Cyber-Physical Systems

By Stefano Zanero. Cybernetics and Systems Analysis, 2016

1,577 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/05a9360b87d34d1ed49222c6877cba22db41bed9

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In Control and Systems Engineering

Citations in the corpus

Internet of Medical Things: A Review of Recent Contributions Dealing With Cyber-Physical Systems in Medicine (2018, positive): “Moreover, tools introduced by the CPS community provide modeling frameworks for both the physical and digital characteristics of medical CPS [6], [20].”
Digital twin-driven product design framework (2019, background): “Some common tasks of data cleaning include record matching, identi ﬁ cation of inaccurate data, evaluation of overall quality, deduplication and column segmentation (Baheti and Gill 2011).”
A Cyber-Physical Systems architecture for Industry 4.0-based manufacturing systems (2015, background): “Recent advances in manufacturing industry has paved way for a systematical deployment of Cyber-Physical Systems (CPS), within which information from all related perspectives is closely monitored and synchronized between the physical factory floor and the cyber computational space.”
Smart Grids: A Cyber–Physical Systems Perspective (2016, background): “Bridging the systems science and engineering and the computer science and engineering for CPS development faces significant technological challenges which are summarized in the following two key aspects [15], [16].”
Review on cyber-physical systems (2017, background): “(air traffic control, war), efficiency (zero net energy buildings), etc [99].”
Design Techniques and Applications of Cyberphysical Systems: A Survey (2015, background): “entire system, to ensure high degree of dependability and reconfigurability [268].”
Implications of the use of artificial intelligence in public governance: A systematic literature review and a research agenda (2021, neutral): “…planning, predictive analytics, knowledge representation and reasoning, search, scheduling, and optimization; and, finally, cyber-physical systems (Baheti & Gill, 2011; Lee, 2008; Radanliev, De Roure, Van Kleek, Santos, & Ani, 2020), including internet-of-things and robotics, computer vision,…”
Toward New-Generation Intelligent Manufacturing (2018, background): “As a result, the performance and efficiency of manufacturing systems can be improved significantly [13,30,37,55,56].”
Deep Learning for Anomaly Detection in Time-Series Data: Review, Analysis, and Guidelines (2021, background): “Recently, cyber-physical systems (CPS) [131] have integrated physical and computational capabilities to remotely control substantial systems in real-time.”
Cloud-based design and manufacturing: A new paradigm in digital manufacturing and design innovation (2015, positive): “In particular, future CPS that exceed today’s levels of autonomy, functionality, reliability, and cyber security will allows for improved connectivity, adaptability, flexibility, and scalability in CBDM [66].”