Preliminary Investigation on Location Estimation using Temperature Time Series Data obtained from Wearable Devices

Wearables Security 2022 - As it becomes easier to obtain various data from wearable devices, it is known that biometric and behavioral information must be handled with care. On the other hand, data on the surrounding environment, such as outside temperature, is seen as having a weak relationship with the wearer, and data handling is considered to be a chore. We believe that even data with weak relationships have the potential to infer information about the wearer if a large amount of data is acquired. In this paper, we verify whether it is possible to estimate the wearer’s location from time series data of outside air temperature using only the temperature sensor. We calculated the average absolute error between the temperature data from the wearable device and the same time-series data obtained from the Japan Meteorological Agency, and we evaluated the wearer’s position estimation. It was found that the location where the temperature was sampled appeared at the top of the estimation ranking, and that cities near the sampling location were estimated to be at the high ranking. It was also found that the number of data to be used can be a factor that increases the estimation ranking.

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Helsinki, Finland
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