Advances in Fuzzy-Based Internet of Medical Things (IoMT)

17Integration of Edge Computing and Fuzzy Logic to Monitor Novel Coronavirus

K. Rama Krishna¹*, R. Sudha², G. N. R. Prasad³ and Jithender Reddy Machana⁴

¹Department of Information Technology, Vasavi College of Engineering, Hyderabad, Telangana, India

²Department of Computer Science and Engineering, Vasavi College of Engineering, Hyderabad, Telangana, India

³Department of MCA, CBIT, Gandipet, Hyderabad, Telangana, India

⁴Vasavi College of Engineering, Telangana, India

Abstract

Opportunities in healthcare have expanded to recent advancements in the Internet of Things (IoT) technology, artificial intelligence, and machine learning. Furthermore, these technical developments equipped us to meet future health-care concerns. Among these problems is the appearance of COVID-19, which has unfathomable consequences. In order to distinguish between patients with and without symptoms, the IoT architecture gathers symptom data in real time from users. In addition, the suggested system can track how well patients who are ill respond to therapy. FLCD is made up of three parts: a cloud-based infrastructure for storing data with a potential judgment (normal, moderate, severe, or critical), a rule-based FLC for combining the system, and symptom data collected through wearable sensors. Experiments with a fabricated COVID-19 sign dataset are done once the required characteristics have been extracted to enable efficient and perfect identification of corona cases. This allowed FLCD to achieve a 95% ...