This framework employs machine learning to improve COVID-19 detection in diverse IoT data, emphasizing feature extraction.
The COVID-19 pandemic has profoundly affected global public health, requiring the creation of precise and effective illness detection tools. The expansion of the healthcare sector has been significantly enhanced by the Internet of Things (IoT), which supports various applications such as telemedicine and direct consultations. COVID-19 can be readily identified by employing artificial intelligence algorithms on users' IoT data. Nevertheless, conventional artificial intelligence algorithms were inadequate in extracting and selecting features from the dataset. This study employed the machine learning optimized COVID-19 classification model to identify SC2, other, and no virus categories from IoT data
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Biswajit Patra (2025) studied this question.
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