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COVID-19 has created a pandemic around the world, paused the path of buildingthe future, and still ongoing without having any long-term solution shortly.The time taken in vaccine distribution is too slow compared to the spread ofCOVID-19. Hence, it is important to aware and takes precautions on time withoutdelaying and waiting for long-duration after getting infected with the virus.Currently used technology is more advanced than ever before. Almost everyonehas access to at least one mobile device with an Internet connection.Therefore, we propose a Fog Server (FS) based system that can be used to createawareness about the spread of COVID-19 within the surroundings of individualsutilizing the concept of Hidden Markov Models (HMM) and Bluetooth contacttracing, in polynomial computational time complexity. Moreover, we evaluate theeffectiveness of the proposed model through real-world data analysis ondifferent simulation parameter settings.

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