Abstract
The future of Location Based Services largely depends on the accuracy of positioning techniques. In the case of indoor positioning, frequently fingerprinting-based solutions are developed. A well known k Nearest Neighbours method is frequently used in this case. However, when the detection of a floor a mobile terminal is located at is an objective, only limited accuracy can be observed when the number of available signals is limited.
The primary objective of this work is to analyse whether the credibility of floor estimates can be a priori assessed. A method assigning weights to individual GSM fingerprints and estimating their reliability in terms of floor estimation is proposed. The method is validated with an extensive radio map. It has been shown that both low and high accuracy floor estimates are correctly identified. Moreover, the objective criterion is proposed to assess individual weight functions from a proposed family of functions.
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Grzenda, M. (2013). On the Prediction of Floor Identification Credibility in RSS-Based Positioning Techniques. In: Ali, M., Bosse, T., Hindriks, K.V., Hoogendoorn, M., Jonker, C.M., Treur, J. (eds) Recent Trends in Applied Artificial Intelligence. IEA/AIE 2013. Lecture Notes in Computer Science(), vol 7906. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38577-3_63
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DOI: https://doi.org/10.1007/978-3-642-38577-3_63
Publisher Name: Springer, Berlin, Heidelberg
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