Project Process
Loading Libraries
- OpenCV: For face detection and recognition.
- NumPy: For data processing and mathematical operations.
- GPIO Zero: For hardware (servo motor) control.
Code Writing
1. Data Collection: Captures and stores face photos.
2. Model Training: Builds a face recognition model with photos.
3. Main System: Recognizes faces via the camera and opens the door. Developed in Python using OpenCV and GPIO Zero.
Hardware Setup
• Raspberry Pi: Main control unit.
• Servo Motor: For door lock mechanism.
• Camera: Captures images for face recognition.
Software-Hardware Integration
The software is installed on the Raspberry Pi, working in integration with the servo motor and camera. When the camera recognizes a face, the servo motor activates to open the door.
Model Testing
The project is tested on a door model. The servo motor simulates the door lock and moves upon successful face recognition verification.
Video Recording
All preparation stages, hardware setups, and software processes of our project have been carefully documented. Explore the details by watching these moments on our YouTube channel.
YouTubePresentation, Report
All project details are available in the prepared presentation and reports. The presentation summarizes the project, while the report includes technical details and results comprehensively.
Website Development
This website showcases all stages and technical details of the project step by step. Design, software, hardware integration, and more are brought together on this platform.