Public health and safety on close contact proximity detection for COVID-19 and alert via IoT

Abstract

Social distancing among people is vital in minimizing spread of COVID-19 within community and can be effective in flattening the outbreak. This research work focuses on developing a close contact proximity detection system among smartphone users, particularly of COVID-19 patient, using Bluetooth signal to identify and analyze close contact proximity and social distancing from other anonymous smartphone user in their surrounding. The system aims to alert user if the social distancing is breached. The methodology rely on 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. An overlap zone of 1-meter is used to indicate detection of closed contact proximity between users. Furthermore, the collected data can be utilized for contact tracing that enabling health officials to identify the closed contact of infected patient systematically and rapidly covering people who may be anonymous or not directly known to the COVID-19 patient. Encouraging results have been obtained for the closed contact proximity detection within the mobile apps. Furthermore, the performance of system for close contact proximity detection has shown that indoor locations have a more robust signal distribution compared to outdoor locations