Smart Attendance Management System using Face Recognition

In recent years, face recognition has emerged as a prominent biometric authentication technique, widely adopted in various domains such as surveillance, access control, and attendance management systems. Traditional attendance tracking methods are often manual, timeconsuming, and susceptible to manipulation. This paper proposes a Face Recognition-Based Smart Attendance System that automates the attendance process using real-time facial recognition powered by deep learning. The system leverages a Convolutional Neural Network (CNN) architecture with transfer learning from pre-trained models to enhance accuracy and reduce training time. A user-friendly interface built with Tkinter allows administrators to manage attendance efficiently. The system also integrates communication modules using SMTP and Twilio APIs to send real-time notifications via email and SMS. Attendance records are maintained in both CSV files and a MySQL database, ensuring secure and scalable data management. Experimental results demonstrate the system’s high accuracy and efficiency, making it suitable for educational and organizational deployment.