Machine Learning Based Low-Cost COVID-19 Monitoring Syste

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2021-12

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Department of Electrical and Electronic Engineering

Abstract

In Bangladesh March 17 2020 every educational institutions ,schools,colleges and university had been shut down because of COVID 19. More than 7000 peoples have been died ,almost 400000 peoples have been infected by COVID 19 in Bangladesh.So we need to design an unique,affordable,reliable and further research-able project. We have created a Mobile Application which can show the dynamic data of student’s temperature and oxygen saturation with heart beat .These type of data have been stored in any data base so that we can further do research how vaccine and medication process develop in our community because everyone’s data have been stored in our dedicated data base .We also have done machine learning formation by linear regression theorem, so we can understand which student are being infected by COVID 19.Since SARC 02(COVID 19) virus can stay in 14 days without showing any type of symptoms so for the very few time our device’s values have not recognized which student could bear COVID 19 by body temperatures and oxygen saturation.On the other hand we have used machine learning theorem so that we can minimize our error rates .Further machine leaning theorem which add any types of sensors that help COVID 19 situation dynamic recognition

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submitted by Riduanul Alam, bearing Matric ID. ET 151002 and Fahim Mohammad Evne Amin, bearing Matric ID. ET 151034 of session Spring 2020

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