The GPS Challengers: New trends in Outdoor LocalizationSpeaker: Moustafa A Youssef – New Borg Elarab City, Alexandria, Egypt
Topic(s): Networks and Communications
Location-based services (LBS) have become an integral part of our daily life with applications including car navigation, location-based social networks, and context-aware predication and advertisement. Different LBS require different localization accuracies; Generally, GPS is considered the de facto standard for ubiquitous and accurate outdoor navigation. However, GPS is an energy-hungry technology that can drain the scarce battery resource of mobile devices quickly. In addition, its accuracy is limited in areas with obscured access to the satellites, e.g. in tunnels and many urban areas. To address the high energy requirement of GPS-based localization, a number of outdoor localization systems have been proposed over the years including city-wide WiFi, cellular-based localization systems, as well as inertial sensors-based systems. These systems, however, trade energy efficiency for reduced localization accuracy, reducing the range of possible LBS.
In this talk, we present Dejavu, a system that uses standard cell-phone sensors to provide accurate and energy-efficient outdoor localization suitable for car navigation. Our analysis shows that different road landmarks have a unique signature on cell-phone sensors; For example, going inside tunnels, moving over bumps, going up a bridge, and even potholes all affect the inertial sensors on the phone in a unique pattern. Dejavu employs a dead-reckoning localization approach and leverages these road landmarks, among other automatically discovered abundant virtual landmarks, to reset the accumulated error and achieve accurate localization. To maintain a low energy profile, Dejavu uses only energy-efficient sensors or sensors that are already running for other purposes. We present the design of Dejavu and how it leverages crowd-sourcing to automatically learn virtual landmarks and their locations. Our evaluation results from implementation on different android devices in both city and highway driving show that Dejavu can localize cell phones to within 8.4m median error in city roads and 16.6m on highways. Moreover, compared to GPS and other state-of-the-art systems, Dejavu can extend the battery lifetime by 347%, achieving even better localization results than GPS in the more challenging in-city driving conditions.
About this LectureNumber of Slides: 40
Duration: 60 minutes
Languages Available: Arabic, English
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