Machine Learning applied to Wi-Fi fingerprinting: The experiences of the Ubiqum Challenge
作者： Jordi Rojo , Carmen Corvalan , Florian Unger , Sara Marin Lopez , Ignacio Soteras
DOI: 10.1109/IPIN.2019.8911761
关键词:
摘要: Wi-Fi Fingerprinting is widely adopted for smartphone-based indoor positioning systems due to the availability of already deployed infrastructure communications. The UJIIndoorLoc database contains data in a large environment covering three multi-tier buildings collected with multiple devices. Since evaluation set private, developers and researchers can still be evaluated under same conditions than participants 2015 EvAAL-ETRI competition. This paper shows results experiences such kind external based on competition provided by students "Data Analytics Machine Learning" program Ubiqum academy, who applied machine learning models they learnt during program. show that state-of-art Learning methods provide good results, but expertise problem needed.
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