IoT-Enabled Remote Teaching Management and Interaction: A Smart Framework for Real-Time Engagement and Environment Optimization

Abstract

The shift to remote teaching has accelerated the demand for intelligent systems that can sustain high engagement and manage virtual classroom environments effectively. This paper proposes an IoT-enabled framework for remote teaching management and interaction that integrates environmental control, behavioral sensing, and real-time feedback mechanisms. The system adopts a three-tier architecture comprisinga perception layer with IoT sensors and edge computing nodes for data collection and preprocessing, a network layer that manages secure communication via the MQTT protocol, and an application layer offering cloud-based analytics, PID control, and user interfaces. This architecture enables precise regulation of temperature and lighting through PID control, as well as real-time tracking of student engagement using multimodal sensing and scoring algorithms. Extensive experiments involving 100 students and six comparison methods demonstrate the superiority of the proposed system in terms of engagement score, environmental stability (RMSE), delay, and instructor satisfaction. Quantitative metrics and visual analyses reveal that our solution reduces average data transmission latency to 21.4 ms and increases engagement by 12% over existing smart classroom models. These findings underscore the potential of IoT-driven intelligent frameworks in enhancing the interactivity, efficiency, and comfort of remote learning environments.