2023-12-052023-12-052022-10-20978-1-6654-8025-3http://hdl.handle.net/20.500.12272/9062This work presents a simple model that expose the information embedded into a sensor signal allowing to share it independently of the signal nature. Today's highly interconnected world requires a representation of sensor signals that let efficient sharing of embedded information. The proposed model is a state matrix that combine two important aspects of any signal: Its value inside a range and its behavior over the time. From this state matrix is possible to obtain a self-learning model observing the state transition probabilities and the time lapse in each state to deduce signal normality- abnormality that allows to infer a better perception of reality.pdfengopenAccesshttp://creativecommons.org/licenses/by-nc-nd/4.0/Attribution-NonCommercial-NoDerivatives 4.0 InternacionalEdge processing, self-learning, data fusion, sensor signal representation, Smart Cities.info:eu-repo/semantics/articleCreative Commos