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A Covel: AI driven COVID-19 Pandemic Prediction using Personal Hand Held Smartphone

Mir Aman Sheheryar, Mir Hamza Shaheryar

Abstract


From the family of renowned viruses that made humans ill came in the lime light under the name coronavirus later as COVID-19. COVID-19 proved fatal in whuhan province of china that later was touted as epicenter of COVID-19. COVID-19 accelerated and expanded its footprint around the countries and is reported as a Pandemic. Currently almost whole globe is struggling to delimit the COVID-19. Not much research have been done in this, thus there arise the need to detect and point out disease COVID-19. The detection mechanism for COVID-19 involve subjection to medical examination that involve CT scan images, blood test, deep throat saliva Analysis and finally stool test. These medical Examinations make the use of MDK (Medical Detection Kits).

Thus herein we have proposed a Covel approach of COVID-19 detection using Personal Hand held smartphone. As in today’s era everybody is having Smartphone so we tried to incorporate same for detection purpose. Today smartphones come with extra onboard features involving high end processors, good primary and secondary storages apart from it the biometric sensors. The biometric sensors include chipset sensor, color sensor, temperature sensor and inertial sensor. Here by using the smartphone sensor we can tout out the symptoms of COVID-19 and Elementary Predict the outcome if person is suffering from COVID-19 or not. By using the proposed mechanism we can delimit the time frame and increase the efficiency of declaring the patient positive for the said disease which will ease the burden on the doctors.

Keywords: Corona Virus, Covid-19, medical Detection Kit, Artificial Intelligence, Epidemic, Pandemic

Cite this Article: Mir Aman Sheheryar, Mir Hamza Shaheryar. A Covel: AI driven COVID-19 Pandemic Prediction using Personal Hand Held Smartphone. Journal of Artificial Intelligence Research & Advances. 2020; 7(2): 1–9p.


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DOI: http://dx.doi.org/10.37591%2Fjoaira.v7i2.2459

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