A Secure IoT-Cloud Based Remote Health Monitoring for Heart Disease Prediction Using Machine Learning and Deep Learning Techniques †

Abstract

The Internet of Things (IoT) refers to a network of interconnected devices as well as technology that enables objects to communicate with one another and the cloud for modern medical treatment. To analyze and handle remotely collected electronic clinical records, it is important to create a disease prediction model with increased accuracy. An RHMIoT framework is proposed in a secure cloud context using lightweight block encryption and decryption approaches. The accuracy levels of cardiac disease are calculated using machine learning and deep learning methods. The ensemble voting classifier provided the greatest accuracy of 95%.