Journals
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Inproceedings
Soichiro Higuma, Kosuke Hatai, Yuuki Nishiyama, Kaoru Sezaki
Towards Estimating UV Exposure Using GPS Signal Strength from a Carrying Smartphone Inproceedings Refereed
In: 2021 IEEE International Conference on Smart Computing (SMARTCOMP), pp. 299-304, IEEE, Irvine, Orange County, California, USA (Virtual Workshop), 2021, ISBN: 2693-8340.
@inproceedings{edgedl2021-uv,
title = {Towards Estimating UV Exposure Using GPS Signal Strength from a Carrying Smartphone},
author = {Soichiro Higuma and Kosuke Hatai and Yuuki Nishiyama and Kaoru Sezaki},
url = {https://www.smart-comp.info/},
doi = {10.1109/SMARTCOMP52413.2021.00063},
isbn = {2693-8340},
year = {2021},
date = {2021-08-23},
urldate = {2021-08-23},
booktitle = {2021 IEEE International Conference on Smart Computing (SMARTCOMP)},
pages = {299-304},
publisher = {IEEE},
address = {Irvine, Orange County, California, USA (Virtual Workshop)},
abstract = {Owing to lifestyle changes, urbanization, and the COVID-19 pandemic, many people spend more time indoors and tend to receive less direct sunlight than before. Although excessive or inadequate ultraviolet (UV) exposure can be harmful to our physical and mental health, moderate UV exposure is essential for vitamin D (VD) production in the body. In this study, we estimate the UV exposure using an off-the-shelf smartphone, and explore the relationship between the UV values and GPS signal strength (C/N0). The results demonstrate that a strong correlation (R 2 = 0.73) between the UV values and carrier to noise density (C/N0) even if the smartphone and UV sensor are moved. Therefore, it is possible to estimate the UV exposure to some extent from a person's location, even while carrying a smartphone.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Soichiro Higuma, Yuuki Nishiyama, Kaoru Sezaki
Towards Estimating UV Light Intensity Using GPS Signal Strength Inproceedings Refereed
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.
@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}
}
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