IoT-Enabled Wireless Sensor Networks for Air Pollution Monitoring with Extended Fractional-Order Kalman Filtering.
Sensors (Basel)
; 21(16)2021 Aug 06.
Article
in English
| MEDLINE | ID: covidwho-1348686
ABSTRACT
This paper presents the development of high-performance wireless sensor networks for local monitoring of air pollution. The proposed system, enabled by the Internet of Things (IoT), is based on low-cost sensors collocated in a redundant configuration for collecting and transferring air quality data. Reliability and accuracy of the monitoring system are enhanced by using extended fractional-order Kalman filtering (EFKF) for data assimilation and recovery of the missing information. Its effectiveness is verified through monitoring particulate matters at a suburban site during the wildfire season 2019-2020 and the Coronavirus disease 2019 (COVID-19) lockdown period. The proposed approach is of interest to achieve microclimate responsiveness in a local area.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Air Pollutants
/
Air Pollution
/
Internet of Things
/
COVID-19
Limits:
Humans
Language:
English
Year:
2021
Document Type:
Article
Affiliation country:
S21165313
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