The COVID-19-patient health tracking system is a risk factormajor public health challenge for COVID-19 patients, and it has inherited an ample supply of mindfulness recently from the medical community because of the ageing population and an increase in chronic illnesses. It is challenging for traditional wireless communication technology to fully meet the real-time requirements for wearable medical devices. Current monitoring framework cannot handle the massive amount of synchronous cardiovascular data due to the lack of effective streaming data processing mechanisms. The suggested paper uses Internet of Things (IoT) technology to obtain patient medical data both locally and remotely. The patient's temperature sensor and pulse sensor send data to a cloud server, which analyses it with the unification of Hybrid deep-learning model combining a convolutional neural network (CNN) and long short-term memory (LSTM) is utilized and manages it for later analysis. According to the experimental findings, the accuracy of our proposed system was 99.4%, sensitivity 99.3%, specificity 99.2%, and F1-score is 98.9% respectively. © 2025 Elsevier B.V., All rights reserved.