Sample Linguistic Variables A Fuzzy Logic Programming Model for Sensor Networks Bradford G. Nickerson and Ke Deng University of New Brunswick Faculty of Computer Science Motivation Our hypothesis is that reliability of web-connected sensor networks can be improved by adding to SWL adaptive control rules represented using a fuzzy logic controller approach. SWL Fuzzy Controller Membership Function Rule 1 If air temperature is freezing for more than 24 consecutive hours, and rainfall amount sensor indicates light rainfall, and water level sensor observation rate is currently normal, then decrease the rate of observation of the water level sensor to infrequent. Simulation Air Temperature 10 deg. C Rainfall Amount 6 mm / 24 hrs Current Observation Rate 5 times / hr Sample Linguistic Variables Category Variable States SI Units water temperature freezing, cold, warm, hot deg. C level low, medium, high m rainfall light, moderate, heavy mm / 24 hrs air humidity low, normal, high, saturated % soil moisture saturated, dry, damp, normal m3m-3 sun solar radiation watts / m2 Rule 2 If air temperature is above freezing for more than 12 consecutive hours, and rainfall amount sensor indicates moderate rainfall, and water level sensor observation rate is currently infrequent, then increase the rate of observation of the water level sensor to normal. Accumulation Function Activation Functions Sensor Network State Sensor Node SN2 Planned Field Experiment Mica2 Mote Filter Water Level Sensor Air Temperature Sensor RF1: rainfall amount sensor WL1: water level sensor AT1: air temperature sensor oi : current observation rate ri(t) : a vector of sensor readings