Abstract
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 gamma 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 testbed can judge the human situation by using gamma waves.
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Yamada, M., Cuka, M., liu, Y., Bylykbashi, K., Matsuo, K., Barolli, L. (2018). Performance Evaluation of an IoT-Based E-Learning Testbed Using Mean-Shift Clustering Approach Considering Gamma Type of Brain Waves. In: Barolli, L., Xhafa, F., Conesa, J. (eds) Advances on Broad-Band Wireless Computing, Communication and Applications. BWCCA 2017. Lecture Notes on Data Engineering and Communications Technologies, vol 12. Springer, Cham. https://doi.org/10.1007/978-3-319-69811-3_60
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DOI: https://doi.org/10.1007/978-3-319-69811-3_60
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