Efficient Voluntary Contact-Tracing System and Network for COVID-19 Patients Using Sound Waves and Predictive Analysis Using K-Means

Abstract

Patient tracking and contact mapping have been a challenge for government and hi-tech companies around the world in terms of precision after WHO declared COVID-19 as a pandemic on March 12, 2020. Our proposed method discloses a voluntary contact-tracing network using smartphone application by means of GPS using a microphone along with short-range communication like Bluetooth. The amalgamation of Bluetooth with a microphone (soundwaves) helps in identifying the distance of two people more accurately as Bluetooth alone does not calculate correct distances. The smartphone application transmits the exact location data captured by GPS and user’s proximity distance data to an intelligent cloud platform using the Internet if the patient is diagnosed with COVID-19 after user content via smartphone. The smartphone captures the signals of nearby phones when in proximity and stores the connections between them in a local database. The data sync to intelligent cloud platform from each smartphone will have the unique mapping of each COVID-19 patient with exact contact tracing with location data once the patient is diagnosed with COVID-19. Hence, if a person tests positive for the COVID-19, the person can notify using an application that they have been infected, and the cloud system notifies other people whose phones came in close contact in the preceding days. The precision of contact mapping using sound wave technology along with Bluetooth will help the people as well as the local administration to deal with pandemics in an effective way. Moreover, the intelligent cloud platform will be enabled with an AI-supported algorithm that generates predictive insights from time to time on smartphones.