Optimal data capturing for indoor location sensing
R.O. van Heerde (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Q. Song – Mentor (TU Delft - Electrical Engineering, Mathematics and Computer Science)
J.A. Martinez Castaneda – Coach (TU Delft - Electrical Engineering, Mathematics and Computer Science)
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Abstract
In today’s world, accurate location sensing is impossible to think away. One of the most prominent and most used techniques for determining location is GPS. In the outside world, GPS is capable of pinpointing a location with only a few meters error. But inside buildings, GPS often fails to deliver the same accuracy. In this paper, a relatively new technique will be presented to solve this problem using acoustic location sensing where a smartphone emits inaudible chirps and records the result. Specifically, this paper will cover what kind of data is needed to train the deep model that will solve this problem.