Abstract
SARS-CoV-2 also known as COVID-19 is a novel corona virus which originated from China. Corona virus disease COVID-19 is the official name given by WHO is caused by SARS (Severe Acute Respiratory Syndrome) which have very mild symptoms in the beginning but slowly progress to failure of multiple organs followed by death. The emergency committee of WHO declared COVID-19 as a pandemic. The disease is spread from person-to-person and the spread is very fast making serious impacts on the lives of the people. CT scan and PCR (Polymerase Chain Reaction) are the tests for the diagnosis of COVID-19 virus in the human body. The symptoms of this disease are very common which include fever, breath shortness, dry cough and pain in the muscles. The solutions which are available currently have less accuracy, take longer time and are costly. In this paper, a framework is proposed based on smart phones and artificial intelligence. The benefits are increased productivity, reliability and availability of advanced infrastructure. There are various sensors embedded in the smart phones such as proximity sensor, light sensor, accelerometer, gyroscope and fingerprint sensors which have very fast processors and memory space making it easy to read the sensors and scan the CT images, the signal measurements in the sensors of the smart phones are read which scan the CT images for reliable diagnosis of the disease. The proposed framework is based on artificial intelligence, cloud network and machine learning.
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Sharma, M., Sharma, B., Gupta, A.K., Khosla, D., Goyal, S., Pandey, D. (2021). A Study and Novel AI/ML-Based Framework to Detect COVID-19 Virus Using Smartphone Embedded Sensors. In: Agrawal, R., Mittal, M., Goyal, L.M. (eds) Sustainability Measures for COVID-19 Pandemic. Springer, Singapore. https://doi.org/10.1007/978-981-16-3227-3_4
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