Secure IoT Communication Systems for Prediction of COVID-19 Outbreak: An Optimal Signal Processing Algorithm

摘要

This paper proposes an innovative COVID-19 stochastic model to secure communication systems for transferring and storing epidemic data. Considering the observable and non-observable COVID-19 states such as infection, confirmed/unconfirmed cases, recovery, and reported/unreported deaths, the dynamic COVID-19 framework is developed and verified. For transmitting local observation information to the central control center like CDC, an innovative internet of things (IoT) based secure communication system is proposed. For predicting COVID-19 model, an optimal signal processing algorithm is developed and implemented. Based on the designed gain, the dynamic system forecasting error is reduced to develop an accurate COVID-19 prediction method. Extensive results show that the proposed technique can properly forecast COVID-19 states within a short period of time. Consequently, the developed simulator and analysis is observed as a valuable resource for COVID-19 state prediction, proactive action and also for information security and privacy.