Smart Attendance System using Face
🚀 A modern attendance monitoring system that integrates Face Recognition and Fingerprint Scanning for secure and automated student/employee attendance.
📌 Features
✅ Face Recognition – Real-time detection and recognition of registered users
✅ Dual Authentication – Option to mark attendance using face, fingerprint, or both
✅ Attendance Storage – Data stored securely in SQLite/Excel/CSV formats
✅ GUI Dashboard – Easy-to-use interface for Admins and Students
✅ Admin Panel – Manage users, view reports, and export attendance
✅ Voice/Beep Feedback – Alerts when attendance is marked successfully
🏗️ Tech Stack
Python 3.10+
Libraries: OpenCV, dlib, face_recognition, Tkinter, sqlite3, pandas, xlwt
Hardware Support: Fingerprint Scanner Module (e.g., R305, Digital Persona)
📂 Project Structure
Smart-Attendance-using-Face-and-Finger-Scanning/
│── face_dataset/ # Registered user face images
│── attendance/ # Attendance records (CSV/Excel)
│── database/ # SQLite DB files
│── gui/ # GUI scripts
│── models/ # Pre-trained models for face recognition
│── app.py # Main application script
│── requirements.txt # Dependencies
│── README.md # Project documentation
⚙️ Installation
Clone this repository
git clone https://github.com/josephsam-hub/Smart-Attendance-using-Face-and-Finger-Scanning.git
cd Smart-Attendance-using-Face-and-Finger-Scanning
Install dependencies
pip install -r requirements.txt
Connect and configure the Fingerprint Scanner
Run the application
python app.py
🎯 Usage
Register Students/Employees with face and fingerprint
Start Attendance Session – System automatically marks attendance
View Attendance Reports – Export data to CSV/Excel for analysis
👨💻 Contributors
Joseph Sam
🏅 Achievements
This project was developed as part of academic/innovation challenges and awarded a Certificate of Achievement.