Multilayer Perceptron for Activity Recognition Using a Batteryless Wearable Sensor

Abstract

Smart City is one of the trends around the world today. In order to achieve a smart city environment, we need everything to be connected and to be managed. As one of the aspects that have strong impact on people life is their own activities, a smart city should be accompanied by smart people which could be actualized by using sensors to recognize their activities. In this research, we present and evaluate a method to recognize the gesture of someone leaving bed using RFID device. We use a classification approach in our system to conduct the experiment. The method that we are using is MLP (Multi-Layer Perceptron). By using this method, we got 90.17% of accuracy, which is slightly better than Naive Bayesian that got 84.46% of accuracy.