Device-Free Localization Using Privacy-Preserving Infrared Signatures Acquired from Thermopiles and Machine Learning

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dc.citation.volume9
dc.contributor.authorFaulkner N
dc.contributor.authorAlam F
dc.contributor.authorLegg M
dc.contributor.authorDemidenko S
dc.date.available2021
dc.date.issued2021-06-04
dc.description.abstractThe development of an accurate passive localization system utilizing thermopile sensing and artificial intelligence is discussed in this paper. Several machine learning techniques are explored to create robust angular and radius coordinate models for a localization target with respect to thermopile sensors. These models are leveraged to develop a reconfigurable passive localization system that can use a varying number of thermopiles without the need for retraining. The proposed robust system achieves high localization accuracy (with the median error between 0.13 m and 0.2 m) while being trained using a single human subject and tested against multiple other subjects. It is shown that the proposed system does not experience any significant performance deterioration when localizing a subject at different ambient temperatures or with different configurations of the thermopile sensors placement.
dc.description.publication-statusPublished
dc.format.extent81786 - 81797
dc.identifierhttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000673983100001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=c5bb3b2499afac691c2e3c1a83ef6fef
dc.identifier.citationIEEE ACCESS, 2021, 9 pp. 81786 - 81797
dc.identifier.doi10.1109/ACCESS.2021.3086431
dc.identifier.elements-id445985
dc.identifier.harvestedMassey_Dark
dc.identifier.issn2169-3536
dc.publisherIEEE
dc.relation.isPartOfIEEE ACCESS
dc.relation.urihttps://ieeexplore.ieee.org/document/9446866
dc.rightsCC BY 4.0
dc.subjectSensors
dc.subjectLocation awareness
dc.subjectSensor phenomena and characterization
dc.subjectSensor systems
dc.subjectImage sensors
dc.subjectCameras
dc.subjectTemperature measurement
dc.subjectDevice-free localization (DFL)
dc.subjecthuman sensing
dc.subjectindoor positioning system (IPS)
dc.subjectinfrared sensing
dc.subjectmachine learning
dc.subjectpassive localization
dc.subjectthermopile
dc.subject.anzsrc08 Information and Computing Sciences
dc.subject.anzsrc09 Engineering
dc.subject.anzsrc10 Technology
dc.titleDevice-Free Localization Using Privacy-Preserving Infrared Signatures Acquired from Thermopiles and Machine Learning
dc.typeJournal article
pubs.notesNot known
pubs.organisational-group/Massey University
pubs.organisational-group/Massey University/College of Sciences
pubs.organisational-group/Massey University/College of Sciences/School of Food and Advanced Technology
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