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Special Issue "New Technologies and Applications for Smart Interactive Cyber-Physical Systems"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Networks".

Deadline for manuscript submissions: 30 June 2020.

Special Issue Editors

Prof. Dr. Youn-Hee Han
Website
Guest Editor
School of Computer Science and Engineering, Korea University of Technology and Education, Chungnam, Korea
Interests: sensor and actuator networks; mobile sensor networks; intelligent IoT and CPS systems; social network analysis
Dr. Jin Ryong Kim
Website
Guest Editor
Alibaba NHCI Laboratory, CA, USA
Interests: human–computer interaction; haptics; virtual reality; wearable computing
Dr. Hyon-Young Choi
Website
Guest Editor
PRECISE Center, School of Engineering and Applied Science, University of Pennsylvania, PA, USA
Interests: software defined networks; network function virtualization; quality of service; mobility support in heterogeneous networks
Prof. Dr. Jong-Hyouk Lee
Website
Guest Editor
Department of Software, Sangmyung University, Cheonan, Korea
Interests: security; authentication; privacy; protocol analysis; blockchain; mobility management
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

The recent technology convergence of sensor devices, networks, and communications has been creating new demands and opportunities for cyberphysical systems and their applications. In particular, the growing number of the heterogeneous sensor and actuator devices and the demanding networking systems of wired/wireless communications in cyberphysical systems have imposed several challenges in both traditional and new research issues. Moreover, human and nonhuman systems interact consistently and allow each to achieve a set of nontrivial technical goals. This Special Issue aims to gather recent advanced technologies and applications that address network protocol design, low latency networking, context-aware interaction, energy efficiency, resource management, security, human–robot interaction, assistive technology and robots, application development, and integration of multiple systems that support cyberphysical systems and smart interaction. Please note that only high-quality, original research papers that cover key issues and topics of smart interactive cyberphysical systems will be accepted for publication. Accordingly, this Special Issue will bring together the industry and academic people and highlight correct current and future directions in the areas.

Prof. Dr. Youn-Hee Han
Dr. Jin Ryong Kim
Dr. Hyon-Young Choi
Prof. Dr. Jong-Hyouk Lee
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 papers will be 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 2000 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.

Keywords

  • Cyberphysical systems for human-centric applications
  • Context management for interaction in cyberphysical systems
  • Sensors management for interaction advanced (mobile) ubiquitous applications
  • Sensor applications and middleware support
  • Reasoning and learning techniques for interaction in smart spaces
  • low latency and real-time communication
  • Energy efficiency
  • Sensors and wireless sensor networks for the Internet of Things
  • Distributed sensing, actuation, control, and coordination
  • Network resilience, fault-tolerance, and reliability
  • Privacy, security and trust management
  • Resource management
  • Functional computation and data aggregation
  • Distributed algorithms and network optimization
  • Prototypes, testbeds, and real-world cyberphysical system

Published Papers (8 papers)

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Research

Open AccessArticle
A Methodology for Network Analysis to Improve the Cyber-Physicals Communications in Next-Generation Networks
Sensors 2020, 20(8), 2247; https://doi.org/10.3390/s20082247 - 16 Apr 2020
Abstract
Cyber-physical systems allow creating new applications and services which will bring people, data, processes, and things together. The network is the backbone that interconnects this new paradigm, especially 5G networks that will expand the coverage, reduce the latency, and enhance the data rate. [...] Read more.
Cyber-physical systems allow creating new applications and services which will bring people, data, processes, and things together. The network is the backbone that interconnects this new paradigm, especially 5G networks that will expand the coverage, reduce the latency, and enhance the data rate. In this sense, network analytics will increase the knowledge about the network and its interconnected devices, being a key feature especially with the increment in the number of physical things (sensors, actuators, smartphones, tablets, and so on). With this increment, the usage of online networking services and applications will grow, and network operators require to detect and analyze all issues related to the network. In this article, a methodology to analyze real network information provided by a network operator and acquire knowledge of the communications is presented. Various real data sets, provided by Telecom Italia, are analyzed to compare two different zones: one located in the urban area of Milan, Italy, and its surroundings, and the second in the province of Trento, Italy. These data sets describe different areas and shapes that cover a metropolitan area in the first case and a mainly rural area in the second case, which implies that these areas will have different comportments. To compare these comportments and group them in a single cluster set, a new technique is presented in this paper to establish a relationship between them and reduce those that could be similar. Full article
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Open AccessArticle
An Efficient, Anonymous and Robust Authentication Scheme for Smart Home Environments
Sensors 2020, 20(4), 1215; https://doi.org/10.3390/s20041215 - 22 Feb 2020
Abstract
In recent years, the Internet of Things (IoT) has exploded in popularity. The smart home, as an important facet of IoT, has gained its focus for smart intelligent systems. As users communicate with smart devices over an insecure communication medium, the sensitive information [...] Read more.
In recent years, the Internet of Things (IoT) has exploded in popularity. The smart home, as an important facet of IoT, has gained its focus for smart intelligent systems. As users communicate with smart devices over an insecure communication medium, the sensitive information exchanged among them becomes vulnerable to an adversary. Thus, there is a great thrust in developing an anonymous authentication scheme to provide secure communication for smart home environments. Most recently, an anonymous authentication scheme for smart home environments with provable security has been proposed in the literature. In this paper, we analyze the recent scheme to highlight its several vulnerabilities. We then address the security drawbacks and present a more secure and robust authentication scheme that overcomes the drawbacks found in the analyzed scheme, while incorporating its advantages too. Finally, through a detailed comparative study, we demonstrate that the proposed scheme provides significantly better security and more functionality features with comparable communication and computational overheads with similar schemes. Full article
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Open AccessArticle
Study of Human Thermal Comfort for Cyber–Physical Human Centric System in Smart Homes
Sensors 2020, 20(2), 372; https://doi.org/10.3390/s20020372 - 09 Jan 2020
Cited by 1
Abstract
An environmental thermal comfort model has previously been quantified based on the predicted mean vote (PMV) and the physical sensors parameters, such as temperature, relative humidity, and air speed in the indoor environment. However, first, the relationship between environmental factors and physiology parameters [...] Read more.
An environmental thermal comfort model has previously been quantified based on the predicted mean vote (PMV) and the physical sensors parameters, such as temperature, relative humidity, and air speed in the indoor environment. However, first, the relationship between environmental factors and physiology parameters of the model is not well investigated in the smart home domain. Second, the model that is not mainly for an individual human model leads to the failure of the thermal comfort system to fulfill the human’s comfort preference. In this paper, a cyber–physical human centric system (CPHCS) framework is proposed to take advantage of individual human thermal comfort to improve the human’s thermal comfort level while optimizing the energy consumption at the same time. Besides that, the physiology parameter from the heart rate is well-studied, and its correlation with the environmental factors, i.e., PMV, air speed, temperature, and relative humidity are deeply investigated to reveal the human thermal comfort level of the existing energy efficient thermal comfort control (EETCC) system in the smart home environment. Experimental results reveal that there is a tight correlation between the environmental factors and the physiology parameter (i.e., heart rate) in the aspect of system operational and human perception. Furthermore, this paper also concludes that the current EETCC system is unable to provide the precise need for thermal comfort to the human’s preference. Full article
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Open AccessArticle
F-DCS: FMI-Based Distributed CPS Simulation Framework with a Redundancy Reduction Algorithm
Sensors 2020, 20(1), 252; https://doi.org/10.3390/s20010252 - 01 Jan 2020
Abstract
A cyber physical system (CPS) is a distributed control system in which the cyber part and physical part are tightly interconnected. A representative CPS is an electric vehicle (EV) composed of a complex system and information and communication technology (ICT), preliminary verified through [...] Read more.
A cyber physical system (CPS) is a distributed control system in which the cyber part and physical part are tightly interconnected. A representative CPS is an electric vehicle (EV) composed of a complex system and information and communication technology (ICT), preliminary verified through simulations for performance prediction and a quantitative analysis is essential because an EV comprises a complex CPS. This paper proposes an FMI-based distributed CPS simulation framework (F-DCS) adopting a redundancy reduction algorithm (RRA) for the validation of EV simulation. Furthermore, the proposed algorithm was enhanced to ensure an efficient simulation time and accuracy by predicting and reducing repetition patterns involved during the simulation progress through advances in the distributed CPS simulation. The proposed RRA improves the simulation speed and efficiency by avoiding the repeated portions of a given driving cycle while still maintaining accuracy. To evaluate the performance of the proposed F-DCS, an EV model was simulated by adopting the RRA. The results confirm that the F-DCS with RRA efficiently reduced the simulation time (over 30%) while maintaining a conventional accuracy. Furthermore, the proposed F-DCS was applied to the RRA, which provided results reflecting real-time sensor information. Full article
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Open AccessArticle
Transparent Film-Type Vibrotactile Actuator Array and Its Haptic Rendering Using Beat Phenomenon
Sensors 2019, 19(16), 3490; https://doi.org/10.3390/s19163490 - 09 Aug 2019
Abstract
The most important thing in a thin and soft haptic module with an electroactive polymer actuator array is to increase its vibrotactile amplitude and to create a variety of vibrotactile sensations. In this paper, we introduce a thin film-type electroactive polymer actuator array [...] Read more.
The most important thing in a thin and soft haptic module with an electroactive polymer actuator array is to increase its vibrotactile amplitude and to create a variety of vibrotactile sensations. In this paper, we introduce a thin film-type electroactive polymer actuator array capable of stimulating two types of human mechanoreceptors simultaneously, and we present a haptic rendering method that maximizes the actuators’ vibrational force without improving the array’s haptic performance. The increase in vibrational amplitude of the soft electroactive polymer actuator array is achieved by creating a beat vibration, which is an interference pattern of two vibrations with slightly different frequencies. The textures of a target object are translated into haptic stimuli using the proposed method. We conducted qualitative and quantitative experiments to evaluate the performance of the proposed rendering method. The results showed that this method not only amplifies the vibration’s amplitude but also haptically simulates various objects’ surfaces. Full article
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Open AccessArticle
A Novel Deep-Learning-Based Bug Severity Classification Technique Using Convolutional Neural Networks and Random Forest with Boosting
Sensors 2019, 19(13), 2964; https://doi.org/10.3390/s19132964 - 05 Jul 2019
Cited by 4
Abstract
The accurate severity classification of a bug report is an important aspect of bug fixing. The bug reports are submitted into the bug tracking system with high speed, and owing to this, bug repository size has been increasing at an enormous rate. This [...] Read more.
The accurate severity classification of a bug report is an important aspect of bug fixing. The bug reports are submitted into the bug tracking system with high speed, and owing to this, bug repository size has been increasing at an enormous rate. This increased bug repository size introduces biases in the bug triage process. Therefore, it is necessary to classify the severity of a bug report to balance the bug triaging process. Previously, many machine learning models were proposed for automation of bug severity classification. The accuracy of these models is not up to the mark because they do not extract the important feature patterns for learning the classifier. This paper proposes a novel deep learning model for multiclass severity classification called Bug Severity classification to address these challenges by using a Convolutional Neural Network and Random forest with Boosting (BCR). This model directly learns the latent and highly representative features. Initially, the natural language techniques preprocess the bug report text, and then n-gram is used to extract the features. Further, the Convolutional Neural Network extracts the important feature patterns of respective severity classes. Lastly, the random forest with boosting classifies the multiple bug severity classes. The average accuracy of the proposed model is 96.34% on multiclass severity of five open source projects. The average F-measures of the proposed BCR and the existing approach were 96.43% and 84.24%, respectively, on binary class severity classification. The results prove that the proposed BCR approach enhances the performance of bug severity classification over the state-of-the-art techniques. Full article
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Open AccessArticle
Brain Inspired Dynamic System for the Quality of Service Control over the Long-Haul Nonlinear Fiber-Optic Link
Sensors 2019, 19(9), 2175; https://doi.org/10.3390/s19092175 - 10 May 2019
Cited by 3
Abstract
Brain-inspired intelligence using the cognitive dynamic system (CDS) concept is proposed to control the quality-of-service (QoS) over a long-haul fiber-optic link that is nonlinear and with non-Gaussian channel noise. Digital techniques such as digital-back-propagation (DBP) assume that the fiber optic link parameters, such [...] Read more.
Brain-inspired intelligence using the cognitive dynamic system (CDS) concept is proposed to control the quality-of-service (QoS) over a long-haul fiber-optic link that is nonlinear and with non-Gaussian channel noise. Digital techniques such as digital-back-propagation (DBP) assume that the fiber optic link parameters, such as loss, dispersion, and nonlinear coefficients, are known at the receiver. However, the proposed CDS does not need to know about the fiber optic link physical parameters, and it can improve the bit error rate (BER) or enhance the data rate based on information extracted from the fiber optic link. The information extraction (Bayesian statistical modeling) using intelligent perception processing on the received data, or using the previously extracted models in the model library, is carried out to estimate the transmitted data in the receiver. Then, the BER is sent to the executive through the main feedback channel and the executive produces actions on the physical system/signal to ensure that the BER is continuously under the forward-error-correction (FEC) threshold. Therefore, the proposed CDS is an intelligent and adaptive system that can mitigate disturbance in the fiber optic link (especially in an optical network) using prediction in the perceptor and/or doing proper actions in the executive based on BER and the internal reward. A simplified CDS was implemented for nonlinear fiber optic systems based on orthogonal frequency division multiplexing (OFDM) to show how the proposed CDS can bring noticeable improvement in the system’s performance. As a result, enhancement of the data rate by 12.5% and the Q-factor improvement of 2.74 dB were achieved in comparison to the conventional system (i.e., the system without smart brain). Full article
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Open AccessArticle
A Secure, Energy- and SLA-Efficient (SESE) E-Healthcare Framework for Quickest Data Transmission Using Cyber-Physical System
Sensors 2019, 19(9), 2119; https://doi.org/10.3390/s19092119 - 07 May 2019
Cited by 4
Abstract
Due to advances in technology, research in healthcare using a cyber-physical system (CPS) opens innovative dimensions of services. In this paper, the authors propose an energy- and service-level agreement (SLA)-efficient cyber physical system for E-healthcare during data transmission services. Furthermore, the proposed phenomenon [...] Read more.
Due to advances in technology, research in healthcare using a cyber-physical system (CPS) opens innovative dimensions of services. In this paper, the authors propose an energy- and service-level agreement (SLA)-efficient cyber physical system for E-healthcare during data transmission services. Furthermore, the proposed phenomenon will be enhanced to ensure the security by detecting and eliminating the malicious devices/nodes involved during the communication process through advances in the ad hoc on-demand distance vector (AODV) protocol. The proposed framework addresses the two security threats, such as grey and black holes, that severely affect network services. Furthermore, the proposed framework used to find the different network metrics such as average qualifying service set (QSS) paths, mean hop and energy efficiency of the quickest path. The framework is simulated by calculating the above metrics in mutual cases i.e., without the contribution of malevolent nodes and with the contribution of malevolent nodes over service time, hop count and energy constraints. Further, variation of SLA and energy shows their expediency in the selection of efficient network metrics. Full article
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