Journal Description
Journal of Sensor and Actuator Networks
Journal of Sensor and Actuator Networks
is an international, peer-reviewed, open access journal on the science and technology of sensor and actuator networks, published bimonthly online by MDPI.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, ESCI (Web of Science), dblp, Inspec, and other databases.
- Journal Rank: JCR - Q2 (Computer Science, Information Systems) / CiteScore - Q1 (Control and Optimization)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 20.4 days after submission; acceptance to publication is undertaken in 5.7 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
3.3 (2023);
5-Year Impact Factor:
3.2 (2023)
Latest Articles
Distributed Consensus Multi-Distribution Filter for Heavy-Tailed Noise
J. Sens. Actuator Netw. 2024, 13(4), 38; https://doi.org/10.3390/jsan13040038 (registering DOI) - 28 Jun 2024
Abstract
Distributed state estimation is one of the critical technologies in the field of target tracking, where the process noise and measurement noise may have a heavy-tailed distribution. Traditionally, heavy-tailed distributions like the student-t distribution are employed, but our observation reveals that Gaussian noise
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Distributed state estimation is one of the critical technologies in the field of target tracking, where the process noise and measurement noise may have a heavy-tailed distribution. Traditionally, heavy-tailed distributions like the student-t distribution are employed, but our observation reveals that Gaussian noise predominates in many instances, with occasional outliers. This sporadic reliance on heavy-tailed distributions can degrade performances or necessitate frequent parameter adjustments. To overcome this, we introduce a novel distributed consensus multi-distribution state estimation method that combines Gaussian and student-t filters. Our approach establishes a system model using both Gaussian and student-t distributions. We derive a multi-distribution filter for a single sensor, assigning probabilities to Gaussian and student-t noise models. Parallel estimation under both distributions, utilizing Gaussian and student-t filters, allows us to calculate the likelihood of each distribution. The fusion of these results yields a mixed-state estimation and corresponding error matrix. Recognizing the increasing degrees of freedom in the student-t distribution over time, we provide an effective approximation. An information consensus strategy for multi-distribution filters is introduced, achieving global estimation through consensus on fused local filter results via interaction with neighboring nodes. This methodology is extended to the distributed case, and the recursive process of the distributed multi-distribution consensus state estimation method is presented. Simulation results demonstrate that the estimation accuracy of the proposed algorithm improved by at least 20% compared to that of the traditional algorithm in scenarios involving both Gaussian and heavy-tailed distributions.
Full article
Open AccessArticle
Beta Maximum Power Extraction Operation-Based Model Predictive Current Control for Linear Induction Motors
by
Mohamed. A. Ghalib, Samir A. Hamad, Mahmoud F. Elmorshedy, Dhafer Almakhles and Hazem Hassan Ali
J. Sens. Actuator Netw. 2024, 13(4), 37; https://doi.org/10.3390/jsan13040037 - 28 Jun 2024
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There is an increasing interest in achieving global climate change mitigation targets that target environmental protection. Therefore, electric vehicles (as linear metros) were developed to avoid greenhouse gas emissions, which negatively impact the climate. Hence, this paper proposes a finite set-model predictive-based current
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There is an increasing interest in achieving global climate change mitigation targets that target environmental protection. Therefore, electric vehicles (as linear metros) were developed to avoid greenhouse gas emissions, which negatively impact the climate. Hence, this paper proposes a finite set-model predictive-based current control (FS-MPCC) strategy of linear induction motor (LIM) for linear metro drives fed by solar cells with a beta maximum power extraction (B-MPE) control approach to achieve lower thrust ripples and eliminate a selection of weighting factors, the main limitation of conventional model predictive-based thrust control (which can be time consuming and challenging). The B-MPE control approach ensures that the solar cells operate at their maximum power output, maximizing the energy harvested from the sun. Considering a single cost function of primary current errors between the predicted values and their references in αβ-axes, the proposed method eliminates the need for weighting factor selection, thus simplifying the control process. A comparison between the conventional and the presented control method is conducted using MATLAB/Simulink under different scenarios. Comprehensive simulation results of the presented system on a 3 kW LIM prototype revealed that the introduced system based on FS-MPCC surpasses the conventional technique, resulting in a maximum power extraction from solar cells and a suppression of the thrust ripples as well as an avoidance of weighting factor tuning, leading to fewer computational steps.
Full article
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Open AccessArticle
A Nature-Inspired Partial Distance-Based Clustering Algorithm
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Mohammed El Habib Kahla, Mounir Beggas, Abdelkader Laouid and Mohammad Hammoudeh
J. Sens. Actuator Netw. 2024, 13(4), 36; https://doi.org/10.3390/jsan13040036 - 21 Jun 2024
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In the rapidly advancing landscape of digital technologies, clustering plays a critical role in the domains of artificial intelligence and big data. Clustering is essential for extracting meaningful insights and patterns from large, intricate datasets. Despite the efficacy of traditional clustering techniques in
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In the rapidly advancing landscape of digital technologies, clustering plays a critical role in the domains of artificial intelligence and big data. Clustering is essential for extracting meaningful insights and patterns from large, intricate datasets. Despite the efficacy of traditional clustering techniques in handling diverse data types and sizes, they encounter challenges posed by the increasing volume and dimensionality of data, as well as the complex structures inherent in high-dimensional spaces. This research recognizes the constraints of conventional clustering methods, including sensitivity to initial centroids, dependence on prior knowledge of cluster counts, and scalability issues, particularly in large datasets and Internet of Things implementations. In response to these challenges, we propose a K-level clustering algorithm inspired by the collective behavior of fish locomotion. K-level introduces a novel clustering approach based on greedy merging driven by distances in stages. This iterative process efficiently establishes hierarchical structures without the need for exhaustive computations. K-level gives users enhanced control over computational complexity, enabling them to specify the number of clusters merged simultaneously. This flexibility ensures accurate and efficient hierarchical clustering across diverse data types, offering a scalable solution for processing extensive datasets within a reasonable timeframe. The internal validation metrics, including the Silhouette Score, Davies–Bouldin Index, and Calinski–Harabasz Index, are utilized to evaluate the K-level algorithm across various types of datasets. Additionally, comparisons are made with rivals in the literature, including UPGMA, CLINK, UPGMC, SLINK, and K-means. The experiments and analyses show that the proposed algorithm overcomes many of the limitations of existing clustering methods, presenting scalable and adaptable clustering in the dynamic landscape of evolving data challenges.
Full article
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Open AccessArticle
Estimation of Vehicle Traffic Parameters Using an Optical Distance Sensor for Use in Smart City Road Infrastructure
by
Rafał Burdzik, Ireneusz Celiński, Minvydas Ragulskis, Vinayak Ranjan and Jonas Matijošius
J. Sens. Actuator Netw. 2024, 13(4), 35; https://doi.org/10.3390/jsan13040035 - 21 Jun 2024
Abstract
In recent decades, the dynamics of road vehicle traffic have significantly evolved, compelling traffic engineers to develop innovative traffic monitoring solutions, especially for dense road networks. Traditional methods for measuring traffic volume along road sections may no longer suffice for modern traffic control
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In recent decades, the dynamics of road vehicle traffic have significantly evolved, compelling traffic engineers to develop innovative traffic monitoring solutions, especially for dense road networks. Traditional methods for measuring traffic volume along road sections may no longer suffice for modern traffic control systems. This is particularly true for induction loops, a widely used method since the last century. In contrast, measuring techniques using microwaves or visible light offer better accuracy but are often hindered by the high cost of sensors. This paper presents new techniques for measuring traffic flow and other parameters that adapt to changing traffic dynamics using low-cost optical distance sensors. Our study demonstrates that the integration of multiple monitoring approaches enhances measurement accuracy, contingent on the dynamics and specific characteristics of the traffic. The results indicate that cheap optical distance sensors are particularly well suited for use in smart city road networks.
Full article
(This article belongs to the Section Network Services and Applications)
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Open AccessArticle
AI-Based Pedestrian Detection and Avoidance at Night Using Multiple Sensors
by
Hovannes Kulhandjian, Jeremiah Barron, Megan Tamiyasu, Mateo Thompson and Michel Kulhandjian
J. Sens. Actuator Netw. 2024, 13(3), 34; https://doi.org/10.3390/jsan13030034 - 14 Jun 2024
Abstract
In this paper, we present a pedestrian detection and avoidance scheme utilizing multi-sensor data collection and machine learning for intelligent transportation systems (ITSs). The system integrates a video camera, an infrared (IR) camera, and a micro-Doppler radar for data acquisition and training. A
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In this paper, we present a pedestrian detection and avoidance scheme utilizing multi-sensor data collection and machine learning for intelligent transportation systems (ITSs). The system integrates a video camera, an infrared (IR) camera, and a micro-Doppler radar for data acquisition and training. A deep convolutional neural network (DCNN) is employed to process RGB and IR images. The RGB dataset comprises 1200 images (600 with pedestrians and 600 without), while the IR dataset includes 1000 images (500 with pedestrians and 500 without), 85% of which were captured at night. Two distinct DCNNs were trained using these datasets, achieving a validation accuracy of 99.6% with the RGB camera and 97.3% with the IR camera. The radar sensor determines the pedestrian’s range and direction of travel. Experimental evaluations conducted in a vehicle demonstrated that the multi-sensor detection scheme effectively triggers a warning signal to a vibrating motor on the steering wheel and displays a warning message on the passenger’s touchscreen computer when a pedestrian is detected in potential danger. This system operates efficiently both during the day and at night.
Full article
(This article belongs to the Special Issue Advances in Intelligent Transportation Systems (ITS))
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Open AccessArticle
A Learning-Based Energy-Efficient Device Grouping Mechanism for Massive Machine-Type Communication in the Context of Beyond 5G Networks
by
Rubbens Boisguene, Ibrahim Althamary and Chih-Wei Huang
J. Sens. Actuator Netw. 2024, 13(3), 33; https://doi.org/10.3390/jsan13030033 - 28 May 2024
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With the increasing demand for high data rates, low delay, and extended battery life, managing massive machine-type communication (mMTC) in the beyond 5G (B5G) context is challenging. MMTC devices, which play a role in developing the Internet of Things (IoT) and smart cities,
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With the increasing demand for high data rates, low delay, and extended battery life, managing massive machine-type communication (mMTC) in the beyond 5G (B5G) context is challenging. MMTC devices, which play a role in developing the Internet of Things (IoT) and smart cities, need to transmit short amounts of data periodically within a specific time frame. Although blockchain technology is utilized for secure data storage and transfer while digital twin technology provides real-time monitoring and management of the devices, issues such as constrained time delays and network congestion persist. Without a proper data transmission strategy, most devices would fail to transmit in time, thus defying their relevance and purpose. This work investigates the problem of massive random access channel (RACH) attempts while emphasizing the energy efficiency and access latency for mMTC devices with critical missions in B5G networks. Using machine learning techniques, we propose an attention-based reinforcement learning model that orchestrates the device grouping strategy to optimize device placement. Thus, the model guarantees a higher probability of success for the devices during data transmission access, eventually leading to more efficient energy consumption. Through thorough quantitative simulations, we demonstrate that the proposed learning-based approach significantly outperforms the other baseline grouping methods.
Full article
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Open AccessArticle
A Sensor to Monitor Soil Moisture, Salinity, and Temperature Profiles for Wireless Networks
by
Xavier Chavanne and Jean-Pierre Frangi
J. Sens. Actuator Netw. 2024, 13(3), 32; https://doi.org/10.3390/jsan13030032 - 27 May 2024
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This article presents a wireless in situ sensor designed to continuously monitor profiles of parameters in porous media, such as soil moisture, salinity, and temperature. A review of existing in situ soil sensors reveals that it is the only device capable of measuring
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This article presents a wireless in situ sensor designed to continuously monitor profiles of parameters in porous media, such as soil moisture, salinity, and temperature. A review of existing in situ soil sensors reveals that it is the only device capable of measuring the complex permittivity of the medium, allowing for conversions into moisture and salinity that are independent of the instrument. Flow perturbation and invasiveness have also been minimized to maintain good representativeness. Plans include autonomous networks of such sensors, facilitated by the use of the recent radio mode LoRaWAN and cost optimizations for series production. Costs were reduced through electronic simplification and integration, and the use of low-cost modular sensing parts in soil, while still maintaining high measurement quality. A complete set of sensor data recorded during a three-month trial is also presented and interpreted.
Full article
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Open AccessArticle
Time Delay Characterization in Wireless Sensor Networks for Distributed Measurement Applications
by
Šarūnas Kilius, Darius Gailius, Mindaugas Knyva, Gintautas Balčiūnas, Asta Meškuotienė, Justina Dobilienė, Simas Joneliūnas and Pranas Kuzas
J. Sens. Actuator Netw. 2024, 13(3), 31; https://doi.org/10.3390/jsan13030031 - 16 May 2024
Abstract
This paper investigates the critical aspect of synchronization in wireless sensor networks (WSNs) across diverse industrial applications. The low-cost sensor network topologies are analyzed. The communication delay measurements and quantitative jitter analysis are performed under different conditions, and dependencies of the propagation time
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This paper investigates the critical aspect of synchronization in wireless sensor networks (WSNs) across diverse industrial applications. The low-cost sensor network topologies are analyzed. The communication delay measurements and quantitative jitter analysis are performed under different conditions, and dependencies of the propagation time delay on the data bitrate and modulation type for different hardware implementations of the WSNs are presented. The time delay distribution influence on the time synchronization error propagation over WSN layers was assessed from the experimental probability density functions. The network synchronization based on the controlled propagation delay jitter approach has been proposed. This research contributes quantitative insights into the complexities of synchronization in WSNs, offering a foundation for optimizing network configurations and parameters to extend the operational life of low-power sensor nodes.
Full article
(This article belongs to the Section Actuators, Sensors and Devices)
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Open AccessArticle
A Multi-Agent Reinforcement Learning-Based Grant-Free Random Access Protocol for mMTC Massive MIMO Networks
by
Felipe Augusto Dutra Bueno, Alessandro Goedtel, Taufik Abrão and José Carlos Marinello
J. Sens. Actuator Netw. 2024, 13(3), 30; https://doi.org/10.3390/jsan13030030 - 30 Apr 2024
Abstract
The expected huge number of connected devices in Internet of Things (IoT) applications characterizes the massive machine-type communication (mMTC) scenario, one prominent use case of beyond fifth-generation (B5G) systems. To meet mMTC connectivity requirements, grant-free (GF) random access (RA) protocols are seen as
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The expected huge number of connected devices in Internet of Things (IoT) applications characterizes the massive machine-type communication (mMTC) scenario, one prominent use case of beyond fifth-generation (B5G) systems. To meet mMTC connectivity requirements, grant-free (GF) random access (RA) protocols are seen as a promising solution due to the small amount of data that MTC devices usually transmit. In this paper, we propose a GF RA protocol based on a multi-agent reinforcement learning approach, applied to aid IoT devices in selecting the least congested RA pilots. The rewards obtained by the devices in collision cases resemble the congestion level of the chosen pilot. To enable the operation of the proposed method in a realistic B5G network scenario and aiming to reduce signaling overheads and centralized processing, the rewards in our proposed method are computed by the devices taking advantage of a large number of base station antennas. Numerical results demonstrate the superior performance of the proposed method in terms of latency, network throughput, and per-device throughput compared with other protocols.
Full article
(This article belongs to the Special Issue Security and Smart Applications in IoT and Wireless Sensor and Actuator Networks)
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Open AccessArticle
Data-Driven Position and Stiffness Control of Antagonistic Variable Stiffness Actuator Using Nonlinear Hammerstein Models
by
Ali Javadi, Hamed Haghighi, Khemwutta Pornpipatsakul and Ronnapee Chaichaowarat
J. Sens. Actuator Netw. 2024, 13(2), 29; https://doi.org/10.3390/jsan13020029 - 19 Apr 2024
Abstract
In this paper, an optimal PID controller is introduced for an antagonistic variable stiffness actuator (AVSA) based on Hammerstein models. A set of Hammerstein models is developed for the AVSA using the voltage difference method. For each stiffness level, linear and nonlinear Hammerstein
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In this paper, an optimal PID controller is introduced for an antagonistic variable stiffness actuator (AVSA) based on Hammerstein models. A set of Hammerstein models is developed for the AVSA using the voltage difference method. For each stiffness level, linear and nonlinear Hammerstein models are identified using the least squares method. Experimental results confirm that the outputs of the Hammerstein models fit the measured data better than linear models, as Hammerstein models can incorporate nonlinear effects such as friction. A genetic algorithm is utilized to find optimal PID gains for different stiffness levels and reference position amplitudes. The final gains are obtained by linearly interpolating the optimal gains obtained. To demonstrate the effectiveness of the proposed design, several scenarios with different reference positions and stiffness profiles are provided. Specifically, square, sinusoidal, and sawtooth waves are used for reference positions and stiffness values. The robustness of the proposed approach is further analyzed by applying a disturbance force on the actuator link. The results are compared with the linear method, showing that the proposed design can handle soft transitions in stiffness variation and ensure perfect tracking.
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(This article belongs to the Section Actuators, Sensors and Devices)
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Open AccessArticle
Level-Crossing Characteristics of an Actively Managed Buffer
by
Andrzej Chydzinski
J. Sens. Actuator Netw. 2024, 13(2), 28; https://doi.org/10.3390/jsan13020028 - 15 Apr 2024
Abstract
In this paper, we examine a buffer with active management that rejects packets basing on the buffer occupancy. Specifically, we derive several metrics characterizing how effectively the algorithm can prevent the queue of packets from becoming too long and how well it assists
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In this paper, we examine a buffer with active management that rejects packets basing on the buffer occupancy. Specifically, we derive several metrics characterizing how effectively the algorithm can prevent the queue of packets from becoming too long and how well it assists in flushing the buffer quickly when necessary. First, we compute the probability that the size of the queue is kept below a predefined level L. Second, we calculate the distribution of the amount of time needed to cross level L, the buffer overflow probability, and the average time to buffer overflow. Third, we derive the distribution of the amount of time required to flush the buffer and its average value. A general modeling framework is used in derivations, with a general service time distribution, general rejection function, and a powerful model of the arrival process. The obtained formulas enable, among other things, the solving of many design problems, e.g., those connected with the design of wireless sensor nodes using the N-policy. Several numerical results are provided, including examples of design problems and other calculations.
Full article
(This article belongs to the Section Communications and Networking)
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Open AccessArticle
Closed-Loop Optical Tracking of a Micro-Conveyor over a Smart Surface
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Saly Malak, Hani Al Hajjar, Erwan Dupont, Muneeb-Ullah Khan, Christine Prelle and Frederic Lamarque
J. Sens. Actuator Netw. 2024, 13(2), 27; https://doi.org/10.3390/jsan13020027 - 13 Apr 2024
Cited by 1
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In this work, a closed loop control system is developed to optically localize and track micro-robots with high precision. These micro-robots (i.e., micro-conveyors) are in motion simultaneously across a smart surface.The developed method’s primary objectives are to optimize their trajectories, avoid collisions between
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In this work, a closed loop control system is developed to optically localize and track micro-robots with high precision. These micro-robots (i.e., micro-conveyors) are in motion simultaneously across a smart surface.The developed method’s primary objectives are to optimize their trajectories, avoid collisions between them, and control their position with micrometric resolution. This article presents and characterizes the tracking of a single micro-conveyor, and the method works similarly when multiple micro-robots move over the surface. Our tracking method starts with a scanning phase, where a 2D steering mirror, placed above the smart surface, reflects a laser beam toward the conveying surface seeking for the target. Localization occurs when this light beam reaches the micro-conveyor. By adding a retro-reflective element, that reflects the light in the same direction of the the incident light, onto the surface of the micro-conveyor, the light will be reflected towards a photodetector. Depending on the feedback from the photodetector, the steering mirror rotates to track the trajectory of the micro-conveyor. The tip-tilt angular values of the steering mirror allows the micro-conveyor position to be obtained via calibrated localization system. The aim of this work is to regulate the micro-conveyor, within a closed-loop control system, to reduce the positional error between the actual and desired position. The actual position value is measured in real-time application using our developed optical sensor. Results for tracking in the x-and y-axis have validated the proposed method, with an average tracking error less than 30 µm within a range 150 mm × 150 mm.
Full article
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Open AccessReview
A Survey on Life-Cycle-Oriented Certificate Management in Industrial Networking Environments
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Julian Göppert, Andreas Walz and Axel Sikora
J. Sens. Actuator Netw. 2024, 13(2), 26; https://doi.org/10.3390/jsan13020026 - 10 Apr 2024
Abstract
Driven by the Industry 4.0 paradigm and the resulting demand for connectivity in industrial networking, there is a convergence of formerly isolated operational technology and information technology networks. This convergence leads to attack surfaces on industrial networks. Therefore, a holistic approach of countermeasures
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Driven by the Industry 4.0 paradigm and the resulting demand for connectivity in industrial networking, there is a convergence of formerly isolated operational technology and information technology networks. This convergence leads to attack surfaces on industrial networks. Therefore, a holistic approach of countermeasures is needed to protect against cyber attacks. One element of these countermeasures is the use of certificate-based authentication for industrial components communicating on the field level. This in turn requires the management of certificates, private keys, and trust anchors in the communication endpoints. The work at hand surveys the topic of certificate management in industrial networking environments throughout their life cycle, from manufacturing until their disposal. To the best of the authors’ knowledge, there is no work yet that surveys the topic of certificate management in industrial networking environments. The work at hand considers contributions from research papers, industrial communication standards, and contributions that originate from the IT domain. In total, 2042 results from IEEE Xplore, Science Direct, Scopus, and Springer Link were taken into account. After applying inclusion and exclusion criteria and title, abstract, and full-text analysis, 20 contributions from research papers were selected. In addition to the presentation of their key contributions, the work at hand provides a synopsis that compares the overarching aspects. This comprises different proposed entity architectures, certificate management functions, involvement of different stakeholders, and consideration of life cycle stages. Finally, research gaps that are to be filled by further work are identified. While the topic of certificate management has already been addressed by the IT domain, its incorporation into industrial communication standards began significantly later and is still the subject of research work.
Full article
(This article belongs to the Section Network Security and Privacy)
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Open AccessArticle
Assessing the Acceptance of a Mid-Air Gesture Syntax for Smart Space Interaction: An Empirical Study
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Ana M. Bernardos, Xian Wang, Luca Bergesio, Juan A. Besada and José R. Casar
J. Sens. Actuator Netw. 2024, 13(2), 25; https://doi.org/10.3390/jsan13020025 - 9 Apr 2024
Abstract
Mid-gesture interfaces have become popular for specific scenarios, such as interactions with augmented reality via head-mounted displays, specific controls over smartphones, or gaming platforms. This article explores the use of a location-aware mid-air gesture-based command triplet syntax to interact with a smart space.
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Mid-gesture interfaces have become popular for specific scenarios, such as interactions with augmented reality via head-mounted displays, specific controls over smartphones, or gaming platforms. This article explores the use of a location-aware mid-air gesture-based command triplet syntax to interact with a smart space. The syntax, inspired by human language, is built as a vocative case with an imperative structure. In a sentence like “Light, please switch on!”, the object being activated is invoked via making a gesture that mimics its initial letter/acronym (vocative, coincident with the sentence’s elliptical subject). A geometrical or directional gesture then identifies the action (imperative verb) and may include an object feature or a second object with which to network (complement), which also represented by the initial or acronym letter. Technically, an interpreter relying on a trainable multidevice gesture recognition layer makes the pair/triplet syntax decoding possible. The recognition layer works on acceleration and position input signals from graspable (smartphone) and free-hand devices (smartwatch and external depth cameras), as well as a specific compiler. On a specific deployment at a Living Lab facility, the syntax has been instantiated via the use of a lexicon derived from English (with respect to the initial letters and acronyms). A within-subject analysis with twelve users has enabled the analysis of the syntax acceptance (in terms of usability, gesture agreement for actions over objects, and social acceptance) and technology preference of the gesture syntax within its three device implementations (graspable, wearable, and device-free ones). Participants express consensus regarding the simplicity of learning the syntax and its potential effectiveness in managing smart resources. Socially, participants favoured the Watch for outdoor activities and the Phone for home and work settings, underscoring the importance of social context in technology design. The Phone emerged as the preferred option for gesture recognition due to its efficiency and familiarity. The system, which can be adapted to different sensing technologies, addresses the scalability concerns (as it can be easily extended for new objects and actions) and allows for personalised interaction.
Full article
(This article belongs to the Special Issue Machine-Environment Interaction, Volume II)
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Open AccessArticle
Hybrid Adaptive Impedance and Admittance Control Based on the Sensorless Estimation of Interaction Joint Torque for Exoskeletons: A Case Study of an Upper Limb Rehabilitation Robot
by
Auwalu Muhammad Abdullahi, Ado Haruna and Ronnapee Chaichaowarat
J. Sens. Actuator Netw. 2024, 13(2), 24; https://doi.org/10.3390/jsan13020024 - 28 Mar 2024
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Physiotherapy is the treatment to recover a patient’s mobility and limb function after an injury, illness, or disability. Rehabilitation robots can be used to replace human physiotherapists. To ensure safety during robot physical therapy, the patient’s limb needs to be controlled to track
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Physiotherapy is the treatment to recover a patient’s mobility and limb function after an injury, illness, or disability. Rehabilitation robots can be used to replace human physiotherapists. To ensure safety during robot physical therapy, the patient’s limb needs to be controlled to track a desired joint trajectory, and the torque due to interaction force/torque needs to be measured and regulated. Therefore, hybrid impedance and admittance with position control (HIPC) is required to track the trajectory and simultaneously regulate the contact torque. The literature describes two structures of HIPC: (1) a switched framework between admittance and impedance control operating in parallel (HIPCSW); and (2) a series connection between admittance and impedance control without switching. In this study, a hybrid adaptive impedance and position-based admittance control (HAIPC) in series is developed, which consists of a proportional derivative-based admittance position controller with gravitational torque compensation and an adaptive impedance controller. An extended state observer is used to estimate the interaction joint torque due to human stiff contact with the exoskeleton without the use of force/torque sensor, which is then used in the adaptive algorithm to update the stiffness and damping gains of the adaptive impedance controller. Simulation results obtained using MATLAB show that the proposed HAIPC significantly reduces the mean absolute values of the actuation torques (control inputs) required for the shoulder and elbow joints in comparison with HIPC and HIPCSW.
Full article
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Open AccessArticle
Structured Data Ontology for AI in Industrial Asset Condition Monitoring
by
Jacob Hendriks, Mana Azarm and Patrick Dumond
J. Sens. Actuator Netw. 2024, 13(2), 23; https://doi.org/10.3390/jsan13020023 - 26 Mar 2024
Cited by 1
Abstract
This paper proposes an ontology for prognostics and health management (PHM) applications involving sensor networks monitoring industrial machinery. Deep learning methods show promise for the development of autonomous PHM systems but require vast quantities of structured and representative data to realize their potential.
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This paper proposes an ontology for prognostics and health management (PHM) applications involving sensor networks monitoring industrial machinery. Deep learning methods show promise for the development of autonomous PHM systems but require vast quantities of structured and representative data to realize their potential. PHM systems involve unique and specialized data characterized by time and context, and thus benefit from tailored data management systems. Furthermore, the use of dissimilar standards and practices with respect to database structure and data organization is a hinderance to interoperability. To address this, this paper presents a robust, structured data ontology and schema that is designed to accommodate a wide breadth of PHM applications. The inclusion of contextual and temporal data increases its value for developing and deploying enhanced ML-driven PHM systems. Challenges around balancing the competing priorities of structure and flexibility are discussed. The proposed schema provides the benefits of a relational schema with some provisions for noSQL-like flexibility in areas where PMH applications demand it. The selection of a database engine for implementation is also discussed, and the proposed ontology is demonstrated using a Postgres database. An instance of the database was loaded with large auto-generated fictitious data via multiple Python scripts. CRUD (create, read, update, delete) operations are demonstrated with several queries that answer common PHM questions.
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(This article belongs to the Special Issue Fault Diagnosis in the Internet of Things Applications)
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Open AccessArticle
An Optimized Link State Routing Protocol with a Blockchain Framework for Efficient Video-Packet Transmission and Security over Mobile Ad-Hoc Networks
by
Huda A. Ahmed and Hamid Ali Abed AL-Asadi
J. Sens. Actuator Netw. 2024, 13(2), 22; https://doi.org/10.3390/jsan13020022 - 11 Mar 2024
Cited by 2
Abstract
A mobile ad-hoc network (MANET) necessitates appropriate routing techniques to enable optimal data transfer. The selection of appropriate routing protocols while utilizing the default settings is required to solve the existing problems. To enable effective video streaming in MANETs, this study proposes a
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A mobile ad-hoc network (MANET) necessitates appropriate routing techniques to enable optimal data transfer. The selection of appropriate routing protocols while utilizing the default settings is required to solve the existing problems. To enable effective video streaming in MANETs, this study proposes a novel optimized link state routing (OLSR) protocol that incorporates a deep-learning model. Initially, the input videos are collected from the Kaggle dataset. Then, the black-hole node is detected using a novel twin-attention-based dense convolutional bidirectional gated network (SA_ DCBiGNet) model. Next, the neighboring nodes are analyzed using trust values, and routing is performed using the extended osprey-aided optimized link state routing protocol (EO_OLSRP) technique. Similarly, the extended osprey optimization algorithm (EOOA) selects the optimal feature based on parameters such as node stability and link stability. Finally, blockchain storage is included to improve the security of MANET data using interplanetary file system (IPFS) technology. Additionally, the proposed blockchain system is validated utilizing a consensus technique based on delegated proof-of-stake (DPoS). The proposed method utilizes Python and it is evaluated using data acquired from various mobile simulator models accompanied by the NS3 simulator. The proposed model performs better with a packet-delivery ratio (PDR) of 91.6%, average end delay (AED) of 23.6 s, and throughput of 2110 bytes when compared with the existing methods which have a PDR of 89.1%, AED of 22 s, and throughput of 1780 bytes, respectively.
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(This article belongs to the Section Network Security and Privacy)
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Open AccessArticle
Veritas: Layer-2 Scaling Solution for Decentralized Oracles on Ethereum Blockchain with Reputation and Real-Time Considerations
by
Moustafa Mowaffak Saad, Dalia Sobhy and Amani A. Saad
J. Sens. Actuator Netw. 2024, 13(2), 21; https://doi.org/10.3390/jsan13020021 - 7 Mar 2024
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Blockchainsand smart contracts are pivotal in transforming interactions between systems and individuals, offering secure, immutable, and transparent trust-building mechanisms without central oversight. However, Smart Contracts face limitations due to their reliance on blockchain-contained data, a gap addressed by ’Oracles’. These bridges to external
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Blockchainsand smart contracts are pivotal in transforming interactions between systems and individuals, offering secure, immutable, and transparent trust-building mechanisms without central oversight. However, Smart Contracts face limitations due to their reliance on blockchain-contained data, a gap addressed by ’Oracles’. These bridges to external data sources introduce the ’Oracle problem’, where maintaining blockchain-like security and transparency becomes vital to prevent data integrity issues. This paper presents Veritas, a novel decentralized oracle system leveraging a layer-2 scaling solution, enhancing smart contracts’ efficiency and security on Ethereum blockchains. The proposed architecture, explored through simulation and experimental analyses, significantly reduces operational costs while maintaining robust security protocols. An innovative node selection process is also introduced to minimize the risk of malicious data entry, thereby reinforcing network security. Veritas offers a solution to the Oracle problem by aligning with blockchain principles of security and transparency, and demonstrates advancements in reducing operational costs and bolstering network integrity. While the study provides a promising direction, it also highlights potential areas for further exploration in blockchain technology and oracle system optimization.
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Open AccessReview
Interconnected Smart Transactive Microgrids—A Survey on Trading, Energy Management Systems, and Optimisation Approaches
by
Ipeleng L. Machele, Adeiza J. Onumanyi, Adnan M. Abu-Mahfouz and Anish M. Kurien
J. Sens. Actuator Netw. 2024, 13(2), 20; https://doi.org/10.3390/jsan13020020 - 1 Mar 2024
Abstract
The deployment of isolated microgrids has witnessed exponential growth globally, especially in the light of prevailing challenges faced by many larger power grids. However, these isolated microgrids remain separate entities, thus limiting their potential to significantly impact and improve the stability, efficiency, and
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The deployment of isolated microgrids has witnessed exponential growth globally, especially in the light of prevailing challenges faced by many larger power grids. However, these isolated microgrids remain separate entities, thus limiting their potential to significantly impact and improve the stability, efficiency, and reliability of the broader electrical power system. Thus, to address this gap, the concept of interconnected smart transactive microgrids (ISTMGs) has arisen, facilitating the interconnection of these isolated microgrids, each with its unique attributes aimed at enhancing the performance of the broader power grid system. Furthermore, ISTMGs are expected to create more robust and resilient energy networks that enable innovative and efficient mechanisms for energy trading and sharing between individual microgrids and the centralized power grid. This paradigm shift has sparked a surge in research aimed at developing effective ISTMG networks and mechanisms. Thus, in this paper, we present a review of the current state-of-the-art in ISTMGs with a focus on energy trading, energy management systems (EMS), and optimization techniques for effective energy management in ISTMGs. We discuss various types of trading, architectures, platforms, and stakeholders involved in ISTMGs. We proceed to elucidate the suitable applications of EMS within such ISTMG frameworks, emphasizing its utility in various domains. This includes an examination of optimization tools and methodologies for deploying EMS in ISTMGs. Subsequently, we conduct an analysis of current techniques and their constraints, and delineate prospects for future research to advance the establishment and utilization of ISTMGs.
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(This article belongs to the Section Network Services and Applications)
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Open AccessArticle
Low-Cost Internet of Things Solution for Building Information Modeling Level 3B—Monitoring, Analysis and Management
by
Andrzej Szymon Borkowski
J. Sens. Actuator Netw. 2024, 13(2), 19; https://doi.org/10.3390/jsan13020019 - 29 Feb 2024
Cited by 1
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The integration of the Internet of Things (IoT) and Building Information Modeling (BIM) is progressing. The use of microcontrollers and sensors in buildings is described as a level 3B maturity in the use of BIM. Design companies, contractors and building operators can use
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The integration of the Internet of Things (IoT) and Building Information Modeling (BIM) is progressing. The use of microcontrollers and sensors in buildings is described as a level 3B maturity in the use of BIM. Design companies, contractors and building operators can use IoT solutions to monitor, analyze or manage processes. As a rule, solutions based on original Arduino boards are quite an expensive investment. The aim of this research was to find a low-cost IoT solution for monitoring, analysis and management, and integrate it with a BIM model. In the present study, an inexpensive NodeMCU microcontroller and a temperature and pressure sensor were used to study the thermal comfort of users in a single-family home. During the summer season, analysis of the monitored temperature can contribute to installation (HVAC) or retrofit work (for energy efficiency). The article presents a low-cost solution for studying the thermal comfort of users using a digital twin built-in BIM. Data obtained from sensors can support both the design and management processes. The main contribution of the article enables the design, construction and use of low-cost circuits (15.57 USD) even in small developments (single-family houses, semi-detached houses, terraced houses, atrium buildings). Combining IoT sensor telemetry with BIM (maturity level 3C) is a challenge that organizations will face in the near future.
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