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dc.contributor.advisorDina Katabi.en_US
dc.contributor.authorHristov, Rumen (Rumen H.)en_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2018-12-11T20:38:41Z
dc.date.available2018-12-11T20:38:41Z
dc.date.copyright2017en_US
dc.date.issued2017en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/119523
dc.descriptionThesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.en_US
dc.descriptionThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.en_US
dc.descriptionCataloged from student-submitted PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 57-59).en_US
dc.description.abstractRecent advances in wireless localization systems show that by transmitting a wireless signal and analyzing its reflections, one can localize a person and track her vital signs without any wearables. These systems can localize with high accuracy even when multiple people are present in the environment. However, a primary limitation is that they cannot identify people and know who is the monitored person. In this thesis, we present a system for identifying people based only on their wireless reflection with high accuracy. We use a semi-supervised learning classifier to assign labels to each person tracked by the device-free localization system. We use recent advances in machine learning to leverage the big amount of unsupervised data that we have. A key challenge that we solve is obtaining labels that are used for guiding the classifier. To get labeled data, we devised a novel scheme to combine data from a sensor that people are carrying with data from a wireless localization system. We deployed and evaluated our system in people's homes. We present a case study of how it can be helpful to monitor people's health more effectively.en_US
dc.description.statementofresponsibilityby Rumen Hristov.en_US
dc.format.extent59 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleAdding identity to device-free localization systemsen_US
dc.typeThesisen_US
dc.description.degreeM. Eng.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.oclc1066694412en_US


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