Extending ERC721: Design and implementation of a novel secure NFT framework for IoT asset authentication in cyber-physical systems

Hardware in the loop simulation for product driven control of a cyber-physical manufacturing system

This chapter provides an overview of a Cyber Physical System (CPS) for civil infrastructural monitoring. Specifically, a prototype design and implementation of a cyber infrastructure framework for the monitoring of bridges along a highway corridor is described. The cyber infrastructure framework includes two basic components, namely a sensing and monitoring component and a cloud-based computational platform. The sensing and monitoring components includes a network of sensors and cameras instrumented along the highway corridor to capture vehicle loads and bridge responses. The computational tasks involve information modeling, database management and web services for supporting SHM applications. Selected examples are provided to illustrate the utilization of the CPS for assessing the fundamental behaviors of bridge structures. Additionally, the CPS provides a platform that enables research and development of new and innovative data-driven approaches for SHM.

This article discusses various aspects of a course on cyber-physical systems (CPS) in the educational programs of defense organizations. CPS are engineered systems that are built from, and depend upon, the seamless integration of computational algorithms and physical components. The article also highlights various objectives of the CPS course. A central challenge to deploying resilient CPSs involves the appreciation for the multi-disciplinary challenges and the lack of a unified framework for CPS analysis, design and implementation. A significant part of the course focuses on a case study in industrial control of a Vinyl Acetate (VAc) chemical plant. The course described herein presents fundamental concepts within the rapidly expanding field of CPS and has been tailored to and is well received by U.S. Naval Academy Systems Engineering senior level engineering students. The U.S. Naval Academy thrust in cyber security studies includes a new major, Cyber Sciences, and construction of a new facility, Hopper Hall, to house the assembled multi-disciplinary teaching and research team.

Most research in cyber-physical systems considers design of algorithms and their implementation separately. This poses a problem when dealing with cyber-physical systems with complex dynamics and uncertainty. In fact, in such cases the effectiveness of designed algorithms can be compromised by the unavoidably nonzero time needed to perform computations. The decentralization of computational resources and other requirements introduced at the implementation stage that were neglected at design will certainly negatively affect the behavior induced by the algorithm. To properly cope with such issues, techniques for the synthesis of algorithms should incorporate information about the computations required to be performed when implemented, and, in some cases, possibly accept a degradation of performance while guaranteeing certain fundamental properties of the entire cyber-physical system, such as resilience, robustness, stability, and safety. The development of such synthesis techniques requires a radical change in the way algorithms for cyber-physical systems are designed, demanding an analysis and design framework in which, rather than being added a posteriori, computation is intrinsic in the sense that the time and cost to compute is part of the design process. The goal of this workshop is to lay out the foundations of such framework for computation-aware algorithmic design of cyber-physical systems by bringing together experts (both practitioners and researchers) in cyber-physical systems and key areas in hardware design, real-time systems, optimization, control, safety, and verification.

Blockchain-enabled cyber-physical system for construction site management: A pilot implementation

Preset day cyber-physical systems (CPS) are the confluence of very large data sets, tight time constraints, and heterogeneous hardware units, ridden with latency and volume constraints, demanding newer analytic perspectives. Their system logistics can be well-defined by the data-streams’ behavioral trends across various modalities, without numerical restrictions, favoring resource-saving over methods of investigating individual component features and operations. The aim of this paper is to demonstrate how behavior patterns and related anomalies comprehensively define a CPS. Tensor decompositions are hypothesized as the solution in the context of multimodal smart-grid-originated Big Data analysis. Tensorial data representation is demonstrated to capture the complex knowledge encompassed in these data flows. The uniqueness of this approach is highlighted in the modified multiway anomaly patterns models. In addition, higher-order data preparation schemes, design and implementation of tensorial frameworks and experimental-analysis are final outcomes.

Cyber-physical systems (CPSs) have attracted significant research interest because of their promising applications across different domains; nonetheless, how to effectively model CPSs in real applications is still a challenge. In this article, a resource sharing-based framework (RSBF) for CPSs is developed to enable flexible modelling of a wide range of CPSs and systems of CPSs, with specific focus on resource sharing. RSBF combines elements from graph theory and social welfare to describe complex arrangements of overlapping task and resource communities in CPSs, with the objective of maximising CPS utility through decentralised control. The framework implementation is validated through three case studies: scheduling in smart factories, energy distribution in smart grids and information routing in multi-robot systems. Results show that RSBF can successfully represent the dissimilar systems under study. Furthermore, performance analysis on benchmark scheduling problems yields near-optimal results with less computational time, showing the potential of the use of social welfare functions to CPS modelling and control.

Cyber Physical System (CPS) is a complex interdisciplinary engineering system with amalgamation of physical-realm entities like machines, sensors, actuators and embedded devices with the cyber-realm system constituting of communication networks, Internet, and network-centric heterogeneous computing platforms like cloud and Fog/Edge computing. Further, with the recent advancements in the field of Internet of Things (IoT) and Machine-to-Machine (M2M) communication as enabling technologies; it is possible to design large scale CPS and deployment of application-specific sensordata acquisition and control systems. This has unfolded another technological dimension of huge data-centric subsystems: Big-Data and Artificial Intelligence (AI) and Machine Learning (ML) based application specific data analytics requirement for future-ready intelligent CPS also popularly referred as Cognitive CPS (CCPS). In this paper, we have proposed a novel four-layer architecture and their design framework with the vision of Next-generation Cyber Physical System (NG-CPS). Some major design attributes of each layer have been considered to formulate eight NG-CPS design goals with a modelling approach and suggested some major design aspects including modularity, scalability.

A cyber-physical system is an integration of computation, networking, and physical processes. This article introduces a novel physical control framework to integrate various devices to form the lower-level abstraction network. Two relevant protocols within this framework are proposed for information exchange between different network environments. Furthermore, a formal verification method for the proposed protocols is discussed. The model-checking tool SPIN is used to model and formally verify such protocols. The properties of the protocols are expressed using linear temporal logic to enable model-checking. Implementation results are presented to provide a deeper understanding of the proposed protocols.

Traditional factories are turning into smart factories with the advent of various ICT technologies, and various control decisions are derived by AI technologies. In this circumstance, runtime verification of a control command is important for zero-defect manufacturing processes but challengeable because factories of the future are highly complex and heterogeneous systems. In this paper, we propose DigTwinOps, a Digital Twin framework for Runtime Verification of Cyber-Physical Production Systems (CPPSs). DigTwinOps features a Digital Twin Execution Engine (DTEE) that manages a Digital Twin Model to synchronize states of a real CPPS object in a production environment. With a monitoring and simulation combination process, a human worker can observe the states of the CPPS object and verify the effectiveness of control commands before applying it to a real production environment. The proposed framework is applied to a CPPS prototype production system, and the results show that the framework can work effectively in the controllability verification of control commands.

Systems development has often resulted as a hit-or-miss proposition before the advent of standardized analysis and design languages providing blueprints understood by both software and systems engineers. This paved the way for modeling cyber-physical systems using established, yet evolving standardized notation widely accepted by industry. In the past, system analysts would try to assess the needs of their clients, generate a requirements analysis in some notation that the analyst understood (but not always the client), give that analysis to a programmer or team of programmers, and hope that the final product was the system the client wanted (Schmuller, 2003). However, advances in UML and SysML have created new pathways to the design process when combined with Concurrent Object Modeling and Architectural Design Method (COMET) methodology that can assist in the realm of complex embedded system design for next generation cyber-physical systems (Rajhans, 2009). In order for product development to meet a desired need, communicating the vision to the developers is of utmost importance. The UML is a visual modeling language that enables system builders to create blueprints that capture their design intentions in a standardized format for effective communication of engineering detail. The paper reviews some key benefits of using UML and SysML during the product development process with COMET. The UML process steps are briefly described, followed by an introduction to the SysML language which is an extension of the UML. The paper provides a process review of embedded system development using SysML for systems engineering that can be useful for modeling aspects of cyber-physical system development during integrated product development. Realizing the fact that SysML may be considered too generic to address embedded and real-time system design, the paper provides a brief review of COMET, a UML based method for the development of concurrent applications, in particular distributed and real-time applications (Gomaa, 2008). The Artificial Intelligence Design Framework introduced as part of the thesis work supported by NASA (Tanik, 2006) can be adapted to cyber-physical system design. The published book detailing the AIDF called Architecting Automated Design Systems is based on this thesis work (Tanik, 2008) and is being used as a basis for supporting cyber-physical system design using artificial intelligence decision support with many application areas, including complex safety-critical medical and space systems design. This journal paper establishes the link between the conference paper on integrated product development (Tanik, 2010), and the previous work on the PhD thesis completed in 2006 that relates to cyber-physical system design frameworks.

Patterns are investigated in relation to the development of applications and frameworks in the context of analysis, design, and implementation. The results are based on a framework for virtual machines. Different pattern characteristics are identified in the analysis, design, and implementation of applications and frameworks.

Control systems using sensors and wireless networks are becoming more prevalent, due to its ease of deployment (no wires and no electricity) and maintenance (longer lifetime). However, interference and noise can cause delays and packet losses that can degrade control system performance, which leads us to find the optimal network configuration to minimize that impact. Another problem of wireless networks for control systems is caused by time-varying fault patterns, which motivates us to do network reconfiguration at runtime. We focus on the online wireless network reconfiguration in an embedded networked and cyber-physical system (CPS), with four main contributions: (1) the design and implementation of a novel network reconfiguration framework with offline and online components that consider time-correlated link failures; (2) a network imperfection model; (3) six online reconfiguration algorithms for wireless control system; (4) a case study with 12 hops and up to 50 nodes that controls a nonlinear small modular nuclear reactor. Our network imperfection model is accurate (with 0.993 Pearson correlation) and our online reconfiguration algorithms have smaller error and longer network lifetime than a state-of-the-art static scheme.

The Internet of Things (IoT) is envisioned to facilitate rich interactions among heterogeneous entities, ranging from simple sensing devices to complex robotic devices and from autonomous service agents to human actors. The complexity and multimodality of human actors require specific interfaces for their integration with IoT frameworks that provide suitable software architectures, data models, protocols, message types, and applications. This study focuses on the requirements and design approaches for integrating human actors in a Cyber-Physical System (CPS) within the application domain of Industry 4.0. After a systematic review and taxonomy of the related research literature, the design and implementation of a comprehensive human-integration framework is presented as part of a multi-agent IoT middleware called CHARIOT. Example applications that are developed to exploit the human integration capabilities of CHARIOT middleware are then presented, which extract data from human activities, enable multimodal interaction between humans and other IoT entities, and assist different human roles in a smart factory environment to satisfy the human-CPS integration requirements.

Based on computation and network technology, Cyber-Physical Systems (CPS) has achieved rapid growth but it is faced with increasingly serious security problems and needs targeted security protection technologies. Considering the characteristics of the typical architecture of CPS, this paper integrates the analytical method of information flow based on the noninterference theory and proposes the security protection design of CPS through formal methods and provides a kind of safety system based on this design framework.