Wireless Sensor Networks for Learning Activity Monitoring: Design and Development
Kai Li, Toyohashi University of Technology, Japan
EdMedia + Innovate Learning, in Victoria, Canada ISBN 978-1-939797-03-2 Publisher: Association for the Advancement of Computing in Education (AACE), Waynesville, NC
This paper describes a design of sensor network for learning activities monitoring. Recent technological advances in sensors, low-power integrated circuits, and wireless communications have enabled the design of low cost, miniature, lightweight, and multimodal intelligent sensor networks. The paper presents a system architecture and hardware organization. With this sensor network for monitoring learning activities, teacher or parents could monitor or analyze learners’ activities for better learning.
Li, K. (2013). Wireless Sensor Networks for Learning Activity Monitoring: Design and Development. In J. Herrington, A. Couros & V. Irvine (Eds.), Proceedings of EdMedia 2013--World Conference on Educational Media and Technology (pp. 1053-1057). Victoria, Canada: Association for the Advancement of Computing in Education (AACE). Retrieved March 21, 2019 from https://www.learntechlib.org/primary/p/112090/.
© 2013 Association for the Advancement of Computing in Education (AACE)
- Bao, L., & Intille, S.S. (2004). Activity recognition from user-annotated acceleration data. In Pervasive Computing (pp. 1-17). Springer Berlin Heidelberg.
- Chen, Y.P., Yang, J.Y., Liou, S.N., Lee, G.Y., & Wang, J.S. (2008). Online classifier construction algorithm for human activity detection using a tri-axial accelerometer. Applied Mathematics and Computation, 205(2), 849-860.
- Egi, H., & Ozawa, S. (2012, March). AccelPen: Detecting Writing Action with Pen Acceleration Toward Learning Support Systems. In Wireless, Mobile and Ubiquitous Technology in Education (WMUTE), 2012 IEEE Seventh International Conference on (pp. 187-189). IEEE.
- Nobuhiro, O., Katsuhiko, K., & Nobuo, K. (2011). Effects of Number of Subjects on Activity Recognition Findings from HASC2010 corpus, International Workshop on Frontiers in Activity Recognition using Pervasive Sensing(IWFAR2011), pp. 48-51.
- Zhang,W., Zhang, L., Ding, Y., Miyaki, T., Gordon, D. And Beigl, M.(2011). Mobile sensing in metropolitan
These references have been extracted automatically and may have some errors. If you see a mistake in the references above, please contact firstname.lastname@example.org.