IJSDR
IJSDR
INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15

Issue: March 2024

Volume 9 | Issue 3

Impact factor: 8.15

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Paper Title: Covid safety Measures Using Machine Learning
Authors Name: Gayatri Navnath Dighe , Akash Dilip Ghuge , Ashwini Babasaheb Kote , Jagruti Arvind Wagh , Prof. Patil P.A.
Unique Id: IJSDR2205038
Published In: Volume 7 Issue 5, May-2022
Abstract: The Covid-19 outbreak has taken the world completely unawares, exposing the vulnerability of public health systems in coping with infectious pandemic. The current death toll of the pandemic is staggering, and it is the need of an hour to eradicate the virus at the earliest and prepare a system that stands tall to armor the world in case the future holds any unpredictable biological or health crisis of this scale. Since December 2019, Novel coronavirus disease has been shown an extensive impact on social, mental, personal, and economic fields throughout the world. In this pandemic situation, people are worried and interested to know what is going on in the upcoming days. Therefore, it is very important to provide relevant information about how many people are affected and will infect in near future. Moreover, they need to know how to spread different symptoms and prevention steps of this disease. This research work proposes a complete COVID-19 safety measures which helps people to defend against it. This is first of its kind application that uses machine learning to combat the need. Machine learning model to be built to deal with various safety measures. By using the technology, it alerts the people who are in need of it. The proposed approach will provide an intuitive way to understand the risk of being getting affected based on the immunization of respiratory system of an individual. The risk factor will provide a basis for personification and to take safety measures in this long-lasting pandemic situation.
Keywords: Covid-19, Machine learning, personification, privacy, prediction, symptoms.
Cite Article: "Covid safety Measures Using Machine Learning", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.7, Issue 5, page no.197 - 201, May-2022, Available :http://www.ijsdr.org/papers/IJSDR2205038.pdf
Downloads: 000336256
Publication Details: Published Paper ID: IJSDR2205038
Registration ID:200369
Published In: Volume 7 Issue 5, May-2022
DOI (Digital Object Identifier):
Page No: 197 - 201
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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