Intelligent windshield system and method

Abstract

The invention discloses an intelligent windshield system and method, and relates to the technical field of automobile manufacturing and intelligent display, and the windshield system comprises a high-definition projection module, an environment perception sensor data acquisition module, a data processing module, an intelligent interaction module and a vehicle state monitoring module. By monitoring the environment around the vehicle and the state of the vehicle in real time, the system can recognize and remind a driver of potential dangers in time, the accident occurrence probability is reduced, the driving safety is improved, the high-definition projection module directly projects key information to the windshield in the form of graphic symbols and characters, and the driving safety is improved. According to the system and the method, a driver can rapidly and visually obtain important information such as navigation, vehicle speed and fuel quantity, distraction caused by checking an instrument panel by lowering the head is reduced, the driver can more naturally interact with the system through an integrated voice, gesture and eyeball tracking control mode, and operation complexity is reduced.

Description

Technical Field

[0001] The present invention relates to the field of automobile manufacturing and intelligent display technology, and in particular to an intelligent windshield system and method. Background Art

[0002] With the advancement of technology and the rapid development of intelligent cars, traditional windshields have gradually failed to meet the needs of modern car users. The main function of traditional windshields is to provide a clear driving view and prevent interference from natural factors such as wind, rain, and sunlight. However, with the popularization of smart cars, users' functional demands for windshields are also increasing, such as information display, interactive feedback, and automatic adjustment of transparency.

[0003] Therefore, the present invention proposes a novel intelligent windshield, which aims to improve driving convenience and safety by integrating multiple intelligent functions. Summary of the invention

[0004] In order to solve the above technical problems, an intelligent windshield system and method are provided, and this technical solution solves the above problems.

[0005] In order to achieve the above purpose, the technical solution adopted by the present invention is: An intelligent windshield system, the windshield system comprising: High-definition projection module: The high-definition projection module is used to display information on the windshield based on optical projection technology; Environmental perception sensor data acquisition module: The environmental perception sensor data acquisition module is electrically connected to the high-definition projection module, and the environmental perception sensor data acquisition module is used to integrate sensor data and capture vehicle surrounding environment information in real time; Data processing module: The data processing module is electrically connected to the environment perception sensor data acquisition module. The data processing module is used to analyze and process the sensor data in real time based on deep learning and computer vision technology, identify key information, and convert it into graphic symbols and text, and project it onto the windshield; Intelligent interaction module: The intelligent interaction module is electrically connected to the data processing module, and is used to capture the driver's voice, gestures and eye information, and control the content and form of information display; Vehicle status monitoring module: The vehicle status monitoring module is electrically connected to the intelligent interaction module. The vehicle status monitoring module is used to monitor the operating parameters of the vehicle in real time. Once an abnormality occurs, a warning is issued on the windshield to remind the driver to take corresponding measures.

[0006] Preferably, the high-definition projection module specifically includes: Requirements acquisition unit: determines the functional requirements of the projection module, including navigation, vehicle speed and warning; Optical System Design Unit: Design projection optical systems, including lenses and reflectors, to ensure that the optical system can project information onto the windshield at the appropriate angle and size, and use simulation software to optimize the optical path; Image processing and generation unit: Based on the functional requirements of the projection module, use image processing technology to generate projection images and use image enhancement technology to process images; Anti-glare design unit: design anti-glare coatings or use special optical materials, evaluate the impact of different coatings on glare, and ensure that the projection is clearly visible in strong light environments; Projection Correction Unit: Performs geometric correction and color correction to ensure that the projected content is accurate and uses correction algorithms to adjust the image.

[0007] Preferably, the environment perception sensor data acquisition module specifically includes: Data acquisition unit: Develop a data acquisition module to acquire data in real time from various sensors, including cameras, radars, and laser scanners; Data fusion unit: Based on the data fusion algorithm, it integrates the data from different sensors, uses Kalman filtering to remove noise, and converts radar and LIDAR data into a unified coordinate system; Among them, the data fusion algorithm formula is:

[0008] In the formula, is the estimated value after fusion, For the The measured value of each sensor, For the The weight of the sensor, is the number of sensors.

[0009] Preferably, the data processing module specifically includes: Environmental feature recognition unit: uses computer vision to analyze the fused data, extract features, and recognize the status of traffic signs, pedestrians, and obstacles; Edge detection unit: calculate the color histogram of each pixel, use the Canny edge detection algorithm to extract the edge features in the image, use the local binary pattern method to extract the texture information of the image, use the directional gradient histogram to extract the shape features of the object, and use the contour detection function of OpenCV to extract the contour information of the object in the image; Feature extraction unit: image classification and feature extraction based on convolutional neural network extraction formula; State recognition unit: outputs the results of the model, sets a confidence threshold, and only retains the detection results above the threshold. Based on non-maximum suppression, it eliminates duplicate bounding boxes and only retains the bounding boxes with the highest confidence. It determines the category of traffic signs, detects the position and movement status of pedestrians, and identifies and classifies the types of obstacles. After identification, the system displays the detection results accordingly. When dangerous traffic signs, pedestrians and obstacles are identified, alarms are triggered and real-time feedback is provided.

[0010] Preferably, the feature extraction unit specifically includes: Image classification and feature extraction are performed based on the convolutional neural network extraction formula to perform real-time target detection. The convolutional neural network extraction formula is:

[0011] In the formula, is an element in the output feature map, is the input feature map, is the convolution kernel, is the bias term are the coordinates of the output feature map, and is the size of the convolution kernel.

[0012] Preferably, the intelligent interaction module specifically includes: Speech recognition unit: recognizes the driver's commands and requests through voice input, collects the driver's voice, can filter background noise, convert audio signals into text, and parse voice commands; Gesture control unit: recognizes the driver's gestures for control, captures the driver's gestures, provides real-time image input, analyzes image data, recognizes specific gestures and performs corresponding operations; Eye tracking unit: Provides control by tracking the driver's line of sight. Based on an infrared camera, it captures eye movements and gaze points, analyzes eye position and movement, and determines the target of gaze. User interface unit: displays information and interacts with the driver; Data processing unit: processes data from various modules and makes decisions, and feeds back the status of executed commands to the driver.

[0013] Preferably, the vehicle status monitoring module specifically includes: Data acquisition unit: The sensor continuously monitors the vehicle's operating parameters and sends the data to the data processing unit in real time; Data processing unit: receives data from each sensor, and uses an abnormality detection algorithm to analyze in real time to determine whether any parameter exceeds the normal range. If an abnormality is detected, the data processing unit immediately sends the information to the warning display unit and the feedback response unit; Warning Display Unit: The warning display unit displays warning information on the windshield through the head-up display, including "engine overheating" and "brake system failure", ensuring that the driver can quickly see the warning during driving; Real-time monitoring unit: In the warning state, the monitoring module continues to monitor relevant parameters in real time to observe whether there is any improvement. The driver takes corresponding measures based on the information provided by the system.

[0014] An intelligent windshield method, comprising: The system uses environmental perception sensors to capture real-time traffic information around it, including the distance to the vehicle ahead, road markings, and traffic light status; Image processing and fusion algorithms transform the collected information into intuitive symbols and arrows, which are projected onto the windshield through a projection module; The system dynamically adjusts the level of detail of navigation instructions based on the vehicle's real-time position and speed, providing detailed turning instructions at complex intersections and reducing information display on straight sections of road; The system displays vehicle speed and fuel level information in real time. When any abnormality is detected, it alerts the driver through icons and sound alarms.

[0015] Preferably, the image processing and fusion algorithm converts the collected information into intuitive symbols and arrows, and projects them onto the windshield through the projection module, specifically including: Use computer vision to analyze the fused data, extract features, and identify the status of traffic signs, pedestrians, and obstacles; Calculate the color histogram of each pixel, extract the edge features and texture information of the image, extract the shape features of the object, and extract the contour information of the object in the image; Image classification and feature extraction based on convolutional neural network extraction formula; The model results are output to determine the type of traffic signs, detect the position and movement status of pedestrians, and identify and classify the types of obstacles. After identification, the system will display the results accordingly.

[0016] Preferably, the system displays the vehicle speed and fuel level information in real time, and when an abnormality is found, it reminds the driver through icons and sound alarms. Specifically, it includes: The sensors continuously monitor the vehicle’s operating parameters and send the data to the data processing unit in real time; Receive data from each sensor, analyze it in real time through anomaly detection algorithm, and determine whether any parameter exceeds the normal range. If an abnormality is detected, the data processing unit immediately sends the information to the warning display unit and the feedback response unit; Warning messages, including "engine overheat" and "brake system failure", are displayed on the windshield. In the warning state, the monitoring module continues to monitor relevant parameters in real time to see if there is any improvement. The driver takes corresponding measures based on the information provided by the system.

[0017] Compared with the prior art, the present invention has the following beneficial effects: The present invention proposes that by real-time monitoring of the environment and vehicle status around the vehicle, the system can promptly identify and remind the driver of potential dangers, such as pedestrians, traffic signs and obstacles. This real-time feedback greatly reduces the probability of accidents and improves driving safety. The high-definition projection module projects key information directly onto the windshield in the form of graphic symbols and text, allowing the driver to quickly and intuitively obtain important information such as navigation, vehicle speed, fuel level, etc., reducing distraction caused by looking down at the dashboard. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a step flow framework diagram of the present invention; Figure 2 It is a system framework diagram of the present invention. DETAILED DESCRIPTION

[0019] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.

[0020] Reference Figure 1 As shown, an intelligent windshield system, the windshield system includes: High-definition projection module: The high-definition projection module is used to display information on the windshield based on optical projection technology; Environmental perception sensor data acquisition module: The environmental perception sensor data acquisition module is electrically connected to the high-definition projection module, and the environmental perception sensor data acquisition module is used to integrate sensor data and capture vehicle surrounding environment information in real time; Data processing module: The data processing module is electrically connected to the environment perception sensor data acquisition module. The data processing module is used to analyze and process the sensor data in real time based on deep learning and computer vision technology, identify key information, and convert it into graphic symbols and text, and project it onto the windshield; Intelligent interaction module: The intelligent interaction module is electrically connected to the data processing module, and is used to capture the driver's voice, gestures and eye information, and control the content and form of information display; Vehicle status monitoring module: The vehicle status monitoring module is electrically connected to the intelligent interaction module. The vehicle status monitoring module is used to monitor the operating parameters of the vehicle in real time. Once an abnormality occurs, a warning is issued on the windshield to remind the driver to take corresponding measures.

[0021] The high-definition projection module specifically includes: Requirements acquisition unit: determines the functional requirements of the projection module, including navigation, vehicle speed and warning; Optical System Design Unit: Design projection optical systems, including lenses and reflectors, to ensure that the optical system can project information onto the windshield at the appropriate angle and size, and use simulation software to optimize the optical path; Image processing and generation unit: Based on the functional requirements of the projection module, use image processing technology to generate projection images and use image enhancement technology to process images; Anti-glare design unit: design anti-glare coatings or use special optical materials, evaluate the impact of different coatings on glare, and ensure that the projection is clearly visible in strong light environments; Projection Correction Unit: Performs geometric correction and color correction to ensure that the projected content is accurate and uses correction algorithms to adjust the image.

[0022] The environment perception sensor data acquisition module specifically includes: Data acquisition unit: Develop a data acquisition module to acquire data in real time from various sensors, including cameras, radars, and laser scanners; Data fusion unit: Based on the data fusion algorithm, it integrates the data from different sensors, uses Kalman filtering to remove noise, and converts radar and LIDAR data into a unified coordinate system; Among them, the data fusion algorithm formula is:

[0023] In the formula, is the estimated value after fusion, For the The measured value of each sensor, For the The weight of the sensor, is the number of sensors.

[0024] The data processing module specifically includes: Environmental feature recognition unit: uses computer vision to analyze the fused data, extract features, and recognize the status of traffic signs, pedestrians, and obstacles; Edge detection unit: calculate the color histogram of each pixel, use the Canny edge detection algorithm to extract the edge features in the image, use the local binary pattern method to extract the texture information of the image, use the directional gradient histogram to extract the shape features of the object, and use the contour detection function of OpenCV to extract the contour information of the object in the image; Feature extraction unit: image classification and feature extraction based on convolutional neural network extraction formula; State recognition unit: outputs the results of the model, sets a confidence threshold, and only retains the detection results above the threshold. Based on non-maximum suppression, it eliminates duplicate bounding boxes and only retains the bounding boxes with the highest confidence. It determines the category of traffic signs, detects the position and movement status of pedestrians, and identifies and classifies the types of obstacles. After identification, the system displays the detection results accordingly. When dangerous traffic signs, pedestrians and obstacles are identified, alarms are triggered and real-time feedback is provided.

[0025] The feature extraction unit specifically includes: Image classification and feature extraction are performed based on the convolutional neural network extraction formula to perform real-time target detection. The convolutional neural network extraction formula is:

[0026] In the formula, is an element in the output feature map, is the input feature map, is the convolution kernel, is the bias term are the coordinates of the output feature map, and is the size of the convolution kernel.

[0027] The intelligent interaction module specifically includes: Speech recognition unit: recognizes the driver's commands and requests through voice input, collects the driver's voice, can filter background noise, convert audio signals into text, and parse voice commands; Gesture control unit: recognizes the driver's gestures for control, captures the driver's gestures, provides real-time image input, analyzes image data, recognizes specific gestures and performs corresponding operations; Eye tracking unit: Provides control by tracking the driver's line of sight. Based on an infrared camera, it captures eye movements and gaze points, analyzes eye position and movement, and determines the target of gaze. User interface unit: displays information and interacts with the driver; Data processing unit: processes data from various modules and makes decisions, and feeds back the status of executed commands to the driver.

[0028] The vehicle status monitoring module specifically includes: Data acquisition unit: The sensor continuously monitors the vehicle's operating parameters and sends the data to the data processing unit in real time; Data processing unit: receives data from each sensor, and uses an abnormality detection algorithm to analyze in real time to determine whether any parameter exceeds the normal range. If an abnormality is detected, the data processing unit immediately sends the information to the warning display unit and the feedback response unit; Warning Display Unit: The warning display unit displays warning information on the windshield through the head-up display, including "engine overheating" and "brake system failure", ensuring that the driver can quickly see the warning during driving; Real-time monitoring unit: In the warning state, the monitoring module continues to monitor relevant parameters in real time to observe whether there is any improvement. The driver takes corresponding measures based on the information provided by the system.

[0029] Reference Figure 2 As shown, an intelligent windshield method includes: The system uses environmental perception sensors to capture real-time traffic information around it, including the distance to the vehicle ahead, road markings, and traffic light status; Image processing and fusion algorithms transform the collected information into intuitive symbols and arrows, which are projected onto the windshield through a projection module; The system dynamically adjusts the level of detail of navigation instructions based on the vehicle's real-time position and speed, providing detailed turning instructions at complex intersections and reducing information display on straight sections of road; The system displays vehicle speed and fuel level information in real time. When any abnormality is detected, it alerts the driver through icons and sound alarms.

[0030] The image processing and fusion algorithm converts the collected information into intuitive symbols and arrows, which are projected onto the windshield through the projection module. Specifically, it includes: Use computer vision to analyze the fused data, extract features, and identify the status of traffic signs, pedestrians, and obstacles; Calculate the color histogram of each pixel, extract the edge features and texture information of the image, extract the shape features of the object, and extract the contour information of the object in the image; Image classification and feature extraction based on convolutional neural network extraction formula; The model results are output to determine the type of traffic signs, detect the position and movement status of pedestrians, and identify and classify the types of obstacles. After identification, the system will display the results accordingly.

[0031] The system displays the vehicle speed and fuel level in real time. When an abnormality is found, the system reminds the driver through icons and sound alarms. The specific information includes: The sensors continuously monitor the vehicle’s operating parameters and send the data to the data processing unit in real time; Receive data from each sensor, analyze it in real time through anomaly detection algorithm, and determine whether any parameter exceeds the normal range. If an abnormality is detected, the data processing unit immediately sends the information to the warning display unit and the feedback response unit; Warning messages, including "engine overheat" and "brake system failure", are displayed on the windshield. In the warning state, the monitoring module continues to monitor relevant parameters in real time to see if there is any improvement. The driver takes corresponding measures based on the information provided by the system.

[0032] In summary, the advantages of the present invention are: By monitoring the vehicle's surroundings and vehicle status in real time, the system can promptly identify and alert the driver to potential dangers, such as pedestrians, traffic signs and obstacles. This real-time feedback greatly reduces the probability of accidents and improves driving safety; The high-definition projection module projects key information directly onto the windshield in the form of graphic symbols and text, allowing the driver to quickly and intuitively obtain important information such as navigation, vehicle speed, fuel level, etc., reducing the distraction caused by looking down at the dashboard; Integrated voice, gesture and eye-tracking control methods allow drivers to interact with the system more naturally, reducing operational complexity while improving the convenience of obtaining information. Drivers can control navigation and vehicle settings with simple voice commands or gestures, enhancing driving pleasure and comfort. The vehicle status monitoring module continuously analyzes real-time data and can quickly warn drivers through visual and sound alarms when the vehicle is abnormal, ensuring that drivers can take timely measures to reduce the risk of accidents caused by faults. The system can dynamically adjust the level of detail of navigation instructions based on the vehicle's real-time location and speed. It provides detailed turning instructions at complex intersections and reduces information display on straight sections to avoid information overload, thus improving navigation efficiency and practicality. The advanced deep learning and computer vision technologies are used for data processing to ensure the accuracy and real-time nature of environmental perception. This efficient data processing can quickly identify the status of traffic signs, pedestrians and obstacles, and display and feedback accordingly, thus improving the intelligence level of the system. Through the optimization of the user interface unit, the driver can view all important information intuitively, and the system's interactive design is more user-friendly, which improves the driver's acceptance and convenience of operation.

[0033] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. An intelligent windshield system, characterized in that: The windshield system includes: High-definition projection module: The high-definition projection module is used to display information on the windshield based on optical projection technology; Environmental perception sensor data acquisition module: The environmental perception sensor data acquisition module is electrically connected to the high-definition projection module, and the environmental perception sensor data acquisition module is used to integrate sensor data and capture vehicle surrounding environment information in real time; Data processing module: The data processing module is electrically connected to the environment perception sensor data acquisition module. The data processing module is used to analyze and process the sensor data in real time based on deep learning and computer vision technology, identify key information, and convert it into graphic symbols and text, and project it onto the windshield; Intelligent interaction module: The intelligent interaction module is electrically connected to the data processing module, and is used to capture the driver's voice, gestures and eye information, and control the content and form of information display; Vehicle status monitoring module: The vehicle status monitoring module is electrically connected to the intelligent interaction module. The vehicle status monitoring module is used to monitor the operating parameters of the vehicle in real time. Once an abnormality occurs, a warning is issued on the windshield to remind the driver to take corresponding measures.

2. The intelligent windshield system according to claim 1, characterized in that: The high-definition projection module specifically includes: Requirements acquisition unit: determines the functional requirements of the projection module, including navigation, vehicle speed and warning; Optical System Design Unit: Design projection optical systems, including lenses and reflectors, to ensure that the optical system can project information onto the windshield at the appropriate angle and size, and use simulation software to optimize the optical path; Image processing and generation unit: Based on the functional requirements of the projection module, use image processing technology to generate projection images and use image enhancement technology to process images; Anti-glare design unit: design anti-glare coatings or use special optical materials, evaluate the impact of different coatings on glare, and ensure that the projection is clearly visible in strong light environments; Projection Correction Unit: Performs geometric correction and color correction to ensure that the projected content is accurate and uses correction algorithms to adjust the image.

3. The intelligent windshield system according to claim 2, characterized in that: The environment perception sensor data acquisition module specifically includes: Data acquisition unit: Develop a data acquisition module to acquire data in real time from various sensors, including cameras, radars, and laser scanners; Data fusion unit: Based on the data fusion algorithm, it integrates the data from different sensors, uses Kalman filtering to remove noise, and converts radar and LIDAR data into a unified coordinate system; Among them, the data fusion algorithm formula is: In the formula, is the estimated value after fusion, For the The measured value of each sensor, For the The weight of each sensor, is the number of sensors.

4. The intelligent windshield system according to claim 3, characterized in that: The data processing module specifically includes: Environmental feature recognition unit: uses computer vision to analyze the fused data, extract features, and recognize the status of traffic signs, pedestrians, and obstacles; Edge detection unit: calculate the color histogram of each pixel, use the Canny edge detection algorithm to extract the edge features in the image, use the local binary pattern method to extract the texture information of the image, use the directional gradient histogram to extract the shape features of the object, and use the contour detection function of OpenCV to extract the contour information of the object in the image; Feature extraction unit: image classification and feature extraction based on convolutional neural network extraction formula; State recognition unit: outputs the results of the model, sets a confidence threshold, and only retains the detection results above the threshold. Based on non-maximum suppression, it eliminates duplicate bounding boxes and only retains the bounding boxes with the highest confidence. It determines the category of traffic signs, detects the position and movement status of pedestrians, and identifies and classifies the types of obstacles. After identification, the system displays the detection results accordingly. When dangerous traffic signs, pedestrians and obstacles are identified, alarms are triggered and real-time feedback is provided.

5. The intelligent windshield system according to claim 4, characterized in that: The feature extraction unit specifically includes: Image classification and feature extraction are performed based on the convolutional neural network extraction formula to perform real-time target detection. The convolutional neural network extraction formula is: In the formula, is an element in the output feature map, is the input feature map, is the convolution kernel, is the bias term are the coordinates of the output feature map, and is the size of the convolution kernel.

6. The intelligent windshield system according to claim 5, characterized in that: The intelligent interaction module specifically includes: Speech recognition unit: recognizes the driver's commands and requests through voice input, collects the driver's voice, can filter background noise, convert audio signals into text, and parse voice commands; Gesture control unit: recognizes the driver's gestures for control, captures the driver's gestures, provides real-time image input, analyzes image data, recognizes specific gestures and performs corresponding operations; Eye tracking unit: Provides control by tracking the driver's line of sight. Based on an infrared camera, it captures eye movements and gaze points, analyzes eye position and movement, and determines the target of gaze. User interface unit: displays information and interacts with the driver; Data processing unit: processes data from various modules and makes decisions, and feeds back the status of executed commands to the driver.

7. The intelligent windshield system according to claim 6, characterized in that: The vehicle status monitoring module specifically includes: Data acquisition unit: The sensor continuously monitors the vehicle's operating parameters and sends the data to the data processing unit in real time; Data processing unit: receives data from each sensor, and uses an abnormality detection algorithm to analyze in real time to determine whether any parameter exceeds the normal range. If an abnormality is detected, the data processing unit immediately sends the information to the warning display unit and the feedback response unit; Warning display unit: The warning display unit displays warning information on the windshield through the head-up display, including "engine overheating" and "brake system failure", ensuring that the driver can quickly see the warning during driving; Real-time monitoring unit: In the warning state, the monitoring module continues to monitor relevant parameters in real time to observe whether there is any improvement. The driver takes corresponding measures based on the information provided by the system.

8. An intelligent windshield method, characterized in that: include: The system uses environmental perception sensors to capture real-time traffic information around it, including the distance to the vehicle ahead, road markings, and traffic light status; Image processing and fusion algorithms transform the collected information into intuitive symbols and arrows, which are projected onto the windshield through a projection module; The system dynamically adjusts the level of detail of navigation instructions based on the vehicle's real-time position and speed, providing detailed turning instructions at complex intersections and reducing information display on straight sections of road; The system displays vehicle speed and fuel level information in real time. When any abnormality is detected, it alerts the driver through icons and sound alarms.

9. The intelligent windshield method according to claim 8, characterized in that: The image processing and fusion algorithm converts the collected information into intuitive symbols and arrows, which are projected onto the windshield through the projection module. Specifically, it includes: Use computer vision to analyze the fused data, extract features, and identify the status of traffic signs, pedestrians, and obstacles; Calculate the color histogram of each pixel, extract the edge features and texture information of the image, extract the shape features of the object, and extract the contour information of the object in the image; Image classification and feature extraction based on convolutional neural network extraction formula; The model results are output to determine the type of traffic signs, detect the position and movement status of pedestrians, and identify and classify the types of obstacles. After identification, the system will display the results accordingly.

10. The intelligent windshield method according to claim 9, characterized in that: The system displays the vehicle speed and fuel level in real time. When an abnormality is found, the system reminds the driver through icons and sound alarms. The specific information includes: The sensors continuously monitor the vehicle’s operating parameters and send the data to the data processing unit in real time; Receive data from each sensor, analyze it in real time through anomaly detection algorithm, and determine whether any parameter exceeds the normal range. If an abnormality is detected, the data processing unit immediately sends the information to the warning display unit and the feedback response unit; Warning information, including "engine overheating" and "brake system failure", is displayed on the windshield. In the warning state, the monitoring module continues to monitor relevant parameters in real time to observe whether there is any improvement. The driver takes corresponding measures based on the information provided by the system.

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