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A drone-based networked system and methods for combating coronavirus disease (COVID-19) pandemic.

Authors
  • Kumar, Adarsh1
  • Sharma, Kriti1
  • Singh, Harvinder2
  • Naugriya, Sagar Gupta3
  • Gill, Sukhpal Singh4
  • Buyya, Rajkumar5
  • 1 Department of Systemics, School of Computer Science, University of Petroleum and Energy Studies, Dehradun, India. , (India)
  • 2 Department of Virtualization, School of Computer Science, University of Petroleum and Energy Studies, Dehradun, India. , (India)
  • 3 Indian Robotics Solution Pvt. Ltd. (IRS), New Delhi, India. , (India)
  • 4 School of Electronic Engineering and Computer Science, Queen Mary University of London, UK.
  • 5 Cloud Computing and Distributed Systems (CLOUDS) Laboratory, School of Computing and Information Systems, The University of Melbourne, Australia. , (Australia)
Type
Published Article
Journal
Future Generation Computer Systems
Publisher
Elsevier
Publication Date
Feb 01, 2021
Volume
115
Pages
1–19
Identifiers
DOI: 10.1016/j.future.2020.08.046
PMID: 32895585
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

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 min 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. © 2020 Elsevier B.V. All rights reserved.

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