COVID-19 Spread Detection and Controlling with Fog-based Infection Probability Evaluation Model

ABSTRACT

COVID-19 has created a pandemic worldwide, paused the path of building the future, and is still ongoing without any long-term solution. The time taken in vaccine distribution is too slow compared to the spread of COVID-19. Hence, it is important to be aware and take precautions on time without delaying and waiting for long-duration after getting infected with the virus. Technology nowadays is more advanced than ever before. Almost everyone has access to at least one mobile device with internet connection. Therefore, we propose a Fog Server (FS) based system that helps create awareness about the spread of COVID-19 within the surroundings of an individual, utilizing the concept of Hidden Markov Model (HMM) and Bluetooth contact tracing in polynomial computational time complexity. Moreover, we evaluate the effectiveness of the proposed model through real-world data analysis on different simulation settings. © 2023 ACM.