Abstract
Nowadays, increasing air-pollution levels are a public health concern that affects all living beings, with the most polluting gases being present in urban environments. For this reason, this research presents portable Internet of Things (IoT) environmental monitoring devices that can be installed in vehicles and that send message queuing telemetry transport (MQTT) messages to a server, with a time series database allocated in edge computing. The visualization stage is performed in cloud computing to determine the city air-pollution concentration using three different labels: low, normal, and high. To determine the environmental conditions in Ibarra, Ecuador, a data analysis scheme is used with outlier detection and supervised classification stages. In terms of relevant results, the performance percentage of the IoT nodes used to infer air quality was greater than 90%. In addition, the memory consumption was 14 Kbytes in a flash and 3 Kbytes in a RAM, reducing the power consumption and bandwidth needed in traditional air-pollution measuring stations.
| Original language | English |
|---|---|
| Article number | 7015 |
| Journal | Sensors |
| Volume | 22 |
| Issue number | 18 |
| ISSN | 1424-8220 |
| DOIs | |
| Publication status | Published - 13 Sept 2022 |
Keywords
- Internet-of-Things
- air quality
- Machine Learning
- data analysis
- Environmental sustainability
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- 2 Journal article
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Smart Farming Robot for Detecting Environmental Conditions in a Greenhouse
Rosero, P., Gordillo, C. & Hernandez, W., 8 Jun 2023, In: IEEE Access. 11Research output: Journal Article or Conference Article in Journal › Journal article › Research › peer-review
Open Access -
Statistical Analysis of the Impact of COVID-19 on PM2.5 Concentrations in Downtown Quito during the Lockdowns in 2020
Hernandez, W., Arques-Orobon, F., Gonzales-Posadas, V., Jimenez-Martin, J. L. & Rosero, P., 6 Nov 2022, In: Sensors. 8985.Research output: Journal Article or Conference Article in Journal › Journal article › Research › peer-review
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