Transducer State Prediction System for Smart Environment Intelligent Control

Smart environments possess devices that collaborate to help the user non-intrusively. One possible aid smart environment offer is to anticipate user´s tasks and perform them on his/her behalf or facilitate the action completion. In this paper, we propose a framework that predicts user´s actions by learning his/her behavior when interacting with the smart environment. We prepare the datasets and train a predictor that is responsible to decide whether a target transducer value should be changed or not. Our solution achieves a significant improvement for all target transducers studied and most combinations of parameters yields better results than the base case.