Indoor Location Estimation in Sensor Networks using AI Algorithm

József Dániel Dombi

Abstract

To determine the indoor location of a person or object, we can use a suitable wireless network. There are different kinds of wireless networks available for this. Independent of the type of the network, using RSSI it is possible to find the position of the moving person close by. Here, we present Wireless Sensor Network and apply it in a real environment. We will mainly concentrate on locating a person using standard artificial intelligence methods. In our system we define nodes (the fingerprint), and supervised learning algorithms that should predict these nodes. In addition, we test whether we can get nice results if we change the granularity of the nodes. Real simulation demonstrates that this system can supply the current position of the moving person with good accuracy.

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Paper Citation


in Harvard Style

Dombi J. (2012). Indoor Location Estimation in Sensor Networks using AI Algorithm . In Proceedings of the 14th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-8565-10-5, pages 349-352. DOI: 10.5220/0004098303490352


in Bibtex Style

@conference{iceis12,
author={József Dániel Dombi},
title={Indoor Location Estimation in Sensor Networks using AI Algorithm},
booktitle={Proceedings of the 14th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2012},
pages={349-352},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004098303490352},
isbn={978-989-8565-10-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 14th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Indoor Location Estimation in Sensor Networks using AI Algorithm
SN - 978-989-8565-10-5
AU - Dombi J.
PY - 2012
SP - 349
EP - 352
DO - 10.5220/0004098303490352