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dc.contributor.authorBibri, Simon Elias
dc.contributor.authorKrogstie, John
dc.date.accessioned2018-01-22T09:14:07Z
dc.date.available2018-01-22T09:14:07Z
dc.date.created2017-12-27T14:57:02Z
dc.date.issued2017
dc.identifier.citationCEUR Workshop Proceedings. 2017, 1818 4-17.nb_NO
dc.identifier.issn1613-0073
dc.identifier.urihttp://hdl.handle.net/11250/2478618
dc.description.abstractInformation processing is increasingly embedded in the systems and processes of the contemporary city to enhance its operations, functions, and designs. This has been fueled by the new digital transition in ICT enabled by an integration of various forms of pervasive computing. Driving this transition predominantly are big data analytics and context–aware computing and their increasing amalgamation in a number of urban application domains, especially when such analytics and computing share the same enabling technologies, namely pervasive sensing devices, computing infrastructures, data processing platforms, and wireless communication networks. The purpose of this paper is to outline the key technological components of big data and context–aware computing, to demonstrate the opportunities and applications computing has to offer, and to identify the challenges it poses in the context of smart sustainable cities. We argue that combining big data analytics and context–aware computing can be leveraged in the advancement of urban sustainability, as their effects in this regard reinforce one another as to their efforts for transforming urban life by employing the data–centric and smart applications and services to improve, harness, and integrate urban systems as well as facilitate collaboration among urban domains.nb_NO
dc.language.isoengnb_NO
dc.publisherCEUR Workshop Proceedingsnb_NO
dc.titleBig Data and Context–Aware Computing Applications for Smart Sustainable Cities of the Futurenb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionacceptedVersionnb_NO
dc.source.pagenumber4-17nb_NO
dc.source.volume1818nb_NO
dc.source.journalCEUR Workshop Proceedingsnb_NO
dc.identifier.cristin1532148
dc.description.localcode© 2017. This is the authors’ accepted and refereed manuscript to the article.nb_NO
cristin.unitcode194,63,10,0
cristin.unitnameInstitutt for datateknologi og informatikk
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


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