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Application of Healthcare Management Technologies for COVID-19 Pandemic Using Internet of Things and Machine Learning Algorithms

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Abstract

Internet of Things (IoT) has acquired persuading research ground as another examination subject under big assortment regards scholarly and modern disciplines, particularly under healthcare. IoT transformation has been reconstructing current healthcare frameworks through consolidating innovative, financial, and social possibilities. It was developing health care frameworks through customary to extra customized healthcare frameworks by kinds of patients may analyzed, handled, and checked all the extra without any problem. Since from the time of pandemic began, there was quick exertion under various examination networks to take advantage of a big assortment of advances to battle this overall danger, and IoT innovation is one of pioneers around here. IoTs sensor-based innovation gives a brilliant capacity to decrease the danger of medical procedure during convoluted cases and supportive for COVID-19 sort pandemic. In the clinical field, IoTs centre is to assist with playing out the treatment of various COVID-19 cases unequivocally. It makes the specialist work simpler through limiting dangers and expanding general presentation. Through utilizing this innovation, specialists can undoubtedly distinguish changes in basic boundaries of the COVID-19 patient. This paper overviews the job of IoT based advancements under COVID-19 and surveys the best in class structures, stages, applications, and modern IoT based arrangements fighting COVID-19 of every three primary stages, including early conclusion, quarantine time, and after recuperation. In conclusion, the paper is revealing that all machine-learning algorithms tested in this study can be used in the prediction of healthcare with a high accuracy; however, the SVM and K-NN algorithms are the best fitting algorithms among all algorithms. Then Naïve Bayes, Decision Table, and Decision Stump follow it respectively.

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Data Availability

The datasets generated during and/or analysed during the current study are not publicly available, but are available from the corresponding author on reasonable request.

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Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

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Authors and Affiliations

  1. Ibn Sina University for Medical and Pharmaceutical Sciences, Baghdad, Iraq

    Nooruldeen Q. Ismaeel

  2. Al-Karkh University of Science, Baghdad, Iraq

    Husam Jasim Mohammed

  3. Al-Esraa University College, Baghdad, Iraq

    Ibrahim Zeghaiton Chaloob

  4. Business Information Technology, University of Sulaimani, Sulaymaniyah, Iraq

    Ameer Sardar Kwekha-Rashid

  5. Yildiz Technical University, Istanbul, Turkey

    Bilal Alhayani

  6. Technical Engineering College, The Islamic University, Najaf, Iraq

    Ahmed Alkhayyat

  7. Department of Computer Engineering Techniques, College of Information Technology, Imam Ja’afar Al-Sadiq University, Baghdad, Iraq

    Sara Taher Abbas

  8. Department of Medical Instrumentation Techniques Engineering, Dijlah University College, Baghdad, 10022, Iraq

    Mohammed Dauwed

  9. Department of Energy Engineering, College of Engineering/ Al-Mussaib, University of Babylon, Babil, Iraq

    Omar A. Alkawak

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  1. Nooruldeen Q. Ismaeel
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  2. Husam Jasim Mohammed
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All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by all authors equally. All authors read and approved the final manuscript.

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Correspondence to Nooruldeen Q. Ismaeel.

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Ismaeel, N.Q., Mohammed, H.J., Chaloob, I.Z. et al. Application of Healthcare Management Technologies for COVID-19 Pandemic Using Internet of Things and Machine Learning Algorithms. Wireless Pers Commun (2023). https://doi.org/10.1007/s11277-023-10663-2

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