scholarly journals Bayesian Network-Based High-Level Context Recognition for Mobile Context Sharing in Cyber-Physical System

2011 ◽  
Vol 7 (1) ◽  
pp. 650387 ◽  
Author(s):  
Han-Saem Park ◽  
Keunhyun Oh ◽  
Sung-Bae Cho
Keyword(s):  
Bayesian Network ◽  
Physical System ◽  
Cyber Physical System ◽  
Context Recognition ◽  
Mobile Context ◽  
High Level

Sensitivity Analysis of a Baysian Network Model on PCM Equipments

2013 ◽  
Vol 391 ◽  
pp. 544-547
Author(s):  
Hui Sheng Gao ◽  
Xu Rui Wang
Keyword(s):  
Sensitivity Analysis ◽  
Bayesian Network ◽  
Physical System ◽  
Communication Systems ◽  
Focus Of Attention ◽  
Cyber Physical System ◽  
Pulse Code Modulation ◽  
Counter Measures ◽  
Security Problem ◽  
Code Modulation

In power communication systems, the pulse code modulation (PCM) equipment play an important role. Its security has been a focus of attention, when the concept of cyber physical system is proposed. In order to solve the security problem of PCM equipments, a Bayesian Network (BN) model is used in this paper. By analyzing the sensitivity of BN model, we can get the influence of each input variable to outcome variables. For illustration, four PCM equipments are selected from some substations. They are utilized to show the feasibility of the BN model in evaluating the security of PCM equipments and the sensitivity analysis. Empirical results show that some effective counter measures can be found to help decision maker improve the security of PCM equipments. The BN model can effectively evaluate the security of PCM equipments. After analyzing the sensitivity, the most reasonable and effective countermeasures are advanced.

scholarly journals Multilevel Simulation Methodology for FMECA Study Applied to a Complex Cyber-Physical System

Electronics ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 1736
Author(s):  
Davide Piumatti ◽  
Jacopo Sini ◽  
Stefano Borlo ◽  
Matteo Sonza Reorda ◽  
Radu Bojoi ◽  
...  
Keyword(s):  
Complex Systems ◽  
Physical System ◽  
Electrical Power ◽  
Cyber Physical Systems ◽  
Cyber Physical System ◽  
Test Case ◽  
Physical Systems ◽  
Failure Classification ◽  
High Level ◽  
Criticality Analysis

Complex systems are composed of numerous interconnected subsystems, each designed to perform specific functions. The different subsystems use many technological items that work together, as for the case of cyber-physical systems. Typically, a cyber-physical system is composed of different mechanical actuators driven by electrical power devices and monitored by sensors. Several approaches are available for designing and validating complex systems, and among them, behavioral-level modeling is becoming one of the most popular. When such cyber-physical systems are employed in mission- or safety-critical applications, it is mandatory to understand the impacts of faults on them and how failures in subsystems can propagate through the overall system. In this paper, we propose a methodology for supporting the failure mode, effects, and criticality analysis (FMECA) aimed at identifying the critical faults and assessing their effects on the overall system. The end goal is to analyze how a fault affecting a single subsystem possibly propagates through the whole cyber-physical system, considering also the embedded software and the mechanical elements. In particular, our approach allows the analysis of the propagation through the whole system (working at high level) of a fault injected at low level. This paper provides a solution to automate the FMECA process (until now mainly performed manually) for complex cyber-physical systems. It improves the failure classification effectiveness: considering our test case, it reduced the number of critical faults from 10 to 6. The remaining four faults are mitigated by the cyber-physical system architecture. The proposed approach has been tested on a real cyber-physical system in charge of driving a three-phase motor for industrial compressors, showing its feasibility and effectiveness.

scholarly journals A Human-Cyber-Physical System toward Intelligent Wind Turbine Operation and Maintenance

2021 ◽  
Vol 13 (2) ◽  
pp. 561
Author(s):  
Xiao Chen ◽  
Martin A. Eder ◽  
Asm Shihavuddin ◽  
Dan Zheng
Keyword(s):  
Wind Turbines ◽  
Physical System ◽  
Cyber Physical System ◽  
Digital Twin ◽  
Effective Training ◽  
Human Decision ◽  
Machine Interface ◽  
Key Enabling Technologies ◽  
Novel Concept ◽  
High Level

This work proposes a novel concept for an intelligent and semi-autonomous human-cyber-physical system (HCPS) to operate future wind turbines in the context of Industry 5.0 technologies. The exponential increase in the complexity of next-generation wind turbines requires artificial intelligence (AI) to operate the machines efficiently and consistently. Evolving the current Industry 4.0 digital twin technology beyond a sole aid for the human decision-making process, the digital twin in the proposed system is used for highly effective training of the AI through machine learning. Human intelligence (HI) is elevated to a supervisory level, in which high-level decisions made through a human–machine interface break the autonomy, when needed. This paper also identifies and elaborates key enabling technologies (KETs) that are essential for realizing the proposed HCPS.

Implementation of a Cyber-Physical System Using Wireless Sensor Networks for Monitoring Patients

2015 ◽  
Vol 1 ◽  
pp. 26 ◽  
Author(s):  
Vo Que Son ◽  
Do Tan A
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Physical System ◽  
Patient Monitoring ◽  
High Reliability ◽  
Vital Signs ◽  
Wireless Sensor ◽  
Cyber Physical System ◽  
Self Administration ◽  
Hospital Units

Sensing, distributed computation and wireless communication are the essential building components of a Cyber-Physical System (CPS). Having many advantages such as mobility, low power, multi-hop routing, low latency, self-administration, utonomous data acquisition, and fault tolerance, Wireless Sensor Networks (WSNs) have gone beyond the scope of monitoring the environment and can be a way to support CPS. This paper presents the design, deployment, and empirical study of an eHealth system, which can remotely monitor vital signs from patients such as body temperature, blood pressure, SPO2, and heart rate. The primary contribution of this paper is the measurements of the proposed eHealth device that assesses the feasibility of WSNs for patient monitoring in hospitals in two aspects of communication and clinical sensing. Moreover, both simulation and experiment are used to investigate the performance of the design in many aspects such as networking reliability, sensing reliability, or end-to-end delay. The results show that the network achieved high reliability - nearly 97% while the sensing reliability of the vital signs can be obtained at approximately 98%. This indicates the feasibility and promise of using WSNs for continuous patient monitoring and clinical worsening detection in general hospital units.

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