Emotion-Aware Classroom Quality Assessment Leveraging IoT-Based Real-Time Student Monitoring

TL;DR

This paper introduces an IoT-based affective computing framework for real-time emotional monitoring in classrooms, improving engagement detection and providing a scalable tool for enhancing educational experiences.

Contribution

It presents a novel, practical IoT framework for emotion-aware classrooms and introduces the Classroom Emotion Dataset for further research validation.

Findings

Achieved 88% accuracy in classifying engagement states

Detected up to 50 faces at 25 FPS in real-time

Received positive feedback from users on classroom interaction improvements

Abstract

This study presents high-throughput, real-time multi-agent affective computing framework designed to enhance classroom learning through emotional state monitoring. As large classroom sizes and limited teacher student interaction increasingly challenge educators, there is a growing need for scalable, data-driven tools capable of capturing students' emotional and engagement patterns in real time. The system was evaluated using the Classroom Emotion Dataset, consisting of 1,500 labeled images and 300 classroom detection videos. Tailored for IoT devices, the system addresses load balancing and latency challenges through efficient real-time processing. Field testing was conducted across three educational institutions in a large metropolitan area: a primary school (hereafter school A), a secondary school (school B), and a high school (school C). The system demonstrated robust performance, detecting up to 50 faces at 25 FPS and achieving 88% overall accuracy in classifying classroom engagement states. Implementation results showed positive outcomes, with favorable feedback from students, teachers, and parents regarding improved classroom interaction and teaching adaptation. Key contributions of this research include establishing a practical, IoT-based framework for emotion-aware learning environments and introducing the 'Classroom Emotion Dataset' to facilitate further validation and research.