Date of Award
2017
Document Type
Honors Thesis (Open Access)
Department
Colby College. Computer Science Dept.
Advisor(s)
Dr. Ying Li
Abstract
Localization of phones is a ubiquitous part of the modern mobile electronics landscape. However, there are many situations where the current method of networked localization fails. A Pedestrian Dead Reckoning System where the location of the user is calculated by counting the steps and direction of the user was implemented as an iOS app with python for data analysis. A novel algorithm for wireless sensor localization using Ad-Hoc Bluetooth networks was proposed. A small experiment was performed proving that the system is nearly equal to state of the art algorithms.
Keywords
Localization, Pedestrian Dead Reckoning, iOS, Networks, Bluetooth, Mobile Computing
Recommended Citation
Murphy, Akira T., "Correcting Pedestrian Dead Reckoning with Monte Carlo Localization Boxed for Indoor Navigation" (2017). Honors Theses. Paper 861.https://digitalcommons.colby.edu/honorstheses/861
Included in
Graphics and Human Computer Interfaces Commons, OS and Networks Commons, Other Computer Sciences Commons