COVID-Tracker: Surveillance of Potential Clusters Using a Wristband and Location-based Data

Abstract

COVID-19 is a global pandemic that has threatened the survival of humans and other living beings. COVID-19 causes illnesses varying from the very mild cold to serious health complications resulting in death. Most Information Technology based solutions have been implemented to prevent the COVID-19 pandemic while raising awareness in the public. However, there is a limited number of reliable and real-time applications of self-awareness on COVID-19. Currently, the globe is dealing with the COVID-19 epidemic, particularly in pursuit of economic growth in each country. Therefore, an accurate, efficient automatic method to raise self-awareness by avoiding risky contacts is useful for human survival. This paper describes the automatic detection of temperature using a wearable device and an automatic alerting mechanism to inform the users of potentially risky contacts with higher temperatures nearby within a considerable time frame. COVID-Tracker produces results with high accuracy and efficiency, this is beneficial to improve self-awareness among users, to visualize potential covid clusters, and also to improve the mental health of self-isolated people. The developed application consists of four main components namely: temperature measuring band, mobile application, prediction model-based visualization dashboard and an AI bot. Based on the results reported here, developed methods can help people to achieve self-awareness of COVID-19 by avoiding risk factors early and accurately.