Estimation of air temperature using smartphones in different contexts

Measuring air temperature at a high spatial resolution is very important for many applications including detection of urban heat islands. However, air temperature is currently measured by weather stations those are very sparse spatially. In this paper, we propose a new approach to estimate air tempe...

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Main Author: Nguyen Hai Chau
Format: Article
Language:English
Published: Taylor & Francis Group 2019-10-01
Series:Journal of Information and Telecommunication
Subjects:
Online Access:http://dx.doi.org/10.1080/24751839.2019.1634869
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spelling doaj-2b20b0693701428d86e67c41def607012020-11-25T01:46:19ZengTaylor & Francis GroupJournal of Information and Telecommunication2475-18392475-18472019-10-013449450710.1080/24751839.2019.16348691634869Estimation of air temperature using smartphones in different contextsNguyen Hai Chau0VNU University of Engineering and TechnologyMeasuring air temperature at a high spatial resolution is very important for many applications including detection of urban heat islands. However, air temperature is currently measured by weather stations those are very sparse spatially. In this paper, we propose a new approach to estimate air temperature using smartphones in different contexts. Most of the smartphones are not equipped with air temperature sensors but they are all equipped with battery temperature sensors. When a smartphone is in idle state, its battery temperature is stable and correlated with ambient air temperature. Furthermore, it is often carried close to human body, e.g. in pockets of coats, trousers and in hand. Therefore we developed a new approach of using two linear regression models to estimate air temperature from the idle smartphones battery temperature given their in-pocket or out-of-pocket positions. Lab test results show that the new approach is better than an existing one in mean absolute error and coefficient of determination metrics. Advantages of the new approach include the simplicity of implementation on smartphones and the ability for creating maps of temperature distribution. However, this approach needs field tests on more smartphone models to achieve its robustness.http://dx.doi.org/10.1080/24751839.2019.1634869smartphonebattery temperatureinternet of thingscrowdsourcing
collection DOAJ
language English
format Article
sources DOAJ
author Nguyen Hai Chau
spellingShingle Nguyen Hai Chau
Estimation of air temperature using smartphones in different contexts
Journal of Information and Telecommunication
smartphone
battery temperature
internet of things
crowdsourcing
author_facet Nguyen Hai Chau
author_sort Nguyen Hai Chau
title Estimation of air temperature using smartphones in different contexts
title_short Estimation of air temperature using smartphones in different contexts
title_full Estimation of air temperature using smartphones in different contexts
title_fullStr Estimation of air temperature using smartphones in different contexts
title_full_unstemmed Estimation of air temperature using smartphones in different contexts
title_sort estimation of air temperature using smartphones in different contexts
publisher Taylor & Francis Group
series Journal of Information and Telecommunication
issn 2475-1839
2475-1847
publishDate 2019-10-01
description Measuring air temperature at a high spatial resolution is very important for many applications including detection of urban heat islands. However, air temperature is currently measured by weather stations those are very sparse spatially. In this paper, we propose a new approach to estimate air temperature using smartphones in different contexts. Most of the smartphones are not equipped with air temperature sensors but they are all equipped with battery temperature sensors. When a smartphone is in idle state, its battery temperature is stable and correlated with ambient air temperature. Furthermore, it is often carried close to human body, e.g. in pockets of coats, trousers and in hand. Therefore we developed a new approach of using two linear regression models to estimate air temperature from the idle smartphones battery temperature given their in-pocket or out-of-pocket positions. Lab test results show that the new approach is better than an existing one in mean absolute error and coefficient of determination metrics. Advantages of the new approach include the simplicity of implementation on smartphones and the ability for creating maps of temperature distribution. However, this approach needs field tests on more smartphone models to achieve its robustness.
topic smartphone
battery temperature
internet of things
crowdsourcing
url http://dx.doi.org/10.1080/24751839.2019.1634869
work_keys_str_mv AT nguyenhaichau estimationofairtemperatureusingsmartphonesindifferentcontexts
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