This repository is about a data-driven approach to indoor localization. The goalis, as a proof of concept, to show how modern data analytics enable us to build a more powerful indoor localization techniques and make use of those data previously deemed to be useless.
The more in-depth discussion of the results are to be found in the following publications:
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Linchen Xiao, Arash Behboodi, Rudolf Mathar, A deep learning approach to Fingerprinting Indoor Localization, International Telecommunication Networks and Applications conference, 22-24 November, 2017, Melbourne, Australia
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Linchen Xiao, Arash Behboodi, Rudolf Mathar, Learning the Localization Function: Machine Learning Approach to Fingerprinting Localization, Arxiv