Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/98272
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dc.contributorDepartment of Logistics and Maritime Studiesen_US
dc.creatorChen, Jen_US
dc.creatorWang, Sen_US
dc.creatorQu, Xen_US
dc.creatorYi, Wen_US
dc.date.accessioned2023-04-27T01:04:26Z-
dc.date.available2023-04-27T01:04:26Z-
dc.identifier.issn2190-3018en_US
dc.identifier.urihttp://hdl.handle.net/10397/98272-
dc.description11th International KES Conference on Intelligent Interactive Multimedia: Systems and Services, Gold Coast, Australia, June 20–22, 2018en_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.rights© Springer International Publishing AG, part of Springer Nature 2019en_US
dc.rightsThis version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use (https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/978-3-319-92231-7_29.en_US
dc.titleA modelling framework of drone deployment for monitoring air pollution from shipsen_US
dc.typeConference Paperen_US
dc.identifier.spage281en_US
dc.identifier.epage288en_US
dc.identifier.volume98en_US
dc.identifier.doi10.1007/978-3-319-92231-7_29en_US
dcterms.abstractSulphur oxide (SOx) emissions impose a serious health threat to the residents and a substantial cost to the local environment. In many countries and regions, ocean-going vessels are mandated to use low-sulphur fuel when docking at emission control areas. Recently, drones have been identified as an efficient way to detect non-compliance of ships, as they offer the advantage of covering a wide range of surveillance areas. To date, the managerial perspective of the deployment of a fleet of drones to inspect air pollution from ships has not been addressed yet. In this paper, we propose a modelling framework of drone deployment. It contains three components: drone scheduling at the operational level, drone assignment at the tactical level and drone base station location at the strategic level.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationSmart innovation, systems and technologies, 2019, v. 98, p. 281-288en_US
dcterms.isPartOfSmart innovation, systems and technologiesen_US
dcterms.issued2019-
dc.identifier.scopus2-s2.0-85049003557-
dc.relation.conferenceInternational KES Conference on Intelligent Interactive Multimedia: Systems and Servicesen_US
dc.identifier.eissn2190-3026en_US
dc.description.validate202304 bckwen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberLMS-0196-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextEnvironment and Conservation Fund Project; Youth Program; General Project; Key Projects of the National Natural Science Foundation of China; Natural Science Foundation of Jiangsu Province in Chinaen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS24587599-
dc.description.oaCategoryGreen (AAM)en_US
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