Title:
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BIG DATA ANALYTICS AND SMART CITIES: A LOOSE OR TIGHT COUPLE? |
Author(s):
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Ahmed M. Shahat Osman, Ahmed Elragal and Birgitta Bergvall-Kåreborn |
ISBN:
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978-989-8533-67-8 |
Editors:
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Piet Kommers and Guo Chao Peng |
Year:
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2017 |
Edition:
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Single |
Keywords:
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Big data, Big data analytics Frameworks, Smart cities |
Type:
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Full Paper |
First Page:
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157 |
Last Page:
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168 |
Language:
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English |
Cover:
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Full Contents:
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click to dowload
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Paper Abstract:
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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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