Cyber-physical-social frameworks for urban big data systems: A survey

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Abstract

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.

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APA

De, S., Zhou, Y., Abad, I. L., & Moessner, K. (2017, October 2). Cyber-physical-social frameworks for urban big data systems: A survey. Applied Sciences (Switzerland). MDPI AG. https://doi.org/10.3390/app7101017

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