Iot And Cloud Computing Platform For Covid-19 Detection And Monitoring In Healthcare

Abstract

Global attention has been focused on COVID-19, a contagious sickness. Modelling illnesses may greatly improve the prediction of their consequences. While traditional statistical modelling may be effective, it may not fully capture the difficulty of the data. Automatic COVID-19 discovery using computed tomography (CT) scans or X-rays is successful, but healthy system design is problematic. This paper suggestsasmart healthcare system using IoT-cloud technology. This design employs smart connection devices and deep learning (DL) for smart city decision-making. The sophisticated technology provides real-time patient tracking and affordable, high-quality healthcare services. DL experiments are used to assess the feasibility of the suggested COVID-19 detecting system. Sensors are used to capture, convey, and monitor healthcare data. IoT sensors electronically transmit patient CT scan pictures to the cloud, where the cognitive unit is kept. The technology determines patient status from CT scan images. The cognitive module of the DL makes real-time decisions on potential actions. Assigning information to a cognitive module, they apply ResNet50, a cutting-edge DL-based classification algorithm, to determine whether patients are healthy or sick with COVID-19. To ensure its robustness and efficacy, the approach is validated using two public datasets (Covid-Chestxray and Chex-Pert). Initially, 5000 photos are gathered from the two datasets. The suggested method was trained on pictures from 80% of datasets and tested on 20%. Tenfold cross-validation is used to evaluate the presentation. The system achieved 99.7% accuracy, 99.3% specificity, 98.4% sensitivity, and 98.88% F1 score. This suggested approach has great accuracy, specificity, sensitivity, and F1 score. Comparing the proposed system to state-of-the-art systems reveals superior performance. The system offered will aid medical diagnostic research and healthcare systems. Additionally, it will aid COVID-19 showing professionals and provide a valued second perspective.