Discovering semantically meaningful places from pervasive RF-beacons

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Discovering semantically meaningful places from pervasive RF-beacons

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ACM International Conference Proceeding Series archive
Proceedings of the 11th international conference on Ubiquitous computing table of contents

Orlando, Florida, USA

SESSION: Places & location table of contents

Pages 21-30

Year of Publication: 2009

ISBN:978-1-60558-431-7

Authors

Donnie H. Kim	UCLA, Los Angeles, CA, USA
Jeffrey Hightower	Intel Labs Seattle, Seattle, WA, USA
Ramesh Govindan	USC, Los Angeles, CA, USA
Deborah Estrin	UCLA, Los Angeles, CA, USA

Sponsors

ACM: Association for Computing Machinery
SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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ACM New York, NY, USA

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ABSTRACT

Detecting visits to semantically meaningful places is important for many emerging mobile applications. We present PlaceSense, a place discovery algorithm suitable for mobile devices that exploits pervasive RF-beacons. By relying on separate mechanisms to detect entrance to and departure from a place and buffering overlapping data for subsequent visits, it is more robust than the state-of-the-art, especially in detecting short visits, places where people are mobile, or where inconsistent beacons are prevalent due to interference. We experimentally evaluate PlaceSense's effectiveness in discovering semantically meaningful places, and compare with other approaches that use coordinates or RF-beacon fingerprints. Our results demonstrate that PlaceSense correctly discovers 92% (compared to between 28% and 65% for previous work) of the visited places and accurately detects their entrance and departure times from both real-life and scripted data sets.

REFERENCES

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