, it provides recommendations to interrupt driving or suggest specific actions (e.g., deep breathing) as needed. 【0198】 Step 7: 【0199】 The user receives notifications from the device and adjusts their driving accordingly. The system receives notifications transmitted from the device as input and takes appropriate driving actions as output (e.g., taking a break, reassessing concentration). This enhances safety and allows for appropriate responses based on the driver's condition. 【0200】 (Application Example 2) 【0201】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal". 【0202】 In autonomous vehicles, a challenge is that changes in the health and emotional state of the driver or passengers can negatively impact vehicle operation. In particular, there is a need for means to respond quickly and appropriately when stress or fatigue is detected. Furthermore, a challenge is the ability to appropriately assess stress levels experienced by the driver monitoring the vehicle and automatically adjust the monitoring level accordingly. 【0203】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0204】 In this invention, the server includes means for acquiring facial expression information of the driver or passenger using an image capture device, means for acquiring biometric information of the driver or passenger using a biosensor, means for analyzing the acquired facial expression information and biometric information to evaluate the health and emotional state of the driver or passenger, means for generating and notifying warnings based on the evaluation results, and means for adjusting the driving monitoring level according to the emotional state. This makes it possible to improve the safety and efficiency of the autonomous vehicle through real-time feedback according to the emotional state of the driver or passenger. 【0205】 A "driver" is an individual whose role is to monitor the operation of automobiles and autonomous vehicles and to ensure their safe operation. 【0206】 A "passenger" is an individual who rides in a car or self-driving vehicle and enjoys the safety and comfort of that vehicle while traveling. 【0207】 An "image acquisition device" is a device that uses a camera or similar device to acquire images or videos of a target in real time. 【0208】 "Facial expression information" refers to data obtained from the facial features and movements of a subject acquired by an image capture device, which is used to indicate emotional states. 【0209】 A "biosensor" is a sensor used to acquire physiological data such as heart rate and body temperature. 【0210】 "Biometric information" refers to physiological data that indicates an individual's health status, obtained through biosensors. 【0211】 "Emotional state" refers to the psychological state of the driver or passenger, and includes stress, joy, anger, etc. 【0212】 "Evaluation" is the process of analyzing acquired data to determine the health and emotional state of the driver or passenger. 【0213】 A "warning" is a notice intended to draw the attention of the driver or passengers in order to ensure the safety of the vehicle. 【0214】 "Adjusting the driving monitoring level" means changing the monitoring mode of the autonomous driving system according to the emotional state of the driver or monitor. 【0215】 This invention is a system for enhancing safety in autonomous vehicles by monitoring the emotions and health status of the driver or passengers in real time. Specific embodiments are described below. 【0216】 Server operation 【0217】 The server receives data from image capture devices and biosensors. Image capture devices acquire facial expression information of the driver or passenger, and biosensors acquire biometric information such as heart rate and body temperature. The server uses facial recognition AI and emotion analysis engine to analyze this data and evaluate the emotional state and health status. Based on the evaluation results, it generates warnings and notifies the terminal. If necessary, it also provides instructions to adjust the driving monitoring level. 【0218】 Terminal operation 【0219】 The terminal is installed inside the autonomous vehicle and displays warnings and notifications sent from the server. Specifically, it alerts the driver or passengers through voice and display. In addition, if the emotional state is unstable, it continues to collect data from image capture devices and biosensors and provides feedback to the server. 【0220】 User actions 【0221】 The user (driver or passenger) receives notifications from the device and manages their emotional and physical state appropriately. For example, if stress levels are assessed as high, the device will provide advice such as, "Take deep breaths to reduce stress, and take a 5-minute break if necessary." 【0222】 Specific example 【0223】 For example, if the system determines that the supervisor of an autonomous vehicle is experiencing high stress levels, it will instruct the vehicle to temporarily increase its monitoring mode and send a notification prompting the supervisor to take a deep breath. This improves the overall safety of the autonomous vehicle. 【0224】 Example of a prompt 【0225】 "I want to develop an emotion monitoring system to be installed in autonomous vehicles. Please create a program that analyzes the emotional state of the observer based on their facial expressions and biometric information, and provides recommendations to reduce stress as needed." 【0226】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0227】 Step 1: 【0228】 The terminal uses an image capture device to acquire facial information of the driver or passenger in real time. The input is image data captured by the camera. The output is facial expression data analyzed by facial recognition AI. Specifically, this data identifies the feature points of each face and quantifies changes in facial expression. 【0229】 Step 2: 【0230】 The server receives biometric information such as heart rate and body temperature from biosensors of the driver or passenger. The input is physiological data from the biosensors. The output is evaluation data that expresses this data as a health status index. Specifically, it calculates the stress level when the heart rate exceeds a certain threshold. 【0231】 Step 3: 【0232】 The server integrates the facial expression data obtained in Step 1 and the physiological data obtained in Step 2, and uses an emotion analysis engine to evaluate the emotional state of the driver or passenger. The inputs are facial expression data and physiological data. The output is an identification result indicating the emotional state. Specifically, the emotional state is classified into categories such as "stress," "relief," and "joy." 【0233】 Step 4: 【0234】 The server generates a warning or notification message based on the emotion assessment results and sends it to the terminal. The input is the evaluation result of the emotion analysis engine. The output is a warning message recommending a specific action. For example, if stress levels are high, it generates a message such as "We recommend you take a break." 【0235】 Step 5: 【0236】 The terminal notifies the user of warning messages received from the server via audio or display. The input is the warning message from the server. The output is an audio or visual prompt to encourage user action. Specifically, this involves displaying the message on the screen and playing an audio alert. 【0237】 Step 6: 【0238】 The user checks notifications from their device and takes appropriate action based on their emotional and health state. The input is a warning message from the device. The output is a change in the user's behavior or improvement in their state. For example, they might take deep breaths to reduce stress or pause the device. 【0239】 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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. 【0240】 Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0241】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14. 【0242】 [Second Embodiment] 【0243】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0244】 As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server. 【0245】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0246】 The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52. 【0247】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0248】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0249】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0250】 Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0251】 The specific processing program 56 is an example of a "program" relating to the technology of this 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. 【0252】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0253】 In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0254】 Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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". 【0255】 The system of the present invention operates on the terminal, server, and user sides to monitor the driver's condition in real time and prevent drowsy driving and inattentive driving. 【0256】 Terminal operation 【0257】 The terminal is a device installed in the driver's seat, such as a smartphone or a dedicated camera. The terminal captures the driver's face with a high-precision camera and captures biometric information. The terminal has the function of periodically sending this data to a server and also plays a role in notifying the user of warning messages received from the server. 【0258】 Server operation 【0259】 The server receives biometric information transmitted from the terminal. The received data is analyzed by an AI model to evaluate the driver's health status and attention level. Based on the analysis results, the server generates necessary warning messages and sends them to the terminal. If the driver's condition is determined to be abnormal, the server also notifies the administrator to prompt a quick response. 【0260】 User actions 【0261】 Users should check warning messages received from their devices and interrupt driving as needed. In particular, if signs of drowsiness are detected, users are advised to take a break in a safe place. Furthermore, abnormal notifications are sent to administrators, allowing them to receive more appropriate instructions and support. 【0262】 Specific example 【0263】 For example, if the device's camera monitors the driver's eye blinking frequency, and the driver blinks infrequently for an extended period, the server will determine that the driver is at risk of falling asleep at the wheel. The server will immediately send a warning to the device stating, "Warning: You may be drowsy. Please take a break." This warning is communicated to the user via voice and on-screen display, allowing them to take prompt action. 【0264】 Thus, the system of the present invention is implemented to continuously evaluate the driver's condition and improve safety. 【0265】 The following describes the processing flow. 【0266】 Step 1: 【0267】 The device activates its camera and takes a picture of the driver's face. The acquired video data is processed in real time to extract biometric information such as eye movements and facial orientation. 【0268】 Step 2: 【0269】 The terminal transmits the extracted biometric information to the server at regular intervals. When transmitting data, it waits for a simple response from the server to confirm the success of the transmission. 【0270】 Step 3: 【0271】 The server receives biometric information transmitted from the terminal. The received data is passed to an AI analysis module to evaluate the driver's health and attention level. 【0272】 Step 4: 【0273】 The server uses an AI model to calculate an anomaly score based on biometric information. If the score exceeds a pre-set threshold, it is determined that the user may be experiencing drowsiness or extreme fatigue. 【0274】 Step 5: 【0275】 If an anomaly is detected, the server will generate a warning message. The warning will include specific action instructions, such as a prompt to stop driving or take a break. 【0276】 Step 6: 【0277】 The server sends the generated warning message to the terminal. It also prepares to send an anomaly notification to the administrator if necessary. 【0278】 Step 7: 【0279】 The terminal receives a warning message from the server and immediately notifies the user. Notification methods can include audio alerts or screen displays. 【0280】 Step 8: 【0281】 The user checks the notification, interrupts driving according to the warning, and takes a break safely. It is also possible for the user to provide feedback on their own condition to the server according to the situation. 【0282】 Step 9: 【0283】 The server receives the feedback from the user and confirms that the condition has improved. After the abnormality is resolved, the system state is reset to prepare for the next driving cycle. 【0284】 (Example 1) 【0285】 Next, Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal". 【0286】 In order to prevent the risk of traffic accidents caused by a driver's drowsy driving or inattentive driving, it is required to monitor the driver's condition in real time and quickly provide appropriate warnings and countermeasures. However, in the conventional technology, it is difficult to effectively detect these conditions, and there are limitations in issuing accurate alerts to the driver. 【0287】 The specific processing by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0288】 In this invention, the server includes means for acquiring the driver's biometric information using an image capture device, means including an artificial intelligence model for analyzing the acquired biometric information to evaluate the driver's attention, and means for generating a warning based on the evaluation result and notifying the terminal. Thereby, real-time state monitoring of the driver and rapid warning notification are possible. 【0289】 The "driver" refers to a person who operates a vehicle during driving. 【0290】 "State monitoring" refers to the act of observing the driver's physical and mental conditions in real time. 【0291】 An "image acquisition device" refers to a device that acquires the driver's posture and facial movements as image data. 【0292】 "Biometric information" refers to information that shows physical or physiological data about the driver. 【0293】 An "artificial intelligence model" refers to a program that uses machine learning or deep learning techniques to analyze the driver's condition. 【0294】 "Attention assessment" refers to the process of measuring and judging a driver's level of concentration and alertness. 【0295】 Generating a "warning" refers to the act of creating necessary alerts and cautionary messages for the driver. 【0296】 "Notifying the device" refers to the process of forwarding the generated warning message to the device operated by the user. 【0297】 A "user" refers to someone who receives warnings and notifications from the system. 【0298】 This invention is a system for supporting safe driving by drivers, and operates in the roles of terminal, server, and user. 【0299】 The terminal uses image capture devices such as smartphones or dedicated camera devices installed in the driver's seat. The terminal's high-precision camera captures the driver's facial expressions and movements in real time, acquiring biometric information. This data is periodically transmitted to a server via a communication network (e.g., 4G / 5G or Wi-Fi). 【0300】 The server analyzes the driver's state using a generative AI model based on biometric information received from the terminal. This artificial intelligence model evaluates the driver's attention level based on factors such as blinking and eye movements. Based on the evaluation results, the server generates a warning message and sends it to the terminal. 【0301】 The terminal notifies the user of the warning message sent from the server. The notification is made by voice or on-screen display, prompting the user with necessary information and cautions. 【0302】 As a specific example, when the camera of the terminal monitors the driver's blink frequency during driving and detects a state where the blinks are extremely few, the server determines this as a sign of drowsiness and generates a warning such as "Attention: There may be a risk of drowsy driving. Please take a break." This warning is presented to the user by the terminal through voice or display, enabling the user to respond promptly. 【0303】 This system aims to continuously evaluate the driver's psychological and physiological states and prevent dangerous driving. 【0304】 An example of a prompt sentence is "Analyze the driver's blink frequency data using an AI model and detect signs of drowsiness." 【0305】 The flow of the specific process in Example 1 will be described using FIG. 11. 【0306】 Step 1: [[ID=S22]] [[ID=S23]] 【0307】 [[ID=S24]] [[ID=S25]]The terminal captures the driver's face using a high-precision camera. As input, the video of the driver's face is acquired in real time. Based on this video data, the feature points of the face are extracted, and biometric information (e.g., blink frequency, line of sight direction) is calculated. As a specific operation, the feature points are automatically identified using the image processing software in the terminal and recorded as numerical data. [[ID=S26]] [[ID=S27]] 【0308】 [[ID=S28]] [[ID=S29]]Step 2: [[ID=S30]] [[ID=S31]] 【0309】 [[ID=S32]] The terminal transmits the acquired biometric information to the server via the network. The input is the numerical data of the biometric information generated in step 1. This data is compressed periodically (for example, every second) and transmitted to the server with low latency. Specifically, the terminal configures the communication protocol, generates data packets, and transmits them. 【0310】 Step 3: 【0311】 The server analyzes biometric information received from the terminal. The input is a dataset of transmitted biometric data. A generative AI model is used to evaluate the driver's attention using this data. In this process, the AI ​​model learns the driver's behavioral patterns and detects signs of drowsiness or inattention. Specifically, the AI ​​software takes in the data, applies the model, and outputs an evaluation score. 【0312】 Step 4: 【0313】 The server generates a warning message based on the analysis results. The input is the analysis score obtained in step 3. Based on this, it sets the warning level for the driver and creates an appropriate message. Specifically, it selects the wording of the warning message and formats it as a digital message. 【0314】 Step 5: 【0315】 The server sends the generated warning message to the terminal. The input is the generated warning message. The server packets the message and sends it quickly to the terminal via the communication network. Specifically, it sets the destination address and sends the message according to the communication protocol. 【0316】 Step 6: 【0317】 The device notifies the user of warning messages received from the server. The input is the warning message sent from the server. The device immediately alerts the user with audio alerts or screen displays according to the notification priority. Specifically, it controls the device's speaker and display to present the message in a way that is easy for the user to understand. 【0318】 (Application Example 1) 【0319】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal." 【0320】 In autonomous vehicles, preventing accidents caused by driver inattention or drowsiness is crucial. However, conventional technology struggles to accurately monitor the driver's condition in real time and provide timely warnings. Furthermore, there are insufficient means to prompt drivers to immediately recognize warnings and take appropriate action. 【0321】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0322】 In this invention, the server includes means for acquiring the driver's biometric information using an image capture device, means for analyzing the acquired biometric information to evaluate the driver's health condition and attention level, and means for providing real-time warnings audibly and visually. This enables rapid and accurate monitoring of the driver's condition, immediate warnings as needed, and allows the driver to take prompt and appropriate action. 【0323】 "Driver's condition" refers to all factors that affect vehicle operation, including the driver's health and attention level. 【0324】 An "image acquisition device" is a device that uses a camera or similar device to acquire the driver's biometric information. 【0325】 "Biometric information" refers to data obtained from the driver's body, such as facial images, eye movements, blinking frequency, and posture. 【0326】 "Health status" refers to the condition of the driver's physical and mental health. 【0327】 "Attention" is the driver's ability to concentrate on and maintain focus on driving operations. 【0328】 "Evaluation" is the process of analyzing acquired biometric information to determine health status and attention span. 【0329】 "Real-time" refers to a state where data acquisition and processing occur almost instantly, with virtually no delay. 【0330】 A "warning" is a notification that informs the driver that there is an imminent danger. 【0331】 "Voice notification" is a method of communicating warnings and instructions to the driver through a speaker using sound. 【0332】 "Visual notification" refers to a method of visually presenting warnings and information to the driver through displays or other means. 【0333】 A system for implementing this invention includes a terminal installed in an autonomous vehicle, a remote server, and a driver. The terminal acquires the driver's biometric information using a smartphone or dedicated video camera inside the autonomous vehicle. The image acquisition device used here includes, for example, a high-performance camera. 【0334】 The device has the function of transmitting acquired biometric information to the server in real time. The server uses an AI model to analyze the received biometric information and evaluate the driver's health status and attention level. The AI ​​model is built using Python and TensorFlow and analyzes the driver's eye movements and facial expressions. Based on the analysis results, the server generates audio and visual warnings and notifies the driver through the device. 【0335】 For example, if the driver's eyes are not opening and closing frequently and their gaze is fixed, the system may determine that they are drowsy and automatically generate a warning message, "Caution: You may be drowsy. Please take a break at a nearby rest stop," which will be displayed on the vehicle's screen. This information will also be communicated to the driver via the in-vehicle audio system. 【0336】 Furthermore, if the driver ignores a warning or fails to respond immediately, the server will consider this an abnormal condition and notify the administrator. The notification function will utilize the in-vehicle network and internet communication. An example of a prompt message is: "Create an AI model that can detect signs of drowsy driving by analyzing the frequency of eye opening and closing and pupil movement while driving." 【0337】 Thus, the present invention provides a system that improves driver safety and helps prevent accidents. 【0338】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0339】 Step 1: 【0340】 The device acquires the driver's biometric information. Using a camera, it captures the driver's face, eye movements, and blinking frequency as video. The input is real-time video data, and the output is digital biometric data. 【0341】 Step 2: 【0342】 The device transmits the acquired biometric information to the server. Real-time performance is maintained by sending the data to a remote server via the internet. The input is digitized biometric information, and the output is data ready for processing on the server side. 【0343】 Step 3: 【0344】 The server analyzes biometric information. It uses an AI model to evaluate the driver's health and attention span. Specifically, it uses TensorFlow to analyze facial expressions and eye movements to detect signs of drowsiness or distraction. The input is biometric information sent to the server, and the output is the analyzed evaluation data. 【0345】 Step 4: 【0346】 The server generates warning messages based on the analysis results. If the evaluation data indicates any signs of impediment to safe driving, it automatically creates the necessary warning messages. The input is the evaluation results, and the output is the digital data of the warning messages. 【0347】 Step 5: 【0348】 The server sends the generated warning message to the terminal. It delivers the message to the terminal to provide audio and visual notifications. The input is the warning message, and the output is the message converted into a notificationable format. 【0349】 Step 6: 【0350】 The terminal notifies the driver of a warning. It conveys the warning message to the driver using an audio output device or a display. The input is a warning message in a notifiable format, and the output is warning information that the driver can see or hear. 【0351】 Step 7: 【0352】 The user receives a warning and chooses a response. If there are signs of drowsiness or distraction, they are prompted to take appropriate action. The input is the warning message received, and the output is the driver's action. 【0353】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0354】 The system of this invention monitors the driver's condition and, in particular, incorporates an emotion engine to recognize the driver's emotional state in real time, thereby providing a higher level of safety. This system exchanges information with each other through terminals, servers, and users, enabling rapid response. 【0355】 Terminal operation 【0356】 The terminal is placed in the driver's seat and captures the driver's face via a camera, acquiring facial expressions along with biometric information. The terminal processes this data with an emotion engine to identify the driver's emotional state, thereby sending more detailed warnings and notifications to the server. 【0357】 Server operation 【0358】 The server receives biometric and emotional data transmitted from the terminal. The emotion engine analyzes this data and evaluates the driver's health and emotional state. Depending on the individual's emotional state, for example, if stress levels are high, it generates a stronger warning than usual to draw attention. It also creates notifications recommending interrupting driving or taking a break based on this emotional data. 【0359】 User actions 【0360】 Users receive audio and visual warnings from their devices and adjust their driving accordingly. If they receive a warning related to their emotional state, they can control their emotions and take measures such as taking a longer break if necessary. 【0361】 Specific example 【0362】 For example, if the emotional engine detects that the driver's stress level is high while driving, the server instantly analyzes this information and sends a message to the device saying, "Warning: Your stress level is high. We recommend taking a deep breath and a break." This notification is displayed to the user in real time, allowing the driver to pay attention to their emotions and drive more safely. 【0363】 Thus, by utilizing an emotion engine and responding not only to the driver's biological state but also to their emotional state, this invention further improves safety in the transportation industry. 【0364】 The following describes the processing flow. 【0365】 Step 1: 【0366】 The device uses a camera to photograph the driver's face, capturing not only biometric information but also facial expression data. This data is processed in real time and prepared to be sent to a server at regular intervals. 【0367】 Step 2: 【0368】 The terminal transmits the acquired biometric information and facial expression data to the server. If the transmission is successful, it receives a confirmation signal. 【0369】 Step 3: 【0370】 Upon receiving the transmitted data, the server uses an emotion engine to analyze the driver's current emotional state. 【0371】 Step 4: 【0372】 Based on the analysis results, the server integrates and evaluates the driver's health and emotional state. In particular, if significant emotional changes (e.g., stress or anger) are detected, it calculates an abnormality score accordingly. 【0373】 Step 5: 【0374】 The server generates customized warnings based on the emotional state assessment results. For example, if stress levels are high, it will create a message such as, "You are feeling stressed. Take a short break." 【0375】 Step 6: 【0376】 The server will send the generated warning to the terminal and will also consider notifying the administrator of the abnormal condition so that they can identify the problem. 【0377】 Step 7: 【0378】 The terminal immediately notifies the user of any warnings sent by the server. Notification methods can include audio alerts and visual messages to ensure the user understands the warning. 【0379】 Step 8: 【0380】 The user checks notifications from their device and takes recommended actions (e.g., deep breathing, short breaks). They take necessary steps to support improvement of their emotional state and maintain safe driving. 【0381】 Step 9: 【0382】 When the server receives emotional feedback from the user, it reviews the data and recognizes that the emotional state has improved. It then resets the system state to prepare for the next analysis cycle. 【0383】 (Example 2) 【0384】 Next, we will describe Example 2. 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". 【0385】 In modern society, traffic accidents caused by driver fatigue and stress are a major social problem. Conventional systems can only provide warnings based on the driver's basic health status and cannot evaluate or notify based on emotional state, resulting in insufficient detection and appropriate countermeasures when a driver is in a potentially dangerous state. Therefore, there is a need for the development of a driver monitoring system capable of more advanced analysis. 【0386】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0387】 In this invention, the server includes means for acquiring the driver's biometric information and facial expression information using image capture means, means for analyzing the acquired biometric information and facial expression information to evaluate the driver's health and emotional state, and means for generating warnings and notifications based on the evaluation results and communicating them to the driver in real time. This enables more detailed monitoring based on the driver's emotional state and prompt countermeasures. 【0388】 "Image capture means" refers to a device installed to photograph the driver's face and facial expressions, and includes means such as cameras and sensors. 【0389】 "Biometric information" refers to data indicating the driver's physical condition, such as heart rate, skin temperature, and respiratory rate. 【0390】 "Facial expression information" refers to information obtained from the driver's facial expressions and includes basic data for analyzing their emotional state. 【0391】 "Emotional state" refers to the driver's psychological state and includes emotions such as joy, anger, sadness, surprise, and fear. 【0392】 "Analysis means" refers to a device or software that uses acquired biometric information and facial expression information to evaluate the driver's health and emotional state. 【0393】 "Warnings and notifications" are messages generated based on analysis results to support safe driving by the driver, and are displayed either audibly or visually. 【0394】 "Real-time" refers to providing processing results immediately without delay, enabling drivers to take immediate action. 【0395】 This invention is a system that promotes safe driving by analyzing the driver's emotional state and health condition in real time. The embodiments thereof are described below. 【0396】 Device Overview 【0397】 The terminal is installed in the driver's seat and primarily consists of a camera and biometric sensors. The camera captures the driver's face and acquires facial expression information. The biometric sensors collect data such as heart rate and skin temperature. This biometric and facial information is processed by software called an emotion engine within the terminal. The emotion engine primarily uses a generative AI model based on deep learning technology to analyze the driver's emotional state. The analysis results are sent to a server as data packets. 【0398】 Server Overview 【0399】 The server is responsible for receiving data packets sent from the terminal and performing detailed analysis. Using a high-performance processor, the server can process the received data quickly in real time. The emotion engine on the server comprehensively evaluates the driver's emotional and physical state. For example, if a high stress level is detected, the server generates a specific notification such as, "We recommend you take a break." This notification is sent to the terminal in audio or visual format and communicated to the user (driver). 【0400】 User Overview 【0401】 Users can receive notifications from their devices and adjust their driving accordingly. For example, a user who receives a notification that their stress levels are rising can choose to take deep breaths or take a break. By following specific advice based on their emotional state, they can drive safely and comfortably. 【0402】 Examples of specific cases and prompt statements 【0403】 For example, if the emotional engine detects that the driver's stress level is high while driving, the server generates a message based on the analysis results, stating, "Warning: Your stress level is high. We recommend taking a deep breath and a break," and sends it to the device. This notification allows the user to respond immediately and maintain safe driving. 【0404】 An example of a prompt would be, "Write a program that acquires the driver's facial expression data and analyzes their stress level. Also, add logic to generate a warning message based on the results." Based on this prompt, the generating AI model constructs the specific operational logic for the emotion engine. 【0405】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0406】 Step 1: 【0407】 The terminal captures the driver's face with a camera and collects facial expression information. It receives image data from the camera as input and generates image information to be processed as output. In this process, preprocessing is performed to reduce noise and adjust the resolution of the image to be used. 【0408】 Step 2: 【0409】 The terminal uses biometric sensors to acquire biometric information such as the driver's heart rate and skin temperature. It receives data from the biometric sensors as input and generates biometric data as output. The acquired data undergoes a smoothing process to remove outliers. 【0410】 Step 3: 【0411】 The emotion engine installed in the terminal receives pre-processed facial and biometric information as input and analyzes the driver's emotional state. As output, it generates an index indicating the driver's emotional state. In this process, an algorithm is applied that uses a generative AI model to determine emotions from the driver's facial expressions. 【0412】 Step 4: 【0413】 The terminal sends the analysis results to the server as data packets. It receives indicators of emotional state as input and generates data packets for transmission to the server as output. These packets include details of the driver's stress level and emotions. 【0414】 Step 5: 【0415】 The server analyzes data packets received from the terminal. Using the received data packets as input, it generates warnings and notifications corresponding to the driver's emotional state as output. In this process, a detailed evaluation is conducted, taking into account the intensity and changes in emotions, to determine the necessary actions. 【0416】 Step 6: 【0417】 The server sends the generated warnings and notifications to the terminal. Using the analyzed evaluation results as input, it generates voice and visual notification messages for the user as output. Specifically, it provides recommendations to interrupt driving or suggest specific actions (e.g., deep breathing) as needed. 【0418】 Step 7: 【0419】 The user receives notifications from the device and adjusts their driving accordingly. The system receives notifications transmitted from the device as input and takes appropriate driving actions as output (e.g., taking a break, reassessing concentration). This enhances safety and allows for appropriate responses based on the driver's condition. 【0420】 (Application Example 2) 【0421】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal." 【0422】 In autonomous vehicles, a challenge is that changes in the health and emotional state of the driver or passengers can negatively impact vehicle operation. In particular, there is a need for means to respond quickly and appropriately when stress or fatigue is detected. Furthermore, a challenge is the ability to appropriately assess stress levels experienced by the driver monitoring the vehicle and automatically adjust the monitoring level accordingly. 【0423】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0424】 In this invention, the server includes means for acquiring facial expression information of the driver or passenger using an image capture device, means for acquiring biometric information of the driver or passenger using a biosensor, means for analyzing the acquired facial expression information and biometric information to evaluate the health and emotional state of the driver or passenger, means for generating and notifying warnings based on the evaluation results, and means for adjusting the driving monitoring level according to the emotional state. This makes it possible to improve the safety and efficiency of the autonomous vehicle through real-time feedback according to the emotional state of the driver or passenger. 【0425】 A "driver" is an individual whose role is to monitor the operation of automobiles and autonomous vehicles and to ensure their safe operation. 【0426】 A "passenger" is an individual who rides in a car or self-driving vehicle and enjoys the safety and comfort of that vehicle while traveling. 【0427】 An "image acquisition device" is a device that uses a camera or similar device to acquire images or videos of a target in real time. 【0428】 "Facial expression information" refers to data obtained from the facial features and movements of a subject acquired by an image capture device, which is used to indicate emotional states. 【0429】 A "biosensor" is a sensor used to acquire physiological data such as heart rate and body temperature. 【0430】 "Biometric information" refers to physiological data that indicates an individual's health status, obtained through biosensors. 【0431】 "Emotional state" refers to the psychological state of the driver or passenger, and includes stress, joy, anger, etc. 【0432】 "Evaluation" is the process of analyzing acquired data to determine the health and emotional state of the driver or passenger. 【0433】 A "warning" is a notice intended to draw the attention of the driver or passengers in order to ensure the safety of the vehicle. 【0434】 "Adjusting the driving monitoring level" means changing the monitoring mode of the autonomous driving system according to the emotional state of the driver or monitor. 【0435】 This invention is a system for enhancing safety in autonomous vehicles by monitoring the emotions and health status of the driver or passengers in real time. Specific embodiments are described below. 【0436】 Server operation 【0437】 The server receives data from image capture devices and biosensors. Image capture devices acquire facial expression information of the driver or passenger, and biosensors acquire biometric information such as heart rate and body temperature. The server uses facial recognition AI and emotion analysis engine to analyze this data and evaluate the emotional state and health status. Based on the evaluation results, it generates warnings and notifies the terminal. If necessary, it also provides instructions to adjust the driving monitoring level. 【0438】 Terminal operation 【0439】 The terminal is installed inside the autonomous vehicle and displays warnings and notifications sent from the server. Specifically, it alerts the driver or passengers through voice and display. In addition, if the emotional state is unstable, it continues to collect data from image capture devices and biosensors and provides feedback to the server. 【0440】 User actions 【0441】 The user (driver or passenger) receives notifications from the device and manages their emotional and physical state appropriately. For example, if stress levels are assessed as high, the device will provide advice such as, "Take deep breaths to reduce stress, and take a 5-minute break if necessary." 【0442】 Specific example 【0443】 For example, if the supervisor of an autonomous vehicle is determined to be in a high-stress state, the system instructs the vehicle to temporarily increase its monitoring mode and sends a notification prompting the supervisor to take a deep breath. In this way, the overall safety of the autonomous vehicle is improved. 【0444】 Example of a prompt 【0445】 "I want to develop an emotion monitoring system to be installed in autonomous vehicles. Please create a program that analyzes the emotional state of the observer based on their facial expressions and biometric information, and provides recommendations to reduce stress as needed." 【0446】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0447】 Step 1: 【0448】 The terminal uses an image capture device to acquire facial information of the driver or passenger in real time. The input is image data captured by the camera. The output is facial expression data analyzed by facial recognition AI. Specifically, this data identifies the feature points of each face and quantifies changes in facial expression. 【0449】 Step 2: 【0450】 The server receives biometric information such as heart rate and body temperature from biosensors of the driver or passenger. The input is physiological data from the biosensors. The output is evaluation data that expresses this data as a health status index. Specifically, it calculates the stress level when the heart rate exceeds a certain threshold. 【0451】 Step 3: 【0452】 The server integrates the facial expression data obtained in Step 1 and the physiological data obtained in Step 2, and uses an emotion analysis engine to evaluate the emotional state of the driver or passenger. The inputs are facial expression data and physiological data. The output is an identification result indicating the emotional state. Specifically, the emotional state is classified into categories such as "stress," "relief," and "joy." 【0453】 Step 4: 【0454】 The server generates a warning or notification message based on the emotion assessment results and sends it to the terminal. The input is the evaluation result of the emotion analysis engine. The output is a warning message recommending a specific action. For example, if stress levels are high, it generates a message such as "We recommend you take a break." 【0455】 Step 5: 【0456】 The terminal notifies the user of warning messages received from the server via audio or display. The input is the warning message from the server. The output is an audio or visual prompt to encourage user action. Specifically, this involves displaying the message on the screen and playing an audio alert. 【0457】 Step 6: 【0458】 The user checks notifications from their device and takes appropriate action based on their emotional and health state. The input is a warning message from the device. The output is a change in the user's behavior or improvement in their state. For example, they might take deep breaths to reduce stress or pause the device. 【0459】 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0460】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0461】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214. 【0462】 [Third Embodiment] 【0463】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0464】 As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server. 【0465】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0466】 The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52. 【0467】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0468】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0469】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0470】 Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0471】 The specific processing program 56 is an example of a "program" relating to the technology of this 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. 【0472】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0473】 In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0474】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal". 【0475】 The system of the present invention operates on the terminal, server, and user sides to monitor the driver's condition in real time and prevent drowsy driving and inattentive driving. 【0476】 Terminal operation 【0477】 The terminal is a device installed in the driver's seat, such as a smartphone or a dedicated camera. The terminal captures the driver's face with a high-precision camera and captures biometric information. The terminal has the function of periodically sending this data to a server and also plays a role in notifying the user of warning messages received from the server. 【0478】 Server operation 【0479】 The server receives biometric information transmitted from the terminal. The received data is analyzed by an AI model to evaluate the driver's health status and attention level. Based on the analysis results, the server generates necessary warning messages and sends them to the terminal. If the driver's condition is determined to be abnormal, the server also notifies the administrator to prompt a quick response. 【0480】 User actions 【0481】 Users should check warning messages received from their devices and interrupt driving as needed. In particular, if signs of drowsiness are detected, users are advised to take a break in a safe place. Furthermore, abnormal notifications are sent to administrators, allowing them to receive more appropriate instructions and support. 【0482】 Specific example 【0483】 For example, if the device's camera monitors the driver's eye blinking frequency, and the driver blinks infrequently for an extended period, the server will determine that the driver is at risk of falling asleep at the wheel. The server will immediately send a warning to the device stating, "Warning: You may be drowsy. Please take a break." This warning is communicated to the user via voice and on-screen display, allowing them to take prompt action. 【0484】 Thus, the system of the present invention is implemented to continuously evaluate the driver's condition and improve safety. 【0485】 The following describes the processing flow. 【0486】 Step 1: 【0487】 The device activates its camera and takes a picture of the driver's face. The acquired video data is processed in real time to extract biometric information such as eye movements and facial orientation. 【0488】 Step 2: 【0489】 The terminal transmits the extracted biometric information to the server at regular intervals. When transmitting data, it waits for a simple response from the server to confirm the success of the transmission. 【0490】 Step 3: 【0491】 The server receives biometric information transmitted from the terminal. The received data is passed to an AI analysis module to evaluate the driver's health and attention level. 【0492】 Step 4: 【0493】 The server uses an AI model to calculate an anomaly score based on biometric information. If the score exceeds a pre-set threshold, it is determined that the user may be experiencing drowsiness or extreme fatigue. 【0494】 Step 5: 【0495】 If an anomaly is detected, the server will generate a warning message. The warning will include specific action instructions, such as a prompt to stop driving or take a break. 【0496】 Step 6: 【0497】 The server sends the generated warning message to the terminal. It also prepares to send an anomaly notification to the administrator if necessary. 【0498】 Step 7: 【0499】 The terminal receives a warning message from the server and immediately notifies the user. Notification methods can include audio alerts or screen displays. 【0500】 Step 8: 【0501】 Users can check notifications, stop driving as advised, and take a safe break. They can also provide feedback on their status to the server as needed. 【0502】 Step 9: 【0503】 The server receives feedback from the user and confirms that the condition has improved. After the anomaly is resolved, the system state is reset and prepared for the next operating cycle. 【0504】 (Example 1) 【0505】 Next, we will describe Example 1. 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." 【0506】 To prevent traffic accidents caused by drowsy or inattentive driving, it is necessary to monitor the driver's condition in real time and provide appropriate warnings and countermeasures quickly. However, conventional technology has had difficulty effectively detecting these conditions, limiting its ability to provide accurate alerts to drivers. 【0507】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0508】 In this invention, the server includes means for acquiring the driver's biometric information using an image capture device, means including an artificial intelligence model that analyzes the acquired biometric information to evaluate the driver's attention span, and means for generating a warning based on the evaluation result and notifying a terminal. This enables real-time monitoring of the driver's condition and rapid warning notification. 【0509】 The term "driver" refers to the person who operates a vehicle while it is in motion. 【0510】 "Condition monitoring" refers to the act of observing the driver's physical and psychological state in real time. 【0511】 An "image acquisition device" refers to a device that acquires the driver's posture and facial movements as image data. 【0512】 "Biometric information" refers to information that shows physical or physiological data about the driver. 【0513】 An "artificial intelligence model" refers to a program that uses machine learning or deep learning techniques to analyze the driver's condition. 【0514】 "Attention assessment" refers to the process of measuring and judging a driver's level of concentration and alertness. 【0515】 Generating a "warning" refers to the act of creating necessary alerts and cautionary messages for the driver. 【0516】 "Notifying the device" refers to the process of forwarding the generated warning message to the device operated by the user. 【0517】 A "user" refers to someone who receives warnings and notifications from the system. 【0518】 This invention is a system for supporting safe driving by drivers, and operates in the roles of terminal, server, and user. 【0519】 The terminal uses image capture devices such as smartphones or dedicated camera devices installed in the driver's seat. The terminal's high-precision camera captures the driver's facial expressions and movements in real time, acquiring biometric information. This data is periodically transmitted to a server via a communication network (e.g., 4G / 5G or Wi-Fi). 【0520】 The server analyzes the driver's state using a generative AI model based on biometric information received from the terminal. This artificial intelligence model evaluates the driver's attention level based on factors such as blinking and eye movements. Based on the evaluation results, the server generates a warning message and sends it to the terminal. 【0521】 The terminal notifies the user of warning messages sent from the server. Notifications are made via audio or on-screen display, prompting the user to provide necessary information and warnings. 【0522】 For example, if the terminal's camera monitors the driver's blinking frequency while driving and detects an extremely low blinking rate, the server will interpret this as a sign of drowsiness and generate a warning message such as, "Caution: You may be drowsy. Please take a break." This warning is presented to the user via voice or on the display of the terminal, allowing the user to take prompt action. 【0523】 This system aims to prevent dangerous driving by continuously evaluating the driver's psychological and physiological state. 【0524】 An example of a prompt message is, "Use an AI model to analyze the driver's blinking frequency data and detect signs of drowsiness." 【0525】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0526】 Step 1: 【0527】 The device uses a high-precision camera to capture the driver's face. The input is real-time video of the driver's face. Based on this video data, it extracts facial feature points and calculates biometric information (e.g., blink frequency, gaze direction). Specifically, it uses image processing software within the device to automatically identify feature points and record them as numerical data. 【0528】 Step 2: 【0529】 The terminal transmits the acquired biometric information to the server via the network. The input is the numerical data of the biometric information generated in step 1. This data is compressed periodically (for example, every second) and transmitted to the server with low latency. Specifically, the terminal configures the communication protocol, generates data packets, and transmits them. 【0530】 Step 3: 【0531】 The server analyzes biometric information received from the terminal. The input is a dataset of transmitted biometric data. A generative AI model is used to evaluate the driver's attention using this data. In this process, the AI ​​model learns the driver's behavioral patterns and detects signs of drowsiness or inattention. Specifically, the AI ​​software takes in the data, applies the model, and outputs an evaluation score. 【0532】 Step 4: 【0533】 The server generates a warning message based on the analysis results. The input is the analysis score obtained in step 3. Based on this, it sets the warning level for the driver and creates an appropriate message. Specifically, it selects the wording of the warning message and formats it as a digital message. 【0534】 Step 5: 【0535】 The server sends the generated warning message to the terminal. The input is the generated warning message. The server packets the message and sends it quickly to the terminal via the communication network. Specifically, it sets the destination address and sends the message according to the communication protocol. 【0536】 Step 6: 【0537】 The device notifies the user of warning messages received from the server. The input is the warning message sent from the server. The device immediately alerts the user with audio alerts or screen displays according to the notification priority. Specifically, it controls the device's speaker and display to present the message in a way that is easy for the user to understand. 【0538】 (Application Example 1) 【0539】 Next, we will explain Application Example 1. In the following explanation, 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." 【0540】 In autonomous vehicles, preventing accidents caused by driver inattention or drowsiness is crucial. However, conventional technology struggles to accurately monitor the driver's condition in real time and provide timely warnings. Furthermore, there are insufficient means to prompt drivers to immediately recognize warnings and take appropriate action. 【0541】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0542】 In this invention, the server includes means for acquiring the driver's biometric information using an image capture device, means for analyzing the acquired biometric information to evaluate the driver's health condition and attention level, and means for providing real-time warnings audibly and visually. This enables rapid and accurate monitoring of the driver's condition, immediate warnings as needed, and allows the driver to take prompt and appropriate action. 【0543】 "Driver's condition" refers to all factors that affect vehicle operation, including the driver's health and attention level. 【0544】 An "image acquisition device" is a device that uses a camera or similar device to acquire the driver's biometric information. 【0545】 "Biometric information" refers to data obtained from the driver's body, such as facial images, eye movements, blinking frequency, and posture. 【0546】 "Health status" refers to the condition of the driver's physical and mental health. 【0547】 "Attention" is the driver's ability to concentrate on and maintain focus on driving operations. 【0548】 "Evaluation" is the process of analyzing acquired biometric information to determine health status and attention span. 【0549】 "Real-time" refers to a state where data acquisition and processing occur almost instantly, with virtually no delay. 【0550】 A "warning" is a notification that informs the driver that there is an imminent danger. 【0551】 "Voice notification" is a method of communicating warnings and instructions to the driver through a speaker using sound. 【0552】 "Visual notification" refers to a method of visually presenting warnings and information to the driver through displays or other means. 【0553】 A system for implementing this invention includes a terminal installed in an autonomous vehicle, a remote server, and a driver. The terminal acquires the driver's biometric information using a smartphone or dedicated video camera inside the autonomous vehicle. The image acquisition device used here includes, for example, a high-performance camera. 【0554】 The device has the function of transmitting acquired biometric information to the server in real time. The server uses an AI model to analyze the received biometric information and evaluate the driver's health status and attention level. The AI ​​model is built using Python and TensorFlow and analyzes the driver's eye movements and facial expressions. Based on the analysis results, the server generates audio and visual warnings and notifies the driver through the device. 【0555】 For example, if the driver's eyes are not opening and closing frequently and their gaze is fixed, the system may determine that they are drowsy and automatically generate a warning message, "Caution: You may be drowsy. Please take a break at a nearby rest stop," which will be displayed on the vehicle's screen. This information will also be communicated to the driver via the in-vehicle audio system. 【0556】 Furthermore, if the driver ignores a warning or fails to respond immediately, the server will consider this an abnormal condition and notify the administrator. The notification function will utilize the in-vehicle network and internet communication. An example of a prompt message is: "Create an AI model that can detect signs of drowsy driving by analyzing the frequency of eye opening and closing and pupil movement while driving." 【0557】 Thus, the present invention provides a system that improves driver safety and helps prevent accidents. 【0558】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0559】 Step 1: 【0560】 The device acquires the driver's biometric information. Using a camera, it captures the driver's face, eye movements, and blinking frequency as video. The input is real-time video data, and the output is digital biometric data. 【0561】 Step 2: 【0562】 The device transmits the acquired biometric information to the server. Real-time performance is maintained by sending the data to a remote server via the internet. The input is digitized biometric information, and the output is data ready for processing on the server side. 【0563】 Step 3: 【0564】 The server analyzes biometric information. It uses an AI model to evaluate the driver's health and attention span. Specifically, it uses TensorFlow to analyze facial expressions and eye movements to detect signs of drowsiness or distraction. The input is biometric information sent to the server, and the output is the analyzed evaluation data. 【0565】 Step 4: 【0566】 The server generates warning messages based on the analysis results. If the evaluation data indicates any signs of impediment to safe driving, it automatically creates the necessary warning messages. The input is the evaluation results, and the output is the digital data of the warning messages. 【0567】 Step 5: 【0568】 The server sends the generated warning message to the terminal. It delivers the message to the terminal to provide audio and visual notifications. The input is the warning message, and the output is the message converted into a notificationable format. 【0569】 Step 6: 【0570】 The terminal notifies the driver of a warning. It conveys the warning message to the driver using an audio output device or a display. The input is a warning message in a notifiable format, and the output is warning information that the driver can see or hear. 【0571】 Step 7: 【0572】 The user receives a warning and chooses a response. If there are signs of drowsiness or distraction, they are prompted to take appropriate action. The input is the warning message received, and the output is the driver's action. 【0573】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0574】 The system of this invention monitors the driver's condition and, in particular, incorporates an emotion engine to recognize the driver's emotional state in real time, thereby providing a higher level of safety. This system exchanges information with each other through terminals, servers, and users, enabling rapid response. 【0575】 Terminal operation 【0576】 The terminal is placed in the driver's seat and captures the driver's face via a camera, acquiring facial expressions along with biometric information. The terminal processes this data with an emotion engine to identify the driver's emotional state, thereby sending more detailed warnings and notifications to the server. 【0577】 Server operation 【0578】 The server receives biometric and emotional data transmitted from the terminal. The emotion engine analyzes this data and evaluates the driver's health and emotional state. Depending on the individual's emotional state, for example, if stress levels are high, it generates a stronger warning than usual to draw attention. It also creates notifications recommending interrupting driving or taking a break based on this emotional data. 【0579】 User actions 【0580】 Users receive audio and visual warnings from their devices and adjust their driving accordingly. If they receive a warning related to their emotional state, they can control their emotions and take measures such as taking a longer break if necessary. 【0581】 Specific example 【0582】 For example, if the emotional engine detects that the driver's stress level is high while driving, the server instantly analyzes this information and sends a message to the device saying, "Warning: Your stress level is high. We recommend taking a deep breath and a break." This notification is displayed to the user in real time, allowing the driver to pay attention to their emotions and drive more safely. 【0583】 Thus, by utilizing an emotion engine and responding not only to the driver's biological state but also to their emotional state, this invention further improves safety in the transportation industry. 【0584】 The following describes the processing flow. 【0585】 Step 1: 【0586】 The device uses a camera to photograph the driver's face, capturing not only biometric information but also facial expression data. This data is processed in real time and prepared to be sent to a server at regular intervals. 【0587】 Step 2: 【0588】 The terminal transmits the acquired biometric information and facial expression data to the server. If the transmission is successful, it receives a confirmation signal. 【0589】 Step 3: 【0590】 Upon receiving the transmitted data, the server uses an emotion engine to analyze the driver's current emotional state. 【0591】 Step 4: 【0592】 Based on the analysis results, the server integrates and evaluates the driver's health and emotional state. In particular, if significant emotional changes (e.g., stress or anger) are detected, it calculates an abnormality score accordingly. 【0593】 Step 5: 【0594】 The server generates customized warnings based on the emotional state assessment results. For example, if stress levels are high, it will create a message such as, "You are feeling stressed. Take a short break." 【0595】 Step 6: 【0596】 The server will send the generated warning to the terminal and will also consider notifying the administrator of the abnormal condition so that they can identify the problem. 【0597】 Step 7: 【0598】 The terminal immediately notifies the user of any warnings sent by the server. Notification methods can include audio alerts and visual messages to ensure the user understands the warning. 【0599】 Step 8: 【0600】 The user checks notifications from their device and takes recommended actions (e.g., deep breathing, short breaks). They take necessary steps to support improvement of their emotional state and maintain safe driving. 【0601】 Step 9: 【0602】 When the server receives emotional feedback from the user, it reviews the data and recognizes that the emotional state has improved. It then resets the system state to prepare for the next analysis cycle. 【0603】 (Example 2) 【0604】 Next, we will describe Example 2. 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." 【0605】 In modern society, traffic accidents caused by driver fatigue and stress are a major social problem. Conventional systems can only provide warnings based on the driver's basic health status and cannot evaluate or notify based on emotional state, resulting in insufficient detection and appropriate countermeasures when a driver is in a potentially dangerous state. Therefore, there is a need for the development of a driver monitoring system capable of more advanced analysis. 【0606】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0607】 In this invention, the server includes means for acquiring the driver's biometric information and facial expression information using image capture means, means for analyzing the acquired biometric information and facial expression information to evaluate the driver's health and emotional state, and means for generating warnings and notifications based on the evaluation results and communicating them to the driver in real time. This enables more detailed monitoring based on the driver's emotional state and prompt countermeasures. 【0608】 "Image capture means" refers to a device installed to photograph the driver's face and facial expressions, and includes means such as cameras and sensors. 【0609】 "Biometric information" refers to data indicating the driver's physical condition, such as heart rate, skin temperature, and respiratory rate. 【0610】 "Facial expression information" refers to information obtained from the driver's facial expressions and includes basic data for analyzing their emotional state. 【0611】 "Emotional state" refers to the driver's psychological state and includes emotions such as joy, anger, sadness, surprise, and fear. 【0612】 "Analysis means" refers to a device or software that uses acquired biometric information and facial expression information to evaluate the driver's health and emotional state. 【0613】 "Warnings and notifications" are messages generated based on analysis results to support safe driving by the driver, and are displayed either audibly or visually. 【0614】 "Real-time" refers to providing processing results immediately without delay, enabling drivers to take immediate action. 【0615】 This invention is a system that promotes safe driving by analyzing the driver's emotional state and health condition in real time. The embodiments thereof are described below. 【0616】 Device Overview 【0617】 The terminal is installed in the driver's seat and primarily consists of a camera and biometric sensors. The camera captures the driver's face and acquires facial expression information. The biometric sensors collect data such as heart rate and skin temperature. This biometric and facial information is processed by software called an emotion engine within the terminal. The emotion engine primarily uses a generative AI model based on deep learning technology to analyze the driver's emotional state. The analysis results are sent to a server as data packets. 【0618】 Server Overview 【0619】 The server is responsible for receiving data packets sent from the terminal and performing detailed analysis. Using a high-performance processor, the server can process the received data quickly in real time. The emotion engine on the server comprehensively evaluates the driver's emotional and physical state. For example, if a high stress level is detected, the server generates a specific notification such as, "We recommend you take a break." This notification is sent to the terminal in audio or visual format and communicated to the user (driver). 【0620】 User Overview 【0621】 Users can receive notifications from their devices and adjust their driving accordingly. For example, a user who receives a notification that their stress levels are rising can choose to take deep breaths or take a break. By following specific advice based on their emotional state, they can drive safely and comfortably. 【0622】 Examples of specific cases and prompt statements 【0623】 For example, if the emotional engine detects that the driver's stress level is high while driving, the server generates a message based on the analysis results, stating, "Warning: Your stress level is high. We recommend taking a deep breath and a break," and sends it to the device. This notification allows the user to respond immediately and maintain safe driving. 【0624】 An example of a prompt would be, "Write a program that acquires the driver's facial expression data and analyzes their stress level. Also, add logic to generate a warning message based on the results." Based on this prompt, the generating AI model constructs the specific operational logic for the emotion engine. 【0625】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0626】 Step 1: 【0627】 The terminal captures the driver's face with a camera and collects facial expression information. It receives image data from the camera as input and generates image information to be processed as output. In this process, preprocessing is performed to reduce noise and adjust the resolution of the image to be used. 【0628】 Step 2: 【0629】 The terminal uses biometric sensors to acquire biometric information such as the driver's heart rate and skin temperature. It receives data from the biometric sensors as input and generates biometric data as output. The acquired data undergoes a smoothing process to remove outliers. 【0630】 Step 3: 【0631】 The emotion engine installed in the terminal receives pre-processed facial and biometric information as input and analyzes the driver's emotional state. As output, it generates an index indicating the driver's emotional state. In this process, an algorithm is applied that uses a generative AI model to determine emotions from the driver's facial expressions. 【0632】 Step 4: 【0633】 The terminal sends the analysis results to the server as data packets. It receives indicators of emotional state as input and generates data packets for transmission to the server as output. These packets include details of the driver's stress level and emotions. 【0634】 Step 5: 【0635】 The server analyzes data packets received from the terminal. Using the received data packets as input, it generates warnings and notifications corresponding to the driver's emotional state as output. In this process, a detailed evaluation is conducted, taking into account the intensity and changes in emotions, to determine the necessary actions. 【0636】 Step 6: 【0637】 The server sends the generated warnings and notifications to the terminal. Using the analyzed evaluation results as input, it generates voice and visual notification messages for the user as output. Specifically, it provides recommendations to interrupt driving or suggest specific actions (e.g., deep breathing) as needed. 【0638】 Step 7: 【0639】 The user receives notifications from the device and adjusts their driving accordingly. The system receives notifications transmitted from the device as input and takes appropriate driving actions as output (e.g., taking a break, reassessing concentration). This enhances safety and allows for appropriate responses based on the driver's condition. 【0640】 (Application Example 2) 【0641】 Next, we will explain Application Example 2. In the following explanation, 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." 【0642】 In autonomous vehicles, a challenge is that changes in the health and emotional state of the driver or passengers can negatively impact vehicle operation. In particular, there is a need for means to respond quickly and appropriately when stress or fatigue is detected. Furthermore, a challenge is the ability to appropriately assess stress levels experienced by the driver monitoring the vehicle and automatically adjust the monitoring level accordingly. 【0643】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0644】 In this invention, the server includes means for acquiring facial expression information of the driver or passenger using an image capture device, means for acquiring biometric information of the driver or passenger using a biosensor, means for analyzing the acquired facial expression information and biometric information to evaluate the health and emotional state of the driver or passenger, means for generating and notifying warnings based on the evaluation results, and means for adjusting the driving monitoring level according to the emotional state. This makes it possible to improve the safety and efficiency of the autonomous vehicle through real-time feedback according to the emotional state of the driver or passenger. 【0645】 A "driver" is an individual whose role is to monitor the operation of automobiles and autonomous vehicles and to ensure their safe operation. 【0646】 A "passenger" is an individual who rides in a car or self-driving vehicle and enjoys the safety and comfort of that vehicle while traveling. 【0647】 An "image acquisition device" is a device that uses a camera or similar device to acquire images or videos of a target in real time. 【0648】 "Facial expression information" refers to data obtained from the facial features and movements of a subject acquired by an image capture device, which is used to indicate emotional states. 【0649】 A "biosensor" is a sensor used to acquire physiological data such as heart rate and body temperature. 【0650】 "Biometric information" refers to physiological data that indicates an individual's health status, obtained through biosensors. 【0651】 "Emotional state" refers to the psychological state of the driver or passenger, and includes stress, joy, anger, etc. 【0652】 "Evaluation" is the process of analyzing acquired data to determine the health and emotional state of the driver or passenger. 【0653】 A "warning" is a notice intended to draw the attention of the driver or passengers in order to ensure the safety of the vehicle. 【0654】 "Adjusting the driving monitoring level" means changing the monitoring mode of the autonomous driving system according to the emotional state of the driver or monitor. 【0655】 This invention is a system for enhancing safety in autonomous vehicles by monitoring the emotions and health status of the driver or passengers in real time. Specific embodiments are described below. 【0656】 Server operation 【0657】 The server receives data from image capture devices and biosensors. Image capture devices acquire facial expression information of the driver or passenger, and biosensors acquire biometric information such as heart rate and body temperature. The server uses facial recognition AI and emotion analysis engine to analyze this data and evaluate the emotional state and health status. Based on the evaluation results, it generates warnings and notifies the terminal. If necessary, it also provides instructions to adjust the driving monitoring level. 【0658】 Terminal operation 【0659】 The terminal is installed inside the autonomous vehicle and displays warnings and notifications sent from the server. Specifically, it alerts the driver or passengers through voice and display. In addition, if the emotional state is unstable, it continues to collect data from image capture devices and biosensors and provides feedback to the server. 【0660】 User actions 【0661】 The user (driver or passenger) receives notifications from the device and manages their emotional and physical state appropriately. For example, if stress levels are assessed as high, the device will provide advice such as, "Take deep breaths to reduce stress, and take a 5-minute break if necessary." 【0662】 Specific example 【0663】 For example, if the supervisor of an autonomous vehicle is determined to be in a high-stress state, the system instructs the vehicle to temporarily increase its monitoring mode and sends a notification prompting the supervisor to take a deep breath. In this way, the overall safety of the autonomous vehicle is improved. 【0664】 Example of a prompt 【0665】 "I want to develop an emotion monitoring system to be installed in autonomous vehicles. Please create a program that analyzes the emotional state of the observer based on their facial expressions and biometric information, and provides recommendations to reduce stress as needed." 【0666】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0667】 Step 1: 【0668】 The terminal uses an image capture device to acquire facial information of the driver or passenger in real time. The input is image data captured by the camera. The output is facial expression data analyzed by facial recognition AI. Specifically, this data identifies the feature points of each face and quantifies changes in facial expression. 【0669】 Step 2: 【0670】 The server receives biometric information such as heart rate and body temperature from biosensors of the driver or passenger. The input is physiological data from the biosensors. The output is evaluation data that expresses this data as a health status index. Specifically, it calculates the stress level when the heart rate exceeds a certain threshold. 【0671】 Step 3: 【0672】 The server integrates the facial expression data obtained in Step 1 and the physiological data obtained in Step 2, and uses an emotion analysis engine to evaluate the emotional state of the driver or passenger. The inputs are facial expression data and physiological data. The output is an identification result indicating the emotional state. Specifically, the emotional state is classified into categories such as "stress," "relief," and "joy." 【0673】 Step 4: 【0674】 The server generates a warning or notification message based on the emotion assessment results and sends it to the terminal. The input is the evaluation result of the emotion analysis engine. The output is a warning message recommending a specific action. For example, if stress levels are high, it generates a message such as "We recommend you take a break." 【0675】 Step 5: 【0676】 The terminal notifies the user of warning messages received from the server via audio or display. The input is the warning message from the server. The output is an audio or visual prompt to encourage user action. Specifically, this involves displaying the message on the screen and playing an audio alert. 【0677】 Step 6: 【0678】 The user checks notifications from their device and takes appropriate action based on their emotional and health state. The input is a warning message from the device. The output is a change in the user's behavior or improvement in their state. For example, they might take deep breaths to reduce stress or pause the device. 【0679】 The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0680】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0681】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314. 【0682】 [Fourth Embodiment] 【0683】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0684】 As shown in Figure 7, the 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. 【0685】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0686】 The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52. 【0687】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0688】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0689】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0690】 The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes. 【0691】 Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0692】 The specific processing program 56 is an example of a "program" relating to the technology of this 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. 【0693】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0694】 In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0695】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0696】 The system of the present invention operates on the terminal, server, and user sides to monitor the driver's condition in real time and prevent drowsy driving and inattentive driving. 【0697】 Terminal operation 【0698】 The terminal is a device installed in the driver's seat, such as a smartphone or a dedicated camera. The terminal captures the driver's face with a high-precision camera and captures biometric information. The terminal has the function of periodically sending this data to a server and also plays a role in notifying the user of warning messages received from the server. 【0699】 Server operation 【0700】 The server receives biometric information transmitted from the terminal. The received data is analyzed by an AI model to evaluate the driver's health status and attention level. Based on the analysis results, the server generates necessary warning messages and sends them to the terminal. If the driver's condition is determined to be abnormal, the server also notifies the administrator to prompt a quick response. 【0701】 User actions 【0702】 Users should check warning messages received from their devices and interrupt driving as needed. In particular, if signs of drowsiness are detected, users are advised to take a break in a safe place. Furthermore, abnormal notifications are sent to administrators, allowing them to receive more appropriate instructions and support. 【0703】 Specific example 【0704】 For example, if the device's camera monitors the driver's eye blinking frequency, and the driver blinks infrequently for an extended period, the server will determine that the driver is at risk of falling asleep at the wheel. The server will immediately send a warning to the device stating, "Warning: You may be drowsy. Please take a break." This warning is communicated to the user via voice and on-screen display, allowing them to take prompt action. 【0705】 Thus, the system of the present invention is implemented to continuously evaluate the driver's condition and improve safety. 【0706】 The following describes the processing flow. 【0707】 Step 1: 【0708】 The device activates its camera and takes a picture of the driver's face. The acquired video data is processed in real time to extract biometric information such as eye movements and facial orientation. 【0709】 Step 2: 【0710】 The terminal transmits the extracted biometric information to the server at regular intervals. When transmitting data, it waits for a simple response from the server to confirm the success of the transmission. 【0711】 Step 3: 【0712】 The server receives biometric information transmitted from the terminal. The received data is passed to an AI analysis module to evaluate the driver's health and attention level. 【0713】 Step 4: 【0714】 The server uses an AI model to calculate an anomaly score based on biometric information. If the score exceeds a pre-set threshold, it is determined that the user may be experiencing drowsiness or extreme fatigue. 【0715】 Step 5: 【0716】 If an anomaly is detected, the server will generate a warning message. The warning will include specific action instructions, such as a prompt to stop driving or take a break. 【0717】 Step 6: 【0718】 The server sends the generated warning message to the terminal. It also prepares to send an anomaly notification to the administrator if necessary. 【0719】 Step 7: 【0720】 The terminal receives a warning message from the server and immediately notifies the user. Notification methods can include audio alerts or screen displays. 【0721】 Step 8: 【0722】 Users can check notifications, stop driving as advised, and take a safe break. They can also provide feedback on their status to the server as needed. 【0723】 Step 9: 【0724】 The server receives feedback from the user and confirms that the condition has improved. After the anomaly is resolved, the system state is reset and prepared for the next operating cycle. 【0725】 (Example 1) 【0726】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0727】 To prevent traffic accidents caused by drowsy or inattentive driving, it is necessary to monitor the driver's condition in real time and provide appropriate warnings and countermeasures quickly. However, conventional technology has had difficulty effectively detecting these conditions, limiting its ability to provide accurate alerts to drivers. 【0728】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0729】 In this invention, the server includes means for acquiring the driver's biometric information using an image capture device, means including an artificial intelligence model that analyzes the acquired biometric information to evaluate the driver's attention span, and means for generating a warning based on the evaluation result and notifying a terminal. This enables real-time monitoring of the driver's condition and rapid warning notification. 【0730】 The term "driver" refers to the person who operates a vehicle while it is in motion. 【0731】 "Condition monitoring" refers to the act of observing the driver's physical and psychological state in real time. 【0732】 An "image acquisition device" refers to a device that acquires the driver's posture and facial movements as image data. 【0733】 "Biometric information" refers to information that shows physical or physiological data about the driver. 【0734】 An "artificial intelligence model" refers to a program that uses machine learning or deep learning techniques to analyze the driver's condition. 【0735】 "Attention assessment" refers to the process of measuring and judging a driver's level of concentration and alertness. 【0736】 Generating a "warning" refers to the act of creating necessary alerts and cautionary messages for the driver. 【0737】 "Notifying the device" refers to the process of forwarding the generated warning message to the device operated by the user. 【0738】 A "user" refers to someone who receives warnings and notifications from the system. 【0739】 This invention is a system for supporting safe driving by drivers, and operates in the roles of terminal, server, and user. 【0740】 The terminal uses image capture devices such as smartphones or dedicated camera devices installed in the driver's seat. The terminal's high-precision camera captures the driver's facial expressions and movements in real time, acquiring biometric information. This data is periodically transmitted to a server via a communication network (e.g., 4G / 5G or Wi-Fi). 【0741】 The server analyzes the driver's state using a generative AI model based on biometric information received from the terminal. This artificial intelligence model evaluates the driver's attention level based on factors such as blinking and eye movements. Based on the evaluation results, the server generates a warning message and sends it to the terminal. 【0742】 The terminal notifies the user of warning messages sent from the server. Notifications are made via audio or on-screen display, prompting the user to provide necessary information and warnings. 【0743】 For example, if the terminal's camera monitors the driver's blinking frequency while driving and detects an extremely low blinking rate, the server will interpret this as a sign of drowsiness and generate a warning message such as, "Caution: You may be drowsy. Please take a break." This warning is presented to the user via voice or on the display of the terminal, allowing the user to take prompt action. 【0744】 This system aims to prevent dangerous driving by continuously evaluating the driver's psychological and physiological state. 【0745】 An example of a prompt message is, "Use an AI model to analyze the driver's blinking frequency data and detect signs of drowsiness." 【0746】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0747】 Step 1: 【0748】 The device uses a high-precision camera to capture the driver's face. The input is real-time video of the driver's face. Based on this video data, it extracts facial feature points and calculates biometric information (e.g., blink frequency, gaze direction). Specifically, it uses image processing software within the device to automatically identify feature points and record them as numerical data. 【0749】 Step 2: 【0750】 The terminal transmits the acquired biometric information to the server via the network. The input is the numerical data of the biometric information generated in step 1. This data is compressed periodically (for example, every second) and transmitted to the server with low latency. Specifically, the terminal configures the communication protocol, generates data packets, and transmits them. 【0751】 Step 3: 【0752】 The server analyzes biometric information received from the terminal. The input is a dataset of transmitted biometric data. A generative AI model is used to evaluate the driver's attention using this data. In this process, the AI ​​model learns the driver's behavioral patterns and detects signs of drowsiness or inattention. Specifically, the AI ​​software takes in the data, applies the model, and outputs an evaluation score. 【0753】 Step 4: 【0754】 The server generates a warning message based on the analysis results. The input is the analysis score obtained in step 3. Based on this, it sets the warning level for the driver and creates an appropriate message. Specifically, it selects the wording of the warning message and formats it as a digital message. 【0755】 Step 5: 【0756】 The server sends the generated warning message to the terminal. The input is the generated warning message. The server packets the message and sends it quickly to the terminal via the communication network. Specifically, it sets the destination address and sends the message according to the communication protocol. 【0757】 Step 6: 【0758】 The device notifies the user of warning messages received from the server. The input is the warning message sent from the server. The device immediately alerts the user with audio alerts or screen displays according to the notification priority. Specifically, it controls the device's speaker and display to present the message in a way that is easy for the user to understand. 【0759】 (Application Example 1) 【0760】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0761】 In autonomous vehicles, preventing accidents caused by driver inattention or drowsiness is crucial. However, conventional technology struggles to accurately monitor the driver's condition in real time and provide timely warnings. Furthermore, there are insufficient means to prompt drivers to immediately recognize warnings and take appropriate action. 【0762】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0763】 In this invention, the server includes means for acquiring the driver's biometric information using an image capture device, means for analyzing the acquired biometric information to evaluate the driver's health condition and attention level, and means for providing real-time warnings audibly and visually. This enables rapid and accurate monitoring of the driver's condition, immediate warnings as needed, and allows the driver to take prompt and appropriate action. 【0764】 "Driver's condition" refers to all factors that affect vehicle operation, including the driver's health and attention level. 【0765】 An "image acquisition device" is a device that uses a camera or similar device to acquire the driver's biometric information. 【0766】 "Biometric information" refers to data obtained from the driver's body, such as facial images, eye movements, blinking frequency, and posture. 【0767】 "Health status" refers to the condition of the driver's physical and mental health. 【0768】 "Attention" is the driver's ability to concentrate on and maintain focus on driving operations. 【0769】 "Evaluation" is the process of analyzing acquired biometric information to determine health status and attention span. 【0770】 "Real-time" refers to a state where data acquisition and processing occur almost instantly, with virtually no delay. 【0771】 A "warning" is a notification that informs the driver that there is an imminent danger. 【0772】 "Voice notification" is a method of communicating warnings and instructions to the driver through a speaker using sound. 【0773】 "Visual notification" refers to a method of visually presenting warnings and information to the driver through displays or other means. 【0774】 A system for implementing this invention includes a terminal installed in an autonomous vehicle, a remote server, and a driver. The terminal acquires the driver's biometric information using a smartphone or dedicated video camera inside the autonomous vehicle. The image acquisition device used here includes, for example, a high-performance camera. 【0775】 The device has the function of transmitting acquired biometric information to the server in real time. The server uses an AI model to analyze the received biometric information and evaluate the driver's health status and attention level. The AI ​​model is built using Python and TensorFlow and analyzes the driver's eye movements and facial expressions. Based on the analysis results, the server generates audio and visual warnings and notifies the driver through the device. 【0776】 For example, if the driver's eyes are not opening and closing frequently and their gaze is fixed, the system may determine that they are drowsy and automatically generate a warning message, "Caution: You may be drowsy. Please take a break at a nearby rest stop," which will be displayed on the vehicle's screen. This information will also be communicated to the driver via the in-vehicle audio system. 【0777】 Furthermore, if the driver ignores a warning or fails to respond immediately, the server will consider this an abnormal condition and notify the administrator. The notification function will utilize the in-vehicle network and internet communication. An example of a prompt message is: "Create an AI model that can detect signs of drowsy driving by analyzing the frequency of eye opening and closing and pupil movement while driving." 【0778】 Thus, the present invention provides a system that improves driver safety and helps prevent accidents. 【0779】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0780】 Step 1: 【0781】 The device acquires the driver's biometric information. Using a camera, it captures the driver's face, eye movements, and blinking frequency as video. The input is real-time video data, and the output is digital biometric data. 【0782】 Step 2: 【0783】 The device transmits the acquired biometric information to the server. Real-time performance is maintained by sending the data to a remote server via the internet. The input is digitized biometric information, and the output is data ready for processing on the server side. 【0784】 Step 3: 【0785】 The server analyzes biometric information. It uses an AI model to evaluate the driver's health and attention span. Specifically, it uses TensorFlow to analyze facial expressions and eye movements to detect signs of drowsiness or distraction. The input is biometric information sent to the server, and the output is the analyzed evaluation data. 【0786】 Step 4: 【0787】 The server generates warning messages based on the analysis results. If the evaluation data indicates any signs of impediment to safe driving, it automatically creates the necessary warning messages. The input is the evaluation results, and the output is the digital data of the warning messages. 【0788】 Step 5: 【0789】 The server sends the generated warning message to the terminal. It delivers the message to the terminal to provide audio and visual notifications. The input is the warning message, and the output is the message converted into a notificationable format. 【0790】 Step 6: 【0791】 The terminal notifies the driver of a warning. It conveys the warning message to the driver using an audio output device or a display. The input is a warning message in a notifiable format, and the output is warning information that the driver can see or hear. 【0792】 Step 7: 【0793】 The user receives a warning and chooses a response. If there are signs of drowsiness or distraction, they are prompted to take appropriate action. The input is the warning message received, and the output is the driver's action. 【0794】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0795】 The system of this invention monitors the driver's condition and, in particular, incorporates an emotion engine to recognize the driver's emotional state in real time, thereby providing a higher level of safety. This system exchanges information with each other through terminals, servers, and users, enabling rapid response. 【0796】 Terminal operation 【0797】 The terminal is placed in the driver's seat and captures the driver's face via a camera, acquiring facial expressions along with biometric information. The terminal processes this data with an emotion engine to identify the driver's emotional state, thereby sending more detailed warnings and notifications to the server. 【0798】 Server operation 【0799】 The server receives biometric and emotional data transmitted from the terminal. The emotion engine analyzes this data and evaluates the driver's health and emotional state. Depending on the individual's emotional state, for example, if stress levels are high, it generates a stronger warning than usual to draw attention. It also creates notifications recommending interrupting driving or taking a break based on this emotional data. 【0800】 User actions 【0801】 Users receive audio and visual warnings from their devices and adjust their driving accordingly. If they receive a warning related to their emotional state, they can control their emotions and take measures such as taking a longer break if necessary. 【0802】 Specific example 【0803】 For example, if the emotional engine detects that the driver's stress level is high while driving, the server instantly analyzes this information and sends a message to the device saying, "Warning: Your stress level is high. We recommend taking a deep breath and a break." This notification is displayed to the user in real time, allowing the driver to pay attention to their emotions and drive more safely. 【0804】 Thus, by utilizing an emotion engine and responding not only to the driver's biological state but also to their emotional state, this invention further improves safety in the transportation industry. 【0805】 The following describes the processing flow. 【0806】 Step 1: 【0807】 The device uses a camera to photograph the driver's face, capturing not only biometric information but also facial expression data. This data is processed in real time and prepared to be sent to a server at regular intervals. 【0808】 Step 2: 【0809】 The terminal transmits the acquired biometric information and facial expression data to the server. If the transmission is successful, it receives a confirmation signal. 【0810】 Step 3: 【0811】 Upon receiving the transmitted data, the server uses an emotion engine to analyze the driver's current emotional state. 【0812】 Step 4: 【0813】 Based on the analysis results, the server integrates and evaluates the driver's health and emotional state. In particular, if significant emotional changes (e.g., stress or anger) are detected, it calculates an abnormality score accordingly. 【0814】 Step 5: 【0815】 The server generates customized warnings based on the emotional state assessment results. For example, if stress levels are high, it will create a message such as, "You are feeling stressed. Take a short break." 【0816】 Step 6: 【0817】 The server will send the generated warning to the terminal and will also consider notifying the administrator of the abnormal condition so that they can identify the problem. 【0818】 Step 7: 【0819】 The terminal immediately notifies the user of any warnings sent by the server. Notification methods can include audio alerts and visual messages to ensure the user understands the warning. 【0820】 Step 8: 【0821】 The user checks notifications from their device and takes recommended actions (e.g., deep breathing, short breaks). They take necessary steps to support improvement of their emotional state and maintain safe driving. 【0822】 Step 9: 【0823】 When the server receives emotional feedback from the user, it reviews the data and recognizes that the emotional state has improved. It then resets the system state to prepare for the next analysis cycle. 【0824】 (Example 2) 【0825】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0826】 In modern society, traffic accidents caused by driver fatigue and stress are a major social problem. Conventional systems can only provide warnings based on the driver's basic health status and cannot evaluate or notify based on emotional state, resulting in insufficient detection and appropriate countermeasures when a driver is in a potentially dangerous state. Therefore, there is a need for the development of a driver monitoring system capable of more advanced analysis. 【0827】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0828】 In this invention, the server includes means for acquiring the driver's biometric information and facial expression information using image capture means, means for analyzing the acquired biometric information and facial expression information to evaluate the driver's health and emotional state, and means for generating warnings and notifications based on the evaluation results and communicating them to the driver in real time. This enables more detailed monitoring based on the driver's emotional state and prompt countermeasures. 【0829】 "Image capture means" refers to a device installed to photograph the driver's face and facial expressions, and includes means such as cameras and sensors. 【0830】 "Biometric information" refers to data indicating the driver's physical condition, such as heart rate, skin temperature, and respiratory rate. 【0831】 "Facial expression information" refers to information obtained from the driver's facial expressions and includes basic data for analyzing their emotional state. 【0832】 "Emotional state" refers to the driver's psychological state and includes emotions such as joy, anger, sadness, surprise, and fear. 【0833】 "Analysis means" refers to a device or software that uses acquired biometric information and facial expression information to evaluate the driver's health and emotional state. 【0834】 "Warnings and notifications" are messages generated based on analysis results to support safe driving by the driver, and are displayed either audibly or visually. 【0835】 "Real-time" refers to providing processing results immediately without delay, enabling drivers to take immediate action. 【0836】 This invention is a system that promotes safe driving by analyzing the driver's emotional state and health condition in real time. The embodiments thereof are described below. 【0837】 Device Overview 【0838】 The terminal is installed in the driver's seat and primarily consists of a camera and biometric sensors. The camera captures the driver's face and acquires facial expression information. The biometric sensors collect data such as heart rate and skin temperature. This biometric and facial information is processed by software called an emotion engine within the terminal. The emotion engine primarily uses a generative AI model based on deep learning technology to analyze the driver's emotional state. The analysis results are sent to a server as data packets. 【0839】 Server Overview 【0840】 The server is responsible for receiving data packets sent from the terminal and performing detailed analysis. Using a high-performance processor, the server can process the received data quickly in real time. The emotion engine on the server comprehensively evaluates the driver's emotional and physical state. For example, if a high stress level is detected, the server generates a specific notification such as, "We recommend you take a break." This notification is sent to the terminal in audio or visual format and communicated to the user (driver). 【0841】 User Overview 【0842】 Users can receive notifications from their devices and adjust their driving accordingly. For example, a user who receives a notification that their stress levels are rising can choose to take deep breaths or take a break. By following specific advice based on their emotional state, they can drive safely and comfortably. 【0843】 Examples of specific cases and prompt statements 【0844】 For example, if the emotional engine detects that the driver's stress level is high while driving, the server generates a message based on the analysis results, stating, "Warning: Your stress level is high. We recommend taking a deep breath and a break," and sends it to the device. This notification allows the user to respond immediately and maintain safe driving. 【0845】 An example of a prompt would be, "Write a program that acquires the driver's facial expression data and analyzes their stress level. Also, add logic to generate a warning message based on the results." Based on this prompt, the generating AI model constructs the specific operational logic for the emotion engine. 【0846】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0847】 Step 1: 【0848】 The terminal captures the driver's face with a camera and collects facial expression information. It receives image data from the camera as input and generates image information to be processed as output. In this process, preprocessing is performed to reduce noise and adjust the resolution of the image to be used. 【0849】 Step 2: 【0850】 The terminal uses biometric sensors to acquire biometric information such as the driver's heart rate and skin temperature. It receives data from the biometric sensors as input and generates biometric data as output. The acquired data undergoes a smoothing process to remove outliers. 【0851】 Step 3: 【0852】 The emotion engine installed in the terminal receives pre-processed facial and biometric information as input and analyzes the driver's emotional state. As output, it generates an index indicating the driver's emotional state. In this process, an algorithm is applied that uses a generative AI model to determine emotions from the driver's facial expressions. 【0853】 Step 4: 【0854】 The terminal sends the analysis results to the server as data packets. It receives indicators of emotional state as input and generates data packets for transmission to the server as output. These packets include details of the driver's stress level and emotions. 【0855】 Step 5: 【0856】 The server analyzes data packets received from the terminal. Using the received data packets as input, it generates warnings and notifications corresponding to the driver's emotional state as output. In this process, a detailed evaluation is conducted, taking into account the intensity and changes in emotions, to determine the necessary actions. 【0857】 Step 6: 【0858】 The server sends the generated warnings and notifications to the terminal. Using the analyzed evaluation results as input, it generates voice and visual notification messages for the user as output. Specifically, it provides recommendations to interrupt driving or suggest specific actions (e.g., deep breathing) as needed. 【0859】 Step 7: 【0860】 The user receives notifications from the device and adjusts their driving accordingly. The system receives notifications transmitted from the device as input and takes appropriate driving actions as output (e.g., taking a break, reassessing concentration). This enhances safety and allows for appropriate responses based on the driver's condition. 【0861】 (Application Example 2) 【0862】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0863】 In autonomous vehicles, a challenge is that changes in the health and emotional state of the driver or passengers can negatively impact vehicle operation. In particular, there is a need for means to respond quickly and appropriately when stress or fatigue is detected. Furthermore, a challenge is the ability to appropriately assess stress levels experienced by the driver monitoring the vehicle and automatically adjust the monitoring level accordingly. 【0864】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0865】 In this invention, the server includes means for acquiring facial expression information of the driver or passenger using an image capture device, means for acquiring biometric information of the driver or passenger using a biosensor, means for analyzing the acquired facial expression information and biometric information to evaluate the health and emotional state of the driver or passenger, means for generating and notifying warnings based on the evaluation results, and means for adjusting the driving monitoring level according to the emotional state. This makes it possible to improve the safety and efficiency of the autonomous vehicle through real-time feedback according to the emotional state of the driver or passenger. 【0866】 A "driver" is an individual whose role is to monitor the operation of automobiles and autonomous vehicles and to ensure their safe operation. 【0867】 A "passenger" is an individual who rides in a car or self-driving vehicle and enjoys the safety and comfort of that vehicle while traveling. 【0868】 An "image acquisition device" is a device that uses a camera or similar device to acquire images or videos of a target in real time. 【0869】 "Facial expression information" refers to data obtained from the facial features and movements of a subject acquired by an image capture device, which is used to indicate emotional states. 【0870】 A "biosensor" is a sensor used to acquire physiological data such as heart rate and body temperature. 【0871】 "Biometric information" refers to physiological data that indicates an individual's health status, obtained through biosensors. 【0872】 "Emotional state" refers to the psychological state of the driver or passenger, and includes stress, joy, anger, etc. 【0873】 "Evaluation" is the process of analyzing acquired data to determine the health and emotional state of the driver or passenger. 【0874】 A "warning" is a notice intended to draw the attention of the driver or passengers in order to ensure the safety of the vehicle. 【0875】 "Adjusting the driving monitoring level" means changing the monitoring mode of the autonomous driving system according to the emotional state of the driver or monitor. 【0876】 This invention is a system for enhancing safety in autonomous vehicles by monitoring the emotions and health status of the driver or passengers in real time. Specific embodiments are described below. 【0877】 Server operation 【0878】 The server receives data from image capture devices and biosensors. Image capture devices acquire facial expression information of the driver or passenger, and biosensors acquire biometric information such as heart rate and body temperature. The server uses facial recognition AI and emotion analysis engine to analyze this data and evaluate the emotional state and health status. Based on the evaluation results, it generates warnings and notifies the terminal. If necessary, it also provides instructions to adjust the driving monitoring level. 【0879】 Terminal operation 【0880】 The terminal is installed inside the autonomous vehicle and displays warnings and notifications sent from the server. Specifically, it alerts the driver or passengers through voice and display. In addition, if the emotional state is unstable, it continues to collect data from image capture devices and biosensors and provides feedback to the server. 【0881】 User actions 【0882】 The user (driver or passenger) receives notifications from the device and manages their emotional and physical state appropriately. For example, if stress levels are assessed as high, the device will provide advice such as, "Take deep breaths to reduce stress, and take a 5-minute break if necessary." 【0883】 Specific example 【0884】 For example, if the supervisor of an autonomous vehicle is determined to be in a high-stress state, the system instructs the vehicle to temporarily increase its monitoring mode and sends a notification prompting the supervisor to take a deep breath. In this way, the overall safety of the autonomous vehicle is improved. 【0885】 Example of a prompt 【0886】 "I want to develop an emotion monitoring system to be installed in autonomous vehicles. Please create a program that analyzes the emotional state of the observer based on their facial expressions and biometric information, and provides recommendations to reduce stress as needed." 【0887】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0888】 Step 1: 【0889】 The terminal uses an image capture device to acquire facial information of the driver or passenger in real time. The input is image data captured by the camera. The output is facial expression data analyzed by facial recognition AI. Specifically, this data identifies the feature points of each face and quantifies changes in facial expression. 【0890】 Step 2: 【0891】 The server receives biometric information such as heart rate and body temperature from biosensors of the driver or passenger. The input is physiological data from the biosensors. The output is evaluation data that expresses this data as a health status index. Specifically, it calculates the stress level when the heart rate exceeds a certain threshold. 【0892】 Step 3: 【0893】 The server integrates the facial expression data obtained in Step 1 and the physiological data obtained in Step 2, and uses an emotion analysis engine to evaluate the emotional state of the driver or passenger. The inputs are facial expression data and physiological data. The output is an identification result indicating the emotional state. Specifically, the emotional state is classified into categories such as "stress," "relief," and "joy." 【0894】 Step 4: 【0895】 The server generates a warning or notification message based on the emotion assessment results and sends it to the terminal. The input is the evaluation result of the emotion analysis engine. The output is a warning message recommending a specific action. For example, if stress levels are high, it generates a message such as "We recommend you take a break." 【0896】 Step 5: 【0897】 The terminal notifies the user of warning messages received from the server via audio or display. The input is the warning message from the server. The output is an audio or visual prompt to encourage user action. Specifically, this involves displaying the message on the screen and playing an audio alert. 【0898】 Step 6: 【0899】 The user checks notifications from their device and takes appropriate action based on their emotional and health state. The input is a warning message from the device. The output is a change in the user's behavior or improvement in their state. For example, they might take deep breaths to reduce stress or pause the device. 【0900】 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0901】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0902】 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414. 【0903】 Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion. 【0904】 Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together. 【0905】 These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression. 【0906】 The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become. 【0907】 Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant. 【0908】 The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more." 【0909】 The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values. 【0910】 The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format. 【0911】 In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data. 【0912】 In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56. 【0913】 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. 【0914】 Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56. 【0915】 The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory. 【0916】 The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor. 【0917】 Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources. 【0918】 Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose. 【0919】 The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above. 【0920】 All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference. 【0921】 The following is further disclosed regarding the embodiments described above. 【0922】 (Claim 1) 【0923】 To monitor the driver's condition, 【0924】 A means for acquiring the driver's biometric information using an image capture means, 【0925】 A means of analyzing acquired biometric information to evaluate the driver's health status, 【0926】 A means for generating and notifying warnings based on evaluation results, 【0927】 A system that includes this. 【0928】 (Claim 2) 【0929】 The system according to claim 1, including a notification prompting the driver to stop the vehicle. 【0930】 (Claim 3) 【0931】 The system according to claim 1, including a notification to the administrator reporting an abnormal condition. 【0932】 "Example 1" 【0933】 (Claim 1) 【0934】 To monitor the driver's condition, 【0935】 A means for acquiring the driver's biometric information using an image capture device, 【0936】 A means including an artificial intelligence model that analyzes acquired biometric information to evaluate the driver's attention, 【0937】 A means of generating a warning based on the evaluation results and notifying the terminal, 【0938】 A means of notifying the user of the transmitted warning by voice or screen display, 【0939】 A system that includes this. 【0940】 (Claim 2) 【0941】 The system according to claim 1, including a notification prompting the driver to stop the vehicle. 【0942】 (Claim 3) 【0943】 The system according to claim 1, including a notification to the administrator reporting an abnormal condition. 【0944】 "Application Example 1" 【0945】 (Claim 1) 【0946】 To monitor the driver's condition, 【0947】 A means for acquiring the driver's biometric information using an image capture device, 【0948】 A means of analyzing acquired biometric information to evaluate the driver's health status and attention span, 【0949】 A means for generating and notifying warnings based on evaluation results, 【0950】 Means for notifying warnings in real time via audio and visual means, 【0951】 A system that includes this. 【0952】 (Claim 2) 【0953】 The system according to claim 1, including a notification prompting the driver to stop the vehicle. 【0954】 (Claim 3) 【0955】 The system according to claim 1, including a notification to the administrator reporting an abnormal condition. 【0956】 "Example 2 of combining an emotion engine" 【0957】 (Claim 1) 【0958】 To monitor the driver's condition and analyze the driver's emotional state, 【0959】 A means for acquiring the driver's biometric information and facial expression information using an image capture means, 【0960】 A means for analyzing acquired biometric and facial information to evaluate the driver's health and emotional state, 【0961】 A means of generating warnings and notifications based on evaluation results and communicating them to the driver in real time, 【0962】 A system that includes this. 【0963】 (Claim 2) 【0964】 The system according to claim 1, including a notification prompting the driver to interrupt operation. 【0965】 (Claim 3) 【0966】 The system according to claim 1, including a notification to the administrator reporting an abnormal condition. 【0967】 "Application example 2 when combining with an emotional engine" 【0968】 (Claim 1) 【0969】 To monitor the condition of the driver or passengers, 【0970】 A means for acquiring facial expression information of the driver or passenger using an image capture device, 【0971】 A means for acquiring biometric information of a driver or passenger using a biosensor, 【0972】 A means for analyzing acquired facial and biometric information to evaluate the health and emotional state of the driver or passenger, 【0973】 A means for generating and notifying warnings based on evaluation results, 【0974】 A means of adjusting the level of driving monitoring according to the emotional state, 【0975】 A system that includes this. 【0976】 (Claim 2) 【0977】 The system according to claim 1, comprising a function to provide a notification prompting the shutdown of the vehicle and a function to adjust the vehicle monitoring level. 【0978】 (Claim 3) 【0979】 The system according to claim 1, including a notification to an administrator or other relevant party reporting an abnormal condition. [Explanation of symbols] 【0980】 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

[Claim 1] To monitor the driver's condition, A means for acquiring the driver's biometric information using an image capture means, A means of analyzing acquired biometric information to evaluate the driver's health status, A means for generating and notifying warnings based on evaluation results, A system that includes this. [Claim 2] The system according to claim 1, including a notification prompting the driver to stop the vehicle. [Claim 3] The system according to claim 1, including a notification to the administrator reporting an abnormal condition.

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