Sensed Signal Strength Forecasting for Wireless Sensors Using Interval Type-2 Fuzzy Logic System
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TL;DR
It is demonstrated that the sensed signals of wireless sensors are self-similar, which means it can be forecasted and can be further used for power on/off control in wireless sensors to save battery energy.
Abstract
In this paper, we present a new approach for sensed signal strength forecasting in wireless sensors using interval type-2 fuzzy logic system (FLS). We show that a type-2 fuzzy membership function, i.e., a Gaussian MF with uncertain mean is most appropriate to model the sensed signal strength of wireless sensors. We demonstrate that the sensed signals of wireless sensors are self-similar, which means it can be forecasted. An interval type-2 FLS is designed for sensed signal forecasting and is compared against a type-1 FLS. Simulation results show that the interval type-2 FLS performs much better than the type-1 FLS in sensed signal forecasting. This application can be further used for power on/off control in wireless sensors to save battery energy.