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Special Issue "Real-Time Sensor Networks and Systems for the Industrial IoT"

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

Deadline for manuscript submissions: closed (31 January 2020).

Special Issue Editors

Dr. Christos Koulamas
Website
Guest Editor
Industrial Systems Institute / “Athena” Research Center, PSP Bldg, Stadiou Strt, 26504, Patras, Greece
Interests: real-time distributed embedded systems; wired/wireless industrial networks; Industrial IoT; WSN/ RFID systems
Special Issues and Collections in MDPI journals
Dr. Mihai T. Lazarescu
Website
Guest Editor
Department of Electronics and Telecommunications, Politecnico di Torino, 24, 10129 Torino TO, Italy
Interests: reusable WSN/IoT platforms; sensing, indoor localization, and data processing for IoT; design for low power; embedded machine learning and neural networks; high-level HW/SW co-design; high-level synthesis
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Real-time embedded systems are quickly achieving ubiquity, both in people’s everyday life and in industrial environments. While many processes already depend on real-time cyber-physical systems and embedded sensors, IoT integration with cognitive computing and real-time data exchanges is essential for real-time analytics and realizations of digital twins in smart environments and services under the Industrial Internet and Industry 4.0 frameworks’ provisions. IoT-enabled industrial sensor networks encompass multiple technologies and raise significant design, optimization, integration and exploitation challenges.

This Special Issue aims to receive contributions on advances of real-time sensor networks and systems that are significant enablers of the Industrial IoT paradigm. The topics of interest include (but are not limited to):

  • Real-time sensing interfaces, processing, specific operating system support
  • Real-time sensor and sensing techniques and technologies
  • Real-time communication for sensing and sensor-driven actuation
  • Middleware and tools for complex real-time sensing and actuation systems
  • Reference architectures, frameworks and performance evaluations for edge and fog computing in real-time IIoT
  • Formal methods, modelling, simulation and development tools for real-time sensor networks
  • Real-time sensor network support for digital twins and edge-based analytics
  • Security for real-time systems: low-overhead, efficient bootstrapping and session establishment, resilience to side-channel attacks, etc.
  • Real-time low-power and low-cost sensing
  • Energy supplies suitable for low maintenance, high availability real-time sensing
  • Real-time sensing for safety systems
  • Applications and use-cases of IoT-enabled, smart, real-time sensor networks and systems in manufacturing, transportation, health and energy sectors.

Dr. Christos Koulamas
Dr. Mihai T. Lazarescu
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

  • Industrial IoT
  • Real-Time Embedded Systems
  • Sensor & Actuator Networks
  • Industrial Internet & Industry 4.0
  • Edge & Fog Computing
  • Real-Time Analytics
  • Real-Time Digital Twins

Published Papers (10 papers)

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Research

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Open AccessArticle
Anomaly Detection Trusted Hardware Sensors for Critical Infrastructure Legacy Devices
Sensors 2020, 20(11), 3092; https://doi.org/10.3390/s20113092 - 30 May 2020
Abstract
Critical infrastructures and associated real time Informational systems need some security protection mechanisms that will be able to detect and respond to possible attacks. For this reason, Anomaly Detection Systems (ADS), as part of a Security Information and Event Management (SIEM) system, are [...] Read more.
Critical infrastructures and associated real time Informational systems need some security protection mechanisms that will be able to detect and respond to possible attacks. For this reason, Anomaly Detection Systems (ADS), as part of a Security Information and Event Management (SIEM) system, are needed for constantly monitoring and identifying potential threats inside an Information Technology (IT) system. Typically, ADS collect information from various sources within a CI system using security sensors or agents and correlate that information so as to identify anomaly events. Such sensors though in a CI setting (factories, power plants, remote locations) may be placed in open areas and left unattended, thus becoming targets themselves of security attacks. They can be tampering and malicious manipulated so that they provide false data that may lead an ADS or SIEM system to falsely comprehend the CI current security status. In this paper, we describe existing approaches on security monitoring in critical infrastructures and focus on how to collect security sensor–agent information in a secure and trusted way. We then introduce the concept of hardware assisted security sensor information collection that improves the level of trust (by hardware means) and also increases the responsiveness of the sensor. Thus, we propose a Hardware Security Token (HST) that when connected to a CI host, it acts as a secure anchor for security agent information collection. We describe the HST functionality, its association with a host device, its expected role and its log monitoring mechanism. We also provide information on how security can be established between the host device and the HST. Then, we introduce and describe the necessary host components that need to be established in order to guarantee a high security level and correct HST functionality. We also provide a realization–implementation of the HST overall concept in a FPGA SoC evaluation board and describe how the HST implementation can be controlled. In addition, in the paper, two case studies where the HST has been used in practice and its functionality have been validated (one case study on a real critical infrastructure test site and another where a critical industrial infrastructure was emulated in our lab) are described. Finally, results taken from these two case studies are presented, showing actual measurements for the in-field HST usage. Full article
(This article belongs to the Special Issue Real-Time Sensor Networks and Systems for the Industrial IoT)
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Open AccessArticle
Deep CNN Sparse Coding for Real Time Inhaler Sounds Classification
Sensors 2020, 20(8), 2363; https://doi.org/10.3390/s20082363 - 21 Apr 2020
Abstract
Effective management of chronic constrictive pulmonary conditions lies in proper and timely administration of medication. As a series of studies indicates, medication adherence can effectively be monitored by successfully identifying actions performed by patients during inhaler usage. This study focuses on the recognition [...] Read more.
Effective management of chronic constrictive pulmonary conditions lies in proper and timely administration of medication. As a series of studies indicates, medication adherence can effectively be monitored by successfully identifying actions performed by patients during inhaler usage. This study focuses on the recognition of inhaler audio events during usage of pressurized metered dose inhalers (pMDI). Aiming at real-time performance, we investigate deep sparse coding techniques including convolutional filter pruning, scalar pruning and vector quantization, for different convolutional neural network (CNN) architectures. The recognition performance has been assessed on three healthy subjects following both within and across subjects modeling strategies. The selected CNN architecture classified drug actuation, inhalation and exhalation events, with 100%, 92.6% and 97.9% accuracy, respectively, when assessed in a leave-one-subject-out cross-validation setting. Moreover, sparse coding of the same architecture with an increasing compression rate from 1 to 7 resulted in only a small decrease in classification accuracy (from 95.7% to 94.5%), obtained by random (subject-agnostic) cross-validation. A more thorough assessment on a larger dataset, including recordings of subjects with multiple respiratory disease manifestations, is still required in order to better evaluate the method’s generalization ability and robustness. Full article
(This article belongs to the Special Issue Real-Time Sensor Networks and Systems for the Industrial IoT)
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Open AccessArticle
Virtualization of Industrial Real-Time Networks for Containerized Controllers
Sensors 2019, 19(20), 4405; https://doi.org/10.3390/s19204405 - 11 Oct 2019
Abstract
The virtualization technology has a great potential to improve the manageability and scalability of industrial control systems, as it can host and consolidate computing resources very efficiently. There accordingly have been efforts to utilize the virtualization technology for industrial control systems, but the [...] Read more.
The virtualization technology has a great potential to improve the manageability and scalability of industrial control systems, as it can host and consolidate computing resources very efficiently. There accordingly have been efforts to utilize the virtualization technology for industrial control systems, but the research for virtualization of traditional industrial real-time networks, such as Controller Area Network (CAN), has been done in a very limited scope. Those traditional fieldbuses have distinguished characteristics from well-studied Ethernet-based networks; thus, it is necessary to study how to support their inherent functions transparently and how to guarantee Quality-of-Service (QoS) in virtualized environments. In this paper, we suggest a lightweight CAN virtualization technology for virtual controllers to tackle both functionality and QoS issues. We particularly target the virtual controllers that are containerized with an operating-system(OS)-based virtualization technology. In the functionality aspect, our virtualization technology provides virtual CAN interfaces and virtual CAN buses at the device driver level. In the QoS perspective, we provide a hierarchical real-time scheduler and a simulator, which enable the adjustment of phase offsets of virtual controllers and tasks. The experiment results show that our CAN virtualization has lower overheads than an existing approach up to 20%. Moreover, we show that the worst-case end-to-end delay could be reduced up to 78.7% by adjusting the phase offsets of virtual controllers and tasks. Full article
(This article belongs to the Special Issue Real-Time Sensor Networks and Systems for the Industrial IoT)
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Open AccessArticle
Efficient Resource Scheduling for Multipath Retransmission over Industrial WSAN Systems
Sensors 2019, 19(18), 3927; https://doi.org/10.3390/s19183927 - 12 Sep 2019
Cited by 1
Abstract
With recent adoption of Wireless Sensor-Actuator Networks (WSANs) in industrial automation, wireless control systems have emerged as a frontier of industrial networks. Hence, it has been shown that existing standards and researches concentrate on the reliability and real-time performance of WSANs. The multipath [...] Read more.
With recent adoption of Wireless Sensor-Actuator Networks (WSANs) in industrial automation, wireless control systems have emerged as a frontier of industrial networks. Hence, it has been shown that existing standards and researches concentrate on the reliability and real-time performance of WSANs. The multipath retransmission scheme with multiple channels is a key approach to guarantee the deterministic wireless communication. However, the efficiency of resource scheduling is seldom considered in applications with diverse data sampling rates. In this paper, we propose an efficient resources scheduling algorithm for multipath retransmission in WSANs. The objective of our algorithm is to improve efficiency and schedulability for the use of slot and channel resources. In detail, the proposed algorithm uses the approaches of CCA (clear channel assessment)-Embedded slot and Multiple sinks with Rate Monotonic scheme (CEM-RM) to decrease the number of collisions. We have simulated and implemented our algorithm in hardware and verified its performance in a real industrial environment. The achieved results show that the proposed algorithm significantly improves the schedulability without trading off reliability and real-time performance. Full article
(This article belongs to the Special Issue Real-Time Sensor Networks and Systems for the Industrial IoT)
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Open AccessArticle
CA-CWA: Channel-Aware Contention Window Adaption in IEEE 802.11ah for Soft Real-Time Industrial Applications
Sensors 2019, 19(13), 3002; https://doi.org/10.3390/s19133002 - 08 Jul 2019
Abstract
In 2016, the IEEE task group ah (TGah) released a new standard called IEEE 802.11ah, and industrial Internet of Things (IoT) is one of its typical use cases. The restricted access window (RAW) is one of the core MAC mechanisms of IEEE 802.11ah, [...] Read more.
In 2016, the IEEE task group ah (TGah) released a new standard called IEEE 802.11ah, and industrial Internet of Things (IoT) is one of its typical use cases. The restricted access window (RAW) is one of the core MAC mechanisms of IEEE 802.11ah, which aims to address the collision problem in the dense wireless networks. However, in each RAW period, stations still need to contend for the channel by Distributed Coordination Function and Enhanced Distributed Channel Access (DCF/EDCA), which cannot meet the real-time requirements of most industrial applications. In this paper, we propose a channel-aware contention window adaption (CA-CWA) algorithm. The algorithm dynamically adapts the contention window based on the channel status with an external interference discrimination ability, and improves the real-time performance of the IEEE 802.11ah. To validate the real-time performance of CA-CWA, we compared CA-CWA with two other backoff algorithms with an NS-3 simulator. The results illustrate that CA-CWA has better performance than the other two algorithms in terms of packet loss rate and average delay. Compared with the other two algorithms, CA-CWA is able to support industrial applications with higher deadline constraints under the same channel conditions in IEEE 802.11ah. Full article
(This article belongs to the Special Issue Real-Time Sensor Networks and Systems for the Industrial IoT)
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Open AccessArticle
A Design Approach to IoT Endpoint Security for Production Machinery Monitoring
Sensors 2019, 19(10), 2355; https://doi.org/10.3390/s19102355 - 22 May 2019
Cited by 1
Abstract
The Internet of Things (IoT) has significant potential in upgrading legacy production machinery with monitoring capabilities to unlock new capabilities and bring economic benefits. However, the introduction of IoT at the shop floor layer exposes it to additional security risks with potentially significant [...] Read more.
The Internet of Things (IoT) has significant potential in upgrading legacy production machinery with monitoring capabilities to unlock new capabilities and bring economic benefits. However, the introduction of IoT at the shop floor layer exposes it to additional security risks with potentially significant adverse operational impact. This article addresses such fundamental new risks at their root by introducing a novel endpoint security-by-design approach. The approach is implemented on a widely applicable production-machinery-monitoring application by introducing real-time adaptation features for IoT device security through subsystem isolation and a dedicated lightweight authentication protocol. This paper establishes a novel viewpoint for the understanding of IoT endpoint security risks and relevant mitigation strategies and opens a new space of risk-averse designs that enable IoT benefits, while shielding operational integrity in industrial environments. Full article
(This article belongs to the Special Issue Real-Time Sensor Networks and Systems for the Industrial IoT)
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Open AccessArticle
Transmission Scheduling Schemes of Industrial Wireless Sensors for Heterogeneous Multiple Control Systems
Sensors 2018, 18(12), 4284; https://doi.org/10.3390/s18124284 - 05 Dec 2018
Cited by 2
Abstract
The transmission scheduling scheme of wireless networks for industrial control systems is a crucial design component since it directly affects the stability of networked control systems. In this paper, we propose a novel transmission scheduling framework to guarantee the stability of heterogeneous multiple [...] Read more.
The transmission scheduling scheme of wireless networks for industrial control systems is a crucial design component since it directly affects the stability of networked control systems. In this paper, we propose a novel transmission scheduling framework to guarantee the stability of heterogeneous multiple control systems over unreliable wireless channels. Based on the explicit control stability conditions, a constrained optimization problem is proposed to maximize the minimum slack of the stability constraint for the heterogeneous control systems. We propose three transmission scheduling schemes, namely centralized stationary random access, distributed random access, and Lyapunov-based scheduling scheme, to solve the constrained optimization problem with a low computation cost. The three proposed transmission scheduling schemes were evaluated on heterogeneous multiple control systems with different link conditions. One interesting finding is that the proposed centralized Lyapunov-based approach provides almost ideal performance in the context of control stability. Furthermore, the distributed random access is still useful for the small number of links since it also reduces the operational overhead without significantly sacrificing the control performance. Full article
(This article belongs to the Special Issue Real-Time Sensor Networks and Systems for the Industrial IoT)
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Open AccessArticle
A New Method of Priority Assignment for Real-Time Flows in the WirelessHART Network by the TDMA Protocol
Sensors 2018, 18(12), 4242; https://doi.org/10.3390/s18124242 - 03 Dec 2018
Abstract
WirelessHART is a wireless sensor network that is widely used in real-time demand analyses. A key challenge faced by WirelessHART is to ensure the character of real-time data transmission in the network. Identifying a priority assignment strategy that reduces the delay in flow [...] Read more.
WirelessHART is a wireless sensor network that is widely used in real-time demand analyses. A key challenge faced by WirelessHART is to ensure the character of real-time data transmission in the network. Identifying a priority assignment strategy that reduces the delay in flow transmission is crucial in ensuring real-time network performance and the schedulability of real-time network flows. We study the priority assignment of real-time flows in WirelessHART on the basis of the multi-channel time division multiple access (TDMA) protocol to reduce the delay and improve the ratio of scheduled. We provide three kinds of methods: (1) worst fit, (2) best fit, and (3) first fit and choose the most suitable one, namely the worst-fit method for allocating flows to each channel. More importantly, we propose two heuristic algorithms—a priority assignment algorithm based on the greedy strategy for C (WF-C) and a priority assignment algorithm based on the greedy strategy for U(WF-U)—for assigning priorities to the flows in each channel, whose time complexity is O ( m a x ( N m l o g ( m ) , ( N m ) 2 ) ) . We then build a new simulation model to simulate the transmission of real-time flows in WirelessHART. Finally, we compare our two algorithms with WF-D and HLS algorithms in terms of the average value of the total end-to-end delay of flow sets, the ratio of schedulable flow sets, and the calculation time of the schedulability analysis. The optimal algorithm WF-C reduces the delay by up to 44.18 % and increases the schedulability ratio by up to 70.7 % , and it reduces the calculation time compared with the HLS algorithm. Full article
(This article belongs to the Special Issue Real-Time Sensor Networks and Systems for the Industrial IoT)
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Open AccessArticle
Protection of Superconducting Industrial Machinery Using RNN-Based Anomaly Detection for Implementation in Smart Sensor
Sensors 2018, 18(11), 3933; https://doi.org/10.3390/s18113933 - 14 Nov 2018
Cited by 3
Abstract
Sensing the voltage developed over a superconducting object is very important in order to make superconducting installation safe. An increase in the resistive part of this voltage (quench) can lead to significant deterioration or even to the destruction of the superconducting device. Therefore, [...] Read more.
Sensing the voltage developed over a superconducting object is very important in order to make superconducting installation safe. An increase in the resistive part of this voltage (quench) can lead to significant deterioration or even to the destruction of the superconducting device. Therefore, detection of anomalies in time series of this voltage is mandatory for reliable operation of superconducting machines. The largest superconducting installation in the world is the main subsystem of the Large Hadron Collider (LHC) accelerator. Therefore a protection system was built around superconducting magnets. Currently, the solutions used in protection equipment at the LHC are based on a set of hand-crafted custom rules. They were proved to work effectively in a range of applications such as quench detection. However, these approaches lack scalability and require laborious manual adjustment of working parameters. The presented work explores the possibility of using the embedded Recurrent Neural Network as a part of a protection device. Such an approach can scale with the number of devices and signals in the system, and potentially can be automatically configured to given superconducting magnet working conditions and available data. In the course of the experiments, it was shown that the model using Gated Recurrent Units (GRU) comprising of two layers with 64 and 32 cells achieves 0.93 accuracy for anomaly/non-anomaly classification, when employing custom data compression scheme. Furthermore, the compression of proposed module was tested, and showed that the memory footprint can be reduced four times with almost no performance loss, making it suitable for hardware implementation. Full article
(This article belongs to the Special Issue Real-Time Sensor Networks and Systems for the Industrial IoT)
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Review

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Open AccessReview
Survey on Wireless Technology Trade-Offs for the Industrial Internet of Things
Sensors 2020, 20(2), 488; https://doi.org/10.3390/s20020488 - 15 Jan 2020
Cited by 3
Abstract
Aside from vast deployment cost reduction, Industrial Wireless Sensor and Actuator Networks (IWSAN) introduce a new level of industrial connectivity. Wireless connection of sensors and actuators in industrial environments not only enables wireless monitoring and actuation, it also enables coordination of production stages, [...] Read more.
Aside from vast deployment cost reduction, Industrial Wireless Sensor and Actuator Networks (IWSAN) introduce a new level of industrial connectivity. Wireless connection of sensors and actuators in industrial environments not only enables wireless monitoring and actuation, it also enables coordination of production stages, connecting mobile robots and autonomous transport vehicles, as well as localization and tracking of assets. All these opportunities already inspired the development of many wireless technologies in an effort to fully enable Industry 4.0. However, different technologies significantly differ in performance and capabilities, none being capable of supporting all industrial use cases. When designing a network solution, one must be aware of the capabilities and the trade-offs that prospective technologies have. This paper evaluates the technologies potentially suitable for IWSAN solutions covering an entire industrial site with limited infrastructure cost and discusses their trade-offs in an effort to provide information for choosing the most suitable technology for the use case of interest. The comparative discussion presented in this paper aims to enable engineers to choose the most suitable wireless technology for their specific IWSAN deployment. Full article
(This article belongs to the Special Issue Real-Time Sensor Networks and Systems for the Industrial IoT)
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