Wave height estimation using a novel seaweed-attached sensor

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dc.contributor.authorEmam, Masoud
dc.contributor.authorPress, Caroline
dc.contributor.authorJafarzadeh, Hamed
dc.contributor.authorBelcastro, Marco
dc.contributor.authorO'Flynn, Brendan
dc.contributor.authorCasserly, Joanne
dc.contributor.authorKane, Frank
dc.contributor.funderHorizon 2020en
dc.contributor.funderScience Foundation Irelanden
dc.contributor.funderEuropean Regional Development Funden
dc.date.accessioned2021-12-10T12:56:17Z
dc.date.available2021-12-10T12:56:17Z
dc.date.issued2021-11-14
dc.date.updated2021-12-10T12:39:51Z
dc.description.abstractThe growth rate of seaweed is significantly affected by wave parameters and sea conditions. The wave characteristics in an aquaculture farm is normally measured using expensive equipment, which is not affordable for many farmers or researchers, and is not easily relocated from place to place to evaluate wave conditions in a variety of locations. In this paper, a sensor fusion method is presented which can estimate wave height using the data logged by a multi modal low-cost seaweed-attached sensor system. The sensor was developed for use in an Aquaculture scenario. This method is based on combination of extended Kalman filter and artificial neural networks. Regarding the importance of studying the impact of wave on seaweeds growth rate, this method will avail many researchers to use wave height data in their study to fill the gap in knowledge of the impact of water motion on aquaculture and maximising of seaweed harvests.en
dc.description.sponsorshipScience Foundation Ireland ((SFI) - co-funded under the European Regional Development Fund under Grant Number 16/RC/3835 – VISTAMILK 16/RC/3835, INSIGHT 13/RC/2077_P2 and CONNECT 13/RC/2077)en
dc.description.statusPeer revieweden
dc.description.versionAccepted Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationEmam, M., Press, C., Jafarzadeh, H., Belcastro, M., O'Flynn, B., Casserly, J. and Kane, F. (2021) 'Wave Height Estimation Using a Novel Seaweed-Attached Sensor ', SENSORCOMM 2021 The Fifteenth International Conference on Sensor Technologies and Applications, Athens, Greece, 14-18 November.en
dc.identifier.endpage4en
dc.identifier.isbn978-1-61208-917-1
dc.identifier.issn2308-4405
dc.identifier.startpage1en
dc.identifier.urihttps://hdl.handle.net/10468/12346
dc.language.isoenen
dc.publisherIARIAen
dc.relation.projectinfo:eu-repo/grantAgreement/EC/H2020::RIA/774109/EU/Intelligent management system for integrated multi-trophic aquaculture/IMPAQTen
dc.relation.projectinfo:eu-repo/grantAgreement/SFI/SFI Research Centres/13/RC/2077/IE/CONNECT: The Centre for Future Networks & Communications/en
dc.relation.urihttps://www.thinkmind.org/
dc.rights© 2018 the authors. IARIA journals are made available for free, proving the appropriate references are made when their content is useden
dc.subjectSeaweed attached sensoren
dc.subjectAquacultureen
dc.subjectUnderwater sensoren
dc.subjectEmbedded systemen
dc.subjectKalman filteren
dc.subjectArtificial Neural Networken
dc.titleWave height estimation using a novel seaweed-attached sensoren
dc.typeConference itemen
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