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Title page for ETD etd-03232015-134316

Type of Document Master's Thesis
Author Wang, Meng
Author's Email Address meng.wang@vanderbilt.edu
URN etd-03232015-134316
Title Indoor navigation systems based on iBeacon fingerprinting
Degree Master of Science
Department Computer Science
Advisory Committee
Advisor Name Title
Douglas C. Schmidt Committee Member
Jules White Committee Member
  • Indoor Navigation Fingerprinting
Date of Defense 2015-04-14
Availability unrestricted
Thesis under the direction of Dr. Jules White

This thesis investigates the use of iBeacon fingerprinting as a localization technique for indoor navigation systems. Fingerprinting uses machine learning to generate a signature for each location based on its Bluetooth signal characteristics. In this thesis, we examine key questions related to how machine learning parameters and beacon setup influence the performance of indoor navigation localization. Our empirical results show that Random Forest provides the best localization performance and can provide high accuracy localization with as few as two visible beacons per location.

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