| Tracking moving devices with the cricket location system |
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International Conference On Mobile Systems, Applications And Services
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Proceedings of the 2nd international conference on Mobile systems, applications, and services
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Boston, MA, USA
SESSION: Support for location
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Pages: 190 - 202
Year of Publication: 2004
ISBN:1-58113-793-1
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Authors
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Adam Smith
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MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA
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Hari Balakrishnan
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MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA
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Michel Goraczko
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MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA
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Nissanka Priyantha
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MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA
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Downloads (6 Weeks): 10, Downloads (12 Months): 143, Citation Count: 16
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ABSTRACT
We study the problem of tracking a moving device under two indoor location architectures: an active mobile architecture and a passive mobile architecture. In the former, the infrastructure has receivers at known locations, which estimate distances to a mobile device based on an active transmission from the device. In the latter, the infrastructure has active beacons that periodically transmit signals to a passively listening mobile device, which in turn estimates distances to the beacons. Because the active mobile architecture receives simultaneous distance estimates at multiple receivers from the mobile device, it is likely to perform better tracking than the passive mobile system in which the device obtains only one distance estimate at a time and may have moved between successive estimates. However, an passive mobile system scales better with the number of mobile devices and puts users in control of whether their whereabouts are tracked.We answer the following question: How do the two architectures compare in tracking performance? We find that the active mobile architecture performs better at tracking, but that the passive mobile architecture has acceptable performance; moreover, we devise a hybrid approach that preserves the benefits of the passive mobile architecture while simultaneously providing the same performance as an active mobile system, suggesting a viable practical solution to the three goals of scalability, privacy, and tracking agility.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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CITED BY 16
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David Moore , John Leonard , Daniela Rus , Seth Teller, Robust distributed network localization with noisy range measurements, Proceedings of the 2nd international conference on Embedded networked sensor systems, November 03-05, 2004, Baltimore, MD, USA
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Gaetano Borriello , Alan Liu , Tony Offer , Christopher Palistrant , Richard Sharp, WALRUS: wireless acoustic location with room-level resolution using ultrasound, Proceedings of the 3rd international conference on Mobile systems, applications, and services, June 06-08, 2005, Seattle, Washington
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Olga Volgin , Wanda Hung , Chris Vakili , Jason Flinn , Kang G. Shin, Context-aware metadata creation in a heterogeneous mobile environment, Proceedings of the international workshop on Network and operating systems support for digital audio and video, June 13-14, 2005, Stevenson, Washington, USA
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Tsenka Stoyanova , Fotis Kerasiotis , Aggeliki Prayati , George Papadopoulos, Evaluation of impact factors on RSS accuracy for localization and tracking applications, Proceedings of the 5th ACM international workshop on Mobility management and wireless access, October 22-22, 2007, Chania, Crete Island, Greece
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Ali Shareef , Yifeng Zhu , Mohamad Musavi, Localization using neural networks in wireless sensor networks, Proceedings of the 1st international conference on MOBILe Wireless MiddleWARE, Operating Systems, and Applications, February 13-15, 2008, Innsbruck, Austria
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