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The Gamification in Education, Healthcare, and Industry

The Gamification in Education, Healthcare, and Industry

Puvvadi Baby Maruthi
Copyright: © 2021 |Pages: 27
ISBN13: 9781799847038|ISBN10: 1799847039|ISBN13 Softcover: 9781799870098|EISBN13: 9781799847045
DOI: 10.4018/978-1-7998-4703-8.ch011
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MLA

Baby Maruthi, Puvvadi. "The Gamification in Education, Healthcare, and Industry." Multimedia and Sensory Input for Augmented, Mixed, and Virtual Reality, edited by Amit Kumar Tyagi, IGI Global, 2021, pp. 206-232. https://doi.org/10.4018/978-1-7998-4703-8.ch011

APA

Baby Maruthi, P. (2021). The Gamification in Education, Healthcare, and Industry. In A. Tyagi (Ed.), Multimedia and Sensory Input for Augmented, Mixed, and Virtual Reality (pp. 206-232). IGI Global. https://doi.org/10.4018/978-1-7998-4703-8.ch011

Chicago

Baby Maruthi, Puvvadi. "The Gamification in Education, Healthcare, and Industry." In Multimedia and Sensory Input for Augmented, Mixed, and Virtual Reality, edited by Amit Kumar Tyagi, 206-232. Hershey, PA: IGI Global, 2021. https://doi.org/10.4018/978-1-7998-4703-8.ch011

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Abstract

Wireless sensor networks (WSN) consist of large numbers of sensor nodes, which are limited in battery power and communication range and have multi-modal sensing capabilities. In this chapter, energy-efficient data aggregation technique is proposed to improve the lifetime of the sensor. Here, the author has used three layer architecture by deploying mobile element/node, which can periodically visit cluster heads (CHs) at which first level data aggregation has been applied to eliminate redundancy. After collecting data from all CHs, mobile element itself will perform second level of data aggregation to eliminate further redundancy. After collecting data from CHs, mobile element will move towards base station/sink and transmits data to base station/sink in order to save energy of entire network. Here, the author has made an attempt to prove that in WSN during data gathering if mobile elements are used to collect the aggregated data from CHs, energy consumption of the entire network will be reduced. The proposed data aggregation with mobile node helps in improving the lifetime of the WSN.

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