FaceTrack – Face ID Based Academic Management System

In many colleges, academic attendance is still recorded manually, which often leads to er rors, time wastage, and difficulty in maintaining records. To overcome these problems, this project presents a FaceTrack System that manages attendance digitally and also moni tors attendance data during lab sessions. The system is developed using Python with a simple graphical interface and uses a SQLite database to store all information. It allows students to log in and mark their attendance by selecting the practical they are performing. Once attendance is marked, the system automatically creates a session and records the login time. An important feature of this system is attendance analytics. While the student is working on the computer, the system tracks the face recognition or application being used and stores this information in the database at regular intervals. This helps teachers understand whether students are using the system for academic purposes or not. The system also provides access to teaching assistants and course incharge, who can view attendance records and manage academic attendance and student records. Reports can be generated in formats like CSV and PDF, making it easier to analyze and maintain records.