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The health crisis has highlighted the shortcomings of the industry sector which has revealed its vulnerability. To date, there is no guarantee of a return to the “world before”. The ability of companies to cope with these changes is a key competitive advantage requiring the adoption/mastery of industry 4.0 technologies. Therefore, companies must adapt their business processes to fit into similar situations.

The proposed methodology comprises three steps. First, a comparative analysis of the existing CPSs is elaborated. Second, following this analysis, a deep learning driven CPS framework is proposed highlighting its components and tiers. Third, a real industrial case is presented to demonstrate the application of the envisioned framework. Deep learning network-based methods of object detection are used to train the model and evaluation is assessed accordingly.

The analysis revealed that most of the existing CPS frameworks address manufacturing related subjects. This illustrates the need for a resilient industrial CPS targeting other areas and considering CPSs as loopback systems preserving human–machine interaction, endowed with data tiering approach for easy and fast data access and embedded with deep learning-based computer vision processing methods.

This study provides insights about what needs to be addressed in terms of challenges faced due to unforeseen situations or adapting to new ones. In this paper, the CPS framework was used as a monitoring system in compliance with the precautionary measures (social distancing) and for self-protection with wearing the necessary equipments. Nevertheless, the proposed framework can be used and adapted to any industrial or non-industrial environments by adjusting object detection purpose.

Despite the growing attention on the relevance of improved building management systems with cognition in recent years in the architecture, engineering, construction and operation (AECO) community, no review has been conducted to understand the human-environment interaction features of cyber-physical systems (CPS) and digital twins (DTs) in developing the concept of a cognitive building (CB). Thus, this paper aims to review existing studies on CPS and DTs for CB to propose a comprehensive system architecture that considers human-environment interactions.

Scientometric analysis and content analysis were adopted for this study.

The scientometric analysis of 1,042 journal papers showed the major themes of CPS/DTs for CB, and these can be categorized into three key technologies to realize CB in the AECO community: CPS, DTs and cognitive computing (CC). Content analysis of 44 relevant publications in the built environment assisted in understanding and evidently confirming the claim of this study on the integration of CPS and DTs for CB in construction by also involving the CC. It is found and confirmed that CB can be realized with CPS and DTs along with the CC. A CB system architecture (CBSA) is proposed from the three key technologies considering the human-environment interactions in the loop. The study discovered the potential applications of the CBSA across the building lifecycle phases, including the design, construction and operations and maintenance, with the potential promise of endowing resilience, intelligence, greater efficiency and self-adaptiveness. Based on the findings of the review, four research directions are proposed: human-environment interactions, CB for sustainable building performance, CB concept for modular buildings and moving beyond CB.

This study stands out for comprehensively surveying the intellectual core and the landscape of the general body of knowledge on CPS/DTs for CB in the built environment. It makes a distinctive contribution to knowledge as it does not only propose CBSA by integrating CPS and DTs along with CC but also suggests some potential practical applications. These may require expert judgments and real case examples to enhance reproducibility and validation.

The purpose of this paper is to review the current research on theoretical foundations and applications for CPS from 2017 to 2019 including the applications in library.

This paper is designed in six parts as Introduction, Literature review, Theoretical foundations of CPS, Applications of CPS, CPS’s application in library and Conclusion. The authors review 70 papers and classify them as the above six parts. The authors collected 70 papers from 2017 to 2019 in the academic databases.

This paper reviews 70 papers regarding theoretical foundations and applications for CPS from 2017 to 2019 in the academic databases aiming to provide scholars and practitioners with a comprehensive overview. The contents of the papers in each research category are summarized from theoretical foundations and applications including the CPS applications in library.

A main contribution of this review paper is that it summarizes the current state-of-the-art theoretical foundations and applications for CPS and in libraries systematically.

The purpose of this paper is to present the current state research of cyber-physical system (CPS) and its application in libraries. CPS is a kind of large-scale and networked system that consists of physical and cyber elements and is currently of interest in academia, industry and government. In this survey, the definitions, theoretical foundation and basic applications of CPS are systematically reviewed. In addition, the development of library and current research of CPS application in library management are presented. The vision and challenge of smart library are also discussed.

By retrieving the main scholarly databases, the literature of CPS and its application in libraries were examined.

This study shows that a lot of CPS technology applications are still in initial stage, and explores CPS potential impacts on libraries.

The application of CPS in library management has not been paid much attention, this study provides a prospective for the application of CPS in libraries.

This paper aims to provide empirically derived insights into trust and its predictors within a cyber-physical system context of a household service.

The methodology comprises an innovative mixed methods design encompassing a videographic animated film portraying a potential “slice of life” household service-system scenario that was subsequently incorporated into a quantitative survey. A total of 400 responses were then used to examine trust dimensions and their hypothesised predictors.

Findings suggest trust is two-dimensional, with “online networking competency”, “perceptions of risk”, “propensity to trust technology in general” and “concerns about security” being significant predictors. Surprisingly, “concerns about privacy” do not have a significant effect.

The contribution of this research is twofold. Firstly, from a theoretical perspective, the paper offers empirical insights into trust and its predictors within a cyber-physical system context of a household service. Secondly, and from a pragmatic perspective, the model derived from this study may aid practitioners in developing trust strategies and trust management systems within such contexts.

The purpose of this paper is threefold: to present internet of things (IoT)-based cyber-physical system (CPS) architecture framework to facilitate the integration of IoT and CPS; to implement an IoT-based CPS prototype based on the architecture framework for a PL application scenario of in a case study; and to devise evaluation methods and conduct experimental evaluations on an IoT-based CPS prototype.

The design research method, case study, emulation experiment method, and cost-benefit analysis are applied in this research. An IoT-based CPS architecture framework is proposed, and followed by the development of prototype system and testbed platform. Then, the emulation and experimental evaluation of IoT-based CPS are conducted on the testbed, and the experimental results are analyzed.

The emulation experiment results show that the proposed IoT-based CPS outperforms current barcode-based system regarding labor cost, efficiency, and operational adaptiveness. The evaluation of the IoT-based CPS prototype indicates significant improvements in PL tasks and reduced part inventory under a dynamic changing shop-floor environment.

The case study shows that the proposed architecture framework and prototype system can be applied to many discrete manufacturing industries, such as automobile, airplane, bicycle, home appliance, and electronics.

The proposed IoT-based CPS is among the first to address the need to integrate IoT and CPS for PL applications, and to conduct experimental evaluations and cost-benefit analysis of adopting IoT-based CPS for PL. This paper also contributes to the IoT research by using diverse research methods to offer broader insights into understanding IoT and CPS.

Cyber physical system (CPS) has attracted much attention from industry, government and academia due to its dramatic impact on society, economy and people’s daily lives. Scholars have conducted a number of studies on CPS. However, despite of the dynamic nature of this research area, a systematic and extensive review of recent research on CPS is unavailable. Accordingly, this paper conducts an intensive literature review on CPS and presents an overview of existing research on CPS. The purpose of this paper is to identify the challenges of studying CPS as well as the directions for future studies on CPS.

This paper examines existing literatures about CPS from 2006 to 2018 in Compendex, presenting its definition, architectures, characteristics and applications.

This study finds that CPS is closely integrated, diversified and large-scale network with complex multiple time scales. It requires dynamic reorganization/reconfiguration, mass computing, and closed, automated and control circuits. Currently, CPS has been applied in smart manufacturing, medical systems, smart city and smart libraries. The main challenges in designing CPS are to develop, to modify, to integrate abstractions and to set predictable timing of openness and physical interconnection of physical devices. Furthermore, security is a key issue in CPS.

This study adds knowledge to the existing literature of CPS by answering what the current level of development on CPS is and what the potential future research directions of CPS are.

The purpose of this paper is to report a study on analysis of barriers for cyber-physical system (CPS) adoption in small and medium enterprises (SMEs).

In Industry 4.0 scenario, Indian SMEs are struggling to bring their manufacturing processes in line with large manufacturing sector. CPS is considered as the backbone of Industry 4.0, and its implementation in SMEs will make significant changes pertaining to manufacturing automation. However, due to the lack of a proper CPS implementation strategy, SMEs face many challenges in its adoption. Hence, this study identified 18 possible barriers and seven performance measures pertaining to CPS adoption in Indian SMEs. Interpretive ranking process (IRP) is used to develop the contextual relationships among CPS barriers. IRP process include structured step-by-step matrix-based approach in which dominance among various alternatives is determined using performance measures developing a structured ranking model.

The developed IRP model revealed that CPS barriers “Lack of skilled manpower (CPSB2)” and “Lack of robustness with respect to environmental conditions in automotive environments (CPSB7)” are the most significant barriers (top two) hindering CPS adoption in SMEs.

In the present study, barriers for CPS adoption has been analyzed. In future, barriers for adopting other Industry 4.0 technologies could be analyzed.

The present research work is one of the few studies which analyzed CPS barriers in SMEs and provided improvement suggestions to the most significant barriers for its smooth adoption. The managerial and practical implications have been derived.

The analysis of barriers for CPS adoption in SMEs is the original contribution of the authors.

This paper aims to offer a comprehensive examination of the various solutions currently accessible for addressing the challenge of semantic interoperability in cyber physical systems (CPS). CPS is a new generation of systems composed of physical assets with computation capabilities, connected with software systems in a network, exchanging data collected from the physical asset, models (physics-based, data-driven, . . .) and services (reconfiguration, monitoring, . . .). The physical asset and its software system are connected, and they exchange data to be interpreted in a certain context. The heterogeneous nature of the collected data together with different types of models rise interoperability problems. Modeling the digital space of the CPS and integrating information models that support cyber physical interoperability together are required.

This paper aims to identify the most relevant points in the development of semantic models and machine learning solutions to the interoperability problem, and how these solutions are implemented in CPS. The research analyzes recent papers related to the topic of semantic interoperability in Industry 4.0 (I4.0) systems.

Semantic models are key enabler technologies that provide a common understanding of data, and they can be used to solve interoperability problems in Industry by using a common vocabulary when defining these models.

This paper provides an overview of the different available solutions to the semantic interoperability problem in CPS.

The purpose of this paper is to propose a comprehensive framework for integrating big data analytics (BDA) into cyber-physical system (CPS) solutions. This framework provides a wide range of functions, including data collection, smart data preprocessing, smart data mining and smart data visualization.

The architecture of CPS was designed with cyber layer, physical layer and communication layer from the perspective of big data processing. The BDA model was integrated into a CPS that enables managers to make sound decisions.

The effectiveness of the proposed BDA model has been demonstrated by two practical cases − the prediction of energy output of the power grid and the estimate of the remaining useful life of the aero-engine. The method can be used to control the power supply system and help engineers to maintain or replace the aero-engine to maintain the safety of the aircraft.

The communication layer, which connects the cyber layer and physical layer, was designed in CPS. From the communication layer, the redundant raw data can be converted into smart data. All the necessary functions of data collection, data preprocessing, data storage, data mining and data visualization can be effectively integrated into the BDA model for CPS applications. These findings show that the proposed BDA model in CPS can be used in different environments and applications.