AIOT based Smart Education System: A Dual Layer Authentication and Context-Aware Tutoring Framework for Learning Environments
October 30, 2025 Β· Declared Dead Β· π arXiv.org
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Authors
Adithya Neelakantan, Pratik Satpute, Prerna Shinde, Tejas Manjunatha Devang
arXiv ID
2510.26999
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.AI
Citations
0
Venue
arXiv.org
Last Checked
4 months ago
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.
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