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A novel Big Data Analytics framework for Smart Cities
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
2018 (English)In: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115Article in journal (Refereed) In press
Abstract [en]

The emergence of smart cities aims at mitigating the challenges raised due to the continuous urbanization development and increasing population density in cities. To face these challenges, governments and decision makers undertake smart city projects targeting sustainable economic growth and better quality of life for both inhabitants and visitors. Information and Communication Technology (ICT) is a key enabling technology for city smartening. However, ICT artifacts and applications yield massive volumes of data known as big data. Extracting insights and hidden correlations from big data is a growing trend in information systems to provide better services to citizens and support the decision making processes. However, to extract valuable insights for developing city level smart information services, the generated datasets from various city domains need to be integrated and analyzed. This process usually referred to as big data analytics or big data value chain. Surveying the literature reveals an increasing interest in harnessing big data analytics applications in general and in the area of smart cities in particular. Yet, comprehensive discussions on the essential characteristics of big data analytics frameworks fitting smart cities requirements are still needed. This paper presents a novel big data analytics framework for smart cities called “Smart City Data Analytics Panel – SCDAP”. The design of SCDAP is based on answering the following research questions: what are the characteristics of big data analytics frameworks applied in smart cities in literature and what are the essential design principles that should guide the design of big data analytics frameworks have to serve smart cities purposes? In answering these questions, we adopted a systematic literature review on big data analytics frameworks in smart cities. The proposed framework introduces new functionalities to big data analytics frameworks represented in data model management and aggregation. The validity of the proposed framework is discussed in comparison to traditional approaches through a real use case for bike sharing prediction system.

Place, publisher, year, edition, pages
2018.
Keywords [en]
Analytics framework; Apache Hadoop; Apache Spark; Big data; Smart cities
National Category
Information Systems
Research subject
Information systems
Identifiers
URN: urn:nbn:se:ltu:diva-69873DOI: 10.1016/j.future.2018.06.046OAI: oai:DiVA.org:ltu-69873DiVA, id: diva2:1223746
Available from: 2018-06-25 Created: 2018-06-25 Last updated: 2018-08-13

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Osman, Ahmed M. Shahat

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
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