Date
Publisher
arXiv
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.
Study at a glance
- Question: Can an integrated AI and IoT system reliably support automated attendance, personalized tutoring, quiz generation, and classroom environmental control?
- Setting and data: Simulated hardware and software environments using Wokwi, Streamlit, and Python command-line tools; no human participants or field locations specified.
- Method: System development and prototype simulation.
Why it matters
Classrooms face persistent challenges including attendance fraud, disengagement, lack of personalized support, and inefficient resource use, while fully integrated AI and IoT systems remain rare due to interoperability, security, and scalability hurdles.
Key findings
- Simulations showed that the dual-factor authentication system reliably detected credentials and connected to WiFi to prevent fraudulent attendance check-ins.
- The AI-powered classroom assistant delivered timely, pedagogically aligned responses with low latency using local vector retrieval and cached document embeddings.
- The AI test generator consistently parsed course documents and automatically created five varied multiple-choice questions per session across different difficulty levels.
Summary drafted with AI from the full paper and may contain errors. See the full paper for details.
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