%0 Journal Article
%@ 1932-6203
%A Islam, Md. Milon
%A Shafi, Imran
%A Din, Sadia
%A Farooq, Siddique
%A Díez, Isabel de la Torre
%A Breñosa, Jose
%A Martínez Espinosa, Julio César
%A Ashraf, Imran
%D 2024
%F unic:11322
%J PLOS ONE
%N 3
%P e0298582
%T Design and development of patient health tracking, monitoring and big data storage using Internet of Things and real time cloud computing
%U http://repositorio.unic.co.ao/id/eprint/11322/
%V 19
%X With the outbreak of the COVID-19 pandemic, social isolation and quarantine have become commonplace across the world. IoT health monitoring solutions eliminate the need for regular doctor visits and interactions among patients and medical personnel. Many patients in wards or intensive care units require continuous monitoring of their health. Continuous patient monitoring is a hectic practice in hospitals with limited staff; in a pandemic situation like COVID-19, it becomes much more difficult practice when hospitals are working at full capacity and there is still a risk of medical workers being infected. In this study, we propose an Internet of Things (IoT)-based patient health monitoring system that collects real-time data on important health indicators such as pulse rate, blood oxygen saturation, and body temperature but can be expanded to include more parameters. Our system is comprised of a hardware component that collects and transmits data from sensors to a cloud-based storage system, where it can be accessed and analyzed by healthcare specialists. The ESP-32 microcontroller interfaces with the multiple sensors and wirelessly transmits the collected data to the cloud storage system. A pulse oximeter is utilized in our system to measure blood oxygen saturation and body temperature, as well as a heart rate monitor to measure pulse rate. A web-based interface is also implemented, allowing healthcare practitioners to access and visualize the collected data in real-time, making remote patient monitoring easier. Overall, our IoT-based patient health monitoring system represents a significant advancement in remote patient monitoring, allowing healthcare practitioners to access real-time data on important health metrics and detect potential health issues before they escalate.