University of Bahrain
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A Framework for Detection and Monitoring of COVID-19 using IoT Environment in Pre-Pandemic Life

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dc.contributor.author Kumar, M.R. Sundara
dc.contributor.author Nayagi, D Salangai
dc.contributor.author G, Kirubasri
dc.contributor.author S, Sankar
dc.date.accessioned 2023-02-28T19:54:27Z
dc.date.available 2023-02-28T19:54:27Z
dc.date.issued 2023-02-28
dc.identifier.issn 2210-142X
dc.identifier.uri https://journal.uob.edu.bh:443/handle/123456789/4763
dc.description.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. en_US
dc.language.iso en en_US
dc.publisher University of Bahrain en_US
dc.subject COVID-19, Vaccines, Pre-pandemic, Cloud server, Data Management, Wearable Devices en_US
dc.title A Framework for Detection and Monitoring of COVID-19 using IoT Environment in Pre-Pandemic Life en_US
dc.type Article en_US
dc.identifier.doi http://dx.doi.org/10.12785/ijcds/130159 en
dc.contributor.authoraffiliation Computer Science and Engineering, Sona College of Technology, Salem, Tamilnadu, India en_US
dc.contributor.authoraffiliation Computer Science and Engineering, New Horizon College of Technology, Bengaluru, Karnataka, India en_US
dc.source.title International Journal of Computing and Digital Systems en_US
dc.abbreviatedsourcetitle IJCDS en_US


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