Implementation of an IoT-Based E-Learning Testbed: Performance Evaluation Using Mean-Shift Clustering Approach Considering Four Types of BrainWaves
Keita Matsuo, Masafumi Yamada, Kevin Bylykbashi, Miralda Cuka, Yi Liu, Leonard Barolli · 2018
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 Mind Wave 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 delta, theta, gamma and alpha brain waves.