Abstract
This work describes the probabilistic modelling of a Bayesian-based mechanism to improve location estimates of an already deployed location system by fusing its outputs with low-cost binary sensors. This mechanism takes advantage of the localization capabilities of different technologies usually present in smart environments deployments. The performance of the proposed algorithm over a real sensor deployment is evaluated using simulated and real experimental data.
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Iglesias, J., Bernardos, A.M., Casar, J.R. (2011). A Bayesian Strategy to Enhance the Performance of Indoor Localization Systems. In: Molina, J.M., Corredera, J.R.C., Pérez, M.F.C., Ortega-García, J., Barbolla, A.M.B. (eds) User-Centric Technologies and Applications. Advances in Intelligent and Soft Computing, vol 94. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19908-0_9
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DOI: https://doi.org/10.1007/978-3-642-19908-0_9
Publisher Name: Springer, Berlin, Heidelberg
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