3,503 research outputs found
Mining users' significant driving routes with low-power sensors
While there is significant work on sensing and recognition of significant
places for users, little attention has been given to users' significant routes.
Recognizing these routine journeys, opens doors to the development of novel
applications, like personalized travel alerts, and enhancement of user's travel
experience. However, the high energy consumption of traditional location
sensing technologies, such as GPS or WiFi based localization, is a barrier to
passive and ubiquitous route sensing through smartphones.
In this paper, we present a passive route sensing framework that continuously
monitors a vehicle user solely through a phone's gyroscope and accelerometer.
This approach can differentiate and recognize various routes taken by the user
by time warping angular speeds experienced by the phone while in transit and is
independent of phone orientation and location within the vehicle, small detours
and traffic conditions. We compare the route learning and recognition
capabilities of this approach with GPS trajectory analysis and show that it
achieves similar performance. Moreover, with an embedded co-processor, common
to most new generation phones, it achieves energy savings of an order of
magnitude over the GPS sensor.This research has been funded by the EPSRC Innovation
and Knowledge Centre for Smart Infrastructure and Construction
project (EP/K000314).This is the author accepted manuscript. The final version is available from ACM via http://dx.doi.org/10.1145/2668332.266834
- …