Estimation of air temperature using smartphones in different contexts

Abstract

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.