Smarter smartphones: understanding and predicting user habits from GPS sensor data

G Maggiore, CA Pereira Santos, A Plaat

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

2 Citations (Scopus)

Abstract

Smartphones and similar devices allow access to a wealth of information. Navigating this wealth of information is problematic. Semantic locations, assigned to observed GPS user movements, can help in providing inforamtion that is useful to the user at a specific time or place. This paper shows how a stream of sensor data can be processed and interpreted to determine (i) the locations of interest for a user, such as home, work, etc, and (ii) to predict the expected future transitions between such locations. We have implemented our algorithms in a fully functional prototype smartphone app and backend, and we present results based on actual usage data gathered over the past few months. We conclude that inferred semantic location information allows a smart device to offer personalized, contextual, information without the need for the user to perform any explicit query. Our system is open source, and can be used to build context-aware recommender systems that suggest content which is at the right time and at the right place.

Original languageEnglish
Title of host publicationProcedia Computer Science
PublisherElsevier
Pages297-304
Number of pages8
Volume34
DOIs
Publication statusPublished - 2014
EventThe 11th International Conference on Mobile Systems and Pervasive Computing (MobiSPC'14), 18-08-2014 -
Duration: 17 Aug 201420 Aug 2014

Conference

ConferenceThe 11th International Conference on Mobile Systems and Pervasive Computing (MobiSPC'14), 18-08-2014
Period17/08/1420/08/14

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