Luo, Yan (2011) Wi-Fi-based indoor positioning using human-centric collaborative feedback. Masters thesis, Memorial University of Newfoundland.
- Accepted Version
Available under License - The author retains copyright ownership and moral rights in this thesis. Neither the thesis nor substantial extracts from it may be printed or otherwise reproduced without the author's permission.
Position information is an important aspect of a mobile device's context. While GPS is widely used to provide location information, it does not work well indoors. Wi-Fi network infrastructure is found in many public facilities and can be used for indoor positioning. In addition, the ubiquity of Wi-Fi-capable devices makes this approach especially cost-effective. -- In recent years, "folksonomy"-like systems such as Wikipedia or Delicious Social Bookmarking have achieved huge successes. User collaboration is the defining characteristic of such systems. For indoor positioning mechanisms, it is also possible to incorporate collaboration in order to improve system performance, especially for fingerprinting-based approaches. -- In this thesis, a robust and efficient model is devised for integrating human-centric collaborative feedback within a baseline Wi-Fi fingerprinting-based indoor positioning system. Experiments show that the baseline system performance (i.e., positioning accuracy and precision) is improved by collecting both positive and negative feedback from users. Moreover, the feedback model is robust with respect to malicious feedback, quickly self-correcting based on subsequent helpful feedback from users.
|Item Type:||Thesis (Masters)|
|Additional Information:||Bibliography: leaves 108-114.|
|Department(s):||Science, Faculty of > Computer Science|
|Library of Congress Subject Heading:||Mobile computing; Wireless communication systems; Location-based services; Fingerprints|
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