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http://dx.doi.org/10.7840/kics.2014.39C.9.820

Localization Estimation Using Artificial Intelligence Technique in Wireless Sensor Networks  

Kumar, Shiu (Department of Electronics Engineering, Mokpo National University)
Jeon, Seong Min (Department of Electronics Engineering, Mokpo National University)
Lee, Seong Ro (Department of Information Electronics Engineering, Mokpo National University)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.39C, no.9, 2014 , pp. 820-827 More about this Journal
Abstract
One of the basic problems in Wireless Sensor Networks (WSNs) is the localization of the sensor nodes based on the known location of numerous anchor nodes. WSNs generally consist of a large number of sensor nodes and recording the location of each sensor nodes becomes a difficult task. On the other hand, based on the application environment, the nodes may be subject to mobility and their location changes with time. Therefore, a scheme that will autonomously estimate or calculate the position of the sensor nodes is desirable. This paper presents an intelligent localization scheme, which is an artificial neural network (ANN) based localization scheme used to estimate the position of the unknown nodes. In the proposed method, three anchors nodes are used. The mobile or deployed sensor nodes request a beacon from the anchor nodes and utilizes the received signal strength indicator (RSSI) of the beacons received. The RSSI values vary depending on the distance between the mobile and the anchor nodes. The three RSSI values are used as the input to the ANN in order to estimate the location of the sensor nodes. A feed-forward artificial neural network with back propagation method for training has been employed. An average Euclidian distance error of 0.70 m has been achieved using a ANN having 3 inputs, two hidden layers, and two outputs (x and y coordinates of the position).
Keywords
Anchor Nodes; Artificial Neural Network (ANN); Levenberg-Marquardt Algorithm; Beacons; Localization Estimation; RSSI values; Wireless Sensor Networks (WSNs). Networks (WSNs);
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