• Polisetty Anusha
• K Anvitha
• K Deepthi
• G Kalyan

This paper introduces a novel Time-Based Attendance Management System, designed to modernize and streamline traditional manual attendance tracking methods. The system utilizes cutting-edge biometric technology, particularly Deep Learning (DL) based Face Recognition algorithms, to accurately identify individuals. By employing LBPH Face Recognizer, human faces are utilized as the primary dataset for training, ensuring reliable recognition.The user interface is developed using the Flask framework, offering a seamless and intuitive web page for users. A notable enhancement of this system is its ability to store attendance data in a database, complete with timestamps, providing administrators with valuable insights and analysis capabilities.Moreover, an innovative feature has been integrated to notify parents about their children's attendance, marks, and behavior through the Fast to SMS website. This feature not only enhances efficiency by automating communication but also strengthens the relationship between educational institutions and parents. By keeping parents informed and engaged, the system fosters a more collaborative and supportive educational environment Overall, this Time-Based Attendance Management System represents a significant advancement in attendance tracking technology, offering efficiency, accuracy, and enhanced communication between educational institutions and parents.

Attendance Management, Computer Vision, Deep Learning, Human Face Images, sending SMS

"Design and implementation of smart attendance with advanced deep learning methods", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 3, page no.j50-j60, March-2024, Available :http://www.jetir.org/papers/JETIR2403909.pdf

"Design and implementation of smart attendance with advanced deep learning methods", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 3, page no. ppj50-j60, March-2024, Available at : http://www.jetir.org/papers/JETIR2403909.pdf