research-article

Mining users' significant driving routes with low-power sensors

Authors:

Cecilia MascoloAuthors Info & Claims

SenSys '14: Proceedings of the 12th ACM Conference on Embedded Network Sensor Systems

Pages 236 - 250

https://doi.org/10.1145/2668332.2668348

Published: 03 November 2014 Publication History

Abstract

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, can open doors for 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.

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Mining users' significant driving routes with low-power sensors

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cover image ACM Conferences

SenSys '14: Proceedings of the 12th ACM Conference on Embedded Network Sensor Systems

November 2014

380 pages

ISBN:9781450331432

DOI:10.1145/2668332

General Chair:
Ákos Lédecz
Vanderbilt University
,
Program Chairs:
Prabal Dutta
University of Michigan
,
Chenyang Lu
Washington Univ. in St. Louis

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 03 November 2014

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SenSys '14: The 12th ACM Conference on Embedded Network Sensor Systems

November 3 - 6, 2014

Tennessee, Memphis

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