ExamX Protocol - AI Exam Integrity System (Proof of Concept)
ExamX Protocol is a cutting-edge examination system that leverages advanced AI technologies to ensure academic integrity during online exams. The system combines computer vision with natural language processing to monitor student behavior in real-time, detecting potential cheating attempts through gaze tracking and speech analysis. Built entirely in Python, it represents a breakthrough in educational technology.
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Project Overview
ExamX Protocol is a cutting-edge examination system that leverages advanced AI technologies to ensure academic integrity during online exams. The system combines computer vision with natural language processing to monitor student behavior in real-time, detecting potential cheating attempts through gaze tracking and speech analysis. Built entirely in Python, it represents a breakthrough in educational technology.
The Challenge
Creating an accurate AI system that could detect cheating behaviors without false positives, while maintaining smooth exam experience and real-time processing capabilities.
The Solution
Developed custom TensorFlow models for gaze detection, integrated OpenAI Whisper for speech recognition, and created a proprietary algorithm for integrity scoring. Used PyQt6 for the exam interface and Firebase for real-time data storage.
Key Features
- Real-time gaze tracking and analysis
- Speech detection and conversation monitoring
- Custom integrity percentage calculation algorithm
- PyQt6-based secure exam interface
- Firebase integration for data storage
- Automatic Google Sheets reporting
- Fine-tuned with real UniMAP student data
- 100% Python implementation
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