Concept Of Cyber-physical Systems Research Articles

Analysis of Security Issues, Threats and Challenges in Cyber–Physical System for IoT Devices

Cyber-Physical System (CPS) is one of the arising technologies which focuses on the communication and computation aspects with control and monitoring strategies. This new paradigm with the Internet of Things (IoT) prompted a new concept, the Internet of Cyber-Physical Things (IoCPT). The rapid expansion of CPS influences different perspectives in individuals' lifestyles which enables an extensive scope of applications include e-health, e-Transport, smart factory, smart home, e-Commerce, etc. The integration between the physical and cyber world results in a high-security breach. So, safety and security are the most challenging aspects related to CPS researchers. This paper gives an overview of CPS concepts, CPS architecture, various security issues, and threats related to CPS. Finally, the paper analysis the open research challenges in the field of CPS security.

Cyber Physical Energy Optimization Control Design for PHEVs Based on Enhanced Firework Algorithm

Energy management strategy (EMS) plays a vital role in improving the fuel economy of plug-in hybrid electric vehicle (PHEV). By virtue of excellent real-time performance, deterministic rule-based (DRB) method is widely introduced into EMS for the control of actual PHEV. However, fixed parameters are usually used as thresholds in traditional DBR control, which makes it difficult for PHEV to achieve excellent fuel economy. To solve this problem, relevant parameters need to be optimized, but the resulting time-consuming and complex process is an obstacle for practical application of this scheme. Nowadays, the emergence of technologies, such as wireless communication, remote monitoring and so on, has gave birth to the concept of cyber-physical system (CPS). It provides an opportunity to optimize parameters of DRB EMS. Motivated by this, this paper proposes a cyber physical energy optimization control design for PHEVs. Among them, DRB control is designed to allocate power tasks for the engine and electric motor (EM), according to state of the charge (SOC) of battery and demand power of vehicle. Moreover, to further improve performance of EMS, an enhanced firework algorithm (EFWA) is firstly proposed to optimize parameters of controller. Compared with original algorithm, a novel selection mechanism for non-CF is introduced in EFWA. It makes the excellent parameters could be obtained in a shorter time, which is more suitable for the complex optimization of EMS. Finally, the effectiveness of proposed EMS is verified and evaluated. The results show that it improves the fuel economy of PHEV by 10% and 12% over that using the unoptimized rule-based EMS, under the China typical urban driving cycle and real-world driving cycle, respectively.

Content-Based Image Retrieval (CBIR) in Big Histological Image Databases

Background: Automatic analysis of Histopathological Images (HIs) demands image processing and Computational Intelligence (CI) techniques. Both Computer-Aided Diagnosis (CAD) and Content-Based Image-Retrieval (CBIR) systems assist diagnosis, disease discovery, and biological decision-making. Classical tests comprise screening examinations and biopsy. Histopathology slides offer more ample diagnosis data. However, manual examination of microscopic images is labor-intensive and time-consuming and may depend on a subjective assessment by the pathologist, which can be a challenge.
 Methods: This work discusses a CBIR framework to extract and handle histological data, histological metadata, integrated patient records, specimen metadata, attributes, and similar stored files. This work presents a scalable image-retrieval framework for intelligent HI analysis with real-time retrieval. The potential applications of this framework include image-guided diagnosis, decision support, healthcare education, and efficient biological data management.
 Results: The considerable amount of biological-related data prompted the development and deployment of large-scale databases and data-driven techniques to bridge the semantic gap between images and diagnostic information. The new cloud computing technologies and the concept of cyber-physical systems have improved the CBIR architectures considerably. The proposed scalable architecture relies on CI and validates performance on several HIs acquired from microscopic tissues. Extensive assessments show improvements in terms of disease classification and retrieval tests.
 Conclusion: This research effort significant contributions are twofold. 1) Defining a comprehensive and large-scale CBIR framework to analyze HIs with high-dimensional features and CI methods successfully. 2) high-performance updating and optimization strategies improve the querying while better handling new training samples than traditional methods.

Development of cyber physical system based manufacturing system design for process optimization

Cyber physical systems (CPS) are known as one of the significant advancement in computer science and IT. Cyber physical manufacturing system is the emerging research area in the field of computer science as well as manufacturing science and technology which is promoting the 4th industrial revolution which is known as Industrie 4.0. CPS generally focuses on the integration of physical world with cyberspace. It is the integration of communication, computation, control and physical elements. At present time, CPS is the point of interest for academia, government and industries. However, a systematic literature review of cyber physical system for manufacturing system is not available. This paper aims to present the findings on cyber physical systems on manufacturing systems and development of cyber physical system for intelligent manufacturing. The CPS is explained with the concept of CPS and five level architecture system for manufacturing systems. Further, key enabling technologies for cyber physical manufacturing systems is also discussed. In this paper both WoS and Scopus databases (2000-2020) is taken in consideration for literature review. Top journals, top cited papers, top authors and top research categories have been found out.

Управление эксплуатационной работой объектов городского магистрального транспорта в рамках концепции киберфизических систем

The information technology concept of cyber-physical systems implemented on the basis of the industrial Internet of things is stated. It is shown that in relation to objects of urban mainstream transport, such systems are able to ensure the implementation of technologies for controlled self-organization of the functioning of technological processes and can be considered as options for intelligent self-controlled systems. The problems of organizing the functioning of cyber-physical systems in relation to the operating conditions of the basic objects of urban main transport are identifi ed. Particular attention is paid to the issues of loss management during technological operations. An approach to modeling the technological process of the station operation within the framework of the concept of cyber-physical systems is presented. The structure of technological operations and a mechanism for managing losses within the approach are proposed.

Modern technologies in Industry 4.0 – cyber-physical systems

With the advent of the Industry 4.0 concept, the approach to production automation has fundamentally changed. The manufacturing industry is based on such modern technologies as the Internet of Things, Big Data, cloud computing, artificial intelligence and cyber-physical systems. These technologies have proven themselves not only in industry, but also in various other branches of life. In this paper, the authors consider the concept of cyber-physical systems – systems based on the interaction of physical processes with computational ones. The article presents a conceptual model of cyber-physical systems that displays its elements and their interaction. In cyber-physical systems, it represents five levels: physical, network, data storage, processing and analytics level, application level. Cyber-physical systems carry out their work using a basic set of technologies: the Internet of things, big data and cloud computing. Additional technologies are used depending on the purpose of the system. At the physical level, data is collected from physical devices. With the help of the Internet of Things at the network level, data is transferred to a data warehouse for further processing or processed almost immediately thanks to cloud computing. The amount of data in cyber-physical systems is enormous, so it is necessary to use big data technology and effective methods for processing and analyzing this data. The main feature of this technological complex is real-time operation. Despite the improvement in the quality of production and human life, cyber-physical systems have a number of disadvantages. The authors highlight the main problems of cyber-physical systems and promising areas of research for their development. Having solved the listed problems, cyber-physical systems will reach a qualitatively new level of utility. The paper also provides examples of the implementation of concepts such as a smart city, smart grid, smart manufacturing, smart house. These concepts are based on the principle of cyber-physical systems.

Cyberphisical adaptive manufacturing control systems

Cyberphysical systems of adaptive manufacturing control are considered. It has been shown that the concept of Cyberphysical systems can be used for both the construction and analysis of adaptive systems. A generalized technology of research is proposed. A generalized model has been formed both for manufacturing in general and for structured manufacturing with a universal structure. All possible perturbations in the system and their compensating controls are considered. It is noted that the prior art publications use simpler system structures. It has been shown that the proposed model can be used in the study of newly studied systems with different structures, including those not previously discussed. Initially, we consider the technology of building a model that allows you to ensure the optimal mode and the prompt transition to the production of new products. Emphasis is placed on obtaining numerical data. A specific technology for using the model for control purposes is then proposed.

Method to assess the adherence of internal logistics equipment to the concept of CPS for industry 4.0

Industry 4.0 foresees benefits to companies and is supported by technologies such as Cyber-Physical Systems (CPS), Internet of Things (IoT), Internet of Services (IoS), among others. CPS, one of Industry 4.0's key technologies, can be applied in many areas including health, mobility, production and logistics. The partial or total incorporation of CPS technologies into internal logistics equipment can present such advantages to businesses as reductions in logistics operational costs and in production cycle times. Although this application is still under development, several manufacturers already offer to the market internal logistics equipment incorporating CPS technologies, presenting them as fully capable of operating in the Industry 4.0 environment. However, it is observed that there is no effective method of assessing whether these devices effectively integrate such technologies and at what level this integration occurs. This manuscript adopted the design science research methodology to propose a method for assessing the adherence of internal logistics equipment to the CPS concept for Industry 4.0. The method is based on a guide for collecting data with questions that identify information about the CPS technologies embedded in the internal logistics equipment, associated with a tool for processing this information. The tool is supported by a properly trained artificial neural network that measures the equipment's adherence to the CPS concept. The method has proved to be adequate because in its application it assessed fifteen equipment, from worldwide-renowned manufacturers, with an error of less than 2%.

Динамические модели управления работой станции в рамках концепции киберфизических систем

Динамические модели управления работой станции в рамках концепции киберфизических систем

Data-Driven Based Cruise Control of Connected and Automated Vehicles Under Cyber-Physical System Framework

Cyber-physical systems (CPS) have become the cutting-edge technology for the next generation of industrial applications, and are rapidly developing and inspiring numerous application areas. This article presents an optimal forward-looking distributed CPS application for the safety-following driving control of connected and automated vehicles (CAV) in the intelligent transportation. The relevant components and required technologies of the CPS concept in intelligent transportation systems are introduced firstly. Under this framework, each CAV is considered as an independent CPS. In the safe driving of vehicles, historical data is used to build vehicle behavior prediction models and dynamic driving system models. At the same time, a new range strategy considering the probability of merging behavior is proposed and applied to the CAV’s safe cruise control. The results show that through the application framework of CPS, the proposed range strategy can improve the following safety of the vehicle.

Classical Failure Modes and Effects Analysis in the Context of Smart Grid Cyber-Physical Systems

Reliability assessment in traditional power distribution systems has played a key role in power system planning, design, and operation. Recently, new information and communication technologies have been introduced in power systems automation and asset management, making the distribution network even more complex. In order to achieve efficient energy management, the distribution grid has to adopt a new configuration and operational conditions that are changing the paradigm of the actual electrical system. Therefore, the emergence of the cyber-physical systems concept to face future energetic needs requires alternative approaches for evaluating the reliability of modern distribution systems, especially in the smart grids environment. In this paper, a reliability approach that makes use of failure modes of power and cyber network main components is proposed to evaluate risk analysis in smart electrical distribution systems. We introduce the application of Failure Modes and Effects Analysis (FMEA) method in future smart grid systems in order to establish the impact of different failure modes on their performance. A smart grid test system is defined and failure modes and their effects for both power and the cyber components are presented. Preventive maintenance tasks are proposed and systematized to minimize the impact of high-risk failures and increase reliability.

Strategic Research on the Goals, Characteristics, and Paths of Intelligentization of Process Manufacturing Industry for 2035

This study focuses on the constitutive characteristics, dissipative structure, dissipative process, modeling mechanism, and other physical essence concerning the manufacturing processes of the process manufacturing industry. The petrochemical and steel industries are used as the major research objects in the study. It integrates intelligence with the concept of cyber-physical systems (CPS) to investigate the possible approaches for realizing self-sensing, self-learning, self-decision-making, self-execution, and self-adaptation of plant-wide dynamic processes including operation, management, and service. It also studies the approaches for building a CPSbased intelligent factory. Furthermore, the goals, characteristics, and paths are proposed for the intelligent development of the process manufacturing industry toward 2035; and countermeasures and suggestions are also proposed regarding mechanism construction, science and technology project, financial support, technology research and development, intellectual property, and international communication.

Design and implementation of a CPS‐based predictive maintenance and automated management platform

The concept of cyber-physical systems (CPSs) is a core technology indispensable to Industry 4.0. The development of an intelligent automatic operational management platform is presented in this study. The platform is used to collect on-site data, provide predictive maintenance, and monitor and control the mobile robots. For predictive maintenance, it is targeted at products from manufacturing big data to cloud computing, and predictive maintenance for all factories around the world. The efficiency of the management system is improved by the performance evaluation strategy. In the experiments, the authors implement and discuss the predictive maintenance platform with generated synthetic data and real-world data collected from a gearbox plant. The results show that the important variables possess large drops according to mean decrease Gini. A warning generation for battery simulation and manufacturing execution is also presented to demonstrate the proposed system design. The results show that the discharge curve drops sharply at the last stage, and the warning value can be set accordingly.

Exploiting visual cues for safe and flexible cyber-physical production systems

Human workers are envisioned to work alongside robots and other intelligent factory modules, and fulfill supervision tasks in future smart factories. Technological developments, during the last few years, in the field of smart factory automation have introduced the concept of cyber-physical systems, which further expanded to cyber-physical production systems. In this context, the role of collaborative robots is significant and depends largely on the advanced capabilities of collision detection, impedance control, and learning new tasks based on artificial intelligence. The system components, collaborative robots, and humans need to communicate for collective decision-making. This requires processing of shared information keeping in consideration the available knowledge, reasoning, and flexible systems that are resilient to the real-time dynamic changes on the industry floor as well as within the communication and computer network infrastructure. This article presents an ontology-based approach to solve industrial scenarios for safety applications in cyber-physical production systems. A case study of an industrial scenario is presented to validate the approach in which visual cues are used to detect and react to dynamic changes in real time. Multiple scenarios are tested for simultaneous detection and prioritization to enhance the learning surface of the intelligent production system with the goal to automate safety-based decisions.

Geo CPS: Spatial challenges and opportunities for CPS in the geographic dimension

Recent advances in the Internet of Things (IoT) have brought great opportunities for geographical information systems (GIS) to be integrated with cyber-physical systems (CPS) in urban management. However, the term IoT and CPS are new in the GIS realm. This article reviews the concepts of IoT and CPS from the perspective of geospatial spaces and proposes the concept of Geo CPS to develop the potential of new technology in the geographic dimension. Two forms of Geo CPS are discussed: pseudo-CPS (PCPS), which projects spatial data onto a display without interaction among data sources, and true-CPS (TCPS), which handles data sources deeply and semantically. While PCPS already has wide industrial applications, TCPS is still in its infancy. The spatial challenge for CPS in geo space involves operating conditions in an open environment, and here, the human-machine system interface will be key. A transformation of our mindset relating to GIS can lead to the creation of new value-added geographical information services. This will require new schemes and platforms for data sharing, processing, security, and privacy, etc.

Manufacturing big data ecosystem: A systematic literature review

Abstract Advanced manufacturing is one of the core national strategies in the US (AMP), Germany (Industry 4.0) and China (Made-in China 2025). The emergence of the concept of Cyber Physical System (CPS) and big data imperatively enable manufacturing to become smarter and more competitive among nations. Many researchers have proposed new solutions with big data enabling tools for manufacturing applications in three directions: product, production and business. Big data has been a fast-changing research area with many new opportunities for applications in manufacturing. This paper presents a systematic literature review of the state-of-the-art of big data in manufacturing. Six key drivers of big data applications in manufacturing have been identified. The key drivers are system integration, data, prediction, sustainability, resource sharing and hardware. Based on the requirements of manufacturing, nine essential components of big data ecosystem are captured. They are data ingestion, storage, computing, analytics, visualization, management, workflow, infrastructure and security. Several research domains are identified that are driven by available capabilities of big data ecosystem. Five future directions of big data applications in manufacturing are presented from modelling and simulation to real-time big data analytics and cybersecurity.

Guest Editorial: Adaptive and Reconfigurable Service‐Oriented, Cloud and Virtualised Architectures

The concept of adaptive and reconfigurable Service Oriented Architecture (SOA) has been introduced in order to describe architectures that exhibit emerging functional and non-functional properties in changing contexts. An adaptive and reconfigurable can repair itself if any execution problem occurs, in order to successfully complete its own execution, while respecting functional and non-functional agreements. In the design of an adaptive and reconfigurable SOA, several aspects have to be considered. For instance, the architecture components should be able to predict and to detect degradations and failures as soon as possible and to enact suitable recovery actions such as scaling-up and scaling-out of virtual execution resources. Moreover, different non-functional service-level requirements might be considered in order to complete the execution in case of a predicted imminent or observed occurring failure. Contributions are devoted to the design and the implementation of adaptive and reconfigurable and related Cloud applications. The issue contains five papers related to the foundations of SOA and Cloud and the tools and applications for and Cyber-Physical environments. Service Oriented Architecture and Cloud Computing E2SM: A Security tool for Adaptive Cloud-based Service-Oriented Applications by Takoua Abdellatif proposes an End-to-end Security Model (E2SM) that aims to protect data confidentiality in adaptive cloud-based applications. Whereas Leah Mutanu and Gerald Kotonya study the key factors that influence runtime adaptation in service-oriented architectures, and examines how well they are addressed in 29 adaptation approaches intended to support service-oriented systems in the paper entitled What, Where, When, How and Right of Runtime Adaptation in Service-Oriented Systems. The paper entitled and Analyzing Elastic Strategies in Cloud by Khaled Khebbeb et al. proposes a Bigraphical Reactive Systems based approach to provide a formal modelling of Cloud systems' structure using bigraphs, and their elastic behaviours using bigraphical reaction rules. Smart and Cyber-Physical environments and Verifying Time-aware Processes for Cyber-Physical Environments by Imen Graja et al. proposes to extend Business Process Modeling Notation to support the various Cyber-physical system concepts and properties. The paper entitled and Safe Self-Adaption of Connected Devices Based on Discrete Controllers by Arthur Gatouillat et al. proposes a self-adaptation framework to deal with changes and takes into account storage, computational and communication constraints.

Modelling and verifying time‐aware processes for cyber‐physical environments

Cyber-physical systems (CPSs) are characterized by a multitude of physical and software. Particularly time-related properties are of paramount importance and they can impact the behaviour of these systems. Designing and verifying CPS while tackling time-related and physical properties are very important steps in the CPS life cycle development. Indeed, it is necessary to capture and characterize the different features and their dependencies with time through expressive models. Then, these models must be verified to prove their correctness. Existing process modelling languages such as business process modelling notation (BPMN) has been widely used to model business processes. However, BPMN lacks several features for modelling rich CPS processes such as those related to time and physical properties. In this study, the authors propose a verification framework for collaborative time-aware CPS processes. In this context, they propose to extend BPMN to support the various CPS concepts and properties. Based on this extension, they propose a consistency verification approach, which aims to verify that the time-related and physical properties associated with each process do not give rise to conflicts. Finally, they propose a compatibility verification approach, which aims to verify that the set of involved CPS processes form consistent inter-CPS processes.

Standards for Cyber-Physical Energy Systems—Two Case Studies from Sensor Technology

Cyber-physical energy systems (CPES) describe a specialization of the cyber-physical system concept, in which energy systems are transformed into intelligent energy networks. These systems provide the basis for the realization of smart microgrids and smart grids. In the last decade, numerous research projects have intensively explored the fundamentals and modeling of CPES and validated them in pilot projects. In the meantime, more and more CPES solutions have been appearing on the market and the battle for the most suitable standards has begun. This paper gives an overview of the currently available standards for CPES sensor technologies and assesses the suitability for implementation. In two case studies in the application area of operational energy management in German companies, a sensor retrofitting is described—once with proprietary technology and once using the standards Long Range (LoRa) Wide Area Network and OPC Unified Architecture (OPC UA). As a result, the shortcomings of the standards for their use in CPES are shown and discussed. OPC UA, which was originally developed for the manufacturing industry, turns out to be to be a suitable standard for a wide range of CPES implementations.

Distributed Control Strategy of Microgrid Based on the Concept of Cyber Physical System

For distributed energy resources (DERs) in islanded microgrid (MG), to improve the control effect on the output voltages and frequency from droop control, a novel distributed control strategy is proposed in this article based on the concept of cyber physical system (CPS). The novel control structure is consisted by the cyber and the physical layers. In the cyber layer: firstly, the communication structures of overall microgrid and single DER are constructed; then, based on the communication structures, the influence of time-delay (delay) and packet loss (loss) on consensus control is analyzed in this article; And then, an event-triggered mechanism combined with adapt virtual leader-following consensus control (AVLFCC) and predictive compensation is proposed in this layer. It is used to solve the problem of time-varying delay and loss rate in the process of consensus control. In the physical layer: firstly, the droop control is used as the primary control on the output voltages and frequency of DERs; then, a novel secondary control method is proposed by using the event-triggered mechanism. And finally, the simulation results confirm the effectiveness of the novel distributed control strategy under communication problems (delay and loss) and during plug-and-play operation.