Maximum likelihood estimation of ground truth for air quality monitoring using vehicular sensor networks
Various works on vehicular sensor networks (VSNs) for air quality monitoring use solid-state gas sensors due to its low cost and compact form factor. However, solid-state gas sensors have poor selectivity and are sensitive to ambient temperature and relative humidity. In addition, the sensitivity an...
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sg-ntu-dr.10356-1027822020-03-07T13:24:51Z Maximum likelihood estimation of ground truth for air quality monitoring using vehicular sensor networks Talampas, Marc Caesar R. Low, Kay-Soon. School of Electrical and Electronic Engineering IEEE Region 10 Conference (TENCON) (2012 : Cebu, Philippines) DRNTU::Engineering::Electrical and electronic engineering Various works on vehicular sensor networks (VSNs) for air quality monitoring use solid-state gas sensors due to its low cost and compact form factor. However, solid-state gas sensors have poor selectivity and are sensitive to ambient temperature and relative humidity. In addition, the sensitivity and accuracy of solid-state gas sensors degrade over time due to aging effects. Frequent recalibration of these sensors are required to maintain the accuracy of their measurements. In large VSNs, it is impractical to manually calibrate each node. Thus, calibration must be performed automatically and in-field. Assuming that the gas concentration is homogenous within an area, co-located VSN nodes can either: (1) copy measurements from a highly accurate fixed station in their immediate vicinity, or, in the absence of a fixed station, (2) collaboratively estimate the ground truth. In this work, we use maximum likelihood estimation for determining the ground truth gas concentration in an area by fusing information from co-located sensors in a VSN. Through simulations, we show that the absolute errors of the proposed method has lower mean and standard deviation as compared with existing work. 2013-10-10T08:06:03Z 2019-12-06T21:00:10Z 2013-10-10T08:06:03Z 2019-12-06T21:00:10Z 2012 2012 Conference Paper Talampas, M. C. R., & Low, K. S. (2012). Maximum likelihood estimation of ground truth for air quality monitoring using vehicular sensor networks. TENCON 2012 - 2012 IEEE Region 10 Conference, pp.1-6. https://hdl.handle.net/10356/102782 http://hdl.handle.net/10220/16430 10.1109/TENCON.2012.6412308 en |
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DRNTU::Engineering::Electrical and electronic engineering Talampas, Marc Caesar R. Low, Kay-Soon. Maximum likelihood estimation of ground truth for air quality monitoring using vehicular sensor networks |
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Various works on vehicular sensor networks (VSNs) for air quality monitoring use solid-state gas sensors due to its low cost and compact form factor. However, solid-state gas sensors have poor selectivity and are sensitive to ambient temperature and relative humidity. In addition, the sensitivity and accuracy of solid-state gas sensors degrade over time due to aging effects. Frequent recalibration of these sensors are required to maintain the accuracy of their measurements. In large VSNs, it is impractical to manually calibrate each node. Thus, calibration must be performed automatically and in-field. Assuming that the gas concentration is homogenous within an area, co-located VSN nodes can either: (1) copy measurements from a highly accurate fixed station in their immediate vicinity, or, in the absence of a fixed station, (2) collaboratively estimate the ground truth. In this work, we use maximum likelihood estimation for determining the ground truth gas concentration in an area by fusing information from co-located sensors in a VSN. Through simulations, we show that the absolute errors of the proposed method has lower mean and standard deviation as compared with existing work. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Talampas, Marc Caesar R. Low, Kay-Soon. |
format |
Conference or Workshop Item |
author |
Talampas, Marc Caesar R. Low, Kay-Soon. |
author_sort |
Talampas, Marc Caesar R. |
title |
Maximum likelihood estimation of ground truth for air quality monitoring using vehicular sensor networks |
title_short |
Maximum likelihood estimation of ground truth for air quality monitoring using vehicular sensor networks |
title_full |
Maximum likelihood estimation of ground truth for air quality monitoring using vehicular sensor networks |
title_fullStr |
Maximum likelihood estimation of ground truth for air quality monitoring using vehicular sensor networks |
title_full_unstemmed |
Maximum likelihood estimation of ground truth for air quality monitoring using vehicular sensor networks |
title_sort |
maximum likelihood estimation of ground truth for air quality monitoring using vehicular sensor networks |
publishDate |
2013 |
url |
https://hdl.handle.net/10356/102782 http://hdl.handle.net/10220/16430 |
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1681039305714171904 |