Abstract
The most common alarming and dangerous disease in the world today is the coronavirus disease 2019 (COVID-19). The coronavirus is perceived as a group of coronaviruses which causes mild to severe respiratory diseases among human beings. The infection is spread by aerosols emitted from infected individuals during talking, sneezing, and coughing. Furthermore, infection can occur by touching a contaminated surface followed by transfer of the viral load to the face. Transmission may occur through aerosols that stay suspended in the air for extended periods of time in enclosed spaces. To stop the spread of the pandemic, it is crucial to isolate infected patients in quarantine houses. Government health organizations faced a lack of quarantine houses and medical test facilities at the first level of testing by the proposed model. If any serious condition is observed at the first level testing, then patients should be recommended to be hospitalized. In this study, an IoT-enabled smart monitoring system is proposed to detect COVID-19 positive patients and monitor them during their home quarantine. The Internet of Medical Things (IoMT), known as healthcare IoT, is employed as the foundation of the proposed model. The least-squares (LS) method was applied to estimate the linear model parameters for a sequential pilot survey. A statistical sequential analysis is performed as a pilot survey to efficiently collect preliminary data for an extensive survey of COVID-19 positive cases. The Bayesian approach is used, based on the assumption of the random variable for the priori distribution of the data sample. Fuzzy inference is used to construct different rules based on the basic symptoms of COVID-19 patients to make an expert decision to detect COVID-19 positive cases. Finally, the performance of the proposed model was determined by applying a four-fold cross-validation technique.
Highlights
IntroductionThe Coronavirus pandemic ( referred to as the COVID-19 epidemic) has generated social and financial disruption worldwide, causing the most significant worldwide downturn since the Great Depression
The Coronavirus pandemic has generated social and financial disruption worldwide, causing the most significant worldwide downturn since the Great Depression
We propose an intelligent health monitoring system to detect COVID-19 positive cases through Internet of Things (IoT) devices
Summary
The Coronavirus pandemic ( referred to as the COVID-19 epidemic) has generated social and financial disruption worldwide, causing the most significant worldwide downturn since the Great Depression. Up to 100 million people have fallen into destitution, and worldwide starvation influences 265 million people. It has prompted the delay or crossing out of brandishing, strict, political, and social occasions, far-reaching deficiencies exacerbated by alarm purchasing, and decreased emissions of contaminants and greenhouse gasses. Recognized in late 2019 as an infectious disease, the Coronavirus affects the human body in several ways. It causes shortness of breath or trouble breathing, fatigue, headache, body aches, loss of taste, loss of smell nausea, or vomiting. Coronavirus spread is considered to occur mainly via saliva droplets or the nasal discharge from an infected person.
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