1. 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