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.