Optimal sensor placement strategy for environmental monitoring using Wireless Sensor Networks

This paper presents a novel strategy in determining an optimal sensor placement scheme for environmental monitoring using Wireless Sensor Networks (WSN). This is accomplished by minimizing the variance of spatial analysis based on randomly chosen points representing the sensor locations. These points are assigned randomly generated measurements based on a specified distribution. Spatial analysis is employed using Geostatistical Analysis (classical variography and ordinary point kriging) and optimization occurs with Monte Carlo Analysis. A simple example of measuring mercury in soil is illustrated in finding the optimal sensor placement using WSNs. Studied variables include the number of sensor locations, variances, and Monte Carlo repetitions.