InCOV Chamber: Intelligent Chamber to Detect Potential COVID-19 Positive Patients

Abstract

COVID-19, the infectious disease with common symptoms such as tiredness, fever, cough, and severe symptoms such as shortness of breath has become a global pandemic that has an enormous negative impact on society.Due to its adverse impact on the operations of organizations, the entire world is highly concerned about the spread of the disease within their organization. Even though fever is the only symptom considered currently to detect suspects, there may be COVID19 patients without any indications of fever. The purpose of this study is to identify potential COVID-19 suspects by taking the aforementioned symptoms into account with the help of an IoT-based chamber. Once a person enters the chamber, our solution uses Neural Networks and Artificial Intelligence(AI) to identify COVID-19 symptoms such as Fever, Anosmia, Cough, and Shortness of Breath. The proposed system yields accuracies of 95% for fever detection, 96% for anosmia detection and 94% for cough analysis.