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In the aftermath of COVID-19, its persistent global influence continues to shape various aspects of society. The World Health Organization (WHO) highlights fever as one of the most common symptoms, leading to the adoption of protective measures such as mask-wearing and social distancing to mitigate the virus spread. These measures have also proven effective in halting the spread of other respiratory diseases such as influenza and pneumonia. This paper addresses the sustained enforcement of these health measures post-pandemic, which is still needed in many closed communities such as hospitals, clinics, elderly care homes, nurseries, and shopping malls by proposing an integrated monitoring and warning system designed for health compliance monitoring. The proposed system employs body temperature screening, mask detection, facial recognition, and social distance monitoring. Real-time access is provided through a mobile application for both authorities and individuals, with notifications triggered for high temperatures or violations of mask-wearing and social distancing protocols.

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IoT Machine Learning-Based Health Compliance Monitoring System

  • 会议论文

  • 发表日期：

    2025年

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  • Ahmad Alnabulsi,
  • Salam Dhou,
  • A. R. Al-Ali,
  • Rim Tawfik,
  • Raneem Al-Qutayri,
  • Ahmed Hamad,
  • Adham Mossalam

摘要

In the aftermath of COVID-19, its persistent global influence continues to shape various aspects of society. The World Health Organization (WHO) highlights fever as one of the most common symptoms, leading to the adoption of protective measures such as mask-wearing and social distancing to mitigate the virus spread. These measures have also proven effective in halting the spread of other respiratory diseases such as influenza and pneumonia. This paper addresses the sustained enforcement of these health measures post-pandemic, which is still needed in many closed communities such as hospitals, clinics, elderly care homes, nurseries, and shopping malls by proposing an integrated monitoring and warning system designed for health compliance monitoring. The proposed system employs body temperature screening, mask detection, facial recognition, and social distance monitoring. Real-time access is provided through a mobile application for both authorities and individuals, with notifications triggered for high temperatures or violations of mask-wearing and social distancing protocols.