A Novel AI-enabled Framework to Diagnose Coronavirus COVID-19 using Smartphone Embedded Sensors: Design Study

Halgurd S. Maghded, Kayhan Zrar Ghafoor, Ali Safaa Sadiq, Kevin Curran, Danda B. Rawat, Khaled Rabie

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

121 Scopus citations

Abstract

Coronaviruses are a famous family of viruses that cause illness in both humans and animals. The new type of coronavirus COVID-19 was firstly discovered in Wuhan, China. However, recently, the virus has widely spread in most of the world and causing a pandemic according to the World Health Organization (WHO). Further, nowadays, all the world countries are striving to control the COVID-19. There are many mechanisms to detect coronavirus including clinical analysis of chest CT scan images and blood test results. The confirmed COVID-19 patient manifests as fever, tiredness, and dry cough. Particularly, several techniques can be used to detect the initial results of the virus such as medical detection Kits. However, such devices are incurring huge cost, taking time to install them and use. Therefore, in this paper, a new framework is proposed to detect COVID-19 using built-in smartphone sensors. The proposal provides a low-cost solution, since most of radiologists have already held smartphones for different daily-purposes. Not only that but also ordinary people can use the framework on their smartphones for the virus detection purposes. Today's smartphones are powerful with existing computation-rich processors, memory space, and large number of sensors including cameras, microphone, temperature sensor, inertial sensors, proximity, colour-sensor, humidity-sensor, and wireless chipsets/sensors. The designed Artificial Intelligence (AI) enabled framework reads the smartphone sensors' signal measurements to predict the grade of severity of the pneumonia as well as predicting the result of the disease.

Original languageEnglish
Title of host publicationProceedings - 2020 IEEE 21st International Conference on Information Reuse and Integration for Data Science, IRI 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages180-187
Number of pages8
ISBN (Electronic)9781728110547
DOIs
StatePublished - Aug 2020
Externally publishedYes
Event21st IEEE International Conference on Information Reuse and Integration for Data Science, IRI 2020 - Virtual, Las Vegas, United States
Duration: 11 Aug 202013 Aug 2020

Publication series

NameProceedings - 2020 IEEE 21st International Conference on Information Reuse and Integration for Data Science, IRI 2020

Conference

Conference21st IEEE International Conference on Information Reuse and Integration for Data Science, IRI 2020
Country/TerritoryUnited States
CityVirtual, Las Vegas
Period11/08/2013/08/20

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

Keywords

  • COVID-19
  • coronavirus Detection
  • smartphone
  • smartphone sensors

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Information Systems
  • Decision Sciences (miscellaneous)
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality

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