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The Role of Internet of Things (IoT) in the Containment and Spread of the Novel COVID-19 Pandemic

Part of the Studies in Computational Intelligence book series (SCI,volume 923)

Abstract

The novel COVID-19 pandemic is hitting the strongest economies in an unprecedented manner leading to the crippling of most economic sectors globally. Movement restriction order profoundly affected many industries, including manufacturing, transportation, aviation, education, tourism, and trade and investment, among others. The consequences resulted in people losing their jobs, corporate organizations and the Government experiencing a sharp drop in income and revenue. Similarly, the global crude oil market prices crash to the lowest rate of less than USD30/barrel. In recent times, the world has not witnessed a pandemic that threatened human existence without any sigh of relief as no cure has been found for the disease. The most effective recommended measure in containing the chain of transmitting the virus is through social distancing as a large gathering of people is highly discouraged. Internet of Things (IoT) alongside other related technologies such as artificial intelligence (AI), drones, robotics, Big Data, and e-learning related technologies were found as platforms that can play a critical role in breaking the chain of the virus transmission. This study highlighted the role of IoT related technologies as a measure that enhances human-machine interaction, which supports the social distancing among people.

Keywords

  • Internet of things
  • Artificial intelligence
  • Robot
  • Drone
  • COVID-19 pandemic

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References

  1. Hossain, M., Islam, S. M. R., Ali, F., Kwak, K.-S., & Hasan, R. (2018). An internet of things-based health prescription assistant and its security system design. Future Generation Computing Systems, 82, 422–439. https://doi.org/10.1016/j.future.2017.11.020.

    CrossRef  Google Scholar 

  2. Ting, D. S. W., Lin, H., Ruamviboonsuk, P., Wong, T. Y., & Sim, D. A. (2020). Artificial intelligence, the internet of things, and virtual clinics: ophthalmology at the digital translation forefront. The Lancet Digital Health, 2(1), e8–e9. https://doi.org/10.1016/S2589-7500(19)30217-1.

    CrossRef  Google Scholar 

  3. Shah, S. J. et al. (2018). Virtual visits partially replaced in-person visits in an ACO-based medical specialty practice. Health Affairs, 37(12), 2045–2051. https://doi.org/10.1377/hlthaff.2018.05105.

  4. Zarpelão, B. B., Miani, R. S., Kawakani, C. T., & de Alvarenga, S. C. (2017). A survey of intrusion detection in Internet of Things. Journal of Network and Computer Applications, 84, 25–37. https://doi.org/10.1016/j.jnca.2017.02.009.

    CrossRef  Google Scholar 

  5. Atzori, L., Iera, A., & Morabito, G. (2010). The internet of things: A survey. Computer Networks, 54(15), 2787–2805. https://doi.org/10.1016/j.comnet.2010.05.010.

    CrossRef  MATH  Google Scholar 

  6. Ericsson. (2019). Ericsson Mobility Report, 2019.

    Google Scholar 

  7. Gupta, S., Kumar, V., & Karam, E. (2019). New-age technologies-driven social innovation: What, how, where, and why? Industrial Marketing Management. https://doi.org/10.1016/j.indmarman.2019.09.009.

    CrossRef  Google Scholar 

  8. Borgia, E. (2014). The internet of things vision: Key features, applications and open issues. Computer Communications, 54, 1–31. https://doi.org/10.1016/j.comcom.2014.09.008.

    CrossRef  Google Scholar 

  9. Chu, D. K., Akl, E. A., Duda, S., Solo, K., Yaacoub, S., & Schünemann, H. J. (2020). Physical distancing, face masks, and eye protection to prevent person-to-person transmission of SARS-CoV-2 and COVID-19: A systematic review and meta-analysis. Lancet, 395(10242), 1973–1987. https://doi.org/10.1016/s0140-6736(20)31142-9.

  10. Kumar, K., & Lu, Y.-H. (2010). Cloud computing for mobile users: Can offloading computation save energy? Computer (Long. Beach. Calif), 43(4), 51–56. https://doi.org/10.1109/mc.2010.98.

  11. Hossain, M. S., & Muhammad, G. (2016). Cloud-assisted industrial internet of things (IIoT)—Enabled framework for health monitoring. Computer Networks, 101, 192–202. https://doi.org/10.1016/j.comnet.2016.01.009.

    CrossRef  Google Scholar 

  12. Sugumar, D., Anita Jones, T., Senthilkumar, K. S., Jeba Kumar, R. J. S., & Thennarasi, G. (2020). Smart vehicle monitoring and tracking system powered by active radio frequency identification and internet of things. In The cognitive approach in cloud computing and internet of things technologies for surveillance tracking systems (pp. 51–64). Amsterdam: Elsevier.

    Google Scholar 

  13. Floreano, D., & Wood, R. J. (2015). Science, technology and the future of small autonomous drones. Nature, 521(7553), 460–466. https://doi.org/10.1038/nature14542.

  14. Swan, E. L., Dahl, A. J., & Peltier, J. W. (2019). Health-care marketing in an omni-channel environment. The Journal of Interactive Marketing, 13(4), 602–618. https://doi.org/10.1108/JRIM-03-2019-0039.

    CrossRef  Google Scholar 

  15. Haenlein, M., & Kaplan, A. (2019). A brief history of artificial intelligence: On the past, present, and future of artificial intelligence. California Management Review, 61(4), 5–14. https://doi.org/10.1177/0008125619864925.

    CrossRef  Google Scholar 

  16. Makridakis, S. (2017). The forthcoming Artificial Intelligence (AI) revolution: Its impact on society and firms. Futures, 90, 46–60. https://doi.org/10.1016/j.futures.2017.03.006.

  17. Qazi, S., & Raza, K. (2020). Smart biosensors for an efficient point of care (PoC) health management. In Smart biosensors in medical care (pp. 65–85). Amsterdam: Elsevier.

    Google Scholar 

  18. Alsabawy, A. Y., Cater-Steel, A., & Soar, J. (2016). Determinants of perceived usefulness of e-learning systems. Computers in Human Behavior, 64, 843–858. https://doi.org/10.1016/j.chb.2016.07.065.

    CrossRef  Google Scholar 

  19. Joo, Y. J., Park, S., & Shin, E. K. (2017). Students’ expectation, satisfaction, and continuance intention to use digital textbooks. Computers in Human Behavior, 69, 83–90. https://doi.org/10.1016/j.chb.2016.12.025.

    CrossRef  Google Scholar 

  20. Dhar, V. (2013). Data science and prediction. Commun ACM, 56(12), 64–73. https://doi.org/10.1145/2500499.

    CrossRef  Google Scholar 

  21. Raza, K., & Qazi, S. (2019). Nanopore sequencing technology and Internet of living things: A big hope for U-healthcare. In Sensors for health monitoring (pp. 95–116). Amsterdam: Elsevier.

    Google Scholar 

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Correspondence to Ibrahim Babangida Mohammed .

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Mohammed, I.B., Isa, S.M. (2021). The Role of Internet of Things (IoT) in the Containment and Spread of the Novel COVID-19 Pandemic. In: Raza, K. (eds) Computational Intelligence Methods in COVID-19: Surveillance, Prevention, Prediction and Diagnosis. Studies in Computational Intelligence, vol 923. Springer, Singapore. https://doi.org/10.1007/978-981-15-8534-0_6

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