Low cost air quality monitoring: comparing the energy consumption of an arduino against a raspberry Pi based system

Okigbo, Chekwube A., Seeam, Amar, Guness, Shivanand P., Bellekens, Xavier, Bekaroo, Girish ORCID: https://orcid.org/0000-0003-1753-4300 and Ramsurrun, Visham (2020) Low cost air quality monitoring: comparing the energy consumption of an arduino against a raspberry Pi based system. Madhavje, Krishnaraj and Soyjaudah, Sunjiv, eds. Proceedings of the 2nd International Conference on Intelligent and Innovative Computing Applications. In: ICONIC'20, 24-25 Sept 2020, Plaine Magnien, Mauritius. ISBN 9781450375580. [Conference or Workshop Item] (doi:10.1145/3415088.3415124)

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Abstract

Air pollution is one of the great challenges facing modern cities. According to the World Health Organization (WHO), 80% of people living in cities with air quality monitoring facilities are living in conditions where the quality of the air is well beyond the limits set out in the air quality guidelines. As more and more people are projected to move into urban areas by 2050, this problem is going to keep on increasing. A possible solution could be the advent of Smart Cities. One of the objectives of Smart Cities is to provide a better living environment to its inhabitants. With the Internet of Things providing easily deployable, low power, low cost air quality monitoring sensors and the resources to process the huge amount of data collected, this objective could be reached. In this paper, we propose an evaluation of the power consumption of two low cost air quality monitoring systems - one based on an Arduino and the other on a Raspberry Pi system. The air quality systems proposed are based on off-the shelf hardware and are easy to assemble and maintain. The proposed systems use Bluetooth Low Energy (BLE) to transmit data while being collected through a mobile app on a smartphone. The data was collected for five days and it was found by performing an ANOVA on the power consumption that there was a significant difference in the mean energy consumption of the two systems.

Item Type: Conference or Workshop Item (Paper)
Research Areas: A. > School of Science and Technology
Item ID: 31115
Notes on copyright: Copyright © 2020 ACM. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Proceedings of the 2nd International Conference on Intelligent and Innovative Computing Applications, https://doi.org/10.1145/3415088.3415124
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Depositing User: Jisc Publications Router
Date Deposited: 05 Oct 2020 09:21
Last Modified: 10 Jun 2021 00:22
URI: https://eprints.mdx.ac.uk/id/eprint/31115

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