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dc.contributor.authorBokolo, Anthony Junior
dc.contributor.authorPetersen, Sobah Abbas
dc.contributor.authorAhlers, Dirk
dc.contributor.authorKrogstie, John
dc.date.accessioned2019-11-13T12:40:01Z
dc.date.available2019-11-13T12:40:01Z
dc.date.created2019-10-31T15:08:23Z
dc.date.issued2019
dc.identifier.issn1478-6451
dc.identifier.urihttp://hdl.handle.net/11250/2628249
dc.description.abstractThe smart city has emerged as a universal term for the pervasive utilisation of information and communication technologies deployed to provide value-added services to citizens based on data generated from sectors such as energy, mobility, etc. However, current approaches are faced with interoperability as a challenging issue in processing big data. Therefore, this study explores the role of application programming interfaces (APIs) for managing real-time, online, and historical energy data in the context of residential buildings and electric vehicles. Moreover, a layered architecture that employs APIs in big data is developed for district energy management towards providing energy information intelligence and support decision-making on energy sustainability in facilitating prosumption operations. Practically, the layered architecture collects energy data and provides data to prosumers who are citizens that produce, consume, share, and sell energy generated from renewable sources such as solar and wind to better improve energy prosumption in smart grid.nb_NO
dc.language.isoengnb_NO
dc.publisherTaylor & Francisnb_NO
dc.titleAPI deployment for big data management towards sustainable energy prosumption in smart cities-a layered architecture perspectivenb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionacceptedVersionnb_NO
dc.source.journalInternational Journal of Sustainable Energynb_NO
dc.identifier.doi10.1080/14786451.2019.1684287
dc.identifier.cristin1742919
dc.description.localcodeLocked until 31.10.2020 due to copyright restrictions. This is an [Accepted Manuscript] of an article published by Taylor & Francis, available at https://doi.org/10.1080/14786451.2019.1684287nb_NO
cristin.unitcode194,63,10,0
cristin.unitcode194,61,50,0
cristin.unitnameInstitutt for datateknologi og informatikk
cristin.unitnameInstitutt for arkitektur og planlegging
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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