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Indoor Localization using Bluetooth RSSI For Context Resolution Jason Tam. Localization Algorithm Flow. Objectives Localize Bluetooth capable smartphones indoors Use localization for more novel context aware grouping. Results Using test conditions: 50 unit spacing; σ = 5; range = 100.
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Indoor Localization using Bluetooth RSSI For Context Resolution Jason Tam Localization Algorithm Flow • Objectives • Localize Bluetooth capable smartphones indoors • Use localization for more novel context aware grouping • Results • Using test conditions: • 50 unit spacing; σ = 5; range = 100 • Approach • Client Side • Simultaneous discovery • Upload to data server • Server Side • Download data • Localize • Update GCRS Reconstruction vs. Truths • Issues • This • Many additional/missing environmental factors • Status / Future • Localization alg done when given distances • RSSI to distance conversion needs help • Integration with machine learning • Sources • [1] Indoor Location Using Trilateration Characteristics, B Cook, G Buckberry, I Scowcroft, J Mitchell, T Allen, 2005 • [2] Robust Distributed Network Localization with Noisy Range Measurements, David Moore, John Leonard, Daniela Rus, Seth Teller MIT Computer Science and Artificial Intelligence Laboratory; 2004 Example Trilateration cases http://summer.winlab.rutgers.edu/projects/wiki/2012/Projects/MobilityFirst/Context WINLAB