???? Project Title:

Face Recognition Attendance System

???? Summary:

The Face Recognition Attendance System is an automated solution for recording and managing attendance using facial recognition technology. It replaces traditional methods of marking attendance (like manual entry or RFID cards) with a more secure and efficient system based on facial recognition.

✨ Key Features:

Real-time facial recognition for attendance marking

Automated attendance logs and reports

User registration for face capture and profile creation

Admin panel to manage users and view attendance records

Alerts for unauthorized access or unrecognized faces

Secure and encrypted data storage

Option for facial recognition to work with webcams or IP cameras

????️ Technologies Used:

Frontend: HTML, CSS, JavaScript, React.js

Backend: Python (Flask/Django) / Node.js

Face Recognition Library: OpenCV / Face Recognition (Python library)

Database: MySQL / PostgreSQL / MongoDB

Authentication: Facial authentication API

Other Tools: TensorFlow / Keras for machine learning

Hardware: Webcam/IP camera for capturing faces

⚙️ Working Process:

User Registration: Users (students or employees) register by capturing their facial images for profile creation.

Face Detection: The system scans the user's face in real-time when they appear in front of the camera.

Attendance Marking: Once the face is recognized, attendance is automatically marked in the database.

Admin Monitoring: Admins can monitor attendance, generate reports, and track who is absent.

Alerts: The system can send alerts if an unregistered face tries to mark attendance.

✅ Benefits:

Reduces the risk of proxy attendance

Increases efficiency and accuracy in attendance tracking

Eliminates manual errors and time wastage

Enhances security by ensuring only registered individuals can mark attendance

Generates automatic reports, saving time for admins

Can be integrated with other systems (e.g., payroll, performance tracking)