IoT2US Lab won 3rd
place in the premier competition of the 10th International Conference on Indoor Positioning
and Indoor Navigation (IPIN). There are fifteen teams in all from top universities (e.g. Ghent University),
institutes or high tech companies (e.g. Intel, Tencent, LINE) and indoor positioning professional companies (e.g. Xihe Tech, Fineway, AraraDS) all over the world. This is one of the most world-famous two indoor positioning competitions, IPIN and Microsoft Indoor Localization Competition (IPSN) [2].
Team information
The work is a product of IoT2US Lab, in the School of (EECS), QMUL, in
collaboration with UCL, Electronic Engineering department. Our team members are
Bang Wu (QMUL), Chengqi Ma (UCL),
Stefan Poslad (supervisor, QMUL), David Selviah (supervisor, UCL), Wei Wu
(WHU), Xiaoshuai Zhang (QMUL) , Guangyuan Zhang (QMUL) , Zixiang Ma (QMUL).
Competition Goal
The goal
of this competition track is to evaluate the performance of different indoor
localization solutions based on the signals available to a smartphone (such as
WiFi readings, inertial measurements, etc…) and received while a person is
walking along several regular unmodified multi-floor buildings. This track is
done off-site, so all data for calibration and evaluation is provided by
competition organizers before the celebration of the IPIN conference. The
competition teams can calibrate their algorithmic models with several databases
containing readings from sensors typically found in modern mobile phones and
some ground-truth positions. Finally, each team will compete using additional
database files, but in this case, the ground-truth reference is not given and
must be estimated by the competitors. This is an off-line competition where all
competitors have the same data of the testing environment, so custom on-site
calibration is not allowed.
Our Solution: Smartphone-based Activity Recognition and Multi-sensor Fusion based Indoor Positioning System
Performance
Poster Display
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