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Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.Elragal, Ahmed Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.ORCID iD: 0000-0003-4250-4752Bergvall-Kåreborn, Birgitta Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.ORCID iD: 0000-0003-4317-9963 2017 (English)Conference paper, Published paper (Refereed)

Abstract [en] : Smart City (SC) is an emerging concept aiming at mitigating the challenges raised due to the continuous urbanization development. To face these challenges, government decision makers sponsor SC projects targeting sustainable economic growth and better quality of life for inhabitants and visitors. Information and Communication Technologies (ICT) is the enabling technology for smartening. These technologies yield massive volumes of data known as Big Data (BD). If spawned BD are integrated and analyzed, both city decision makers and citizens can benefit from valuable insights and information services. The process of extracting information and insights from BD is known as Big Data Analytics (BDA). Although BDA involves non-trivial challenges, it attracted academician and industrialist. Surveying the literature reveals the novelty and increasing interest in addressing BD applications in SCs. Although literature is replete with abundant number of articles about SCs applications harnessing BD, comprehensive discussion on BDA frameworks fitting SCs requirements is still needed. This paper attempts to fill this gap. It is a systematic literature review on BDA frameworks in SCs. In this review, we will try to answer the following research questions: what are the big data analytics frameworks applied in smart cities? what are the functional gaps in the current available frameworks? what are the conceptual guidelines of designing integrated scalable big data analytics frameworks for smart cities purposes? The paper concludes with a proposal for a novel conceptual analytics framework to serve SCs requirements. Additionally, open issues and further research directions are presented.

Place, publisher, year, edition, pages: 2017.

Keyword [en] : Big data, Big data analytics Frameworks, Smart cities

National Category : Computer Science Information Systems, Social aspects

Research subject: Information systems

Identifiers: URN: urn:nbn:se:ltu:diva-63718OAI: oai:DiVA.org:ltu-63718DiVA: diva2:1105669

Conference: International Conference on Connected Smart Cities 2017 (CSC 2017), Lisbon, 20-22 July 2017 Available from: 2017-06-05 Created: 2017-06-05 Last updated: 2017-06-29Bibliographically approved



Author: Osman, Ahmed M. Shahat

Source: http://ltu.diva-portal.org/







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