kumoh national institute of technology
Networked Systems Lab.

Rizki Rivai Ginanjar, and Dong-Seong Kim, "Real-Time SLFN-based Node Localization using UAV", IEEE International Conference on Industrial Cyber-Physical Systems (ICPS) 2019, pp.101-105, May 6th - 9th, 2019, Taipei, Taiwan (N1) (A)
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Date : 2019-02-20
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In this paper, a novel real-time single hidden layer feedforward neural network (SLFN)-based node localization technique in the wireless sensor network (WSN) is proposed. The localization is performed using mobile unmanned aerial vehicles (UAVs) as the anchor nodes to send the beacon signals every period of time, thus every unknown node can predict it's current position based on the RSSI values of the received beacon signals by training the SLFN using extreme learning machine (ELM) technique. There are no deployed ground anchor nodes and require fewer anchor nodes compared to traditional RSSI-based localization technique to yield better accuracy. Simulation results show that this technique is capable of performing real-time unknown nodes localization with less localization error by using ELM compared to other traditional machine learning algorithms.
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