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Research Journal of Information Technology

Year: 2012 | Volume: 4 | Issue: 4 | Page No.: 155-165
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Authors

Azat Rozyyev

Halabi Hasbullah

Fazli Subhan

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Research Article

Combined K-Nearest Neighbors and Fuzzy Logic Indoor Localization Technique for Wireless Sensor Network

Azat Rozyyev, Halabi Hasbullah and Fazli Subhan
The use of Wireless Sensor Network (WSN) has been growing each year. One of the more popular uses of WSN is object tracking. There are many localization techniques available for WSN. Some techniques have high accuracy, while the complexity is higher than others as well. K-Nearest Neighbors (KNN) has high accuracy in indoor environment. The accuracy of KNN could be improved by combining it with fuzzy logic. Fuzzy logic will allow the algorithm complexity to stay low. This study presents the results of experiment where the combined KNN and fuzzy logic localization technique (fuzzy KNN) improved the accuracy of KNN. When compared to other localization techniques from the literature with high accuracy, Multilateration and fuzzy logic indoor positioning system fuzzy KNN performed better in terms of accuracy and algorithm complexity.
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How to cite this article

Azat Rozyyev, Halabi Hasbullah and Fazli Subhan, 2012. Combined K-Nearest Neighbors and Fuzzy Logic Indoor Localization Technique for Wireless Sensor Network. Research Journal of Information Technology, 4: 155-165.

URL: https://scialert.net/abstract/?doi=rjit.2012.155.165

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