Remote Health Parameter Monitoring Using Internet of Things: An Edge-Cloud Centric Integration for Real-time Reporting

Abstract

Monitoring human health has become a phenomenon that integrates cutting-edge technology, which is capable of provisioning updated and sufficient data information to support human well-being in general. A key component of healthy living is preventing disease and health issues in general. The development of Internet of Things (IoT) technology has greatly improved a number of industries, including healthcare. In this study, a unique four-layered architecture for a Remote Health Parameter Monitoring (RHPM) system that uses sensors to monitor blood oxygen concentration (SpO2), body temperature (BT), and heart rate (HR) is presented. The system incorporates edge and cloud computing technologies. Data preprocessing at the edge is performed using an Arduino ESP8266 board and transmitted to cloud servers via the Message Queuing Telemetry Transport protocol for real-time processing and visualization. The testing of the system returned very high accuracy, yielding Mean Absolute Percentage Error (MAPE) values of 2.32%, 2.94%, and 3.43% for BT, SpO2, and HR, respectively. Another metric of evaluation was the R-squared value, which yielded 98% for BT and 97% for both SpO2 and HR, respectively. This paper integrates Support Vector Machine models, which enhances its predictive capability and achieves a cross-validation accuracy of 94.7%. The result indicated that the RHPM system is able to improve the well-being of the patient through early detection and informed preventive health management. Health institutions can tap into the real-time characteristics of the health parameters being monitored in fueling medical decision support systems for improved customer satisfaction and the delivery of modern healthcare solutions.