ABSTRACT
Autonomous unmanned aerial vehicles (UAVs) have witnessed a rapid increase in their utilization in various applications and will continue to do so in the coming decades. These UAVs, also known as drones, are designed to either assist humans or perform tasks that involve people. Drones of today have grown to be faster and less expensive by integrating several technologies, supported by hybrid algorithms, and perform various tedious, challenging, filthy and hazardous tasks. The deployment of machine learning and other AI-based algorithms enhances drones' autonomous and vision capabilities. Today, part of an effort to curtail the spread of COVID-19, this research has designed, developed and built a mobile disinfectant dispenser based on autonomous quadrotor UAV. It is a 'flying dispenser', able to detect a person's hand gestures from afar, based on machine learning (ML), to fly and maneuver towards the person and finally spray disinfectant on his/her hand. In order to identify various hand motions for maneuvering, this research studies and improves the ML algorithms and carries out various experiments to improve the drones' response time and maneuvering performance, for the final objective of taking precautions to protect humans from Covid-19. © 2022 IEEE.
ABSTRACT
Being researchers, it is an utmost responsibility to provide insight on social issues thus, this work addresses the dynamic modeling of first and most contagious disease named as COVID-19 caused by coronavirus. The first case of COVID-19 appeared in Pakistan was on 26th February 2020 and in Malaysia on 27th February 2020;both patients had foreign travel history. In the paper, the number of total affected cases and total deaths in both countries, are quite the same up till 12th April 2020 but the frequency of new cases per day and recovery rate are different from one another. The movement control approach had also been imposed on 18th March 2020 by both countries. Keeping these facts and figures, the paper proposes a mathematical model based on Lotka-Volterra equations and provides numerical solution of differential equations using the suspectable, exposed, infected, and recovered people data to estimate future consequences and address the difference in the growth rate of COVID-19 patients before and after locked down to reduce the spread further by taking pro-active approaches i.e., social distancing and being quarantined for the essential time frame. © 2021 IEEE