IoT enabled healthcare monitoring system using convolutional neural network

Abstract

Recent development in the Internet of Things (IoT) based smart mobile healthcare monitoring provides better dimensionalities and smart services. The introduction of IoT-based wearable sensor devices circumvents the death of millions of people with regular monitoring and better treatments. This type of monitoring system also increases the data and it is necessary to store the data in any service-provided platform and the cloud is one among them all. The security of data is also a concern while transmitting the data. Further, the prediction of diseases from the collected data is also an intricate process. To address these issues, we propose a novel deep learning-based approach known as Convolutional Neural network-based disease prediction, and the security of the data stored in the cloud can be acquired by the Rivest-Shamir-Adleman (RSA) cryptography algorithm. The performance of our proposed work is analyzed with some state-of-art works. The comparative study shows that the proposed work achieves better security and also the prediction accuracy of our proposed is higher.