Abstract—The Internet of Things (IoT) concept is one of the
most popular concepts that can be applied from simple things to
the smart appliances of today. IoT also helps human life to be
more convenient and easier. IoT for learning and teaching in
higher education is so important to help students gain their
knowledge and experience before graduation and industrial
work. An Introduction of IoT course for undergraduate
students mostly focuses on the IoT concepts and fundamentals
which may affect learners to understand well about the
concepts. To apply those concepts into practice is still quite
difficult for learners. This article proposes the development of a
learning kit for the Smart Transformer Detection System using
IoT as teaching material. The capability of this tool can help
learners automatically detect and notify events using online
tools. Moreover, it helps students monitor the transformer
system with IoT concepts more clearly, practically, and
understandingly. The study volunteered a sample group of
students who used this kit in their learning and practices. Then,
the sample did a survey on learning satisfaction. The results
show that students were very satisfied with both accuracy of the
work system and the quality of the learning kit.
Index Terms—Internet of things (IoT), learning kit, transformer, undergraduate students.
Chanudon Chueapram, Kanyama Kamata, and Tanapoom Rueangphaisan are King Mongkut’s University of Technology Thonburi, Thailand (e-mail: firstname.lastname@example.org, email@example.com, firstname.lastname@example.org).
Yuwarat Srisupawong is with National Broadcasting and Telecommunications Commission, Thailand (e-mail: email@example.com).
Noritsugu Kamata is with Tokyo Denki University, Japan (e-mail: firstname.lastname@example.org).
Cite: Chanudon Chueapram, Kanyama Kamata, Tanapoom Rueangphaisan, Yuwarat Srisupawong, and Noritsugu Kamata, "Development of the Smart Transformer Detection Learning Kit Using IoT," International Journal of Information and Education Technology vol. 12, no. 11, pp. 1191-1197, 2022.Copyright © 2022 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).