Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/98272
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Logistics and Maritime Studies | en_US |
| dc.creator | Chen, J | en_US |
| dc.creator | Wang, S | en_US |
| dc.creator | Qu, X | en_US |
| dc.creator | Yi, W | en_US |
| dc.date.accessioned | 2023-04-27T01:04:26Z | - |
| dc.date.available | 2023-04-27T01:04:26Z | - |
| dc.identifier.issn | 2190-3018 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10397/98272 | - |
| dc.description | 11th International KES Conference on Intelligent Interactive Multimedia: Systems and Services, Gold Coast, Australia, June 20–22, 2018 | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Springer | en_US |
| dc.rights | © Springer International Publishing AG, part of Springer Nature 2019 | en_US |
| dc.rights | This 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.title | A modelling framework of drone deployment for monitoring air pollution from ships | en_US |
| dc.type | Conference Paper | en_US |
| dc.identifier.spage | 281 | en_US |
| dc.identifier.epage | 288 | en_US |
| dc.identifier.volume | 98 | en_US |
| dc.identifier.doi | 10.1007/978-3-319-92231-7_29 | en_US |
| dcterms.abstract | Sulphur 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.accessRights | open access | en_US |
| dcterms.bibliographicCitation | Smart innovation, systems and technologies, 2019, v. 98, p. 281-288 | en_US |
| dcterms.isPartOf | Smart innovation, systems and technologies | en_US |
| dcterms.issued | 2019 | - |
| dc.identifier.scopus | 2-s2.0-85049003557 | - |
| dc.relation.conference | International KES Conference on Intelligent Interactive Multimedia: Systems and Services | en_US |
| dc.identifier.eissn | 2190-3026 | en_US |
| dc.description.validate | 202304 bckw | en_US |
| dc.description.oa | Accepted Manuscript | en_US |
| dc.identifier.FolderNumber | LMS-0196 | - |
| dc.description.fundingSource | Others | en_US |
| dc.description.fundingText | Environment 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 China | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.identifier.OPUS | 24587599 | - |
| dc.description.oaCategory | Green (AAM) | en_US |
| Appears in Collections: | Conference Paper | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Chen_Modelling_Framework_Drone.pdf | Pre-Published version | 691.88 kB | Adobe PDF | View/Open |
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