Paper Contents
Abstract
Abstract - A new era of smart classrooms has begun with the incorporation of Internet of Things (IoT) technologies, completely changing how teachers and students teach and learn. This research presents a stable and efficient Internet of Things-driven architecture for analyzing how students perform in smart classrooms. The framework provides current knowledge about student interactions, engagement, and academic success by utilizing an interconnected network of devices, sensors, and data analytics. IoT sensors that are thoughtfully positioned throughout the classroom to collect a variety of data points, including student attendance, engagement, and biometric data, are among the framework's essential elements. A central data hub receives this data for processing and analysis in real-time. To identify both group and individual achievement indicators, machine learning algorithms are utilized to extract significant variations and patterns from the data. Teachers can use the resultant insights to modify their lesson plans, provide challenging students with timely interventions, and enhance the atmosphere of learning for better results. Security and privacy were given top priority when designing this framework. The suggested IoT-driven framework offers teachers and educational institutions data-driven tools to improve teaching strategies and student outcomes, which has the potential to greatly improve the educational experience. Through the development of a more dynamic and flexible learning environment, this framework hopes to support the continued advancement of smart classrooms in the age of digital technology.Keywords: IoT, Smart Classrooms, RFID, Student Performance Analysis, Data Analytics, Machine Learning, Privacy, Security.
Copyright
Copyright © 2023 D HEMA PRIYA. This is an open access article distributed under the Creative Commons Attribution License.
