Abstract:
COVID-19 (SARS-Cov-2virus), a family of CORONA viruses, is disseminated worldwide to make a pandemic to the whole
world thereby disturbing human being’s normal life. As per World Health Organization (WHO) statement, it spreads consistently and
affects human society unless they follow the precautionary measures prescribed by them. Moreover, this virus disseminated from the
human-to-human body within a short period which even leads to death. Intense Research is carried out globally to produce vaccines
for the virus. Meanwhile, people are advised to protect themselves through various operational procedures and precautions that are
prescribed periodically. Recent techniques are used to detect the COVID-19 virus symptoms in the early stage of normal people and are
insisted to take precautionary steps in early pandemic life. IoT is a framework used in the human body with wearable devices developed
using sensors to communicate directly or indirectly with human bodies. Sensors generate signals from the human body and send them
to the server connected via the internet. Data analytics are done on the server-side to diagnose whether the human is affected by the
COVID-19 virus or not. Finally, data is stored in a real-time cloud server which is managed as a framework efficiently. This research
work proposes a framework for data management for early detection and monitoring of the COVID-19 virus-affected people in the early
stage through IoT wearable devices in a pre-pandemic life. A pre-trained model was created with Deep Neural Networks (DNN) in
order to make predictions based on the data from the human bodies using classifiers. Experiments are conducted at different conditional
zones and their results are shown as symptoms of COVID-19 with localized datasets. Parallel work reveals that data management in
a cloud server by tracking and storing the data. This research work data set is derived from various internet sources like government
websites, and the Kaggle platform(Open Research Dataset about COVID-19), and the results have exposed the diagnosis or detection
of COVID-19 precisely in real-time.
