Detecting Technique of COVID-19 Via an Optimized Piezoelectric Sensor

In the last few years, SARS-CoVID-19 pandemic was the main cause of millions of deaths around the world and was the main reason for global economic recession. It is vital to explore noninvasive procedures to detect and eliminate this pandemic expeditious. In this research, we introduce a technique for detecting and quarantine the SARS-CoVID-19 by designing a piezoelectric device with a natural frequency that is equal to the virus structural natural frequency. Because of the resonance effect, the vibration of the device increases, and the power output produced by the piezoelectric layer in the harvester is used to detect the COVID-19 by powering a small LED. The light of the LED is a sign of infection. Furthermore, when the virus's natural frequency is determined, an ultrasonic resonance device can be used to eliminate the virus. Polymerase chain reaction test (PCR) is costly and time-consuming. Our proposed technique is both fast and inexpensive. The installing of the device, the modeling, and the treatment potentiality are discussed in this paper. To maximize the output power of the device at the virus natural frequency, three optimization algorithms are performed. It is observed that Bound Optimization by Quadratic approximation (BOBYQA) optimization algorithm enhances the output power. The analytical model of the proposed sensing device is derived based on the theory of Euler–Bernoulli. The voltage and power frequency response for open and closed circuits are analytically derived. A Finite Element Method (FEM) for the proposed sensing device is developed and analytically verified.