A Covid-19 Identification Framework for Vulnerable Using Technology Intervention-Reference-Cited by-同舟云学术

A Covid-19 Identification Framework for Vulnerable Using Technology Intervention

Published:2024-01-29 Issue: Volume:6 Page:1-5
ISSN:2692-5079
Container-title:Engineering World
language:en
Short-container-title:

Author:

Sahu Swatantra Kumar¹,Sahu Neeraj²,Bakariya Brijesh³

Affiliation:

1. Department of Physical Science Mahatma Gandhi Chitrakoot Gramoday Vishwavidyalaya 4VX3+4HM, Janki Kund, Chitrakoot, Madhya Pradesh 485334 INDIA

2. Department of Computer Science & Engineering G H Raisoni University Anjangaon Bari Rd, Badnera, Amravati, Maharashtra 444701 INDIA

3. Department of Computer Science and Engineering I.K. Gujral Punjab Technical University Campus, Hoshiarpur, Punjab INDIA

Abstract

The World Health Organization (WHO) mentioned the Global Outbreak Alert and Response Network (GOARN) has launched a GOARN COVID-19 Knowledge hub. Fever, dry cough, and tiredness are the most common symptoms of COVID-19. Another report from WHO says that laboratory testing guidance for COVID- 19 in suspected human cases. Recognizing that the global spread of COVID-19 has increased the number of suspected cases. Thus, a well-formed people support framework is required to safeguard the vulnerable from COVID-19-like disasters in the future. This short paper reports the research findings we conducted by laying out a safeguard and sensible framework for people's well-being during disastrous times. The proposed framework is a fuzzy soft algorithm to improve possible COVID-19 case identification more quickly using a smartphone. The proposed framework has a parameter of fuzzy soft set values like Fever, dry cough, tiredness,etc fed by the user in the mobile application that is identified by using a fuzzy soft algorithm.

Publisher

World Scientific and Engineering Academy and Society (WSEAS)

Reference7 articles.

1. G. R. Shinde, A. B. Kalamkar, P. N. Mahalle, N. Dey, J. Chaki and A. E. Hassanien, “Forecasting Models for Coronavirus Disease (COVID-19): A Survey of the Stateof-the-Art,” SN Computer Science (2020) vol. 1, pp-1.15, 2020.

2. H. Garg, G. Shahzadi, M. Akram, “DecisionMaking Analysis Based on Fermatean Fuzzy Yager Aggregation Operators with Application in COVID-19 Testing Facility”, Advances in Numerical Optimization: Theory, Models, and Applications, 2020.

3. S. Ashraf, S. Abdullah, A. O. Almagrabi, “A new emergency response of spherical intelligent fuzzy decision process to diagnose of COVID19,” Soft Computing, Oct 2020.

4. N.R. Raajan, V.S. R. Lakshmi and N. Prabaharan, “Non-Invasive Technique-Based Novel Corona(COVID-19) Virus Detection Using CNN,” National Academy Science Letters, July 2020.

5. A. H. Matamoros, H. Fujita, T. Hayashi, and H. P. Meana, “Forecasting of COVID-19 per regions using ARIMA models and polynomial functions,” Applied Soft Computing, vol. 96, Nov.2020.