Please use this identifier to cite or link to this item:
http://oaps.umac.mo/handle/10692.1/168
Full metadata record
DC Field | Value | Language |
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dc.contributor.author | KUAN, PUI ON (關培安) | - |
dc.date.accessioned | 2017-10-06T10:45:44Z | - |
dc.date.available | 2017-10-06T10:45:44Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | KUAN, P. O. (2017). The Rise of Magnetic Positioning: An Emerging and Infrastructure Free Solution for Indoor Positioning (Outstanding Academic Papers by Students (OAPS)). Retrieved from University of Macau, Outstanding Academic Papers by Students Repository. | en_US |
dc.identifier.uri | http://oaps.umac.mo/handle/10692.1/168 | - |
dc.description.abstract | Existing indoor positioning systems require some infrastructure setup, e.g., Wi-Fi or Bluetooth. The maintenance cost of such systems makes them not easy to deploy everywhere. In this project, our goal is to develop an infrastructure free solution for the Indoor Positioning System (IPS) using magnetic field. To build an infrastructure free solution, we first build a magnetic footprint database for the targeted environment. Given the footprint database, we can estimate a user location based on her magnetic trajectory, where a Dynamic Time Warping (DTW) like algorithm does the estimation. In addition, we also study some pruning strategies to improve the computation time further. Besides the technical development, we also attempt to run the system in real scenarios. One testing case is to use the indoor positioning in our university library. We design a prototype system, called BookFinder, which can help people to find the book’s position and guide them to the destination by Augmented Reality. Lastly, we also conduct quite a few of experiments to confirm the robustness of the system design. In summary, the infrastructure free solution still has room for improvement but it definitely has a bright future. | en_US |
dc.language.iso | en_US | en_US |
dc.title | The Rise of Magnetic Positioning: An Emerging and Infrastructure Free Solution for Indoor Positioning | en_US |
dc.type | OAPS | en_US |
dc.contributor.department | Department of Computer and Information Science | en_US |
dc.description.instructor | Prof. LEONG, HON U | en_US |
dc.contributor.faculty | Faculty of Science and Technology | en_US |
dc.description.programme | Bachelor of Science in Computer Science | en_US |
Appears in Collections: | FST OAPS 2017 |
Files in This Item:
File | Description | Size | Format | |
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OAPS_2017_FST_018.pdf | 5.59 MB | Adobe PDF | View/Open |
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