Published November 22, 2024
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Integrating eye status detection system into an automotive grid involves using eye-tracking data to enhance driver safety and vehicle functionality. Here's a conceptual approach to connect project within an automotive environment:
Purpose:
- Drowsiness Detection: The primary goal is to monitor the driver’s eye status to detect drowsiness or inattention, which can then trigger alerts or vehicle control actions.
Components Required
- Camera Module
Part Number: Logitech C270 or similar - Microcontroller / Processor
Part Number: ESP32-WROOM-32 and Sipeed Maixduino Dev. Kit - CAN Bus Module (Optional for Vehicle Integration)
Part Number: MCP2515 - Alert Mechanism - Buzzer
- Alert Mechanism - LED Indicators
Part Number: 5mm LED
Component Selection Rationale:
- Camera Module: Provides the video feed for eye detection.
- ESP32: Serves as the processing unit for running the detection algorithm and handling communication tasks.
- Voltage Regulator & Power Module: Ensures stable power supply, critical for consistent operation.
- CAN Bus Module: Facilitates vehicle integration, allowing data sharing with other automotive systems.
- Alert Mechanisms: Buzzer, LEDs, and speakers provide real-time feedback based on the eye status.
- Passive Components: Resistors, capacitors, and diodes ensure proper circuit functionality, filtering, and protection.
Camera: A camera mounted on the dashboard or near the rearview mirror, focused on the driver's face to capture real-time video.
Onboard Computer: An automotive-grade computer (like a Raspberry Pi or dedicated microcontroller) to run the eye detection and status processing algorithms.
CAN Bus Interface: Interface to the vehicle’s CAN (Controller Area Network) bus to communicate with other vehicle systems.
Alert System: Speakers, vibration motors, or visual indicators (e.g., dashboard lights) to alert the driver.
Communication Module: Wi-Fi, GSM, or Bluetooth module for remote data transmission and integration with cloud services or external servers.
Power Supply: Connection to the vehicle’s 12V or 24V electrical system, with appropriate voltage regulation to power the components.
Circuit diagram
Workflow:
1. Capture and Process Data:
- The camera captures the driver’s eye movements in real-time.
- The onboard computer processes the video feed using the provided eye detection algorithm to determine the eye aspect ratio (EAR).
2. Drowsiness Detection:
- If the EAR falls below the threshold, indicating closed or nearly closed eyes, the system identifies potential drowsiness.
3. Trigger Alerts:
- Upon detecting drowsiness, the system sends a signal to the alert system via the CAN bus.
- Alerts can include an audible warning, seat vibrations, or visual cues on the dashboard.
4. Vehicle Control Integration:
- For advanced implementations, the system can communicate with vehicle control systems (like lane-keeping assist or cruise control) via the CAN bus to initiate corrective actions, such as slowing down the vehicle.
5. Power Management:
- Ensure the system is connected to the vehicle’s power supply with appropriate fuses and voltage regulators to handle the automotive environment’s power fluctuations.
Integration Challenges:
- Vibration and Noise: Automotive environments are noisy and vibrate, which can affect camera stability. Use vibration-damping mounts for the camera.
- Temperature Variations: Automotive environments experience extreme temperature variations. Use automotive-grade components designed to operate in such conditions.
- Real-Time Processing: Ensure that the onboard computer can handle real-time video processing with minimal latency.
- Safety and Compliance: Ensure the system complies with automotive safety standards and does not interfere with critical vehicle systems.
Open eye Image
Close eye Image.
