قاعة المحاضرات الذكية المبنية على الذكاء الاصطناعي للحضور والتحكم بالإيماءات

*Brief Overview*:

The AI-Based Smart Lecture Hall (AURA) is a graduation project that builds a fully touchless, AI-powered classroom management system. It combines facial recognition for automated student attendance with hand gesture recognition for controlling classroom appliances — lighting, fans, AC, door lock, and audio-visual equipment — all without any physical contact. The system runs on a dual-processor architecture: an ESP32-CAM handles face recognition using a CNN-based model, while a Raspberry Pi 5 manages gesture processing via MediaPipe. A central Flask server on a laptop ties everything together with a SQLite database for real-time attendance logging.

*Project Objectives*:

1. Design and deploy a low-cost, scalable IoT architecture suitable for university-wide implementation using ESP32-CAM and Raspberry Pi platforms.

2. Develop a robust software pipeline for grayscale conversion, thresholding, and contour extraction to achieve high-accuracy gesture recognition.

3. Implement a secure door-locking mechanism integrated with the attendance and instructor-detection logic.

4. Evaluate system performance in terms of recognition latency and accuracy under various environmental lighting conditions.

5. Replace traditional manual or contact-based biometric attendance methods with a hygienic, automated, and secure zero-touch alternative.

6. Create a scalable, cost-effective ecosystem that bridges the gap between computer vision research and real-world educational applications.

1-Omnia Ebrahim Farouk Ali

2-Rahma Ahmed Youssef Amin

3-Ethar Adnan Ibrahim Al-Blaidy

4-Nada Mahmoud Mohammed Mohammed

5-Ahmed Elsayed Abuzaid Abuzaid

6-Mohammed Ramadan Farahat Younes