Automated COVID-19 Detection Using ML & IOT

COVID-19 has emerged as the biggest fear of all time. The timely and accurate detection of COVID-19 infection is very crucial for preventing the spread of infection. The behavior and symptoms of the infection is changing gradually and thus the existing statistical model fails to capture the dynamic behavior of the Coronavirus and its associated infected patient symptoms. Therefore, the objective of this study is to propose a novel framework that collects the data dynamically with IoT sensors and then utilizes that data to develop automated statistical model for the detection of corona infection. COVID-19 associated data is captured dynamically through IoT sensors. The dynamic data is further utilized to develop the machine learning model for the detection of infection. The amalgamation of IoT and Machine Learning can help in developing the automated machine learning model that can handle the dynamic behavior and changing symptoms of corona virus and assists the medical expert in making timely and effective decisions.