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A Geometric Approach to Device-Free Motion Localization Using Signal Strength

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Language
LanguageTerm (authority = ISO 639-3:2007); (type = text)
English
Genre (authority = RULIB-FS)
Other
Genre (authority = marcgt)
technical report
PhysicalDescription
InternetMediaType
application/pdf
Extent
11 p.
Note (type = special display note)
Technical report DCS-TR-674
Name (authority = RutgersOrg-School); (type = corporate)
NamePart
School of Arts and Sciences (SAS) (New Brunswick)
Name (authority = RutgersOrg-Department); (type = corporate)
NamePart
Computer Science (New Brunswick)
TypeOfResource
Text
TitleInfo
Title
A Geometric Approach to Device-Free Motion Localization Using Signal Strength
Abstract (type = abstract)
In this work we describe and evaluate an approach to accurately infer the position in a building where human motion occurs. Our approach does not require the humans to wear any type of device. Such passive mobility localization is applicable in a wide variety of application domains, including those in security, human workflows, and systems management. We position human motion using the change in standard deviation of the received signal strength between stationary transmitters and receivers at known locations. Using a modest transmission rate of once per second, we localize the motion at 2-5 second timescales using a lines-intersecting-tiles method where each line is a straight path between a transmitter and receiver. Our algorithm returns a set of rectangular tiles where the motion has occurred. We experimentally validate our scheme in two different building environments, one containing a cluttered space and a second with a more open arrangement. We show good results for basic mobility detection, with a low number of false positives and negatives. We show that we can localize human motion with a median error of less than 20 ft. We can achieve these results with a modest density of inexpensive active RFID tags, one per 500 ft.2. We also explored how our results degrade with reduced density of transmitters and receivers, and show our mobility detection rates remain good although the geometric precision of the results degrades in line with the density of transmitters.
Name (type = personal)
NamePart (type = family)
Moore
NamePart (type = given)
Robert
Affiliation
Computer Science (New Brunswick)
Role
RoleTerm (authority = marcrt); (type = text)
author
Name (type = personal)
NamePart (type = family)
Howard
NamePart (type = given)
Richard
Affiliation
Computer Science (New Brunswick)
Role
RoleTerm (authority = marcrt); (type = text)
author
Name (type = personal)
NamePart (type = family)
Kuksa
NamePart (type = given)
Pavel
Affiliation
Computer Science (New Brunswick)
Role
RoleTerm (authority = marcrt); (type = text)
author
Name (type = personal)
NamePart (type = family)
Martin
NamePart (type = given)
Richard P.
Affiliation
Computer Science (New Brunswick)
Role
RoleTerm (authority = marcrt); (type = text)
author
OriginInfo
DateCreated (encoding = w3cdtf); (keyDate = yes); (qualifier = exact)
2010-09
RelatedItem (type = host)
TitleInfo
Title
Martin, Richard P.
Identifier (type = local)
rucore30231500001
RelatedItem (type = host)
TitleInfo
Title
Computer Science (New Brunswick)
Identifier (type = local)
rucore21032500001
Location
PhysicalLocation (authority = marcorg); (displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier (type = doi)
doi:10.7282/T3PC35T2
Genre (authority = ExL-Esploro)
Technical Documentation
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Copyright protected
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Open
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Technical

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ContentModel
Document
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