IoT-Based Patient Monitoring System

Lack of supervision in home quarantine processes and deficiencies, such as limited vital assessment and no Internet of Things (IoT) integrated into existing healthcare monitoring devices, were factors in brought-in-dead (BID) cases during the coronavirus disease endemic (COVID-19) in Malaysia. This research aims to develop an IoMT remote healthcare monitoring system that monitors five physiological parameters and fall accidents. The proposed system generates alert messages with GPS location when an abnormal vital value or fall is detected. The system is equipped with e-health sensors, triaxial accelerometers, and a GPS module. The collected data are transmitted to an IoT platform via Wi-Fi communication using a message queueing telemetry transport (MQTT) protocol for further processing and analysis. Web and mobile applications are developed for visualizing and receiving alert messages. The performance of the proposed system is benchmarked with the medical devices in the market. The average accuracies of measuring oxygen saturation (SpO2), heart rate, body temperature, and respiratory rate are 98.83%, 98.12%, 98.88%, and 97.61%, respectively. The accuracy, sensitivity, and specificity of fall detection are 95%, 94%, and 96%. The system is a viable solution enabling medical professionals to perform in-time treatment during emergencies and mitigate BID cases and fall problems.