Issue No. 02 - Apr.-June (2017 vol. 16)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MPRV.2017.24
This article addresses several challenges for practical deployment of Wi-Fi fingerprinting localization. First, the signals of virtual access points (VAPs) from the same physical access point have high correlation, and hence should be filtered for computational efficiency. Second, because heterogeneous devices might report the same signal differently, their readings must be calibrated appropriately. Finally, to provide a better user experience, it's necessary to properly estimate the localization error. To overcome these challenges, the authors present three plug-ins for existing localization systems. They merge VAPs using a clique-finding algorithm, propose a crowdsourced approach to accommodate new devices, and derive the region where the target might be located. Extensive experimental trials in indoor sites support the practicality and effectiveness of the solutions.
Calibration, Fingerprint recognition, Virtualization, Error analysis, Computational modeling, Mobile communication, Wireless fidelity, Wireless fidelity,indoor localization, Wi-Fi fingerprinting, practical deployment, virtual access point filtering, device calibration, error estimation, pervasive computing, mobile, networking
"Toward Practical Deployment of Fingerprint-Based Indoor Localization", IEEE Pervasive Computing, vol. 16, no. , pp. 76-83, Apr.-June 2017, doi:10.1109/MPRV.2017.24