Smart Village Health System IoT to Envisage Chronical Disease Using Artificial Neural Network

Abstract

A Smart Village Health System (SVHS) understands the infrastructure, facilities, and schemes open to its villager. The Internet of Things (IoT) transforms a village health system into an SVHS using ANN that includes schools, highways, environment, and globalization. It has been designed with the intension to provide basic healthcare facilities to the inhabitant. It also gives information about the chronic diseases by employing Artificial Neural Network (ANN). A SVHS model based on HCV dataset is proposed in this paper. The system is built with cloud and IoT to enable data by means of the patient's input parameters to be collected, indexed and visualized in a smart village. The Levenberg-Marquardt (LM), Bayesian Regularization (BR) and the Scale Conjugate Gradient (SCG) algorithms are implemented with ANN-based approach named as " IoT enabled Smart Village Health System to Predict Chronical Disease empowered with Artificial Neural Network (ToVHS)" in order to develop an efficient and smart CHP model. The evaluation of the proposed method indicates that the SCG algorithm achieves promising results with respect to accuracy and miss rates. The predicted accuracy of the proposed model shows 90.39% performance of CHP on the given factors.