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Real-Time Emotion Assessment System in Smart Classrooms Using Wearable Bracelets

Authors:
Edgar Batista
Laia Cot
Valeria Pérez
Antoni Martínez-Ballesté

Keywords: smart classroom; emotions; bracelets; wearables; EmotiBit; artificial intelligence; education.

Abstract:
Smart classrooms are the next frontier in education to accelerate and improve both teaching and learning processes. These environments integrate sensors, ubiquitous computing systems, Artificial Intelligence (AI) techniques, and high-speed data networks to create more cognitive, effective, interactive, and adaptive learning settings. Among other applications, students' emotions are key to maintain a positive learning atmosphere. Unlike traditional video analysis approaches, emotions can be detected through physiological data, such as electrodermal activity, heart rate, and skin temperature, which can be collected using non-invasive and user-friendly wearable devices. To this end, this paper presents a real-time emotion assessment system intended for both students and teachers within smart classrooms. A prototype has been developed using EmotiBit bracelets and a Raspberry Pi. Initial testing in laboratory settings has shown the system could smoothly run in off-the-shelf technology. However, the deployment of this system in real-world classrooms reveals several challenges that must be addressed, namely data volume, battery duration, data security concerns, and the lack of training datasets for the AI model.

Pages: 36 to 41

Copyright: Copyright (c) IARIA, 2024

Publication date: September 29, 2024

Published in: conference

ISSN: 2308-4278

ISBN: 978-1-68558-191-6

Location: Venice, Italy

Dates: from September 29, 2024 to October 3, 2024