Soichiro Higuma presented his research “Towards estimating UV light intensity using GPS signal strength” at an in-conjunction workshop (WellComp2020) in ACM UbiComp2020

Soichiro Higuma presented his research “Towards estimating UV light intensity using GPS signal strength” at an in-conjunction workshop (WellComp2020) in ACM UbiComp2020

Soichiro Higuma, Yuuki Nishiyama, Kaoru Sezaki: Towards Estimating UV Light Intensity Using GPS Signal Strength. In: Adjunct Proceedings of the 2020 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2020 ACM International Symposium on Wearable Computers, pp. 684–687, Association for Computing Machinery, Virtual Event, Mexico, 2020, ISBN: 9781450380768.

Abstract

Due to recent urbanization and changing lifestyles, many people have been spending more time indoors. Hence, they tend to receive less direct sunlight than ever before. Although excessive/inadequate UV exposure can be harmful to human health leading to illnesses such as skin cancer, spots, or depression, moderate UV exposure is necessary for vitamin D production in the body. Therefore, estimating UV exposure with a commonly used device is useful for maintaining a healthy lifestyle from excessive/inadequate UV exposure in our daily life. In this study, we aim to estimate UV exposure, and to this end, we used the GPS signal strength (C/No) collected from an off-the-shelf smartphone for exploring the relationship between UV values and C/No. We conducted an experiment and measured UV values and C/No from 10 places in two different situations. From the results, we observed a significant correlation (R2 more than 0.87) between UV values and C/No when all the data were divided by the sun/shade condition. This result supports the fact that UV values potentially can be inferred from C/No to some degree if the sun/shade condition can be detected.

Soichiro Higuma presented his research “Towards estimating UV light intensity using GPS signal strength” at an in-conjunction workshop (WellComp2020) in ACM UbiComp2020