Iot Based Machine Learning Framework for COVID-19 Management

Monitoring COVID-19 patients and making predictions is still a difficult task, even after a few years of a serious pandemic crisis. Moreover, it is also challenging to manage the COVID-19 patient's status at home, especially considering the aged patients. Apart from the need for periodic monitoring, timely up-to-date health updates of the patient are also requisites to their family members. Thus, an IoT-based Machine Learning Framework is proposed to perform this task automatically and with ease. The idea is to develop an intelligent COVID-19 patient global positioning framework to monitor the infected patient's health and utilize the internet to alert their relatives as well as local administration in case of emergency. To achieve this, the proposed framework uses the eight responses provided by persons using mobile phones. This data is processed in the Data Analysis Center, where further categorization is performed by dividing persons into colored zones, indicating the severity of the illness. Then accordingly, appropriate treatments and guidelines are suggested for the mildly to severely infected patients or healthy persons. Therefore, the present IoT-based machine learning framework for COVID-19 detection and prediction may save a significant amount of valuable and crucial time and also helps the administration for efficient management of the resources required during a pandemic.