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dc.contributor.author
Maag, Balz
dc.contributor.author
Zhou, Zimu
dc.contributor.author
Saukh, Olga
dc.contributor.author
Thiele, Lothar
dc.date.accessioned
2017-11-22T10:53:52Z
dc.date.available
2017-10-09T11:31:12Z
dc.date.available
2017-11-22T10:53:52Z
dc.date.issued
2017-06
dc.identifier.issn
2474-9567
dc.identifier.other
10.1145/3090084
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/193273
dc.description.abstract
Urban air pollution monitoring with mobile, portable, low-cost sensors has attracted increasing research interest for their wide spatial coverage and affordable expenses to the general public. However, low-cost air quality sensors not only drift over time but also suffer from cross-sensitivities and dependency on meteorological effects. Therefore calibration of measurements from low-cost sensors is indispensable to guarantee data accuracy and consistency to be fit for quantitative studies on air pollution. In this work we propose sensor array network calibration (SCAN), a multi-hop calibration technique for dependent low-cost sensors. SCAN is applicable to sets of co-located, heterogeneous sensors, known as sensor arrays, to compensate for cross-sensitivities and dependencies on meteorological influences. SCAN minimizes error accumulation over multiple hops of sensor arrays, which is unattainable with existing multi-hop calibration techniques. We formulate SCAN as a novel constrained least-squares regression and provide a closed-form expression of its regression parameters. We theoretically prove that SCAN is free from regression dilution even in presence of measurement noise. In-depth simulations demonstrate that SCAN outperforms various calibration techniques. Evaluations on two real-world low-cost air pollution sensor datasets comprising 66 million samples collected over three years show that SCAN yields 16% to 60% lower error than state-of-the-art calibration techniques
en_US
dc.language.iso
en
en_US
dc.publisher
Association for Computing Machinery
dc.subject
Sensor Array
en_US
dc.subject
Calibration
en_US
dc.subject
Urban Sensing
en_US
dc.title
SCAN: Multi-Hop Calibration for Mobile Sensor Arrays
en_US
dc.type
Conference Paper
ethz.journal.title
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
ethz.journal.volume
1
en_US
ethz.journal.issue
2
en_US
ethz.journal.abbreviated
IMWUT
ethz.pages.start
19
en_US
ethz.event
UbiComp 2017: 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing
en_US
ethz.event.location
Maui, HI, USA
ethz.event.date
September 11-15, 2017
en_US
ethz.publication.place
New York, NY
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02640 - Inst. f. Technische Informatik und Komm. / Computer Eng. and Networks Lab.::03429 - Thiele, Lothar (emeritus) / Thiele, Lothar (emeritus)
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02640 - Inst. f. Technische Informatik und Komm. / Computer Eng. and Networks Lab.::03429 - Thiele, Lothar (emeritus) / Thiele, Lothar (emeritus)
en_US
ethz.relation.isSupplementedBy
handle/20.500.11850/352334
ethz.date.deposited
2017-10-09T11:31:12Z
ethz.source
FORM
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2017-11-22T10:53:54Z
ethz.rosetta.lastUpdated
2024-02-02T03:13:05Z
ethz.rosetta.versionExported
true
ethz.COinS
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