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An Internet of Things Platform for Air Station Remote Sensing and Smart Monitoring

David Corral-Plaza1, Juan Boubeta-Puig1, Guadalupe Ortiz1, Alfonso Garcia-de-Prado2,*

1 Department of Computer Science and Engineering, University of Cadiz, Avda. de la Universidad de Cádiz no 10, 11519, Puerto Real, Cádiz, Spain
2 Department of Computer Technology and Architecture, University of Cadiz, Avda. de la Universidad de Cádiz no 10, 11519, Puerto Real, Cádiz, Spain

* Corresponding Author: {david.corral, juan.boubeta, guadalupe.ortiz, alfonso.garciadeprado}@uca.es

Computer Systems Science and Engineering 2020, 35(1), 5-12. https://doi.org/10.32604/csse.2020.35.005

Abstract

Air pollution is currently receiving more attention by international governments and organizations. Nevertheless, current systems for air quality monitoring lack essential requirements which are key in order to be effective concerning users’ access to the information and efficient regarding real-time monitoring and notification. This paper presents an Internet of Things platform for air station remote sensing and smart monitoring that combines Big Data and Cloud Computing paradigms to process and correlate air pollutant concentrations coming from multiple remote stations, as well as to trigger automatic and personalized alerts when a health risk for their particular context is detected. This platform has been tested by analyzing the results of observing Andalusian, South of Spain, sensor network during a long period of time. The results show that this novel solution can help to reduce the impact of air pollution on human health since citizens are alerted in real time.

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Cite This Article

D. Corral-Plaza, J. Boubeta-Puig, G. Ortiz and A. Garcia-de-Prado, "An internet of things platform for air station remote sensing and smart monitoring," Computer Systems Science and Engineering, vol. 35, no.1, pp. 5–12, 2020. https://doi.org/10.32604/csse.2020.35.005

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cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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