Use of ANN for embedded domotic system based on IoT

Abstract

Energy consumption is one factor of risk in the medium term around of the world, that can be minimized by efficient use of electrical devices include its disconnection after use. This article presents a system focused on smart homes, where the concepts of Internet of Things and Artificial Intelligence are applied in the designing of a system that allows a user from a web application to disconnect and connect an electrical network in a node. From the power of the device, time of use and consumption of this, an artificial neural network was designed and trained with the backpropagation algorithm, to discriminate between seven categories (fridge, TV, iron, dryer, lamp, computer and washing machine). A percentage of accuracy of 98.914% was obtained in the training of the network and, thanks to the feedback of the user in the web application, 99.369 and 99.174% were obtained in two cases of retraining of the network.