Adaptive Localization in a Dynamic WiFi Environment through Multi-view Learning

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Wi-Fi Fingerprint-Based Indoor Positioning: Recent Advances and Comparisons (2016, background): “Recent works often leverage the signal correlation [143], user feedback [144] and crowdsourcing [43].”
Transfer Learning via Dimensionality Reduction (2008, unknown): “Some previous works have discovered that the distribution of RSS values P (x), where x represents RSS values, may be non-Gaussian and can vary greatly due to dynamic environmental factors (Pan et al. 2007 ).”
A Survey on Transfer Learning (2010, background): “In [75], [76], [77], [78], [79], transfer learning techniques are proposed to extract knowledge from WiFi localization models across time periods, space, and mobile devices, to benefit WiFi 1354 IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 22, NO. 10, OCTOBER 2010 7.”
Transfer Learning for Activity Recognition: A Survey (2013, methodology): “Several papers focus specifically on transferring across time differences [30,47,48,69], differences between people [12,23,54,79], and differences between devices [78,81].”
Transferring Localization Models over Time (2008, unknown): “90% 0.4 0.5 0.6 0.7 0.8 0.9 1 07:10pm Ratio of locations used for reference points Culmulative probability TrHMM LeManCoR RADAR LANDMARC (b) Impact of reference points for 07:10pm 0 5 10 15 20 25 30 0.65 0.7 0.75 0.8 0.85 0.9 04:21pm Number of unlabled traces Culmulative probability TrHMM UnHMM LeMa”