@inproceedings{10.1145/3410530.3414434,
title = {Towards Estimating UV Light Intensity Using GPS Signal Strength},
author = {Soichiro Higuma and Yuuki Nishiyama and Kaoru Sezaki},
url = {https://doi.org/10.1145/3410530.3414434},
doi = {10.1145/3410530.3414434},
isbn = {9781450380768},
year = {2020},
date = {2020-09-13},
urldate = {2020-09-13},
booktitle = {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},
pages = {684–687},
publisher = {Association for Computing Machinery},
address = {Virtual Event, Mexico},
series = {UbiComp-ISWC '20},
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.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}