@INPROCEEDINGS{Barr1010:Interactionless,
AUTHOR="Andrew J Barry and Mark L Chang and Noah L Tye",
TITLE="Interactionless {Calendar-Based} Training for {802.11} Localization",
BOOKTITLE="The Seventh IEEE International Conference on Mobile Ad-hoc and Sensor
Systems (IEEE MASS 2010)",
ADDRESS="San Francisco, USA",
DAYS=12,
MONTH=10,
YEAR=2010,
KEYWORDS="Location measurement; calendar; crowdsourcing; localization; location
representation; location-based services",
ABSTRACT="This paper presents our work in solving one of the weakest links in
802.11-based indoor-localization: the training of ground-truth received
signal strength data. While crowdsourcing this information has been
demonstrated to be a viable alternative to the time consuming and
accuracy-limited process of manual training, one of the chief drawbacks is
the rate at which a system can be trained. We demonstrate an approach that
utilizes users' calendar and appointment information to perform
interactionless training of an 802.11-based indoor localization system. Our
results show that with no user interaction beyond calendar/appointment
data, the accuracy of our system is comparable to our previously published
large-scale crowdsourced deployment, and in ideal conditions the time to
train the system to the same level of accuracy can be reduced by over a
factor of six."
}