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  • 1.
    Osman, Ahmed M. Shahat
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    A novel Big Data Analytics framework for Smart Cities2019In: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 91, p. 620-633Article in journal (Refereed)
    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.

  • 2.
    Osman, Ahmed M. Shahat
    et al.
    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.
    Bergvall-Kåreborn, Birgitta
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Big Data Analytics and Smart Cities: A Loose or Tight Couple?2017In: Proceedings of the International Conference on ICT, Society and Human Beings 2017: Part of the Multi Conference on Computer Science and Information Systems 2017 / [ed] Kommers P.,Rodrigues L., IADIS , 2017, p. 157-168Conference 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.

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