2013 · 18 citations · 16 references
ComputingGeoinformaticsMobile ComputingSensor FusionWireless CommunicationsContext-aware ComputingIndoor LocalizationLocalization UncertaintyMobile SensingOutdoor LocalizationPedestrian WayfindingContext-aware ApplicationsContext-aware LocalizationLaser ScannersLocation SensingLocation TrackingMobile Location-aware SystemsNavigationPedestrian Navigation
In this paper, we propose a novel approach to positioning mobile phone users in a crowd of people. We assume such a situation that people in specific space (e.g., an exhibition hall) have mobile phones and they periodically probe proximity between the surrounding users via short-range wireless communication (e.g., Bluetooth). We also assume that laser range scanners (LRSs) are deployed in the space to track positions of those mobile phone users. By fusing the accurate, but anonymous trace information obtained by LRSs and the identified phone-to-phone proximity information, our method derives accurate identified traces of each mobile phone user, which are essential for pedestrian navigation and other emerging location/situation-aware applications. Through extensive simulations, we show that the tracking error quickly converges below 1m in most cases.
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Computing, Electrical Engineering, Information Technology +13
LANDMARC: Indoor Location Sensing Using Active RFID
Lionel M. Ni, Yunhao Liu, Yiu Cho Lau · Wireless Networks · 2004 · 1.4K citations
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