AIOT based Smart Education System: A Dual Layer Authentication and Context-Aware Tutoring Framework for Learning Environments
Abstract
The AIoT-Based Smart Education System integrates Artificial Intelligence and IoT to address persistent challenges in contemporary classrooms: attendance fraud, lack of personalization, student disengagement, and inefficient resource use. The unified platform combines four core modules: (1) a dual-factor authentication system leveraging RFID-based ID scans and WiFi verification for secure, fraud-resistant attendance; (2) an AI-powered assistant that provides real-time, context-aware support and dynamic quiz generation based on instructor-supplied materials; (3) automated test generators to streamline adaptive assessment and reduce administrative overhead; and (4) the EcoSmart Campus module, which autonomously regulates classroom lighting, air quality, and temperature using IoT sensors and actuators. Simulated evaluations demonstrate the system's effectiveness in delivering robust real-time monitoring, fostering inclusive engagement, preventing fraudulent practices, and supporting operational scalability. Collectively, the AIoT-Based Smart Education System offers a secure, adaptive, and efficient learning environment, providing a scalable blueprint for future educational innovation and improved student outcomes through the synergistic application of artificial intelligence and IoT technologies.
Cite
@article{arxiv.2510.26999,
title = {AIOT based Smart Education System: A Dual Layer Authentication and Context-Aware Tutoring Framework for Learning Environments},
author = {Adithya Neelakantan and Pratik Satpute and Prerna Shinde and Tejas Manjunatha Devang},
journal= {arXiv preprint arXiv:2510.26999},
year = {2025}
}