  Coronavirus disease (COVID-19) is an infectious disease caused by a newly
discovered coronavirus. It is similar to influenza viruses and raises concerns
through alarming levels of spread and severity resulting in an ongoing pandemic
worldwide. Within eight months (by August 2020), it infected 24.0 million
persons worldwide and over 824 thousand have died. Drones or Unmanned Aerial
Vehicles (UAVs) are very helpful in handling the COVID-19 pandemic. This work
investigates the drone-based systems, COVID-19 pandemic situations, and
proposes an architecture for handling pandemic situations in different
scenarios using real-time and simulation-based scenarios. The proposed
architecture uses wearable sensors to record the observations in Body Area
Networks (BANs) in a push-pull data fetching mechanism. The proposed
architecture is found to be useful in remote and highly congested pandemic
areas where either the wireless or Internet connectivity is a major issue or
chances of COVID-19 spreading are high. It collects and stores the substantial
amount of data in a stipulated period and helps to take appropriate action as
and when required. In real-time drone-based healthcare system implementation
for COVID-19 operations, it is observed that a large area can be covered for
sanitization, thermal image collection, and patient identification within a
short period (2 KMs within 10 minutes approx.) through aerial route. In the
simulation, the same statistics are observed with an addition of
collision-resistant strategies working successfully for indoor and outdoor
healthcare operations. Further, open challenges are identified and promising
research directions are highlighted.
