Real-time Gradient-Aware Indigenous AQI Estimation IoT Platform
Real-time Gradient-Aware Indigenous AQI Estimation IoT Platform
Date
2020-12
item.page.datecreated
Authors
Tariq, Hasan
Abdaoui, Abderrazak
Touati, Farid
Al Hitmi, Mohammad Abdullah
Crescini, Damiano
Mnaouer, Adel Ben
Journal Title
Journal ISSN
Volume Title
Publisher
ASTES Publishers
Abstract
Environmental monitoring has gained significant importance in outdoor air quality measurement and assessment for fundamental survival as well as ambient assisted living. In real-time outdoor urban scale, instantaneous air quality index estimation, the electrochemical sensors warm-up time, cross-sensitivity computation-error, geo-location typography, instantaneous capacity or back up time; and energy efficiency are the six major challenges. These challenges lead to real-time gradient anomalies that effect the accuracy and pro-longed lags in air quality index mapping campaigns for state and environmental/meteorological agencies. In this work, a gradient-aware, multi-variable air quality sensing node is proposed with event-triggered sensing based on position, gas magnitudes, and cross-sensitivity interpolation. In this approach, temperature, humidity, pressure, geo-position, photovoltaic power, volatile organic compounds, particulate matter (2.5), ozone, Carbon mono-oxide, Nitrogen dioxide, and Sulphur dioxide are the principle variables. Results have shown that the proposed system optimized the real-time air quality monitoring for the chosen geo-spatial cluster (Qatar University). © 2020 ASTES Publishers. All rights reserved.
Description
This article is not available at CUD collection. The version of scholarly record of this article is published in Advances in Science, Technology and Engineering Systems (2020), available online at: https://doi.org/10.25046/aj0506198
item.page.type
Article
item.page.format
Keywords
Air quality , Gas sensors node , IoT , Mapping , Multi-variable environmental
Citation
Tariq, H., Abdaoui, A., Touati, F., Hitmi, M.A.A., Crescini, D. & Mnaouer, A.B. (2020). Real-time Gradient-Aware Indigenous AQI Estimation IoT Platform. Advances in Science, Technology and Engineering Systems Journal, 5(6), pp. 1666-1673. https://doi.org/10.25046/aj0506198