Enhancing Campus Security Through Smart Surveillance System

In modern educational environments, maintaining campus security and ensuring student attendance during scheduled academic hours pose significant challenges. The issue of students skipping classes and engaging in inappropriate activities, which are against the code of conduct of the universities and also affect their studies, is a concern. This project introduces an advanced face recognition system designed to monitor students during academic hours, creating a safer and more secure campus environment. The system operates by capturing and analyzing facial features, allowing for accurate student identification. Once a student is recognized during academic hours, the system promptly sends notifications to their respective class advisors with proof. To enhance the system's effectiveness, exceptions are made for institute officials, teaching and non-teaching staff, coworkers, and parents visiting the campus. These exceptions are handled through the approach of machine learning, image processing, and computer vision.