Indoor localization in wireless sensor networks

Abstract

We considered the issue of indoor localization through the use of wireless sensor networks (WSN). We value not necessary the algorithm that provides the best accuracy but the one that provides a good enough level of accuracy in a simple and efficient manner. In the first part of our work we examined some state-of-the-art localization techniques that are deployable on wireless sensor motes. These techniques are evaluated to a set of criteria that an indoor WSN-based localization application mustconsider. In our investigation, we considered not only accuracy but many other factors that determine a suitable indoor WSN-based localization system. These factors among other things determine energy efficiency. We broadly separate the criteria list into two categories: efficiency-based and accuracy-based. We discovered that one of the techniques, Ecolocation, evaluates quite well to the efficiency-based criteria, but the evaluationof the accuracy-based criterions is not as promising. However, the inherent simplicity and potential for good performance (based on openenvironment results) make the algorithm quite attractive. We proceeded to modify the algorithm to improve its accuracy while maintaining itspositive qualities. Our Weighted-Constraints algorithm, named as such due to the nature of the modification, performs in terms of average error 13.1% better than the original Ecolocation algorithm in an open environment. Furthermore, our modified algorithm shows it is more robustto noise compared to the original algorithm by perform on average 21.2% better in a noisy environment.