Design of intelligent IoT for smart healthcare monitoring system using optimal neural network (IONN) model

Abstract

One of the most important aspects of human life is health. Every society is paying more attention to and implementing technology in the areas of health and healthcare. In the healthcare sector, Artificial Intelligence (AI) is frequently employed to deliver quick and reliable results. Early disease predictions assist doctors in making timely decisions to save patients' lives. The Internet of Things (IoT) is assisting AI applications in healthcare by acting as a catalyst. The data of the patients is gathered by IoT sensor, and the data is analysed using machine learning algorithms. The IONN model, an innovative and intelligent healthcare monitoring system based on modern technologies such as the IoT, optimization techniques, and machine learning, is introduced in this study to detect various diseases early and precisely. For people who reside in rural places, this system gives a low-cost solution. The accuracy of the proposed IONN model has enhanced by 4% to 15% when compared to existing approaches. Furthermore, as compared to ANNs that use the BPN algorithm, the IONN model reduces the overall training time by 15% to 52%.