Selective RF Fingerprint Scanning for Large-Scale Wi-Fi Positioning Systems
Rapid growth in mobile communication and the proliferation of smartphones have drawn significant attention to location-based services (LBSs). One of the most important factors in the vitalization of LBSs is the accurate position estimation of a mobile device. The traditional global positioning system method has a critical weakness in terms of its limited availability, e.g., in indoor environments. The Wi-Fi positioning system is an attractive method that measures received signal strength indication data from all Wi-Fi access points (APs) and stores them in a huge database in the form of a radio frequency (RF) fingerprint map. Because of the millions of APs in urban areas, RF fingerprints are easily contaminated and transfigured. For this reason, a frequent rescanning of fingerprints is essential for fingerprint data integrity. However, rescanning fingerprints for an entire area requires a considerable amount of cost and effort. Therefore, we present a selective fingerprint rescan method for efficient fingerprint map management. All fingerprint data used in the developed test-bed are harvested from actual radio fingerprint measurements taken throughout Seoul, Korea, to demonstrate the practical usefulness of the proposed methodology.
location-based services data analytics wps