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dc.contributor.authorposlad, Sen_US
dc.date.accessioned2015-12-23T14:05:12Z
dc.date.available2015-04-25en_US
dc.date.submitted2015-12-02T21:41:58.740Z
dc.identifier.issn2168-6750en_US
dc.identifier.urihttp://qmro.qmul.ac.uk/xmlui/handle/123456789/10072
dc.description.sponsorshipThis work was supported in part by the European FP7 Funded Project TRIDEC under Grant 258723, the other project partners in helping to deliver the complete project Syste, in particular, GFZ, and the German Research Centre for Geosciences, Potsdam, Germany. The work of R. Tao was supported by the Queen Mary University of London for a Ph.D. studentship.en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.relation.ispartofIEEE Transactions on Emerging Topics in Computingen_US
dc.rights10.1109/TETC.2015.2432742
dc.titleA Semantic IoT Early Warning System for Natural Environment Crisis Managementen_US
dc.typeArticle
dc.rights.holder© Copyright 2015 IEEE
pubs.notesNot knownen_US
pubs.notesLink to grant does not show the EU grant, no obvious way to correct this.en_US
pubs.publication-statusPublisheden_US
dcterms.dateAccepted2015-04-25en_US


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