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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.

Cross-docking is a supply chain distribution and logistics strategy for which less-than-truckload shipments are consolidated into full-truckload shipments. Goods are stored up to a maximum of 24 hours in a cross-docking terminal. In this chapter, we build on the literature review by Ladier and Alpan (2016), who reviewed cross-docking research and conducted interviews with cross-docking managers to find research gaps and provide recommendations for future research. We conduct a systematic literature review, following the framework by Ladier and Alpan (2016), on cross-docking literature from 2015 up to 2020. We focus on papers that consider the intersection of research and industry, e.g., case studies or studies presenting real-world data. We investigate whether the research has changed according to the recommendations of Ladier and Alpan (2016). Additionally, we examine the adoption of Industry 4.0 practices in cross-docking research, e.g., related to features of the physical internet, the Internet of Things and cyber-physical systems in cross-docking methodologies or case studies. We conclude that only small adaptations have been done based on the recommendations of Ladier and Alpan (2016), but we see growing attention for Industry 4.0 concepts in cross-docking, especially for physical internet hubs.

On modern markets, supply chains (SC) shape the competition landscape. At the same time, considerable research advancements have been recently achieved in the area of collaborative networks. Trends in information technology progress for networked systems include development of cyber‐physical networks, cloud service environments, etc. The purpose of this paper is to identify an inter‐disciplinary perspective and modelling tools for new generation SCs which will be collaborative cyber‐physical networks.

This study addresses the above‐mentioned research goal by first, developing a methodical vision of an inter‐disciplinary modelling framework for SCM based on the existing studies on SC operations, control and systems theories; and second, by integrating elements of different structures with structures dynamics within an adaptive framework based upon the authors' own research.

The inter‐disciplinary modelling framework for multi‐structural SCs has been developed. A new inter‐disciplinary level of model‐based decision‐making support in those SCs is claimed based on the integration of previously isolated problems and modelling tools developed in such disciplines like operations research, control theory, system dynamics, and artificial intelligence.

The novelty of this paper is the consideration of SC modelling in the context of collaborative cyber‐physical systems. This topic is particularly relevant for researchers and practitioners who are interested in future generation SCs. Particular focus is directed towards the multi‐structural SC modelling, structure dynamics, and inter‐disciplinary problems and models in future SCs. Challenges of integrated optimization in the organizational and informational context are discussed.

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.

Cyber resilience in cyber supply chain (CSC) systems security has become inevitable as attacks, risks and vulnerabilities increase in real-time critical infrastructure systems with little time for system failures. Cyber resilience approaches ensure the ability of a supply chain system to prepare, absorb, recover and adapt to adverse effects in the complex CPS environment. However, threats within the CSC context can pose a severe disruption to the overall business continuity. The paper aims to use machine learning (ML) techniques to predict threats on cyber supply chain systems, improve cyber resilience that focuses on critical assets and reduce the attack surface.

The approach follows two main cyber resilience design principles that focus on common critical assets and reduce the attack surface for this purpose. ML techniques are applied to various classification algorithms to learn a dataset for performance accuracies and threats predictions based on the CSC resilience design principles. The critical assets include Cyber Digital, Cyber Physical and physical elements. We consider Logistic Regression, Decision Tree, Naïve Bayes and Random Forest classification algorithms in a Majority Voting to predicate the results. Finally, we mapped the threats with known attacks for inferences to improve resilience on the critical assets.

The paper contributes to CSC system resilience based on the understanding and prediction of the threats. The result shows a 70% performance accuracy for the threat prediction with cyber resilience design principles that focus on critical assets and controls and reduce the threat.

Therefore, there is a need to understand and predicate the threat so that appropriate control actions can ensure system resilience. However, due to the invincibility and dynamic nature of cyber attacks, there are limited controls and attributions. This poses serious implications for cyber supply chain systems and its cascading impacts.

ML techniques are used on a dataset to analyse and predict the threats based on the CSC resilience design principles.

There are no social implications rather it has serious implications for organizations and third-party vendors.

The originality of the paper lies in the fact that cyber resilience design principles that focus on common critical assets are used including Cyber Digital, Cyber Physical and physical elements to determine the attack surface. ML techniques are applied to various classification algorithms to learn a dataset for performance accuracies and threats predictions based on the CSC resilience design principles to reduce the attack surface for this purpose.

In recent times, the construction industry is being influenced by technological innovations when delivering a better, more effective and efficient desired project, cyber-physical systems (CPSs) offer a coupling of the physical and engineered systems by monitoring, coordinating, controlling and integrating their operations. This study aims to examine the level of awareness of professionals and usage of CPSs for construction projects in Nigerian construction industry.

The target population for this study was the professionals in the construction industry consisting Architects, Quantity Surveyors, Engineers and Builders. Data collection was through the use of a structured questionnaire administered to the target population. The data was analyzed by using statistical tools.

This study concluded that the construction professionals in the Nigerian construction industry are mostly aware about the heating, ventilation and air conditioning (HVAC) systems, global positioning system, microphone, speakers and camera as the most widely used CPSs in construction industry. HVAC systems was also found to be the mostly adopted technologies in the construction industry.

This study recommended that platforms that increase the awareness and encourage the usage of CPSs in construction industry should be encouraged by stakeholders concerned with management of construction projects. Such include electronic construction and adoption of blockchain technology.

This chapter aimed to uncover the gaps in the existing construction supply chain management (CSCM) models. Organisational culture and the fourth industrial revolution (4IR) components are the two gaps that were identified through reviewing existing CSCM models. The 4IR is driven by three components which are smart management, virtualisation and cyber-physical system. It was proposed in this chapter that the practice of CSCM should be in tandem with the components of 4IR. This chapter recommended that for the effective practice of the construction supply chain (CSC) in the 4IR era, construction stakeholders should adopt an innovative and collaborative organisational culture. The organisational culture adopted by a construction firm performs a crucial role in encouraging construction stakeholders in adopting 4IR components for CSCM. Each of the 4IR components is driven by technologies like autonomous robots, building information modelling (BIM), radio frequency identification (RFID), the internet of things (IoT) and others. Among all the technologies, it was discovered that RFID and BIM had gained prominence in most CSC literature. The chapter recommended that blockchain, digital twins and the cyber-physical system are the next trending technology for CSCM.

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.