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International Journal of Sensors, Wireless Communications and Control

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ISSN (Print): 2210-3279
ISSN (Online): 2210-3287

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Research Article

MLCEL: Machine Learning and Cost-Effective Localization Algorithms for WSNs

Author(s): Omkar Singh* and Lalit Kumar

Volume 13, Issue 2, 2023

Published on: 22 May, 2023

Page: [82 - 88] Pages: 7

DOI: 10.2174/2210327913666230502124733

Price: $65

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Abstract

Introduction: Wireless communication systems provide an indispensable act in real-life scenarios and permit an extensive range of services based on the users' location. The forthcoming implementation of versatile localization networks and the formation of subsequent generation Wireless Sensor Network (WSN) will permit numerous applications.

Materials and Methods: In this perspective, localization algorithms have converted into an essential tool to afford compact implementation for the location-based system to increase accuracy and reduce computational time, proposing a Machine Learning and Cost-Effective Localization (MLCEL) algorithm. MLCEL algorithm is assessed with considered localization algorithms called Support Vector Machine for Regression (SVR), Artificial Neural Network (ANN), and K Nearest Neighbor (KNN). Numerous outcomes show that the MLCEL algorithm performs better than state art algorithms. The simulation is implemented in MATLAB version 8.1 for a network size of 100 nodes. Sensor nodes are positioned in a network area of 100 ×100 m2.

Conclusion and Results Discussion: The results are assessed on different parameters, and MLCEL achieves better results in localization error 13% 16%, cumulative probability 19%-21%, root mean square error 14%-18%, distance error 17%-20%, and computational time 22%-24% than SVR, ANN, and KNN.

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