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Detecting a Coronavirus Through Breathing Using 3D Modeling and Artificial Intelligence

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Human Interaction, Emerging Technologies and Future Systems V (IHIET 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 319))

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Abstract

A coronavirus called COVID-19 appeared in Wuhan, China in December 2019. By early 2020 it caused a worldwide pandemic of a respiratory illness. This virus crisis affected the economy in the world in 2020 and will affect it in 2021, a lot of companies lost $ billions, especially the airlines, and because of that a lot of people lost their jobs; it also caused deaths of many people and till now it causes deaths of thousands of people in the world every day, a lot of people have died and till now a lot of people are dying every day because of a late detection of the virus in their bodies. The coronavirus can spread from an infected person’s mouth or nose in small liquid particles, having different sizes, ranging from larger ‘respiratory droplets’ to smaller ‘aerosols’, when they cough, sneeze, speak, sing or breathe heavily, which means that it can be spread through breathing from an infected person to another person. There are different types (shapes) of COVID-19. This article aims to introduce a new approach that allows us to detect a coronavirus immediately using the artificial intelligence techniques and 3D modeling. The basic idea is to use 3D modeling technology to prepare the geometric data for different shapes of COVID-19 and AI technique, which can detect a coronavirus immediately through breathing by comparing the respiratory droplets or smaller aerosols with the shapes of COVID-19 specified by the 3D model .

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Acknowledgments

The author would like to thank the president of Lebanese International University HE Abdel Rahim Mourad and the LIU Bekaa campus administration for their continuous encouragement of research activities at the university.

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Authors and Affiliations

  1. Computer Science/Information Technology Departments, Lebanese International University – LIU, Bekaa-Lebanon, Beirut, Lebanon

    Haissam El-Aawar

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  1. Haissam El-Aawar
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Correspondence to Haissam El-Aawar .

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Editors and Affiliations

  1. Institute for Advanced Systems Engineering, University of Central Florida, Orlando, FL, USA

    Tareq Ahram

  2. Campus du Moulin de la Housse, Université de Reims Champagne Ardenne GRESPI, Reims Cedex, France

    Redha Taiar

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El-Aawar, H. (2022). Detecting a Coronavirus Through Breathing Using 3D Modeling and Artificial Intelligence. In: Ahram, T., Taiar, R. (eds) Human Interaction, Emerging Technologies and Future Systems V. IHIET 2021. Lecture Notes in Networks and Systems, vol 319. Springer, Cham. https://doi.org/10.1007/978-3-030-85540-6_109

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  • DOI: https://doi.org/10.1007/978-3-030-85540-6_109

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-85539-0

  • Online ISBN: 978-3-030-85540-6

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