Due to the opportunities provided by the Internet, people are taking advantage of e-learning courses and enormous research efforts have been dedicated to the development of e-learning systems. So far, many e-learning systems are proposed and used practically. However, in these systems the e-learning completion rate is low. One of the reasons is the low study desire and motivation. In this work, we present an IoT-Based E-Learning testbed using Raspberry Pi mounted on Raspbian. We carried out some experiments with a student of our laboratory for theta type of brain waves. We used MindWave Mobile (MWM) to get the data and considered four situations: sleeping, relaxing, active and moving. Then, we used mean-shift clustering algorithm to cluster the data. The evaluation results show that our tesbed can judge the human situation by using theta waves.
CITATION STYLE
Yamada, M., Cuka, M., Liu, Y., Oda, T., Matsuo, K., & Barolli, L. (2018). Performance evaluation of an iot-based e-learning testbed using mean-shift clustering approach considering theta type of brain waves. In Lecture Notes on Data Engineering and Communications Technologies (Vol. 8, pp. 62–72). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-319-65636-6_6
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