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The Automatic Student Entry and Exit Detection System is a real-time attendance monitoring system designed to automate the detection of students entering and leaving classrooms using computer vision and machine learning technologies. By utilizing live camera feeds and facial recognition, the system automatically identifies students, classifies their activities as entry or exit, and records attendance events without requiring manual interaction.
The system combines real-time face detection, facial recognition, movement classification, and video recording to create a comprehensive attendance management solution. Detection results, attendance history, and video recordings are securely stored in a centralized database for archival and auditing purposes.
A Laravel & Python based web enables administrators to monitor classroom activities in real time, manage student information, configure cameras, administer user accounts, and analyze attendance data through interactive tables, charts, and statistical reports. The system improves attendance accuracy, enhances data security, and provides actionable insights for academic evaluation and decision-making.
Project Summary
The system combines real-time face detection, facial recognition, movement classification, and video recording to create a comprehensive attendance management solution. Detection results, attendance history, and video recordings are securely stored in a centralized database for archival and auditing purposes.
A Laravel & Python based web enables administrators to monitor classroom activities in real time, manage student information, configure cameras, administer user accounts, and analyze attendance data through interactive tables, charts, and statistical reports. The system improves attendance accuracy, enhances data security, and provides actionable insights for academic evaluation and decision-making.
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