Avaliação de desempenho de técnicas de localização em ambientes reais aplicadas a redes de sensores sem fio

Abstract

The location of wireless sensor networks is a challenge that goes beyond the use of popular GPS through several studies that aim to improve it or even replace it. The location can be performed using multiple antennas and their respective angles, and time synchronization, time differential between transmission of two different or same power with a radio signal. From these patterns estimated, various techniques have been postulated in order to use the resources available to measure distances and estimate the coordinates of a node. Among these techniques may be cited as the most important Lateração, Nearest Neighbor, K-Nearest Neighbor, Min-Max, Non-Linear Regression, Linear Regression Non-Iterative, Sum-Dist, Dv-hop, Artificial Neural Network, filter Kalman . This paper conducts a series of tests conducted in two environments, the first indoor, outdoor and the second using the hardware as the MEMSIC IRIS modules to perform the experiment. These tests are compared Lateração, KNN and an Artificial Neural Network techniques is proposed for the purpose of estimating the location of a WSN node. Lateração mathematical formulations KNN and are presented as well as the configuration of the neural network used in the tests conducted in this work. The results are shown taking the benchmark for comparative analysis techniques to the percentage there between and better quantitative analysis, the data are tabulated for display accuracy.