Cyber-physical Interaction Research Articles

Multi-objective hierarchical energy management for connected plug-in hybrid electric vehicle with cyber–physical interaction

Recently, the overall performances of plug-in hybrid electric vehicles (PHEVs) are expected to be further improved by integrating multiple objectives and cyber–physical interaction (CPI), which pose challenges to existing hierarchical and synchronous optimization frameworks in terms of performances improvement effect and optimization efficiency. In this paper, the CPI based hierarchical optimization framework (HOF) is proposed for the first time to explore the overall performances improvement potential of PHEVs by integrating multi-dimensional traffic information. Particularly, the decomposition based multi-objective evolutionary algorithm is employed in the cyber level to achieve motion planning by balancing various objectives including economy, comfort, safety, and traffic efficiency. Furthermore, the CPI mechanism is developed under the option-critic architecture, which achieves the bi-directional interaction between cyber and physical levels, thus contributing to obtaining superior optimization effect and computational efficiency. Benefiting from the CPI mechanism, the power distribution is finished in the physical level, in which the engine steady-transient characteristic and powertrain efficiency are highlighted comprehensively. The simulation verification with real traffic data demonstrates that the proposed strategy achieves a 4.73% and 5.91% improvement in overall performances compared to synchronous and hierarchical optimization, respectively.

Optimal defense strategy selection method for CPS considering integrated cyber–physical losses

Cyber-attacks against the cyber–physical power system (CPPS) may lead to major power outages and even system collapse in severe cases. In order to quantify the attack losses and select optimal strategies to defend against cyber-attacks, this paper proposes a computational model of integrated cyber–physical losses based on the theory of interdependent network. Based on the multiple coupling relationship between cyber system and physical network, the monitoring system is regarded as the cyber–physical interaction layer, and the information network operation constraint, physical system load reduction constraint, and monitoring equipment operation constraint are established respectively to analyze the impact on another network after a failed node appears in one layer of network, and proposed the cyber–physical integrated loss objective function. The offensive and defensive processes are abstracted into a two-player zero-sum game model, which evolves into a multi-stage game according to the changes in the system state during the game, and the integrated cyber–physical loss is used as the game gain of both the attacker and defender, and the Minimax-Q algorithm is introduced to solve for the optimal gain and select the optimal defense strategy. Finally, the IEEE 30 node cyber–physical system is used as a simulation example to verify whether the proposed loss calculation model can effectively quantify the losses caused by the attack on the information network and the power grid, and has practical guidance for the selection of the optimal defense strategy.

A state-of-the-art survey on Augmented Reality-assisted Digital Twin for futuristic human-centric industry transformation

The combination of Augmented Reality (AR) and Digital Twin (DT) has begun to show its potential nowadays, leading to a growing research interest in both academia and industry. Especially under the current human-centric trend, AR embraces the potential to integrate operators into the new generation of Human Cyber–Physical System (HCPS), in which DT is a pillar component. Some review articles have focused on this topic and discussed the benefits of combining AR and DT, but all of them are limited to a specific domain. To fill the gap, this research conducts a state-of-the-art survey (till 17-July-2022) from the AR-assisted DT perspective across different sectors of the industrial field, covering a total of 118 selected publications. Firstly, application scenarios and functions of AR-assisted DT are summarized by following the engineering lifecycle, among which production process, service design, and Human–Machine Interaction (HMI) are hot topics. Then, improvements specifically brought by AR are analyzed according to three dimensions, namely virtual twin, hybrid twin, and cognitive twin, respectively. Finally, challenges and future perspectives of AR-assisted DT for futuristic human-centric industry transformation are proposed, including promoting product design, robotic-related works, cyber–physical interaction, and human ergonomics.

Toward Cyber-physical Interaction for Natural Connection of Real Space and Cyberspace

Toward Cyber-physical Interaction for Natural Connection of Real Space and Cyberspace

Research on ACPS Architecture of Precision Prataculture: A Case of Water Precision Regulation for Alfalfa

Highlights A precision regulation architecture of prataculture based on agriculture cyber-physical system (PRACPS) was proposed. The PRACPS-ALFA model was designed and implemented through the actual physical environment and Ptolemy tool. The PRACPS-ALFA has good applicability in the Ningxia irrigation area of the Yellow River. The architecture can achieve precise water regulation of forage under a complex physical environment. Abstract. Because the architecture of prataculture precision irrigation cannot dynamically track forage growth and change in future physical environments, a precision regulation architecture of prataculture based on an agriculture cyber-physical system (PRACPS) is proposed. We use the most widely planted alfalfa as an example and design an alfalfa application architecture based on the PRACPS (PRACPS-ALFA). An alfalfa growth model based on water factor was built into the PRACPS-ALFA. We discuss the construction methods of the physical space, the cyber space, and the cyber-physical interaction interfaces. The PRACPS-ALFA is designed and implemented through the actual physical environment and the Ptolemy tool. Four evaluation indices are designed to evaluate the applicability and accuracy of the architecture. Finally, through field experiments in the Ningxia irrigation area of the Yellow River, the model is validated and analyzed by the simulated and observed values of each evaluation indicator. The results show that the PRACPS-ALFA has good applicability in the Ningxia irrigation area of the Yellow River and can achieve precise water regulation of forage in a complex physical environment. Keywords: ACPS, Alfalfa, Applicability, Prataculture, Precision regulation, Ptolemy.

EduTalk: An IoT Environment for Learning Computer Programming and Physics

This article proposes EduTalk, an out-of-the-box Internet of Things (IoT)-based smart learning environment for programming education. In particular, EduTalk enables the students to write VPython programs that render 3-D animations in the browser without installing extra software or using any specific (and typically expensive) hardware. EduTalk takes the user’s smartphone as a controller for cyber–physical interaction, which nicely integrates with learning of other core courses such as physics and mathematics. EduTalk allows building science exhibition projects by writing VPython programs to show 3-D animation, where the cost for EduTalk’s cyber–physical interaction is low and is almost maintenance free. The major contribution of this article is the IoT-based EduTalk proposal that subtly utilizes an IoT platform IoTtalk to conveniently generate cyber–physical interaction for learning how to program as well as learning core courses such as physics. The programming exercises can be easily extended to science exhibition projects and then the development of digital twin applications. A mechanism is provided to easily integrate GlowScript animation demos with EduTalk, which significantly simplifies the effort for teachers to prepare the lecturers. Finally, we show how data collected from EduTalk can be analyzed to improve learning design for cyber–physical interactive animation.

A Data-Driven Algorithm for Enabling Delay Tolerance in Resilient Microgrid Controls Using Dynamic Mode Decomposition

The increased implementation of smart grid technologies in the power distribution grid presents unique opportunities that enable resiliency, but also brings challenges motivating needs for novel solutions and mitigation techniques. The bi-directional power and data flow allow for the grid to operate with increased resiliency, which is the ability to avoid discontinuity of service to end-use loads during extreme events. However, in applications where control of the distribution grid or microgrid relies on communication networks, the degradation of communication systems in the form of loss or high latency can cause maloperation and result in loss of end-use loads. This paper presents a novel framework to enable delay tolerance of centralized microgrid control schemes to mitigate communication system latency impacts and guarantee successful control action. We demonstrate the delay tolerance on a control scheme that operates a battery energy storage system (BESS) to offset the sudden loss of generation and maintain system frequency. During periods of severely degraded communication system performance, the proposed delay-tolerant algorithm compensates for the latency by utilizing a data-driven model generated at the device level using dynamic mode decomposition (DMD) to determine the performance of the communications. The DMD technique predicts the system’s frequency using device-level terminal measurements and provides updated control signals. The HELICS cosimulation platform evaluates the cyber-physical interaction of the power system model in GridLAB-D, the centralized control agent in Python, and the discrete network model in NS-3. The framework is tested and validated on the IEEE-123 node system modified to represent a networked remote microgrid model, and the results show an improvement in the dynamic performance of the control scheme when subject to communication delays.

Stability-Oriented Minimum Switching/Sampling Frequency for Cyber-Physical Systems: Grid-Connected Inverters Under Weak Grid

Although the cyber-physical system stability is widely studied, scholars focus more on system stability with communication time delay. Therein, grid-connected inverters with the digital control system are regarded as one simplest and typical cyber-physical system. Meanwhile, the switching/sampling frequency of the inverter is always selected as low as possible from an efficiency viewpoint, resulting in unavoidable delay time. This delay time is apt to cause the system instability, which is more prone to severity under weak grid. To this end, this paper provides a minimum switching/sampling frequency for grid-connected inverters. Firstly, the system impedance model with equivalent delay time is constructed, which is based on padé approximate approach. This equivalent delay time consists of three parts, i.e., sampling delay time in cyber/physical level, calculation delay time in cyber level and pulsewidth modulation delay time in physical level, which reflects the cyber-physical interaction impact. Furthermore, the stability forbidden criterion is applied to make the switching/sampling frequency solving process become Hurwitz matrix identification problem through space mappings. Based on these space mappings, an adaptive step search approach is adopted to obtain the minimum switching/sampling frequency. Finally, the proposed approach can well evaluate the system stability under different frequencies through simulation and experiment.

Digital Medical Education Empowered by Intelligent Fabric Space

Medical education plays an important role in promoting the development of global medical science. Nevertheless, the intrinsic gap existing between institutional medical teaching and practical clinical tasks causes low education efficiency and students’ weak initiative. Recent developments of sensing fabric and embedded computing, along with the advances in Artificial intelligence (AI) and digital twin technology are paving the way for the transformation of medical research towards digitization. In this work, we present an intelligent fabric space based on novel functional fabric materials and digital twin networking enabled by 5G and Internet of Things (IoT) technologies. In this space, medical students can learn knowledge with collaborative mapping of the digital and real world, cyber-physical interaction and real-time tactile feedback. And the proposed service system will evaluate and feedback students’ operational behaviors to improve their experimental skills. We provide four typical applications of intelligent fabric space for medical education, including medical education training, health and behavior tracking, operation playback and reproduction, as well as medical knowledge popularization. The proposed intelligent fabric space has the potential to promote innovative technologies for training cutting-edge medical students by effective and efficient ways.

Cyber security risk assessment in autonomous shipping

Autonomous ships would require higher cyber-physical interaction in comparison with traditional shipping operations, thus increasing the vulnerabilities associated with cyber security. The increasing complexity surrounding the innate characteristics of the shipping industry makes it challenging to build a resilient framework for ensuring cyber security. This study proposes a multi-criteria decision-making (MCDM) framework for assessing cyber security risk in the autonomous shipping context. The research was validated through surveying subject matter experts, system designers and seafarers. Different types of equipment and systems are ranked based on their perceived vulnerability to cyber threats. Survey data from 28 subject matter experts are collected and analysed through the Bayesian best–worst method (BWM). At system level, the results indicate that navigational systems are the most vulnerable to potential cyber threats, while propulsion systems are the least vulnerable element in the context of future autonomous shipping operations. On a sub-system level, the three most vulnerable parts are Global Navigation Satellite System (GNSS), Electronic Chart Display and Information System (ECDIS) and the communication devices on shore control centres (SCC), while the least vulnerable parts are engine controls, SCC integration platforms and cargo handling at ports.

CATtalk: An IoT-Based Interactive Art Development Platform

Interactive art has been significant advanced by the Internet of Things (IoT) and cyber physical interaction technologies, which enables the participants to engage with the art devices. Several tools and platforms have been proposed to create the art devices. However, the interactive artworks are typically developed with these art devices in ad hoc approaches, and the artists need to spend significant programming efforts to integrate the art devices. This paper proposes CATtalk, a platform to create and maintain interactive artworks. The novel idea is to treat all art devices in an interactive artwork as IoT devices that can be transparently reused by reconfiguration in CATtalk. Therefore, the artworks developed independently by individual artists can be quickly integrated to create new interactive applications. Through CATtalk’s no-code and low-code mechanisms, the artists can manipulate CATtalk with little or no programing efforts. CATtalk offers a built-in mechanism so that any person in the audience can play with an interactive artwork with his/her smartphone. We also conduct analytic analysis, simulation and measurements to ensure that the interactive art performance in cross-country remote stages are not affected by the communications delays. In our measurements, the average local and remote communication delays are about 0.01 and 0.05 seconds, respectively. If the art performance is designed such that the average delay between two actions of a local (remote) performer is longer than 0.1 seconds, then the probability of out-of-sequence actions is less than 0.01%. That is, the local dancer should perform slower than the remote dancer. Such delay analysis for remote interactive art performance has not been conducted in the literature.

Cyber‐physical description and CPS‐based pinning approach of mixed traffic

In this paper, a cyber-physical description of mixed traffic that can reflect the interaction between vehicles is first proposed. By treating vehicles as nodes and the cyber-physical interaction between vehicles as directed edges between nodes, the network of vehicles in traffic is obtained. The small-world and scale-free characteristics of mixed traffic are found under this description. Then the CPS-based pinning approach for achieving indirect control of HVs is proposed. Besides the control algorithm of pinning nodes, the impact of the spatial distribution of automated vehicles on traffic is studied. The approach is compatible with the existing control of automated vehicle in mixed vehicle platoon. Numerical simulation results under three-lane scenario illustrated the effectiveness of the proposed pinning approach.

Coding the circularity. Design for the disassembly and reuse of building components

The architecture design today has new expressive features due to the parametric and computational modelling software, which greatly amplify the potential of language. This condition makes it possible to generate customised elements and systems through a process of cyber-physical interaction between design and architectural production. As well as the geometric constraints, dictated by manufacturing and assembly processes of materials, they can be incorporated in the generative design codes. The article examines the possibility to also include the main conditions that enable the selective disassembly of the elements and their reuse at the end of life, avoiding the generation of parts that are not remanufacturable or reusable.

Self-Adaptive Data Processing to Improve SLOs for Dynamic IoT Workloads

Internet of Things (IoT) covers scenarios of cyber–physical interaction of smart devices with humans and the environment and, such as applications in smart city, smart manufacturing, predictive maintenance, and smart home. Traditional scenarios are quite static in the sense that the amount of supported end nodes, as well as the frequency and volume of observations transmitted, does not change much over time. The paper addresses the challenge of adapting the capacity of the data processing part of IoT pipeline in response to dynamic workloads for centralized IoT scenarios where the quality of user experience matters, e.g., interactivity and media streaming as well as the predictive maintenance for multiple moving vehicles, centralized analytics for wearable devices and smartphones. The self-adaptation mechanism for data processing IoT infrastructure deployed in the cloud is horizontal autoscaling. In this paper we propose augmentations to the computation schemes of data processing component’s desired replicas count from the previous work; these augmentations aim to repurpose original sets of metrics to tackle the task of SLO violations minimization for dynamic workloads instead of minimizing the cost of deployment in terms of instance seconds. The cornerstone proposed augmentation that underpins all the other ones is the adaptation of the desired replicas computation scheme to each scaling direction (scale-in and scale-out) separately. All the proposed augmentations were implemented in the standalone self-adaptive agent acting alongside Kubernetes’ HPA such that limitations of timely acquisition of the monitoring data for scaling are mitigated. Evaluation and comparison with the previous work show improvement in service level achieved, e.g., latency SLO violations were reduced from 2.87% to 1.70% in case of the forecasted message queue length-based replicas count computation used both for scale-in and scale-out, but at the same time higher cost of the scaled data processor deployment is observed.

Nash optimality based distributed model predictive control for vehicle platoon

In this paper, a distributed model predictive control algorithm (DMPC) based on Nash optimality is proposed for automated vehicle platoon control. The optimization decision of vehicle platoon is decomposed into the decentralized optimization of single vehicles, in which the Nash optimality algorithm is adopted to solve the decentralized optimization problem. Thus, each vehicle can reach the local optimal target and the whole team can reach its Nash equilibrium. The methodology employs neighborhood information of the entire platoon through on-board sensors and V2V communication to achieve coordination of the entire platoon. The ability of the methods in terms of robustness to disturbances and cyber-physical interaction is demonstrated with simulation case studies.

Hierarchical Flow Model-Based Impact Assessment of Cyberattacks for Critical Infrastructures

Critical infrastructures (CIs) are essential for the national security, economy, and public safety, whose protection against cyberattacks has become the focus of significant attention. Impact assessment plays an important role in this protection, which provides real-time situations for security managers. The assessment of CIs not only need to analyze the cyberattack's impact on any specific station, but also to consider the spreading process of the negative impact. However, few research in this domain consider the above two aspects simultaneously due to the complexity of CIs and their operation. To tackle this problem, a hierarchical flow model (HFM)-based impact assessment is presented. In this approach, a novel HFM method is proposed to describe a system from a function system perspective, which combines a flow model and hierarchical knowledge. By using this method, a CI model which considers cyber–physical interaction within a station, dependence among stations, and the topological structure of the physical network is established. Next, based on the CI model, an impact assessment is proposed to quantify the loss which is caused by the impact spreading within the CI network. Finally, case studies on a gas supply system are conducted to verify the effectiveness of the proposed approach.

Blockchain and IoT-Based Cognitive Edge Framework for Sharing Economy Services in a Smart City

In this paper, we propose a Blockchain-based infrastructure to support security- and privacy-oriented spatio-temporal smart contract services for the sustainable Internet of Things (IoT)-enabled sharing economy in mega smart cities. The infrastructure leverages cognitive fog nodes at the edge to host and process offloaded geo-tagged multimedia payload and transactions from a mobile edge and IoT nodes, uses AI for processing and extracting significant event information, produces semantic digital analytics, and saves results in Blockchain and decentralized cloud repositories to facilitate sharing economy services. The framework offers a sustainable incentive mechanism, which can potentially support secure smart city services, such as sharing economy, smart contracts, and cyber-physical interaction with Blockchain and IoT. Our unique contribution is justified by detailed system design and implementation of the framework.

Flower Sermon: An Interactive Visual Design Using IoTtalk

IoTtalk is a platform for IoT device interaction, which has been used to develop many IoT applications such as home automation. This paper uses Flower Sermon artwork as an example to show how interactive visual design can be conveniently implemented in IoTtalk. The Flower Sermon artwork conducts cyber physical interaction, which animates a dandelion in a mirror when a person smiles at that mirror. The dandelion grows larger as the person smiles bigger. The flower also vibrates following the heartbeat rate of the person. In our approach, the camera detecting the face expression and the heartbeat rate is considered as an input IoT device, and the mirror display for dandelion animation is considered as an output IoT device. In IoTtalk, the features of the dandelion animation are considered as the actuators that can be independently controlled. IoTtalk nicely connects these IoT devices, where various features can be created for interactive visual design with little or without any programming effort. We also measure the time complexity for data delivery among the input and the output IoT devices. Our study indicates that the time delays are less than 0.07 s on the average even if the IoTtalk server is located in a cloud.

Engfi Gate: An Indoor Guidance System using Marker-based Cyber-Physical Augmented-Reality

A guidance system is needed when freshmen explore their new building environment. With the advancements of mobile technologies, a guidance system using mobile computing devices such as mobile phones or tablets could aid freshmen in locating the desired destination with ease. The proposed system consists of three main subsystems: the marker-based cyber-physical interaction (CPI) system, the indoor positioning (IP) system, and the augmented-reality (AR) system. With the help of visible markers and invisible markers, the CPI system allows the users to do interactions between the physical and cyber environments; the IP system produces accurate user position information; the AR system provides the users with good user experiences. An Android application, named Engfi Gate, is developed to realize the system design in the test environment. This paper also shows the comparisons of the proposed system with other related systems. Furthermore, the design architecture of Engfi Gate system can be used in other location-based applications.

Data and Decision Intelligence for Human-in-the-Loop Cyber-Physical Systems: Reference Model, Recent Progresses and Challenges

With the rapid development of sensing technology, Cyber-Physical Systems (CPS) are connecting our real-world and cyber spaces by real-time situation awareness and intelligent control. In this process, one of the major challenge is how to make fast, accurate and intelligent decisions based on high-dimension, speed and volume sensing data stream. In this paper, we put human into the traditional CPS data process model and formulate a closed-loop computing paradigm for CPS data and decision intelligence. We propose a human-in-the-loop reference model for CPS, which extends the traditional cyber-physical interaction into a closed-loop process based on cyber, physical and human factors. We define the key features of human-in-the-loop CPS, summarize it as three aspects: semantic, interactive, iterative and analyze the major challenges from the perspective of data characteristics. Recent progresses in three typical application domains are reviewed and examined for their decision models and whether they have solved the target issues of human-in-the-loop CPS. According to the review and comparison, the paper finally summarizes several key future opportunities to establish an intelligent human-in-the-loop CPS.