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Performance Evaluation of an IoT-Based E-Learning Testbed Using Mean-Shift Clustering Approach Considering Gamma Type of Brain Waves

  • Masafumi Yamada
  • Miralda Cuka
  • Yi liu
  • Kevin Bylykbashi
  • Keita Matsuo
  • Leonard Barolli
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 12)

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.

Keywords

Internet of Things Testbed Raspberry Pi Raspbian MindWave Mobile Mean-shift Gamma type 

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Masafumi Yamada
    • 1
  • Miralda Cuka
    • 1
  • Yi liu
    • 1
  • Kevin Bylykbashi
    • 2
  • Keita Matsuo
    • 3
  • Leonard Barolli
    • 3
  1. 1.Graduate School of EngineeringFukuoka Institute of Technology (FIT)FukuokaJapan
  2. 2.Faculty of Information TechnologyPolytechnic University of TiranaTiranaAlbania
  3. 3.Department of Information and Communication EngineeringFukuoka Institute of Technology (FIT)FukuokaJapan

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