ABSTRACT
World Health Organization (WHO) studies indicate that people with pre-existing diseases are prone to suffer the severity of the effects of COVID-19 in case of infection. This work presents a mobile application development through open-source software and machine learning techniques for the prediction of the COVID-19 severity in an individual based on pre-existing disease information. For the prediction of the severity and to determine the possibility that an individual ends up in an intensive care unit (ICU), we set a machine learning algorithm, which resulted in a higher probability of prediction when the user undergoes cases of pre-existing diseases, with an efficiency rate of 98 %. We carried out load and stress testing to verify the processing performance, battery consumption, startup latency, and maximum amount of user connections supported by the application, complemented with a wristband for individual's real-time monitoring to attain low battery consumption when using public cloud services and low-power technologies for the connection. © 2023 IEEE.