  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: a) use a personal device to
identify the user while designing a secure protocol to anonymize the user's
identity; b) leverage networking technologies to analyze and store the data; c)
exploit rich sensing features on the user device to detect the interaction
among users and thus estimate the exposure risk. This paper 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 use 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.
