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3rd International Conference on Mobile Systems, Applications, and Services — Abstract
Pp. 233–246 of the Proceedings
Accuracy Characterization for Metropolitan-scale Wi-Fi Localization
Yu-Chung Cheng, Intel Research Seattle and University of California, San Diego; Yatin Chawathe and Anthony LaMarca, Intel Research Seattle; John Krumm, Microsoft Research
Abstract
Location systems have long been identified as an important component of emerging mobile applications. Most research on location systems has focused on precise location in indoor environments. However, many location applications (for example, location-aware web search) become interesting only when the underlying location system is available ubiquitously and is not limited to a single office environment. Unfortunately, the installation and calibration overhead involved for most of the existing research systems is too prohibitive to imagine deploying them across, say, an entire city. In this work, we evaluate the feasibility of building a wide-area 802.11 Wi-Fi-based positioning system. We compare a suite of wireless-radio-based positioning algorithms to understand how they can be adapted for such ubiquitous deployment with minimal calibration. In particular, we study the impact of this limited calibration on the accuracy of the positioning algorithms. Our experiments show that we can estimate a user's position with a median positioning error of 13-40Êmeters (depending upon the characteristics of the environment). Although this accuracy is lower than existing positioning systems, it requires substantially lower calibration overhead and provides easy deployment and coverage across large metropolitan areas.
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