Smart Classroom Surveillance: AI-Powered Cheating Detection System

Overview

The Classroom Cheat Detection System is a cutting-edge solution designed to maintain academic integrity by detecting suspicious behavior during exams using real-time video analytics.

Key Features

• Real-Time Head Orientation Detection: Monitors student head movements to identify signs of cheating.
• Mobile Phone Detection: Detects unauthorized phone usage during examinations using YOLOv8 model.
• Student Tracking & Movement Monitoring: Tracks movement patterns to flag unusual behavior.
• Suspicious Behavior Alerts: Sends instant alerts when potential cheating is detected.
• Log and Snapshot Storage: Automatically captures snapshots and logs incidents for later review.
• Web Dashboard: User-friendly interface to monitor live feeds and access recorded events.

Applications

• Academic institutions for maintaining exam integrity.
• Online proctoring systems with physical classroom integration.
• Behavioral analysis tools for educational research.
• Surveillance systems in controlled environments.

Why Choose This System?

This system leverages modern computer vision techniques and machine learning models to offer an automated, scalable, and accurate approach to monitoring classrooms without human supervision. It’s ideal for universities, colleges, and competitive exam centers aiming to prevent malpractice.