Review of the Potential for a Cyber-Physical System Approach to Temporary Structures Monitoring

Yuan, Xin; Anumba, Chimay J.; Parfitt, Kevin M.

doi:10.26687/archnet-ijar.v9i3.841

Cited by 11 publications

(13 citation statements)

References 51 publications

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“…Indeed, CPSs are made of elements having heterogeneous nature [5,25,26]. According to Yuan, Anumba and Parfitt [27], CPSs are heterogeneous because they integrate several different systems together with standard communication and information exchange. They integrate various devices, including sensors, mobile devices, workstations and servers.…”

Section: Complexity/heterogeneity Encapsulation (C1)mentioning

confidence: 99%

A review on the characteristics of cyber-physical systems for the future smart factories

Napoleone

Macchi

Pozzetti

2020

Journal of Manufacturing Systems

149

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The emergence of new technologies is providing new ways to compete in the current context of changeable and unpredictable market requirements. The focus of this paper is on Cyber-Physical Systems (CPSs), as one of the most promising transformative technological concept of such a context, thus considered by literature as the building blocks of future smart factories. However, CPSs are still in their conceptualization phase. To this end, much literature effort has been put on their technological characterization, while there is a lack of knowledge on operations management characterization to manage such new systems. To contribute in this latter direction, this paper reviews literature in order to distinguish between technological characteristics of CPSs and operations management characteristics to build future CPS-based smart factories. This paper remarks the need for research on operations management characteristics as these may be the ones actually leading operations managers to the concrete implementation of CPS-based factories in manufacturing.

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Section: Complexity/heterogeneity Encapsulation (C1)mentioning

confidence: 99%

A review on the characteristics of cyber-physical systems for the future smart factories

Napoleone

Macchi

Pozzetti

2020

Journal of Manufacturing Systems

149

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“…The analysis of current practices to predict future behaviour and provide security to components, machines and infrastructures are presented in (Gölzer et al 2015). The concept to achieve greater storage for historic data to predict future trends is plausible, however new sensory data processing and decisionmaking technologies are required (Yuan et al 2015). The computational requirements in relation to operating systems, programming languages, user interfaces, and networking technologies have become more sophisticated in relation to software managing, information flow control, error control, redundancy, reliability and latency in heterogeneous global networks (Watteyne et al 2016).…”

Section: Introductionmentioning

confidence: 99%

Computational Intelligence for Simulating a LiDAR Sensor

Castaño

Beruvides

Villalonga

et al. 2019

Sensor Systems Simulations

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In this chapter, an overview of some of the most commonly Computational Intelligence techniques used to provide new capabilities to sensor networks in Cyber-Physical and Internet-of-Things environments, and for verifying and evaluating the reliability issues of sensor networks is presented. Nowadays, on-chip Light Detection and Ranging (LiDAR) concept has driven a great technological challenge into sensor networks application for Cyber-Physical and Internet-of-Things systems. Therefore, the modelling and simulation of a LiDAR sensor networks is also included in this chapter that is structured as follows. First, a brief description of the theoretical modelling of the mathematical principle of operation is outlined. Subsequently, a review of the state-of-art of Computational Intelligence techniques in sensor system simulations is explained. Likewise, a use case of applying computational intelligence techniques to LiDAR sensor networks in a Cyber-Physical System environment is presented. In this use case, a model library with four specific Artificial Intelligence-based methods is also designed based on sensory information database provided by the LiDAR simulation. Some of them are multi-layer perceptron neural network, a self-organization map, a support vector machine and a k-nearest neighbours. The results demonstrate the suitability of using Computational Intelligence methods to increase the reliability of sensor networks when addressing the key challenges of safety and security in automotive applications.

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“…Their work paves the road for educators to implement collaboration into courses. Yuan et al (2015) reflected on the challenges and risks associated with construction labour working on or near temporary structures. Introducing Cyber-Physical Systems (CPS) as a viable solution for preventing potential structural hazards, Yuan et al (2014) provide a scaffolding system exemplar application scenario to demonstrate how CPS worked in structural monitoring, including the requirements and system architecture.…”

Section: Design Creativity -Future Directions For Integrated Visualismentioning

confidence: 99%

A Decade of Architectural and Urban Research Published in ‘Archnet-Ijar: International Journal of Architectural Research’

Salama¹,

Remali²,

Rahimian³

2017

ArchNet-IJAR

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Review of the Potential for a Cyber-Physical System Approach to Temporary Structures Monitoring

Abstract: Abstract

Cited by 11 publications

References 51 publications

A review on the characteristics of cyber-physical systems for the future smart factories

A review on the characteristics of cyber-physical systems for the future smart factories

Computational Intelligence for Simulating a LiDAR Sensor

A Decade of Architectural and Urban Research Published in ‘Archnet-Ijar: International Journal of Architectural Research’

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