Abstract
This work describes a complete indoor location system, from its creation, development and deployment. This location system is a capable way of retrieving the position of wireless devices using a simple software solution, no additional hardware is necessary. The positioning engine uses artificial neural networks (ANN) to describe the behaviour of a specific indoor propagation channel. The training of the ANN is assured using a slight variation of the radio frequency fingerprinting technique. Results show that the location system has high accuracy with an average error below two meters.
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Claro, P., Carvalho, N.B. (2007). Local Positioning System Based on Artificial Neural Networks. In: de Sá, J.M., Alexandre, L.A., Duch, W., Mandic, D. (eds) Artificial Neural Networks – ICANN 2007. ICANN 2007. Lecture Notes in Computer Science, vol 4669. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74695-9_72
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DOI: https://doi.org/10.1007/978-3-540-74695-9_72
Publisher Name: Springer, Berlin, Heidelberg
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