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Wednesday, May 11 • 3:00pm - 3:50pm
Crowd Learning for Indoor Positioning - Thomas Burgess, indoo.rs GmbH

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Real-time accurate indoor positioning poses many new possibilities and challenges. At indoo.rs (Austrian based start-up founded in 2010), we enable positioning within mobile applications (Android/iOS) so that users can find themselves and navigate through floor plans. In practice, we estimate location and movement, using motion sensors and comparisons of radio scans (WiFi/iBeacon) to pre-measured reference measurements (fingerprints). We currently are transitioning from using dedicated measurements to an approach that learns and updates references by analyzing data from navigating users.This approach uses the Hadoop ecosystem to combine the output of the IOT network of mobiles and beacons with big data based machine learning and near real-time analytics (including visualizations). The complete solution reduces implementation and maintenance cost of installing indoor location.

Speakers
avatar for Thomas Burgess

Thomas Burgess

Director of research, indoo.rs GmbH
Thomas is the CRO of indoo.rs and leads its research efforts since 2012. Earlier, he did his PhD in particle physics at Stockholm University for the AMANDA/IceCube neutrino telescopes, and worked as a postdoctoral researcher at University of Bergen for the ATLAS experiment at the LHC. At indoors he does modeling, statistics, data science, machine learning, and new algorithms for mobile indoor navigation. He has given numerous public talks for... Read More →



Wednesday May 11, 2016 3:00pm - 3:50pm
Plaza A

Attendees (17)