Digital contact tracing has emerged as a viable tool supplementing manual contact tracing. To date, more than 100 contact tracing applications have been published to slow down the spread of highly contagious Covid-19. Despite subtle variabilities among these applications, all of them achieve contact tracing by manipulating the following three components: use of a personal device to identify the user while designing a secure protocol to anonymize the user's identity; leverage networking technologies to analyze and store the data; and exploit rich sensing features on the user device to detect the interaction among users and thus estimate the exposure risk. This article reviews the current digital contact tracing based on these three components. We focus on two personal devices that are intimate to the user: smartphones and wearables. We discuss the centralized and decentralized networking approaches that are used to facilitate the data flow. Lastly, we investigate the sensing feature available on smartphones and wearables to detect the proximity between any two users and present experiments comparing the proximity sensing performance between these two personal devices.

中文翻译：

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用于接触者追踪的个人设备：智能手机和可穿戴设备对抗 Covid-19

数字联系人跟踪已成为补充手动联系人跟踪的可行工具。迄今为止，已经发布了 100 多个联系人追踪应用程序，以减缓具有高度传染性的 Covid-19 的传播。尽管这些应用程序之间存在细微的差异，但它们都通过操纵以下三个组件来实现联系人跟踪：使用个人设备来识别用户，同时设计一个安全协议来匿名用户的身份；利用网络技术来分析和存储数据；并利用用户设备上丰富的感知特征来检测用户之间的交互，从而估计暴露风险。本文基于这三个组件回顾了当前的数字联系人跟踪。我们专注于与用户亲密的两种个人设备：智能手机和可穿戴设备。我们讨论了用于促进数据流的集中式和分散式网络方法。最后，我们研究了智能手机和可穿戴设备上可用的传感功能，以检测任意两个用户之间的接近度，并进行实验，比较这两个个人设备之间的接近度传感性能。