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Cyber–Physical–Social Frameworks for Urban Big Data Systems: A Survey

De, Suparna, Zhou, Yuchao, Abad, IL and Moessner, Klaus (2017) Cyber–Physical–Social Frameworks for Urban Big Data Systems: A Survey MDPI Applied Sciences, 7 (10), 101017.

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The integration of things’ data on the Web and Web linking for things’ description and discovery is leading the way towards smart Cyber–Physical Systems (CPS). The data generated in CPS represents observations gathered by sensor devices about the ambient environment that can be manipulated by computational processes of the cyber world. Alongside this, the growing use of social networks offers near real-time citizen sensing capabilities as a complementary information source. The resulting Cyber–Physical–Social System (CPSS) can help to understand the real world and provide proactive services to users. The nature of CPSS data brings new requirements and challenges to different stages of data manipulation, including identification of data sources, processing and fusion of different types and scales of data. To gain an understanding of the existing methods and techniques which can be useful for a data-oriented CPSS implementation, this paper presents a survey of the existing research and commercial solutions. We define a conceptual framework for a data-oriented CPSS and detail the various solutions for building human–machine intelligence.

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
Abad, IL
Date : 2 October 2017
DOI : 10.3390/app7101017
Copyright Disclaimer : © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (
Uncontrolled Keywords : Cyber–Physical–Social Systems; survey; cross-space data fusion; social intelligence; urban awareness; Internet of Things
Depositing User : Melanie Hughes
Date Deposited : 03 Oct 2017 10:12
Last Modified : 16 Jan 2019 18:57

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