Published Paper Details:

The Smart Hybrid Attendance Management System Using Face Recognition is an innovative and efficient solution designed to automate attendance tracking in educational institutions. Traditional attendance methods, such as manual registers or RFID-based systems, are prone to errors and time-consuming processes. This system leverages Artificial Intelligence (AI) and Machine Learning (ML) to streamline attendance marking by recognizing student faces in real time. The system maintains a student database that stores essential details such as name, ID, roll number, department, course, year, semester, and guardian contact information, along with face samples that are used for facial recognition. These face samples are trained using machine learning algorithms to ensure accurate identification of students. The Face Recognition Module is responsible for automating the attendance process. When students appear before the system, their faces are detected and compared with the pre-stored dataset. If a match is found, they are marked as "Present", and their details are logged into attendance.csv. The Attendance Panel allows administrators to manually verify and manage attendance records, ensuring flexibility and accuracy. In cases where students are absent, the system provides an interface where administrators can manually mark them as "Absent" and store their details in a separate absentees.csv file. The system also includes a refresh button to update records dynamically and a manual control button for faculty to review and adjust attendance as needed. A key feature of this system is its Automated Absentee Notification System, which ensures effective communication between the institution and parents. Once students are manually marked as absent, their details are retrieved from absentees.csv, and an email notification is sent to their respective guardians informing them of their child's absence from class. This feature helps improve parental involvement, enhances institutional transparency, and ensures that students maintain regular attendance. By integrating biometric-based attendance tracking with manual oversight and automated reporting, this system significantly reduces administrative workload while ensuring secure, accurate, and real-time attendance monitoring.