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Collaborative Internet of Things (C-IOT): correlation of physiological and performance measure for develop interactivity metric

Bandara, Indra; Ioras, F. and Kaner, J. (2016). Collaborative Internet of Things (C-IOT): correlation of physiological and performance measure for develop interactivity metric. In: ICERI2016 Proceedings, 14-16 Nov 2016, Seville, Spain, IATED, pp. 3393–3400.

DOI (Digital Object Identifier) Link: https://doi.org/10.21125/iceri.2016.1792
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Abstract

Nowadays the trend is toward increasing internet capabilities into an expanding number of devices and sensor connectivity creating an “Internet of Things (IoT)”. These new distributed dispensation and networked devices will provide an adaptable learning ability, real-time video analytics, data acquisition, and gamification techniques. This is becoming core to engagement strategy for development of innovative mobile learning (m-Learning) interactivity systems.


Eyes are considered to be the most powerful human sense. Intelligent video camera captures and analyse spontaneous eye blink that was consistently dependent on the activities of subjective behaviors. This information has been used by the authors to develop interactivity metric. In this empirical study authors research on development of a new metric that analyse the user interaction to virtual reality (VR) activities that positively affect learning when applied to any application. Also, authors discuss how the effectiveness and user interaction is influenced by implementation of VR activities in m-Learning environment.


Moreover, the authors present innovative system architecture to exemplify how user interactivity responsiveness is enhanced by the proposed novel metric based on correlation of physiological and performance measures using multiple interconnected sensor system. This collaborative IoT system and metric are being included in a personalized intelligent mobile learning system in order to improve user engagement by enriching the learning experience.


IoT system supported by physiological and performance measure of m-learning users’ responsiveness to VR activities are presented by the present article as a viable solution for improving participants learning experience in an environment defined by smart objects and gamification. The data analyses and new metric solution underline C-IOT as a powerful tool in education.

Item Type: Conference or Workshop Item
ISBN: 84-617-5895-1, 978-84-617-5895-1
ISSN: 2340-1095
Keywords: internet of things (iot); gamification; smart objects; system architecture; m-learning; vr
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 59098
Depositing User: Indra Bandara
Date Deposited: 14 Feb 2019 12:39
Last Modified: 29 Mar 2019 11:33
URI: http://oro.open.ac.uk/id/eprint/59098
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