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Cyber-Physical Systems - from Perception to Action

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Fault Diagnosis & Sensors".

Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 17876

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Special Issue Editors

Prof. Ioan Dumitrache

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Guest Editor

Department of Automation and Industrial Informatics, Romanian Academy and University Politehnica of Bucharest, Bucharest, Romania
Interests: cyber-physical systems; complex systems; human perception; advanced control strategies; intelligent; mobile and autonomous robots; bio-engineering; bio-informatics; sensing systems; sensor networks

Prof. Simona Iuliana Caramihai

E-Mail Website
Guest Editor

Department of Automation and Industrial Informatics, University Politehnica of Bucharest, Bucharest, Romania
Interests: cyber-physical systems; complex systems; human perception; advanced control strategies; intelligent; mobile and autonomous robots; bio-engineering; bio-informatics; discrete event dynamical systems; sensing systems; sensor networks

Dr. Ioan Stefan Sacala

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Guest Editor

Department of Automatic Control and Systems Engineering, Faculty of Automatic Control and Computers, University Politehnica of Bucharest, Bucharest, Romania
Interests: cyber-physical systems; sensing systems; wireless sensor networks
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The capacity to make intelligent decisions is critically dependent on the ability to recognize and interpret relevant information. Large networks of sensors are able to provide important quantities of reliable data, but it is important to find a way to qualitatively interpret them in order to allow the most efficient approach for problem solving. Although cyber-physical systems have been widely used in order to define and model large scale systems, there is an increasing interest in integrating cognitive technologies. Perception is a key element for problem solving approaches in various cyber-physical systems, representing the ability to capture, process, and actively make sense of the environmental information in order to interpret environment with the stimuli received throughout sensorial devices.

This Special Issue encourages authors from all research areas to submit their research results concerning concepts and applications of cyber-physical systems. The Special Issue topics include, but are not limited to:

Intelligent and cognitive manufacturing
Cognitive systems and control
Cyber-physical systems
Fault-tolerant control
Biologically inspired systems
Human perception
Deep learning in control
Intelligent transportation systems
Network controlled systems
Predictive maintenance systems
Predictive control
Smart cities
Smart grids
System identification
Sensor fusion
Novel technologies
New applications
State-of-the-art devices

Prof. Ioan Dumitrache
Prof. Simona Iuliana Caramihai
Dr. Ioan Stefan Sacala
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (7 papers)

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Research

25 pages, 2205 KiB

Open AccessArticle

Community- and Data-Driven Services for Multi-Policy Pedestrian Routing

by Ioan Damian, Anca Daniela Ionita and Silvia Oana Anton

Sensors 2022, 22(12), 4515; https://doi.org/10.3390/s22124515 - 15 Jun 2022

Cited by 5 | Viewed by 1690

Abstract

Pedestrian routing is important in a multitude of public spaces, especially those characterized by a large number of newcomers. Their needs may be diverse, with priority for the shortest path, the less crowded or the less polluted one, the accessibility for reduced mobility, or the sheltering from unfavorable weather conditions. Hence, typical graph-based routing must be enriched to support multiple policies, at the choice of each person. The paper proposes a systemic approach and a set of services for orientation and accessibility, which are both community-driven and data-driven, for correctly perceiving the routing necessities and the surrounding situation. The response time to a pathfinding query depends on the types of policies applied and not only on their number, because each of them contributes to the customization of the weighted graph, although it refers to the same physical space traversed by pedestrians. The paper also presents results of loading tests for up to 5000 Virtual Users, inspired from real-life requirements and executed on a graph that models a real building in our university; different policies are applied to assess performance metrics, with simulated community feedback and sensor data. Full article

(This article belongs to the Special Issue Cyber-Physical Systems - from Perception to Action)

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24 pages, 18186 KiB

Open AccessArticle

Anomaly Detection with Feature Extraction Based on Machine Learning Using Hydraulic System IoT Sensor Data

by Doyun Kim and Tae-Young Heo

Sensors 2022, 22(7), 2479; https://doi.org/10.3390/s22072479 - 23 Mar 2022

Cited by 15 | Viewed by 3612

Abstract

Hydraulic systems are advanced in function and level as they are used in various industrial fields. Furthermore, condition monitoring using internet of things (IoT) sensors is applied for system maintenance and management. In this study, meaningful features were identified through extraction and selection of various features, and classification evaluation metrics were presented through machine learning and deep learning to expand the diagnosis of abnormalities and defects in each component of the hydraulic system. Data collected from IoT sensor data in the time domain were divided into clusters in predefined sections. The shape and density characteristics were extracted by cluster. Among 2335 newly extracted features, related features were selected using correlation coefficients and the Boruta algorithm for each hydraulic component and used for model learning. Linear discriminant analysis (LDA), logistic regression, support vector classifier (SVC), decision tree, random forest, XGBoost, LightGBM, and multi-layer perceptron were used to calculate the true positive rate (TPR) and true negative rate (TNR) for each hydraulic component to detect normal and abnormal conditions. Valve condition, internal pump leakage, and hydraulic accumulator data showed TPR performance of 0.94 or more and a TNR performance of 0.84 or more. This study’s findings can help to determine the stable and unstable states of each component of the hydraulic system and form the basis for engineers’ judgment. Full article

(This article belongs to the Special Issue Cyber-Physical Systems - from Perception to Action)

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17 pages, 393 KiB

Open AccessArticle

Implementing Replication of Objects in DOORS—The Object-Oriented Runtime System for Edge Computing

by Dorin Palanciuc and Florin Pop

Sensors 2021, 21(23), 7883; https://doi.org/10.3390/s21237883 - 26 Nov 2021

Cited by 1 | Viewed by 1427

Abstract

Aiming for simplicity and efficiency in the domain of edge computing, DOORS is a distributed system expected to scale up to hundreds of nodes, which encapsulates application state and behavior into objects and gives them the ability to exchange asynchronous messages. DOORS offers semi-synchronous replication and the ability to explicitly move objects from one node to another, as methods to achieve scalability and resilience. The present paper gives an outline of the system structure, describes how DOORS implements object replication, and describes a basic set of measurements, yielding an initial set of conclusions for the improvements of the design. Full article

(This article belongs to the Special Issue Cyber-Physical Systems - from Perception to Action)

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25 pages, 4977 KiB

Open AccessArticle

Fostering Cyber-Physical Social Systems through an Ontological Approach to Personality Classification Based on Social Media Posts

by Alexandra Cernian, Nicoleta Vasile and Ioan Stefan Sacala

Sensors 2021, 21(19), 6611; https://doi.org/10.3390/s21196611 - 04 Oct 2021

Cited by 4 | Viewed by 2574

Abstract

The exponential increase in social networks has led to emergent convergence of cyber-physical systems (CPS) and social computing, accelerating the creation of smart communities and smart organizations and enabling the concept of cyber-physical social systems. Social media platforms have made a significant contribution to what we call human behavior modeling. This paper presents a novel approach to developing a users’ segmentation tool for the Romanian language, based on the four DISC personality types, based on social media statement analysis. We propose and design the ontological modeling approach of the specific vocabulary for each personality and its mapping with text from posts on social networks. This research proposal adds significant value both in terms of scientific and technological contributions (by developing semantic technologies and tools), as well as in terms of business, social and economic impact (by supporting the investigation of smart communities in the context of cyber-physical social systems). For the validation of the model developed we used a dataset of almost 2000 posts retrieved from 10 social medial accounts (Facebook and Twitter) and we have obtained an accuracy of over 90% in identifying the personality profile of the users. Full article

(This article belongs to the Special Issue Cyber-Physical Systems - from Perception to Action)

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20 pages, 2391 KiB

Open AccessArticle

A Combined Model and Data-Driven Approach for the Determination of Rotor Temperature in an Induction Machine

by Razvan Mocanu, Alexandru Onea and Constantin Catalin Dosoftei

Sensors 2021, 21(13), 4512; https://doi.org/10.3390/s21134512 - 30 Jun 2021

Cited by 1 | Viewed by 1839

Abstract

The need for protection of electrical machines comes as a demand of safety regulations in the automotive industry as well as a result of the general desire to obtain a robust and reliable electric powertrain. This paper introduces a hybrid method for estimating the temperature of the rotor of an Induction Machine (IM) based on a Nonlinear Autoregressive Network with Exogenous inputs (NARX) used as a prediction function within a particle filter. The temperature of the stator case is measured, and the information is used as an input to a NARX network and as a variable to a thermal process with first-order dynamics which serves as an observation function. Uncertainties of the NARX and thermal model are determined and used to correct the posterior estimate. Experimental data are used from a real IM test-bench and the results prove the applicability and good performance. Full article

(This article belongs to the Special Issue Cyber-Physical Systems - from Perception to Action)

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16 pages, 1001 KiB

Open AccessArticle

A Coalitional Distributed Model Predictive Control Perspective for a Cyber-Physical Multi-Agent Application

by Anca Maxim and Constantin-Florin Caruntu

Sensors 2021, 21(12), 4041; https://doi.org/10.3390/s21124041 - 11 Jun 2021

Cited by 7 | Viewed by 1767

Abstract

Following the current technological development and informational advancement, more and more physical systems have become interconnected and linked via communication networks. The objective of this work is the development of a Coalitional Distributed Model Predictive Control (C- DMPC) strategy suitable for controlling cyber-physical, multi-agent systems. The motivation behind this endeavour is to design a novel algorithm with a flexible control architecture by combining the advantages of classical DMPC with Coalitional MPC. The simulation results were achieved using a test scenario composed of four dynamically coupled sub-systems, connected through an unidirectional communication topology. The obtained results illustrate that, when the feasibility of the local optimization problem is lost, forming a coalition between neighbouring agents solves this shortcoming and maintains the functionality of the entire system. These findings successfully prove the efficiency and performance of the proposed coalitional DMPC method. Full article

(This article belongs to the Special Issue Cyber-Physical Systems - from Perception to Action)

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16 pages, 681 KiB

Open AccessArticle

Multivariable Optimisation for Waiting-Time Minimisation at Roundabout Intersections in a Cyber-Physical Framework

by Ovidiu Pauca, Anca Maxim and Constantin-Florin Caruntu

Sensors 2021, 21(12), 3968; https://doi.org/10.3390/s21123968 - 09 Jun 2021

Cited by 1 | Viewed by 2548

Abstract

The evolution of communication networks offers new possibilities for development in the automotive industry. Smart vehicles will benefit from the possibility of connecting with the infrastructure and from an extensive exchange of data between them. Furthermore, new control strategies can be developed that benefit the advantages of these communication networks. In this endeavour, the main purposes considered by the automotive industry and researchers from academia are defined by: (i) ensuring people’s safety; (ii) reducing the overall costs, and (iii) improving the traffic by maximising the fluidity. In this paper, a cyber-physical framework (CPF) to control the access of vehicles in roundabout intersections composed of two levels is proposed. Both levels correspond to the cyber part of the CPF, while the physical part is composed of the vehicles crossing the roundabout. The first level, i.e., the edge-computing layer, is based on an analytical solution that uses multivariable optimisation to minimise the waiting times of the vehicles entering a roundabout intersection and to ensure a safe crossing. The second level, i.e., the cloud-computing layer, stores information about the waiting times and trajectories of all the vehicles that cross the roundabout and uses them for long-term analysis and prediction. The simulated results show the efficacy of the proposed method, which can be easily implemented on an embedded device for real-time operation. Full article

(This article belongs to the Special Issue Cyber-Physical Systems - from Perception to Action)

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