Public Health and Safety on Close Contact Proximity Detection for COVID-19 and Alert via IoT

Abstract

The social distancing among people is vital in minimizing spread of COVID-19 among community and can be effective in flattening the outbreak. This research work on developing a close contact proximity detection system among smartphone users and particularly of COVID-19 patient using Bluetooth signal to identify and analyze close contact proximity and social distancing from other anonymous smartphone user in his/her surrounding and to alert user if the social distancing is breached. The methodology used the Radio Signal Strength Indicator (RSSI) signal to analyze and estimate the proximity distance and duration of the individual’s exposure to other peoples in surrounding area. The overlap zone of 1-meter is used to indicate detection of closed contact proximity between users. Furthermore, the collected data can be used to do contact tracing that enable health official to identify the closed contact of infected patient systematically, faster and can ensure coverage of people that anonymously and not directly known to the COVID-19 patient. An encouraging result is obtained on the closed contact proximity detection which shown within the mobile apps. Furthermore, the performance of system for close contact proximity detection shown that indoor location has a good signal distribution compared to outdoor location.