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We present <i>Dejavu</i>, 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(More)
Map matching has been used to reduce the noisiness of the location estimates by aligning them to the road network on a digital map. A growing number of applications, e.g. energy-efficient localization and cellular provider side localization, depend on the availability of only sparse and coarse-grained positioning data; leading to a challenging map matching(More)
We present the <italic>SnapNet</italic> system, which provides accurate real-time map matching for cellular-based trajectory traces. Such traces are characterized by input locations that are far from the actual road segment, errors on the order of kilometers, back-and-forth transitions, and highly sparse input data. <italic>SnapNet</italic> applies a series(More)
Digital maps have become a part of our daily life with a number of commercial and free map services. These services have still a huge potential for enhancement with rich semantic information to support a large class of mapping applications. In this paper, we present Map++, a system that leverages standard cell-phone sensors in a crowdsensing approach to(More)
Current outdoor localization techniques fail to provide the required accuracy for estimating the car's lane. In this paper, we present LaneQuest: a system that leverages the ubiquitous and low-energy inertial sensors available in commodity smart-phones to provide an accurate estimate of the car's current lane. LaneQuest leverages hints from the phone(More)
We present the <i>SnapNet</i>, a system that provides accurate real-time map matching for cellular-based trajectories. Such coarse-grained trajectories introduce new challenges to map matching including (1) input locations that are far from the actual road segment (errors in the orders of kilometers), (2) back-and-forth transitions, and (3) highly sparse(More)
Ubiquity of Internet-connected and sensor-equipped portable devices sparked a new set of mobile computing applications that leverage the proliferating sensing capabilities of smartphones. For many of these applications, accurate estimation of the user heading, as compared to the phone heading, is of paramount importance. This is of special importance for(More)
Human respiratory rate is widely recognized as a vital measure of a patient's health and a primary indicator of several medical problems. Yet, it is usually ignored by medical practitioners due to limitations with available measurements techniques that are either performed through visual counting by trained personnel or using invasive and/or devices limited(More)