Internet of Things for Healthcare: An Intelligent and Energy Efficient Position Detection Algorithm

Abstract

In this article, we develop a novel approach for detecting patients’ position using the radial basis function of the neural network. This new approach aims to continuously monitor the patients’ health statistics and real-time prediction, even when they are outside of cellular coverage. Our research is driven by an initiative to innovate a novel healthcare system of significant importance for intelligent and efficient medical services. For example, doctors need to remotely monitor any patient’s health with the provided health statistics derived from data collected from battery-powered Internet of Things sensors. To this end, our proposed method has been quantified with a holistic mathematical analysis and extensive simulations considering realistic network situations. Our results have accredited the efficiency in the prediction of localization for the patients’ position for the anticipated intelligent healthcare system.