Opportunistic Sensing: Unattended Acoustic Sensor Selection using Crowdsourcing Models

Simple item page
dc.contributor.authorHuang, P.-S.en_US
dc.contributor.authorHasegawa-Johnson, M.en_US
dc.contributor.authorYin, W.en_US
dc.contributor.authorHuang, T.S.en_US
dc.date.accessioned2018-06-19T17:48:01Zen_US
dc.date.available2018-06-19T17:48:01Zen_US
dc.date.issued2012-08en_US
dc.date.noteAugust 2012en_US
dc.description.abstractUnattended wireless sensor networks have been widely used in many applications. This paper proposes automatic sensor selection methods based on crowdsourcing models in the Opportunistic Sensing framework, with applications to unattended acoustic sensor selection. Precisely, we propose two sensor selection criteria and solve them via greedy algorithm and quadratic assignment. Our proposed method achieves, on average, 5.64% higher accuracy than the traditional approach under sparse reliability conditions.en_US
dc.format.extent6 ppen_US
dc.identifier.citationHuang, P.-S., Hasegawa-Johnson, M., Yin, W., et al.. "Opportunistic Sensing: Unattended Acoustic Sensor Selection using Crowdsourcing Models." (2012) <a href="https://hdl.handle.net/1911/102208">https://hdl.handle.net/1911/102208</a>.en_US
dc.identifier.digitalTR12-19en_US
dc.identifier.urihttps://hdl.handle.net/1911/102208en_US
dc.language.isoengen_US
dc.titleOpportunistic Sensing: Unattended Acoustic Sensor Selection using Crowdsourcing Modelsen_US
dc.typeTechnical reporten_US
dc.type.dcmiTexten_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
TR12-19.PDF
Size:
547.48 KB
Format:
Adobe Portable Document Format
Download
Collections
CMOR Technical Reports