The Research on the Framework of Cyber-Physical Systems for the Reliable Sensing and Optimization Scheduling

2011 ◽  
Vol 65 ◽  
pp. 451-454
Author(s):  
Yong Liang Lun ◽  
Liang Lun Cheng
Keyword(s):  
Data Processing ◽  
Physical World ◽  
Cyber Physical Systems ◽  
Research Directions ◽  
Physical Systems ◽  
Tight Integration ◽  
Optimization Scheduling

CPS is characterized by the tight integration of physical world and cyber world. Based on the brief introduction of the CPS and the research of its framework, we purpose a novel framework of the CPS aiming on the reliable sensing and optimization scheduling. The framework has five layers which are access layer, apperceive layer, networks layer, data processing layer and services layer. We make the introduction and analysis of each layer and point out the further research directions of them.

Emerging Cyber-Physical Systems : An Overview

2018 ◽  
pp. 306-316
Author(s):  
Okolie S.O. ◽  
Kuyoro S.O. ◽  
Ohwo O. B
Keyword(s):  
Health Care ◽  
Economic Benefit ◽  
Physical World ◽  
Cyber Physical Systems ◽  
Cyber Physical System ◽  
Economic Sectors ◽  
Strategic Research ◽  
Physical Systems ◽  
Security Issues ◽  
Wide Range

Cyber-Physical Systems (CPS) will revolutionize how humans relate with the physical world around us. Many grand challenges await the economically vital domains of transportation, health-care, manufacturing, agriculture, energy, defence, aerospace and buildings. Exploration of these potentialities around space and time would create applications which would affect societal and economic benefit. This paper looks into the concept of emerging Cyber-Physical system, applications and security issues in sustaining development in various economic sectors; outlining a set of strategic Research and Development opportunities that should be accosted, so as to allow upgraded CPS to attain their potential and provide a wide range of societal advantages in the future.

A Hybrid Siamese Neural Network for Natural Language Inference in Cyber-Physical Systems

2021 ◽  
Vol 21 (2) ◽  
pp. 1-25
Author(s):  
Pin Ni ◽  
Yuming Li ◽  
Gangmin Li ◽  
Victor Chang
Keyword(s):  
Natural Language ◽  
Language Processing ◽  
Short Term Memory ◽  
Physical World ◽  
Heterogeneous Data ◽  
Cyber Physical Systems ◽  
Physical Systems ◽  
Language Data ◽  
Text Language ◽  
Different Sources

Cyber-Physical Systems (CPS), as a multi-dimensional complex system that connects the physical world and the cyber world, has a strong demand for processing large amounts of heterogeneous data. These tasks also include Natural Language Inference (NLI) tasks based on text from different sources. However, the current research on natural language processing in CPS does not involve exploration in this field. Therefore, this study proposes a Siamese Network structure that combines Stacked Residual Long Short-Term Memory (bidirectional) with the Attention mechanism and Capsule Network for the NLI module in CPS, which is used to infer the relationship between text/language data from different sources. This model is mainly used to implement NLI tasks and conduct a detailed evaluation in three main NLI benchmarks as the basic semantic understanding module in CPS. Comparative experiments prove that the proposed method achieves competitive performance, has a certain generalization ability, and can balance the performance and the number of trained parameters.

scholarly journals Embedded Deep Learning Prototyping Approach for Cyber-Physical Systems: Smart LIDAR Case Study

2021 ◽  
Vol 10 (1) ◽  
pp. 18
Author(s):  
Quentin Cabanes ◽  
Benaoumeur Senouci ◽  
Amar Ramdane-Cherif
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Computation Time ◽  
Physical World ◽  
Cyber Physical Systems ◽  
Physical Systems ◽  
Research Technology ◽  
Standard Design ◽  
Hardware Architectures ◽  
Voxel Grid

Cyber-Physical Systems (CPSs) are a mature research technology topic that deals with Artificial Intelligence (AI) and Embedded Systems (ES). They interact with the physical world via sensors/actuators to solve problems in several applications (robotics, transportation, health, etc.). These CPSs deal with data analysis, which need powerful algorithms combined with robust hardware architectures. On one hand, Deep Learning (DL) is proposed as the main solution algorithm. On the other hand, the standard design and prototyping methodologies for ES are not adapted to modern DL-based CPS. In this paper, we investigate AI design for CPS around embedded DL. The main contribution of this work is threefold: (1) We define an embedded DL methodology based on a Multi-CPU/FPGA platform. (2) We propose a new hardware design architecture of a Neural Network Processor (NNP) for DL algorithms. The computation time of a feed forward sequence is estimated to 23 ns for each parameter. (3) We validate the proposed methodology and the DL-based NNP using a smart LIDAR application use-case. The input of our NNP is a voxel grid hardware computed from 3D point cloud. Finally, the results show that our NNP is able to process Dense Neural Network (DNN) architecture without bias.

Monitoring and Control of Dual-Arm Industrial Robot Tasks Using IoT Application and Services

2015 ◽  
Vol 762 ◽  
pp. 255-260 ◽  
Author(s):  
Mircea Murar ◽  
Stelian Brad
Keyword(s):  
Experimental Testing ◽  
Industrial Robot ◽  
Cyber Physical Systems ◽  
Monitoring And Control ◽  
Research Directions ◽  
Physical Systems ◽  
Selection For ◽  
Robot Tasks ◽  
And Control ◽  
Dual Arm

In the context of latest technological revolution, Industry 4.0, connectivity and therefore access and control of cyber-physical systems and resources from any place, at any time by any means represent a technological enabler of crucial importance. The first part of this paperwork contains a brief introduction of cyber-physical systems and IoT concepts, together with a review of major IoT providers. The second part introduces an approach towards achieving connectivity and remote control of task selection for a dual-arm industrial robot using a commercially available IoT infrastructure and technology provided by ioBridge. Within the third part, details about experimental testing and evaluation of the selected solutions are presented. The last part is allocated for conclusions and further research directions.

scholarly journals Leveraging Stack4Things for Federated Learning in Intelligent Cyber Physical Systems

2020 ◽  
Vol 9 (4) ◽  
pp. 59
Author(s):  
Fabrizio De Vita ◽  
Dario Bruneo
Keyword(s):  
Intelligent Systems ◽  
Physical World ◽  
Cyber Physical Systems ◽  
Training Data ◽  
Cloud Platform ◽  
Model Accuracy ◽  
Training Time ◽  
Physical Systems ◽  
The Internet Of Things ◽  
And Training

During the last decade, the Internet of Things acted as catalyst for the big data phenomenon. As result, modern edge devices can access a huge amount of data that can be exploited to build useful services. In such a context, artificial intelligence has a key role to develop intelligent systems (e.g., intelligent cyber physical systems) that create a connecting bridge with the physical world. However, as time goes by, machine and deep learning applications are becoming more complex, requiring increasing amounts of data and training time, which makes the use of centralized approaches unsuitable. Federated learning is an emerging paradigm which enables the cooperation of edge devices to learn a shared model (while keeping private their training data), thereby abating the training time. Although federated learning is a promising technique, its implementation is difficult and brings a lot of challenges. In this paper, we present an extension of Stack4Things, a cloud platform developed in our department; leveraging its functionalities, we enabled the deployment of federated learning on edge devices without caring their heterogeneity. Experimental results show a comparison with a centralized approach and demonstrate the effectiveness of the proposed approach in terms of both training time and model accuracy.

scholarly journals Design of IoT-based Cyber–Physical Systems: A Driverless Bulldozer Prototype

Information ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 343 ◽  
Author(s):  
Nelson H. Carreras Guzman ◽  
Adam Gergo Mezovari
Keyword(s):  
Autonomous Vehicles ◽  
Industrial Revolution ◽  
Physical World ◽  
Cyber Physical Systems ◽  
Transportation Systems ◽  
Small Scale ◽  
Security Risk ◽  
Physical Systems ◽  
Wireless Communication Network ◽  
Enhance Efficiency

From autonomous vehicles to robotics and machinery, organizations are developing autonomous transportation systems in various domains. Strategic incentives point towards a fourth industrial revolution of cyber–physical systems with higher levels of automation and connectivity throughout the Internet of Things (IoT) that interact with the physical world. In the construction and mining sectors, these developments are still at their infancy, and practitioners are interested in autonomous solutions to enhance efficiency and reliability. This paper illustrates the enhanced design of a driverless bulldozer prototype using IoT-based solutions for the remote control and navigation tracking of the mobile machinery. We illustrate the integration of a cloud application, communication protocols and a wireless communication network to control a small-scale bulldozer from a remote workstation. Furthermore, we explain a new tracking functionality of work completion using maps and georeferenced indicators available via a user interface. Finally, we provide a preliminary safety and security risk assessment of the system prototype and propose guidance for application in real-scale machinery.

scholarly journals Hardware-in-the-loop test based non-intrusive diagnostics of cyber-physical systems using microcontroller debug ports

ACTA IMEKO ◽  
2018 ◽  
Vol 7 (1) ◽  
pp. 27
Author(s):  
Balázs Scherer
Keyword(s):  
Measurement Method ◽  
Internal State ◽  
Physical World ◽  
Cyber Physical Systems ◽  
Hardware In The Loop ◽  
Access Port ◽  
Physical Systems ◽  
Testing Phase ◽  
Software Interface ◽  
Novel Approach

<p class="Abstract"><span lang="EN-US">Cyber-physical systems have extensive contact with the physical world. Usually during the development of these systems, the testing phase cannot be done efficiently or safely in the complete real environment, and therefore HIL (Hardware In the Loop) simulators are used. During HIL testing, diagnostic protocols are used very often to gather detailed information about the DUT’s (Device Under Test) internal state. Diagnostic protocols are very useful during testing, but they cause a significant load to the DUT. This paper introduces a novel approach to replace traditional diagnostic protocols with a non-intrusive solution. The presented method is based on the debug capabilities of modern ARM Cortex M core microcontroller, and uses a CMSIS-DAP (Cortex Microcontroller Software Interface Standard Debug - Access Port) based interface. This paper also introduces a solution to integrate this non-intrusive measurement method to NI LabVIEW based test environments and NI VeriStand based HIL simulations. </span></p>

Simulating Timing Behaviors for Cyber-Physical Systems Using Modelica

2019 ◽  
Vol 11 (3) ◽  
pp. 44-67
Author(s):  
Hao Zhou ◽  
Mengyao Zhao ◽  
Linbo Wu ◽  
Xiaohong Chen
Keyword(s):  
Time Dependence ◽  
Automatic Generation ◽  
Physical World ◽  
Cyber Physical Systems ◽  
Timing Constraints ◽  
Sequence Diagrams ◽  
Sensors And Actuators ◽  
Physical Systems ◽  
Parachute System ◽  
Simulation Parameter

Cyber-physical systems (CPSs) connect the cyber world with the physical world through a network of interrelated elements, such as sensors and actuators, robots, and other computing devices. Timing constraints on the interactions (timing behaviors) should be modelled and verified as cyber-physical systems are becoming more and more complex. This article proposes modeling the typical timing behaviors according to their time characteristics, periodicity, multiform time, and synchronization, and verifies them against properties using simulations. Sequence diagrams are presented for the modeling, and modelica is used for simulation. In the simulation, the time dependence relations are defined, and used for simulation parameter data automatic generation, in addition to the paths from the sequence diagrams. Finally, a Parachute System is used as an example to show the feasibility and effectiveness of the approach.

Sign in / Sign up

Export Citation Format

Share Document