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Wi-Fi based indoor location systems have been shown to be both cost-effective and accurate, since they can attain meter-level positioning accuracy by using existing Wi-Fi infrastructure in the environment. However, two major technical challenges persist for current Wi-Fi based location systems, instability in positioning accuracy due to changing(More)
Hardware variance can significantly degrade the positional accuracy of RSS-based WiFi localization systems. Although manual adjustment can reduce positional error, this solution is not scalable as the number of new WiFi devices increases. We propose an unsupervised learning method to automatically solve the hardware variance problem in WiFi localization.(More)
—WiFi fingerprint-based localization is currently the most promising approach to building metropolitan-scale localization systems for both indoor and outdoor environments. A WiFi-fingerprint localization system makes use of a radio map that contains WiFi signals received at various locations, and uses the map for location estimation. Thus, the accuracy of a(More)
Camera-enabled mobile devices are commonly used as interaction platforms for linking the user's virtual and physical worlds in numerous research and commercial applications, such as serving an augmented reality interface for mobile information retrieval. The various application scenarios give rise to a key technique of daily life visual object recognition.(More)
We propose MobileQueue, a mobile queue-card management system that offers more freedom to customers by enabling image-based queue-card retrieving and service-information querying actions using mobile phones. MobileQueue interacts with cloud services allowing customers to query summary description and availability (e.g., available seats) of services provided(More)
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