Mining Users' Significant Driving Routes with Low-power Sensors
SenSys '14 Proceedings of the 12th ACM Conference on Embedded Network Sensor Systems
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Nawaz, S., & Mascolo, C. (2014). Mining Users' Significant Driving Routes with Low-power Sensors. SenSys '14 Proceedings of the 12th ACM Conference on Embedded Network Sensor Systems, 236-250. https://doi.org/10.1145/2668332.2668348
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 orWiFi 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).
External DOI: https://doi.org/10.1145/2668332.2668348
This record's URL: https://www.repository.cam.ac.uk/handle/1810/245827