Internet of Things for Current COVID-19 and Future Pandemics: an Exploratory Study.
Mohammad Nasajpour,Seyedamin Pouriyeh,Reza M. Parizi,Mohsen Dorodchi,Maria Valero,Hamid R. Arabnia +5 more
- Vol. 4, Iss: 4, pp 1-40
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TLDR
The role of IoT-based technologies in COVID-19 is surveyed and the state-of-the-art architectures, platforms, applications, and industrial IoT- based solutions combating CO VID-19 in three main phases, including early diagnosis, quarantine time, and after recovery are reviewed.Abstract:
In recent years, the Internet of Things (IoT) has gained convincing research ground as a new research topic in a wide variety of academic and industrial disciplines, especially in healthcare. The IoT revolution is reshaping modern healthcare systems by incorporating technological, economic, and social prospects. It is evolving healthcare systems from conventional to more personalized healthcare systems through which patients can be diagnosed, treated, and monitored more easily. The current global challenge of the pandemic caused by the novel severe respiratory syndrome coronavirus 2 presents the greatest global public health crisis since the pandemic influenza outbreak of 1918. At the time this paper was written, the number of diagnosed COVID-19 cases around the world had reached more than 31 million. Since the pandemic started, there has been a rapid effort in different research communities to exploit a wide variety of technologies to combat this worldwide threat, and IoT technology is one of the pioneers in this area. In the context of COVID-19, IoT-enabled/linked devices/applications are utilized to lower the possible spread of COVID-19 to others by early diagnosis, monitoring patients, and practicing defined protocols after patient recovery. This paper surveys the role of IoT-based technologies in COVID-19 and reviews the state-of-the-art architectures, platforms, applications, and industrial IoT-based solutions combating COVID-19 in three main phases, including early diagnosis, quarantine time, and after recovery.read more
Citations
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Information Technology Solutions, Challenges, and Suggestions for Tackling the COVID-19 Pandemic.
TL;DR: Emerging technologies used to mitigate the threats of COVID-19 and relevant challenges related to technology design, development, and use are examined and insights and suggestions into how information systems and technology scholars can help fight the CO VID-19 pandemic are provided.
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A systematic review of IoT in healthcare: Applications, techniques, and trends
TL;DR: This paper aims to identify, compare systematically, and classify existing investigations taxonomically in the Healthcare IoT (HIoT) systems by reviewing 146 articles between 2015 and 2020, and presents a comprehensive taxonomy in the HIoT.
Journal ArticleDOI
Internet of Things (IoT) enabled healthcare helps to take the challenges of COVID-19 Pandemic
Mohd Javaid,Ibrahim Haleem Khan +1 more
TL;DR: In this article, a literature-based study may guide professionals in envisaging solutions to related problems and fighting against the COVID-19 type pandemic, which is a need to study different applications of IoT enabled healthcare.
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Automation and manufacturing of smart materials in additive manufacturing technologies using Internet of Things towards the adoption of industry 4.0
TL;DR: IoT application in AM improves production processes' efficiency followed by reduced manufacturing waste and fulfilled customer specifications and concludes that IoT application inAM improves production process' efficiency and fulfilled customers' specifications.
Journal ArticleDOI
A critical review of emerging technologies for tackling COVID-19 pandemic.
Elliot Mbunge,Boluwaji Akinnuwesi,Stephen G. Fashoto,Andile Simphiwe Metfula,Petros Mashwama +4 more
TL;DR: A comprehensive review of emerging technologies for tackling COVID‐19 with emphasis on the features, challenges, and country of domiciliation shows that performance of the emerging technologies is not yet stable and there is a strong need for the emergence of a robust computationally intelligent model for early differential diagnosis.
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