论文标题
智能手机传感器的流行接触跟踪
Epidemic contact tracing with smartphone sensors
论文作者
论文摘要
接触追踪被广泛认为是反对流行病的有效程序。但是，基于技术的接触追踪的挑战之一是误报数量很高，质疑其在更广泛的人群中的信任度和效率。为此，本文提出了一种新颖但实用的基于智能手机的接触跟踪方法，该方法采用WiFi和声音进行相对距离估计，除了气压和磁场以匹配环境环境。我们提出了一个组合6个智能手机传感器的型号，在满足某些条件时将其中一些列为优先级。我们在各种现实的环境中经验验证了我们的方法，以证明其误报的成就少了95％，而仅比蓝牙系统更准确了62％。据我们所知，本文是提出智能手机传感器进行接触跟踪的第一批作品之一。
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 air pressure and the magnetic field for ambient 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.
