Design of IoT Enabled Cloud Assisted Health Monitoring System for Covid-19 Patients

Abstract

Covid-19 is one of the life-threatening diseases which requires intensifying attention to combat disease by designing a smart and effective healthcare system for patients towards diagnosing and managing the Covid-19 disease. Various systems have been developed for diagnosing patient with diseases, but intelligent and feasible solution to explore and monitor the accurate predictive health conditions of affected patients has not been provided yet. In this paper, a new Contactless IoT-enabled cloud-assisted health monitoring system has been designed and developed. The system is made up of unobtrusive sensors, a data acquisition unit, a microcontroller, wi-fi Module, Web server, and Web application or mobile application. It illustrates the design of the system to monitor and detect the severity of the coronavirus in the patients using various unobtrusive sensors to measure disease-specific vital parameters such as heart rate, temperature, oxygen level and pulse rate as main symptoms of the coronavirus are high fever, fatigue, and difficult breathing. Sensor acquired patient data is transformed using the HTTP protocol to cloud server using microcontroller and wi-fi module in real-time. Transformed data of patient condition is processed in the cloud server using data predictive algorithms such as Severity Defined Convolution Neural Network with respect to data collected and severity specific data thresholds and severity class predicted patient information will alarm the healthcare provider on the abnormalities detected in the patient health. A particular model is capable of forecasting the health situation of the patients. Experimental analysis of the proposed architectures finds it effective in monitoring the status of the severity of breathing on the patients. Finally, the performance of the architecture is validated over accuracy and scalability measures.