Eye Controlled wheelchair

11000 ~~15000~~

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Product Name: Eye-Controlled Wheelchair
Version: 1.0
Platform: Python 3.x
Hardware Requirements:
- Camera Module (for eye tracking)
- Raspberry Pi or similar single-board computer
- Motorized wheelchair with motor driver
- Display Screen
- Control buttons (optional)
Software Requirements:
- Python 3.x
- OpenCV library for image processing
- Dlib library for facial landmark detection
- Numpy library
- Imutils library
Functional Requirements:
- Real-time eye tracking and gaze direction detection
- Control signals for wheelchair movement based on eye direction
- Emergency stop mechanism
Non-functional Requirements:
- High accuracy in eye tracking and gaze detection
- Low latency in processing and movement control
- User-friendly interface
- Robustness and reliability in various lighting conditions

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Key Features:

Real-time Eye Tracking:
- The system continuously captures video frames of the user's face and eyes using a camera module.
- The captured frames are processed in real-time to detect facial landmarks and eye position.
Gaze Direction Detection:
- The system analyzes the direction of the user's gaze to determine the intended movement.
- Various gaze directions are mapped to specific wheelchair commands (e.g., forward, backward, left, right).
Wheelchair Control:
- Based on the detected gaze direction, the system sends appropriate control signals to the motorized wheelchair.
- The wheelchair moves in the desired direction as long as the user maintains their gaze.
Emergency Stop Mechanism:
- The system includes an emergency stop feature that allows the user to halt the wheelchair immediately.
- This can be triggered by a specific eye gesture or a control button.