Epidemic contact tracing with smartphone sensors
release_3jdqwlqrizayhbpgocxc2kghyy
by
Khuong An Nguyen, Zhiyuan Luo, Chris Watkins
2020
Abstract
Contact tracing is widely considered as an effective procedure in the fight
against epidemic diseases. However, one of the challenges for technology based
contact tracing is the high number of false positives, questioning its
trust-worthiness and efficiency amongst the wider population for mass adoption.
To this end, this paper proposes a novel, yet practical smartphone based
contact tracing approach, employing WiFi and acoustic sound for relative
distance estimate, in addition to the ambient air pressure and magnetic field
environment matching. We present a model combining 6 smartphone sensors,
prioritising some of them when certain conditions are met. We empirically
verified our approach in various realistic environments to demonstrate an
achievement of up to 95% fewer false positives, and 62% more accurate than
Bluetooth-only system. To the best of our knowledge, this paper was one of the
first work to propose a combination of smartphone sensors for contact tracing.
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