Learning significant user locations with GPS and GSM
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2008
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| Online Access: | http://hdl.handle.net/1721.1/42121 |
| _version_ | 1826216842398531584 |
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| author | Yu, Xiao, M. Eng. Massachusetts Institute of Technology |
| author2 | Larry Rudolph. |
| author_facet | Larry Rudolph. Yu, Xiao, M. Eng. Massachusetts Institute of Technology |
| author_sort | Yu, Xiao, M. Eng. Massachusetts Institute of Technology |
| collection | MIT |
| description | Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006. |
| first_indexed | 2024-09-23T16:54:00Z |
| format | Thesis |
| id | mit-1721.1/42121 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T16:54:00Z |
| publishDate | 2008 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/421212019-04-10T08:47:44Z Learning significant user locations with GPS and GSM Yu, Xiao, M. Eng. Massachusetts Institute of Technology Larry Rudolph. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006. Includes bibliographical references (leaves 57-59). This thesis addresses the tasks of place discovery and place recognition - learning and recognizing places significant to a user - by analyzing GPS location and GSM cell tower data collected from the user's mobile phone. Location provides valuable context into the user's environment, and place-discovery and recognition algorithms enable human-centric systems to communicate with the user in human terms. In this thesis, we introduce a novel two-phased approach to place-discovery and recognition that combines the advantages of GPS and GSM cell data. We design and implement a system that produces a compact travel summary from the user's daily GPS logs. We then use computational geometry to investigate the aspect ratios of GSM cell coverage polygons as an optimization to place recognition. Finally, we conclude by presenting a one-month empirical study to demonstrate the effectiveness of our two-phased approach, and identify a set of anomalies in our experiment that can direct further development of place-discovery systems. by Xiao Yu. M.Eng. 2008-09-03T14:39:11Z 2008-09-03T14:39:11Z 2006 2006 Thesis http://hdl.handle.net/1721.1/42121 227037360 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 59 leaves application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Yu, Xiao, M. Eng. Massachusetts Institute of Technology Learning significant user locations with GPS and GSM |
| title | Learning significant user locations with GPS and GSM |
| title_full | Learning significant user locations with GPS and GSM |
| title_fullStr | Learning significant user locations with GPS and GSM |
| title_full_unstemmed | Learning significant user locations with GPS and GSM |
| title_short | Learning significant user locations with GPS and GSM |
| title_sort | learning significant user locations with gps and gsm |
| topic | Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/42121 |
| work_keys_str_mv | AT yuxiaomengmassachusettsinstituteoftechnology learningsignificantuserlocationswithgpsandgsm |