A Hybrid Model for Selection of Patients for COVID-19 Testing

Bhavya Alankar1, Rehan Ahmad2, Harleen Kaur3

1Bhavya Alankar, School of Engineering Sciences and Technology, Jamia Hamdard, New Delhi, India.

2Rehan Ahmad, School of Engineering Sciences and Technology, Jamia Hamdard, New Delhi, India.

3Harleen Kaur, School of Engineering Sciences and Technology, Jamia Hamdard, New Delhi, India.

Manuscript received on 29 November 2020 | Revised Manuscript received on 10 December 2020 | Manuscript Accepted on 15 December 2020 | Manuscript published on 30 December 2020 | PP: 28-32 | Volume-1 Issue-1, December 2020 | Retrieval Number: A1008061120/2020©LSP

Open Access | Ethics and Policies | Indexing and Abstracting
© The Authors. Published by Lattice Science Publication (LSP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Today the whole world is suffering from corona virus or Covid-19. The World Health Organization (WHO) also declared it as “pandemic” which means that it has spread over a large geographical area and affecting an exceptionally high proportion of the population. The world has already seen some others pandemic too, such as H1N1 virus, Ebola, AIDS, etc. but none of them has covered this much of the world’s population. Today the total cases of covid-19 are approx. 7.94 million out of which 435 thousand have already died and this graph is increasing day by day. In this paper we have shown a hybrid model comprising of technologies such as thermal detectors, audio-based sensors and deep learning techniques that will help us in selecting the patient for Covid-19 testing.

Keywords: Corona Virus, Covid-19, Pandemic, Thermal Sensors, Audio-Based Sensors, Artificial Intelligence, Deep Learning.
Scope of the Article: Covid-19