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vContact: Private WiFi-based IoT Contact Tracing With Virus Lifespan

Authors :
Li, Guanyao
Hu, Siyan
Zhong, Shuhan
Tsui, Wai Lun
Chan, Gary Shueng Han
Li, Guanyao
Hu, Siyan
Zhong, Shuhan
Tsui, Wai Lun
Chan, Gary Shueng Han
Publication Year :
2021

Abstract

Covid-19 is primarily spread through contact with the virus which may survive on surfaces with a lifespan of hours or even days if not sanitized. To curb its spread, it is hence of vital importance to detect those who have been in contact with the virus for a sustained period of time, the so-called close contacts. Most of the existing digital approaches for contact tracing focus only on direct face-to-face contacts. There has been little work on detecting indirect environmental contact, which is to detect people coming into a contaminated area with the live virus, i.e., an area last visited by an infected person within the virus lifespan. In this work, we study automatic IoT contact tracing when the virus has a lifespan which may depend on the disinfection frequency at a location. Leveraging the ubiquity of WiFi signals, we propose vContact, a novel, private, pervasive and fully distributed WiFi-based IoT contact tracing approach. Users carrying an IoT device (phone, wearable, dongle, etc.) continuously scan WiFi access points (APs) and store their hashed IDs. Given a confirmed case, the signals are then uploaded to a server for other users to match in their local IoT devices for virus exposure notification. vContact is not based on device pairing, and no information of other users is stored locally. The confirmed case does not need to have the device for it to work properly. As WiFi data are sampled sporadically and asynchronously, vContact uses novel and effective signal processing approaches and a similarity metric to align and match signals at any time. We conduct extensive indoor and outdoor experiments to validate vContact performance. Our results demonstrate that vContact is effective and accurate for contact detection. The precision, recall and F1-score of contact detection are high (up to 90%) for close contact proximity (2m). Its performance is robust against AP numbers, AP changes and phone heterogeneity. Having implemented vContact as an Android SDK and

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1280086933
Document Type :
Electronic Resource