Localization of a Mobile Device with Sensor Using a Cascade Artificial Neural Network-Based Fingerprint Algorithm

DOI

10.2991/ijcis.2018.125905644How to use a DOI?

Keywords

Zigbee; Fingerprint algorithm; Wireless sensor network; Cascade artificial neural network

Abstract

One of the important functions of sensor networks is that they collect data from the physical environment and transmit them to a center for processing. The location from which the collected data is obtained is crucial in many applications, such as search and rescue, disaster relief, and target tracking. In this respect, determination of the location with low-cost, scalable, and efficient algorithms is required. This study presents the implementation of a fingerprint-based location determination algorithm by using the cascade artificial neural network (ANN). A 15.6 × 13.8 m² implementation area, in which an anchor node is placed at each corner, is divided into grids with a 60-cm edge. The proposed algorithm consists of two phases: offline and online. In the offline phase, first a mobile device with an Xbee sensor, which is able to move sensitively and communicate with anchor nodes, is used. With this device, the implementation area is visited, and at each grid point, received signal strength indicator (RSSI) values and real distances measured from the anchor nodes are recorded in a database. The training of the cascade ANN is done using the database for both range and location determination. In the online phase, the RSSIs measured by the anchor nodes are provided as the input to the cascade ANN algorithm by means of a mobile device in any coordinate. The location of the mobile device and its distance to the anchor nodes are determined with minimum error. To show the superiority of the proposed method, the results obtained are compared with those in the literature and it has been shown that this location determination is made with a smaller error.

Copyright

© 2019 The Authors. Published by Atlantis Press SARL.

Open Access

This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Ebubekir Erdem
AU  - Taner Tuncer
AU  - Resul Doğan
PY  - 2019
DA  - 2019/01/24
TI  - Localization of a Mobile Device with Sensor Using a Cascade Artificial Neural Network-Based Fingerprint Algorithm
JO  - International Journal of Computational Intelligence Systems
SP  - 238
EP  - 249
VL  - 12
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.2018.125905644
DO  - 10.2991/ijcis.2018.125905644
ID  - Erdem2019
ER  -