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A Comprehensive Review of the COVID-19 Pandemic and the Role of IoT, Drones, AI, Blockchain, and 5G in Managing its Impact
Open accessAbstract
The unprecedented outbreak of the 2019 novel coronavirus, termed as COVID-19 by the World Health Organization (WHO), has placed numerous governments around the world in a precarious position. The impact of the COVID-19 outbreak, earlier witnessed by the citizens of China alone, has now become a matter of grave concern for virtually every country in the world. The scarcity of resources to endure the COVID-19 outbreak combined with the fear of overburdened healthcare systems has forced a majority of these countries into a state of partial or complete lockdown. The number of laboratory-confirmed coronavirus cases has been increasing at an alarming rate throughout the world, with reportedly more than 3 million confirmed cases as of 30 April 2020. Adding to these woes, numerous false reports, misinformation, and unsolicited fears in regards to coronavirus, are being circulated regularly since the outbreak of the COVID-19. In response to such acts, we draw on various reliable sources to present a detailed review of all the major aspects associated with the COVID-19 pandemic. In addition to the direct health implications associated with the outbreak of COVID-19, this study highlights its impact on the global economy. In drawing things to a close, we explore the use of technologies such as the Internet of Things (IoT), Unmanned Aerial Vehicles (UAVs), blockchain, Artificial Intelligence (AI), and 5G, among others, to help mitigate the impact of COVID-19 outbreak.
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“In nature, the essence of the COVID-19 pandemic itself is distributed [293].”
From A survey on the adoption of blockchain in IoT: challenges and solutions (2021) · cites this paper as [293]
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“Blockchain and AI are able to provide viable solutions to cope with the coronavirus epidemic from various aspects (Chamola et al. 2020).”
From Blockchain and Artificial Intelligence Technology in E-Health (2021) · cites this paper as Chamola et al. 2020
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Comparative Analysis of Supervised Machine Learning Algorithms for COVID-19 Prediction
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Machine Learning Analysis in the Field of Heart Disease
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Libraries on the Global Health Crisis
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Breakthroughs in Information Technology and Their Implications for Education and Health
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Use of ICT to Confront COVID-19
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Fukami, Y., & Masuda, Y. (2021) · Smart innovation, systems and technologies · doi:10.1007/978-981-16-3013-2_2 · Cited by 1
IoT-Based Method to Enhance Testing Frequency Against COVID-19
Emmanuel, A., Ezeh, C., & Okoronkwo, C. D. (2021) · IEEE International Conference on Cyberspace (CYBER NIGERIA) · doi:10.1109/cybernigeria51635.2021.9428816 · Cited by 1
5G Awareness and its Link to COVID-19: Case of Zambians with Access to Internet
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Connected Medical Kiosks to Counter COVID-19: Needs, Architecture & Design Guidelines
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Prediction and Diagnosis of COVID-19 using Machine Learning Algorithms
Savla, H., Mehta, V., & Mangrulkar, R. S. (2020) · International Journal of Recent Technology and Engineering (IJRTE) · doi:10.35940/ijrte.c4676.099320 · Cited by 1
Privacy-Aware Content-of-Interest Search and Recommendation in Internet of Things for Cross-Dressers
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Mobile Applications for COVID-19: Benefits, Technologies and Future Research Opportunities
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An Optimal Scheme to Recharge Communication Drones
Arribas, E., Cholvi, V., & Mancuso, V. (2022) · Nova Science Publishers (Nova Science Publishers, Inc.) · doi:10.1109/globecom46510.2021.9685363 · Cited by 1
Impact of Loneliness and Quarantine on COVID-19 Patients with Artificial Intelligence Applications
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Dual-Polarized Vivaldi Antenna Development for a Multi-technology Testbed
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Autonomous Temperature scan system using IoT to detect COVID-19 symptom
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Metadata
- Authors
- Chamola, V., Hassija, V., Gupta, V., & Guizani, M.
- Affiliations
- Birla Institute of Technology and Science, Pilani (IN)
- Jaypee Institute of Information Technology (IN)
- Qatar University (QA)
- Venue
- IEEE Access
- Published
- 2020
- Volume
- 8
- Pages
- 90225-90265
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W3023617420
- Cited by
- 1,099
- References
- 56
- Citations by year
- 2026: 29 · 2025: 69 · 2024: 97 · 2023: 179 · 2022: 259 · 2021: 359 · 2020: 107
- FWCI
- 212.83
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- IEEE Access (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Qatar University QSpace (Qatar University) (submittedVersion)
- Funders
- Qatar National Research Fund (NPRP10-1205-160012)
- Topics
- Physical Sciences › Computer Science › Information Systems › Healthcare during COVID-19 Pandemic
- Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Data and IoT Technologies
- Keywords
- COVID-19 pandemic, Internet of Things, unmanned aerial vehicles, artificial intelligence, blockchain, 5G, healthcare burden, lockdown, economic impact, misinformation
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