Welcome to IJSDR UGC CARE norms ugc approved journal norms IJRTI Research Journal | ISSN : 2455-2631
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.15 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)

Issue: June 2022

Volume 7 | Issue 6

Impact factor: 8.15

Click Here For more Info

Imp Links for Author
Imp Links for Reviewer
Research Area
Subscribe IJSDR
Visitor Counter

Copyright Infringement Claims
Indexing Partner
Published Paper Details
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: 00096793
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

Click Here to Download This Article

Article Preview

Click here for Article Preview

Major Indexing from www.ijsdr.org
Google Scholar ResearcherID Thomson Reuters Mendeley : reference manager Academia.edu
arXiv.org : cornell university library Research Gate CiteSeerX DOAJ : Directory of Open Access Journals
DRJI Index Copernicus International Scribd DocStoc

Track Paper
Important Links
Conference Proposal
DOI (A digital object identifier)

Providing A digital object identifier by DOI
How to GET DOI and Hard Copy Related
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Creative Commons License
This material is Open Knowledge
This material is Open Data
This material is Open Content
Social Media

Indexing Partner