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 design and implement an IoT-Based E-Learning testbed using Raspberry Pi mounted on Raspbian. We analyze the performance of mean shift clustering algorithm considering electroencephalogram data. For evaluation we considered attention value. The evaluation results show that by the mean shift clustering algorithm the learner concentration is increased.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
K. Matsuo, L. Barolli, F. Xhafa, V. Kolici, A. Koyama, A. Durresi, R. Miho, “Implementation of an E-Learning System Using P2P, Web and Sensor Technologies”, Proc. of AINA-2009, pp. 800-807, 2009.
M. G. Domingo, J. A. M. Forner, “Expanding the Learning Environment: Combining Physicality and Virtuality - The Internet of Things for eLearning”, Proc. of IEEE 10th International Conference on Advanced Learning Technologies (ICALT), pp. 730-731, 2010.
I. Gasparini, V. Eyharabide, S. Schiaffino, M. S. Pimenta, A. Amandi, J. P. M. de Oliveira, “Improving User Profiling for a Richer Personalization: Modeling Context in E-Learning”, Intelligent and Adaptive Learning Systems: Technology Enhanced Support for Learners and Teachers, Chapter 12, pp. 182-197, 2012.
V. de Freitas, V. P. Marcal, I. Gasparini, M. A. Amaral, M. L. Proenca Jr., M. A. C. Brunetto, M. S. Pimenta, C. H. F. P. Ribeiro, J. V. de Lima, J. P. M. de Oliveira, “AdaptWeb: an adaptive web-based courseware”, Proc. of ICTE-2002, pp. 131-134, 2002.
S. Schiaffino, P. Garcia, A. Amandi, “eTeacher: Providing personalized assistance to e-learning students”, Computers & Education, Vol. 51, pp. 1744-1754, 2008.
A. Zanella, N. Bui, A. Castellani, L. Vangelista, “Internet of Things for Smart Cities”, IEEE Internet of Things Journal, Vol. 1, No. 1, pp. 22-32, 2014.
L. Atzori, A. Iera, and G. Morabito, “The internet of things: A survey”, Comput. Netw., Vol. 54, No. 15, pp. 2787-2805, 2010.
P. Bellavista, G. Cardone, A. Corradi, and L. Foschini, “Convergence of MANET and WSN in IoT urban scenarios”, IEEE Sens. J., Vol. 13, No. 10, pp. 3558-3567, Oct. 2013.
R. Obukata, T. Oda, D. Elmazi, L. Barolli, K. Matsuo, I. Woungang, “Performance Evaluation of an Ambient Intelligence Testbed for Improving Quality of Life: Evaluation Using Clustering Approach”, The 9-th International Workshop on Intelligent Informatics and Natural Inspired Computing (IINIC-2016), Fukuoka Institute of Technology, Fukuoka, Japan, July 6-8, 2016.
K. G. Derpanis, “Mean shift clustering”, See http://www.cse.yorku.ca/~kosta/CompVis_Notes/mean_shift.pdf accessed on 14 September 2016.
O. Tuzel, F. Porikli, P. Meer, “Kernel methods for weakly supervised mean shift clustering”, IEEE 12th International Conference on Computer Vision, pp. 48-55, 2009.
D. Comaniciu, “Variable bandwidth density-based fusion”, In Proc. IEEE Conf. on Comp. Vis. and Pat. Recog., Madison, WI, Vol. 1, pp. 56-66, 2003.
D. Comaniciu and P. Meer, “Mean shift: A robust approach toward feature space analysis”, IEEE Trans. Pat. Anal. Mach. Intell., 24:603-619, 2002.
M. Yamada, T. Oda, K. Matsuo, L. Barolli, “Design of an IoT-Based E-Learning Testbed”, The 9-th International Symposium on Mining and Web (MAW-2016), pp. 720-724, 2016.
“Raspberry Pi Foundation.”, http://www.raspberrypi.org/.
T. Oda, A. Barolli, S. Sakamoto, L. Barolli, M. Ikeda, K. Uchida, “Implementation and Experimental Results of a WMN Testbed in Indoor Environment Considering LoS Scenario”, The 29-th IEEE International Conference on Advanced Information Networking and Applications (AINA-2015), pp. 37-42, 2015.
“NeuroSky to Release MindWave mobile”, http://mindwavemobile.neurosky.com.
W. Salabun, “Processing and spectral analysis of the raw EEG signal from the MindWave”, Przeglad Elektrotechniczny, Vol. 90, No. 2, pp. 169-174, February 2014.
K. Matsuo, L. Barolli, J. Arnedo-Moreno, F. Xhafa, A. Koyama, A. Durresi, “Experimental Results and Evaluation of SmartBox Stimulation Device in a P2P E-learning System”, Proc. of NBiS-2009, pp. 37-44, 2009.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Yamada, M., Oda, T., Liu, Y., Matsuo, K., Barolli, L. (2017). Performance Evaluation of an IoT-Based E-Learning Testbed Using Mean Shift Clustering Approach Considering Electroencephalogram Data. In: Barolli, L., Xhafa, F., Yim, K. (eds) Advances on Broad-Band Wireless Computing, Communication and Applications. BWCCA 2016. Lecture Notes on Data Engineering and Communications Technologies, vol 2. Springer, Cham. https://doi.org/10.1007/978-3-319-49106-6_54
Download citation
DOI: https://doi.org/10.1007/978-3-319-49106-6_54
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-49105-9
Online ISBN: 978-3-319-49106-6
eBook Packages: EngineeringEngineering (R0)