Framework based on parameterized images on ResNet to identify intrusions in smartwatches or other related devices

Abstract

A conceptual and algebraically framework that did not exist up until then in its morphology, was developed. What is more, it is pioneer on its implementation in the area of Artificial Intelligence (AI) and it was started up in laboratory, on its structural aspects, as a fully operational model. At qualitative level, its greatest contribution to AI is applying the conversion or transduction of parameters obtained by ternary logic (multi-valued systems) and associating them with an image. This image will be analysed by means of a residual artificial network ResNet34, to warn us of an intrusion. The field of application of this framework includes everything from smartwatches, tablets, and PC’s to the home automation based on the KNX standard.