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Sustainability 2016, 8(9), 881; doi:10.3390/su8090881

A Comprehensive Real-Time Indoor Air-Quality Level Indicator

1
Department of Computer Science & Engineering, Soongsil University, Seoul 156-743, Korea
2
Department of Embedded Systems Engineering, Incheon National University, Incheon 402-772, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Marc A. Rosen
Received: 1 May 2016 / Revised: 29 August 2016 / Accepted: 30 August 2016 / Published: 1 September 2016
(This article belongs to the Special Issue Advanced IT based Future Sustainable Computing)
View Full-Text   |   Download PDF [5056 KB, uploaded 1 September 2016]   |  

Abstract

The growing concern about Indoor Air-Quality has accelerated the development of small, low-cost air-quality monitoring systems. These systems are capable of monitoring various indoor air pollutants in real time, notifying users about the current air-quality status and gathering the information to the central server. However, most Internet of Things (IoT)-based air-quality monitoring systems numerically present the sensed value per pollutant, making it difficult for general users to identify how polluted the air is. Therefore, in this paper, we first introduce a tiny air-quality monitoring system that we developed and, based on the system, we also test the applicability of the comprehensive Air-Quality Index (AQI), which is widely used all over the world, in terms of its capacity for a comprehensive indoor air-quality indication. We also develop design considerations for an IoT-based air-quality monitoring system and propose a real-time comprehensive indoor air-quality level indication method, which effectively copes with dynamic changes and is efficient in terms of processing and memory overhead. View Full-Text
Keywords: indoor air-quality; air-quality index; real-time air-quality monitoring indoor air-quality; air-quality index; real-time air-quality monitoring
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Kang, J.; Hwang, K.-I. A Comprehensive Real-Time Indoor Air-Quality Level Indicator. Sustainability 2016, 8, 881.

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