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Editor’s Choice Articles

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

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15 pages, 8787 KiB  
Letter
Real-Time Moving Object Detection in High-Resolution Video Sensing
by Haidi Zhu, Haoran Wei, Baoqing Li, Xiaobing Yuan and Nasser Kehtarnavaz
Sensors 2020, 20(12), 3591; https://doi.org/10.3390/s20123591 - 25 Jun 2020
Cited by 56 | Viewed by 5175
Abstract
This paper addresses real-time moving object detection with high accuracy in high-resolution video frames. A previously developed framework for moving object detection is modified to enable real-time processing of high-resolution images. First, a computationally efficient method is employed, which detects moving regions on [...] Read more.
This paper addresses real-time moving object detection with high accuracy in high-resolution video frames. A previously developed framework for moving object detection is modified to enable real-time processing of high-resolution images. First, a computationally efficient method is employed, which detects moving regions on a resized image while maintaining moving regions on the original image with mapping coordinates. Second, a light backbone deep neural network in place of a more complex one is utilized. Third, the focal loss function is employed to alleviate the imbalance between positive and negative samples. The results of the extensive experimentations conducted indicate that the modified framework developed in this paper achieves a processing rate of 21 frames per second with 86.15% accuracy on the dataset SimitMovingDataset, which contains high-resolution images of the size 1920 × 1080. Full article
(This article belongs to the Section Sensor Networks)
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18 pages, 3643 KiB  
Article
A Human Support Robot for the Cleaning and Maintenance of Door Handles Using a Deep-Learning Framework
by Balakrishnan Ramalingam, Jia Yin, Mohan Rajesh Elara, Yokhesh Krishnasamy Tamilselvam, Madan Mohan Rayguru, M. A. Viraj J. Muthugala and Braulio Félix Gómez
Sensors 2020, 20(12), 3543; https://doi.org/10.3390/s20123543 - 23 Jun 2020
Cited by 55 | Viewed by 9322
Abstract
The role of mobile robots for cleaning and sanitation purposes is increasing worldwide. Disinfection and hygiene are two integral parts of any safe indoor environment, and these factors become more critical in COVID-19-like pandemic situations. Door handles are highly sensitive contact points that [...] Read more.
The role of mobile robots for cleaning and sanitation purposes is increasing worldwide. Disinfection and hygiene are two integral parts of any safe indoor environment, and these factors become more critical in COVID-19-like pandemic situations. Door handles are highly sensitive contact points that are prone to be contamination. Automation of the door-handle cleaning task is not only important for ensuring safety, but also to improve efficiency. This work proposes an AI-enabled framework for automating cleaning tasks through a Human Support Robot (HSR). The overall cleaning process involves mobile base motion, door-handle detection, and control of the HSR manipulator for the completion of the cleaning tasks. The detection part exploits a deep-learning technique to classify the image space, and provides a set of coordinates for the robot. The cooperative control between the spraying and wiping is developed in the Robotic Operating System. The control module uses the information obtained from the detection module to generate a task/operational space for the robot, along with evaluating the desired position to actuate the manipulators. The complete strategy is validated through numerical simulations, and experiments on a Toyota HSR platform. Full article
(This article belongs to the Section Sensor Networks)
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21 pages, 4606 KiB  
Review
Graphene Plasmonics in Sensor Applications: A Review
by Shinpei Ogawa, Shoichiro Fukushima and Masaaki Shimatani
Sensors 2020, 20(12), 3563; https://doi.org/10.3390/s20123563 - 23 Jun 2020
Cited by 40 | Viewed by 6864
Abstract
Surface plasmon polaritons (SPPs) can be generated in graphene at frequencies in the mid-infrared to terahertz range, which is not possible using conventional plasmonic materials such as noble metals. Moreover, the lifetime and confinement volume of such SPPs are much longer and smaller, [...] Read more.
Surface plasmon polaritons (SPPs) can be generated in graphene at frequencies in the mid-infrared to terahertz range, which is not possible using conventional plasmonic materials such as noble metals. Moreover, the lifetime and confinement volume of such SPPs are much longer and smaller, respectively, than those in metals. For these reasons, graphene plasmonics has potential applications in novel plasmonic sensors and various concepts have been proposed. This review paper examines the potential of such graphene plasmonics with regard to the development of novel high-performance sensors. The theoretical background is summarized and the intrinsic nature of graphene plasmons, interactions between graphene and SPPs induced by metallic nanostructures and the electrical control of SPPs by adjusting the Fermi level of graphene are discussed. Subsequently, the development of optical sensors, biological sensors and important components such as absorbers/emitters and reconfigurable optical mirrors for use in new sensor systems are reviewed. Finally, future challenges related to the fabrication of graphene-based devices as well as various advanced optical devices incorporating other two-dimensional materials are examined. This review is intended to assist researchers in both industry and academia in the design and development of novel sensors based on graphene plasmonics. Full article
(This article belongs to the Collection Advances in Metamaterials or Plasmonics-Based Sensors)
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24 pages, 7285 KiB  
Article
Image-Processing-Based Low-Cost Fault Detection Solution for End-of-Line ECUs in Automotive Manufacturing
by Adrian Korodi, Denis Anitei, Alexandru Boitor and Ioan Silea
Sensors 2020, 20(12), 3520; https://doi.org/10.3390/s20123520 - 22 Jun 2020
Cited by 16 | Viewed by 5521
Abstract
The manufacturing industry is continuously researching and developing strategies and solutions to increase product quality and to decrease production time and costs. The approach is always targeting more automated, traceable, and supervised production, minimizing the impact of the human factor. In the automotive [...] Read more.
The manufacturing industry is continuously researching and developing strategies and solutions to increase product quality and to decrease production time and costs. The approach is always targeting more automated, traceable, and supervised production, minimizing the impact of the human factor. In the automotive industry, the Electronic Control Unit (ECU) manufacturing ends with complex testing, the End-of-Line (EoL) products being afterwards sent to client companies. This paper proposes an image-processing-based low-cost fault detection (IP-LC-FD) solution for the EoL ECUs, aiming for high-quality and fast detection. The IP-LC-FD solution approaches the problem of determining, on the manufacturing line, the correct mounting of the pins in the locations of each connector of the ECU module, respectively, other defects as missing or extra pins, damaged clips, or surface cracks. The IP-LC-FD system is a hardware–software structure, based on Raspberry Pi microcomputers, Pi cameras, respectively, Python and OpenCV environments. This paper presents the two main stages of the research, the experimental model, and the prototype. The rapid integration into the production line represented an important goal, meaning the accomplishment of the specific hard acceptance requirements regarding both performance and functionality. The solution was implemented and tested as an experimental model and prototype in a real industrial environment, proving excellent results. Full article
(This article belongs to the Section Fault Diagnosis & Sensors)
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32 pages, 9734 KiB  
Review
Enzyme-Based Biosensors: Tackling Electron Transfer Issues
by Paolo Bollella and Evgeny Katz
Sensors 2020, 20(12), 3517; https://doi.org/10.3390/s20123517 - 21 Jun 2020
Cited by 90 | Viewed by 8058
Abstract
This review summarizes the fundamentals of the phenomenon of electron transfer (ET) reactions occurring in redox enzymes that were widely employed for the development of electroanalytical devices, like biosensors, and enzymatic fuel cells (EFCs). A brief introduction on the ET observed in proteins/enzymes [...] Read more.
This review summarizes the fundamentals of the phenomenon of electron transfer (ET) reactions occurring in redox enzymes that were widely employed for the development of electroanalytical devices, like biosensors, and enzymatic fuel cells (EFCs). A brief introduction on the ET observed in proteins/enzymes and its paradigms (e.g., classification of ET mechanisms, maximal distance at which is observed direct electron transfer, etc.) are given. Moreover, the theoretical aspects related to direct electron transfer (DET) are resumed as a guideline for newcomers to the field. Snapshots on the ET theory formulated by Rudolph A. Marcus and on the mathematical model used to calculate the ET rate constant formulated by Laviron are provided. Particular attention is devoted to the case of glucose oxidase (GOx) that has been erroneously classified as an enzyme able to transfer electrons directly. Thereafter, all tools available to investigate ET issues are reported addressing the discussions toward the development of new methodology to tackle ET issues. In conclusion, the trends toward upcoming practical applications are suggested as well as some directions in fundamental studies of bioelectrochemistry. Full article
(This article belongs to the Special Issue Biosensors – Recent Advances and Future Challenges)
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58 pages, 21886 KiB  
Review
Wireless Power Transfer Techniques for Implantable Medical Devices: A Review
by Sadeque Reza Khan, Sumanth Kumar Pavuluri, Gerard Cummins and Marc P. Y. Desmulliez
Sensors 2020, 20(12), 3487; https://doi.org/10.3390/s20123487 - 19 Jun 2020
Cited by 162 | Viewed by 19573
Abstract
Wireless power transfer (WPT) systems have become increasingly suitable solutions for the electrical powering of advanced multifunctional micro-electronic devices such as those found in current biomedical implants. The design and implementation of high power transfer efficiency WPT systems are, however, challenging. The size [...] Read more.
Wireless power transfer (WPT) systems have become increasingly suitable solutions for the electrical powering of advanced multifunctional micro-electronic devices such as those found in current biomedical implants. The design and implementation of high power transfer efficiency WPT systems are, however, challenging. The size of the WPT system, the separation distance between the outside environment and location of the implanted medical device inside the body, the operating frequency and tissue safety due to power dissipation are key parameters to consider in the design of WPT systems. This article provides a systematic review of the wide range of WPT systems that have been investigated over the last two decades to improve overall system performance. The various strategies implemented to transfer wireless power in implantable medical devices (IMDs) were reviewed, which includes capacitive coupling, inductive coupling, magnetic resonance coupling and, more recently, acoustic and optical powering methods. The strengths and limitations of all these techniques are benchmarked against each other and particular emphasis is placed on comparing the implanted receiver size, the WPT distance, power transfer efficiency and tissue safety presented by the resulting systems. Necessary improvements and trends of each WPT techniques are also indicated per specific IMD. Full article
(This article belongs to the Special Issue Smart IoT Systems for Pervasive Healthcare)
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18 pages, 1154 KiB  
Article
An Efficient Distributed Area Division Method for Cooperative Monitoring Applications with Multiple UAVs
by José Joaquín Acevedo, Ivan Maza, Anibal Ollero and Begoña C. Arrue
Sensors 2020, 20(12), 3448; https://doi.org/10.3390/s20123448 - 18 Jun 2020
Cited by 12 | Viewed by 2807
Abstract
This article addresses the area division problem in a distributed manner providing a solution for cooperative monitoring missions with multiple UAVs. Starting from a sub-optimal area division, a distributed online algorithm is presented to accelerate the convergence of the system to the optimal [...] Read more.
This article addresses the area division problem in a distributed manner providing a solution for cooperative monitoring missions with multiple UAVs. Starting from a sub-optimal area division, a distributed online algorithm is presented to accelerate the convergence of the system to the optimal solution, following a frequency-based approach. Based on the “coordination variables” concept and on a strict neighborhood relation to share information (left, right, above and below neighbors), this technique defines a distributed division protocol to determine coherently the size and shape of the sub-area assigned to each UAV. Theoretically, the convergence time of the proposed solution depends linearly on the number of UAVs. Validation results, comparing the proposed approach with other distributed techniques, are provided to evaluate and analyze its performance following a convergence time criterion. Full article
(This article belongs to the Special Issue UAV-Based Smart Sensor Systems and Applications)
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15 pages, 2119 KiB  
Article
Layered Double Hydroxide-Modified Organic Electrochemical Transistor for Glucose and Lactate Biosensing
by Isacco Gualandi, Marta Tessarolo, Federica Mariani, Danilo Arcangeli, Luca Possanzini, Domenica Tonelli, Beatrice Fraboni and Erika Scavetta
Sensors 2020, 20(12), 3453; https://doi.org/10.3390/s20123453 - 18 Jun 2020
Cited by 44 | Viewed by 4670
Abstract
Biosensors based on Organic Electrochemical Transistors (OECTs) are developed for the selective detection of glucose and lactate. The transistor architecture provides signal amplification (gain) with respect to the simple amperometric response. The biosensors are based on a poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) channel and the gate [...] Read more.
Biosensors based on Organic Electrochemical Transistors (OECTs) are developed for the selective detection of glucose and lactate. The transistor architecture provides signal amplification (gain) with respect to the simple amperometric response. The biosensors are based on a poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) channel and the gate electrode is functionalised with glucose oxidase (GOx) or lactate oxidase (LOx) enzymes, which are immobilised within a Ni/Al Layered Double Hydroxide (LDH) through a one-step electrodeposition procedure. The here-designed OECT architecture allows minimising the required amount of enzyme during electrodeposition. The output signal of the biosensor is the drain current (Id), which decreases as the analyte concentration increases. In the optimised conditions, the biosensor responds to glucose in the range of 0.1–8.0 mM with a limit of detection (LOD) of 0.02 mM. Two regimes of proportionality are observed. For concentrations lower than 1.0 mM, a linear response is obtained with a mean gain of 360, whereas for concentrations higher than 1.0 mM, Id is proportional to the logarithm of glucose concentration, with a gain of 220. For lactate detection, the biosensor response is linear in the whole concentration range (0.05–8.0 mM). A LOD of 0.04 mM is reached, with a net gain equal to 400. Full article
(This article belongs to the Special Issue New Generation of Electrochemical Sensors)
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13 pages, 2927 KiB  
Article
Development of Taste Sensor to Detect Non-Charged Bitter Substances
by Jumpei Yoshimatsu, Kiyoshi Toko, Yusuke Tahara, Misaki Ishida, Masaaki Habara, Hidekazu Ikezaki, Honami Kojima, Saeri Ikegami, Miyako Yoshida and Takahiro Uchida
Sensors 2020, 20(12), 3455; https://doi.org/10.3390/s20123455 - 18 Jun 2020
Cited by 22 | Viewed by 4331
Abstract
A taste sensor with lipid/polymer membranes is one of the devices that can evaluate taste objectively. However, the conventional taste sensor cannot measure non-charged bitter substances, such as caffeine contained in coffee, because the taste sensor uses the potentiometric measurement based mainly on [...] Read more.
A taste sensor with lipid/polymer membranes is one of the devices that can evaluate taste objectively. However, the conventional taste sensor cannot measure non-charged bitter substances, such as caffeine contained in coffee, because the taste sensor uses the potentiometric measurement based mainly on change in surface electric charge density of the membrane. In this study, we aimed at the detection of typical non-charged bitter substances such as caffeine, theophylline and theobromine included in beverages and pharmaceutical products. The developed sensor is designed to detect the change in the membrane potential by using a kind of allosteric mechanism of breaking an intramolecular hydrogen bond between the carboxy group and hydroxy group of aromatic carboxylic acid (i.e., hydroxy-, dihydroxy-, and trihydroxybenzoic acids) when non-charged bitter substances are bound to the hydroxy group. As a result of surface modification by immersing the sensor electrode in a modification solution in which 2,6-dihydroxybenzoic acid was dissolved, it was confirmed that the sensor response increased with the concentration of caffeine as well as allied substances. The threshold and increase tendency were consistent with those of human senses. The detection mechanism is discussed by taking into account intramolecular and intermolecular hydrogen bonds, which cause allostery. These findings suggest that it is possible to evaluate bitterness caused by non-charged bitter substances objectively by using the taste sensor with allosteric mechanism. Full article
(This article belongs to the Section Chemical Sensors)
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11 pages, 1643 KiB  
Article
Intelligent Data Management and Security in Cloud Computing
by Lidia Ogiela, Marek R. Ogiela and Hoon Ko
Sensors 2020, 20(12), 3458; https://doi.org/10.3390/s20123458 - 18 Jun 2020
Cited by 46 | Viewed by 3829
Abstract
This paper will present the authors’ own techniques of secret data management and protection, with particular attention paid to techniques securing data services. Among the solutions discussed, there will be information-sharing protocols dedicated to the tasks of secret (confidential) data sharing. Such solutions [...] Read more.
This paper will present the authors’ own techniques of secret data management and protection, with particular attention paid to techniques securing data services. Among the solutions discussed, there will be information-sharing protocols dedicated to the tasks of secret (confidential) data sharing. Such solutions will be presented in an algorithmic form, aimed at solving the tasks of protecting and securing data against unauthorized acquisition. Data-sharing protocols will execute the tasks of securing a special type of information, i.e., data services. The area of data protection will be defined for various levels, within which will be executed the tasks of data management and protection. The authors’ solution concerning securing data with the use of cryptographic threshold techniques used to split the secret among a specified group of secret trustees, simultaneously enhanced by the application of linguistic methods of description of the shared secret, forms a new class of protocols, i.e., intelligent linguistic threshold schemes. The solutions presented in this paper referring to the service management and securing will be dedicated to various levels of data management. These levels could be differentiated both in the structure of a given entity and in its environment. There is a special example thereof, i.e., the cloud management processes. These will also be subject to the assessment of feasibility of application of the discussed protocols in these areas. Presented solutions will be based on the application of an innovative approach, in which we can use a special formal graph for the creation of a secret representation, which can then be divided and transmitted over a distributed network. Full article
(This article belongs to the Special Issue Selected Papers from the 11-th International Conference on Intelligent Networking and Collaborative Systems (INCoS-2019) and the 22nd International Conference on Network-Based Information Systems (NBiS-2019))
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13 pages, 3974 KiB  
Article
Magnetic Bioreactor for Magneto-, Mechano- and Electroactive Tissue Engineering Strategies
by Nelson Castro, Margarida M. Fernandes, Clarisse Ribeiro, Vítor Correia, Rikardo Minguez and Senentxu Lanceros-Méndez
Sensors 2020, 20(12), 3340; https://doi.org/10.3390/s20123340 - 12 Jun 2020
Cited by 23 | Viewed by 4127
Abstract
Biomimetic bioreactor systems are increasingly being developed for tissue engineering applications, due to their ability to recreate the native cell/tissue microenvironment. Regarding bone-related diseases and considering the piezoelectric nature of bone, piezoelectric scaffolds electromechanically stimulated by a bioreactor, providing the stimuli to the [...] Read more.
Biomimetic bioreactor systems are increasingly being developed for tissue engineering applications, due to their ability to recreate the native cell/tissue microenvironment. Regarding bone-related diseases and considering the piezoelectric nature of bone, piezoelectric scaffolds electromechanically stimulated by a bioreactor, providing the stimuli to the cells, allows a biomimetic approach and thus, mimicking the required microenvironment for effective growth and differentiation of bone cells. In this work, a bioreactor has been designed and built allowing to magnetically stimulate magnetoelectric scaffolds and therefore provide mechanical and electrical stimuli to the cells through magnetomechanical or magnetoelectrical effects, depending on the piezoelectric nature of the scaffold. While mechanical bioreactors need direct application of the stimuli on the scaffolds, the herein proposed magnetic bioreactors allow for a remote stimulation without direct contact with the material. Thus, the stimuli application (23 mT at a frequency of 0.3 Hz) to cells seeded on the magnetoelectric, leads to an increase in cell viability of almost 30% with respect to cell culture under static conditions. This could be valuable to mimic what occurs in the human body and for application in immobilized patients. Thus, special emphasis has been placed on the control, design and modeling parameters governing the bioreactor as well as its functional mechanism. Full article
(This article belongs to the Special Issue Electronics for Sensors)
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23 pages, 704 KiB  
Review
Internet of Robotic Things in Smart Domains: Applications and Challenges
by Laura Romeo, Antonio Petitti, Roberto Marani and Annalisa Milella
Sensors 2020, 20(12), 3355; https://doi.org/10.3390/s20123355 - 12 Jun 2020
Cited by 84 | Viewed by 13769
Abstract
With the advent of the Fourth Industrial Revolution, Internet of Things (IoT) and robotic systems are closely cooperating, reshaping their relations and managing to develop new-generation devices. Such disruptive technology corresponds to the backbone of the so-called Industry 4.0. The integration of robotic [...] Read more.
With the advent of the Fourth Industrial Revolution, Internet of Things (IoT) and robotic systems are closely cooperating, reshaping their relations and managing to develop new-generation devices. Such disruptive technology corresponds to the backbone of the so-called Industry 4.0. The integration of robotic agents and IoT leads to the concept of the Internet of Robotic Things, in which innovation in digital systems is drawing new possibilities in both industrial and research fields, covering several domains such as manufacturing, agriculture, health, surveillance, and education, to name but a few. In this manuscript, the state-of-the-art of IoRT applications is outlined, aiming to mark their impact on several research fields, and focusing on the main open challenges of the integration of robotic technologies into smart spaces. IoRT technologies and applications are also discussed to underline their influence in everyday life, inducing the need for more research into remote and automated applications. Full article
(This article belongs to the Special Issue Robot and Sensor Networks for Environmental Monitoring)
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28 pages, 1397 KiB  
Review
MRI Segmentation and Classification of Human Brain Using Deep Learning for Diagnosis of Alzheimer’s Disease: A Survey
by Nagaraj Yamanakkanavar, Jae Young Choi and Bumshik Lee
Sensors 2020, 20(11), 3243; https://doi.org/10.3390/s20113243 - 7 Jun 2020
Cited by 125 | Viewed by 13861
Abstract
Many neurological diseases and delineating pathological regions have been analyzed, and the anatomical structure of the brain researched with the aid of magnetic resonance imaging (MRI). It is important to identify patients with Alzheimer’s disease (AD) early so that preventative measures can be [...] Read more.
Many neurological diseases and delineating pathological regions have been analyzed, and the anatomical structure of the brain researched with the aid of magnetic resonance imaging (MRI). It is important to identify patients with Alzheimer’s disease (AD) early so that preventative measures can be taken. A detailed analysis of the tissue structures from segmented MRI leads to a more accurate classification of specific brain disorders. Several segmentation methods to diagnose AD have been proposed with varying complexity. Segmentation of the brain structure and classification of AD using deep learning approaches has gained attention as it can provide effective results over a large set of data. Hence, deep learning methods are now preferred over state-of-the-art machine learning methods. We aim to provide an outline of current deep learning-based segmentation approaches for the quantitative analysis of brain MRI for the diagnosis of AD. Here, we report how convolutional neural network architectures are used to analyze the anatomical brain structure and diagnose AD, discuss how brain MRI segmentation improves AD classification, describe the state-of-the-art approaches, and summarize their results using publicly available datasets. Finally, we provide insight into current issues and discuss possible future research directions in building a computer-aided diagnostic system for AD. Full article
(This article belongs to the Section Biomedical Sensors)
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24 pages, 4632 KiB  
Article
Design and Intensive Experimental Evaluation of an Enhanced Visible Light Communication System for Automotive Applications
by Sebastian-Andrei Avătămăniței, Alin-Mihai Căilean, Adrian Done, Mihai Dimian, Valentin Popa and Marius Prelipceanu
Sensors 2020, 20(11), 3190; https://doi.org/10.3390/s20113190 - 4 Jun 2020
Cited by 15 | Viewed by 3579
Abstract
As the interest toward communication-based vehicle safety applications is increasing, the development of secure wireless communication techniques has become an important research area. In this context, the article addresses issues that are related to the use of the visible light communication (VLC) technology [...] Read more.
As the interest toward communication-based vehicle safety applications is increasing, the development of secure wireless communication techniques has become an important research area. In this context, the article addresses issues that are related to the use of the visible light communication (VLC) technology in vehicular applications. Thus, it provides an extensive presentation concerning the main challenges and issues that are associated to vehicular VLC applications and of some of the existing VLC solutions. Moreover, the article presents the aspects related to the design and intensive experimental evaluation of a new automotive VLC system. The experimental evaluation performed in indoor and outdoor conditions shows that the proposed system can achieve communication distances up to 50 m and bit error ratio (BER) lower than 10−6, while being exposed to optical and weather perturbations. This article provides important evidence concerning the snowfall effect on middle to long range outdoor VLC, as the proposed VLC system was also evaluated in snowfall conditions. Accordingly, the experimental evaluation showed that snowfall and heavy gust could increase bit error rate by up to 10,000 times. Even so, this article provides encouraging evidence that VLC systems will soon be able to reliably support V2X communications. Full article
(This article belongs to the Special Issue State-of-the-Art Indoor and Outdoor Visible Light Communications (VLC) Applications and Systems)
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18 pages, 3710 KiB  
Review
A Review of Bolt Tightening Force Measurement and Loosening Detection
by Rusong Miao, Ruili Shen, Songhan Zhang and Songling Xue
Sensors 2020, 20(11), 3165; https://doi.org/10.3390/s20113165 - 2 Jun 2020
Cited by 77 | Viewed by 8948
Abstract
Pre-stressed bolted joints are widely used in civil structures and industries. The tightening force of a bolt is crucial to the reliability of the joint connection. Loosening or over-tightening of a bolt may lead to connectors slipping or bolt strength failure, which are [...] Read more.
Pre-stressed bolted joints are widely used in civil structures and industries. The tightening force of a bolt is crucial to the reliability of the joint connection. Loosening or over-tightening of a bolt may lead to connectors slipping or bolt strength failure, which are both harmful to the main structure. In most practical cases it is extremely difficult, even impossible, to install the bolts to ensure there is a precise tension force during the construction phase. Furthermore, it is inevitable that the bolts will loosen due to long-term usage under high stress. The identification of bolt tension is therefore of great significance for monitoring the health of existing structures. This paper reviews state-of-the-art research on bolt tightening force measurement and loosening detection, including fundamental theories, algorithms, experimental set-ups, and practical applications. In general, methods based on the acoustoelastic principle are capable of calculating the value of bolt axial stress if both the time of incident wave and reflected wave can be clearly recognized. The relevant commercial instrument has been developed and its algorithm will be briefly introduced. Methods based on contact dynamic phenomena such as wave energy attenuation, high-order harmonics, sidebands, and impedance, are able to correlate interface stiffness and the clamping force of bolted joints with respective dynamic indicators. Therefore, they are able to detect or quantify bolt tightness. The related technologies will be reviewed in detail. Potential challenges and research trends will also be discussed. Full article
(This article belongs to the Section Fault Diagnosis & Sensors)
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19 pages, 3806 KiB  
Article
Strain Transfer in Surface-Bonded Optical Fiber Sensors
by Francesco Falcetelli, Leonardo Rossi, Raffaella Di Sante and Gabriele Bolognini
Sensors 2020, 20(11), 3100; https://doi.org/10.3390/s20113100 - 30 May 2020
Cited by 57 | Viewed by 4687
Abstract
Fiber optic sensors represent one of the most promising technologies for the monitoring of various engineering structures. A major challenge in the field is to analyze and predict the strain transfer to the fiber core reliably. Many authors developed analytical models of a [...] Read more.
Fiber optic sensors represent one of the most promising technologies for the monitoring of various engineering structures. A major challenge in the field is to analyze and predict the strain transfer to the fiber core reliably. Many authors developed analytical models of a coated optical fiber, assuming null strain at the ends of the bonding length. However, this configuration only partially reflects real experimental setups in which the cable structure can be more complex and the strains do not drastically reduce to zero. In this study, a novel strain transfer model for surface-bonded sensing cables with multilayered structure was developed. The analytical model was validated both experimentally and numerically, considering two surface-mounted cable prototypes with three different bonding lengths and five load cases. The results demonstrated the capability of the model to predict the strain profile and, differently from the available strain transfer models, that the strain values at the extremities of the bonded fiber length are not null. Full article
(This article belongs to the Special Issue Fiber Optic Sensing Technology)
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24 pages, 943 KiB  
Article
IoT-Blockchain Enabled Optimized Provenance System for Food Industry 4.0 Using Advanced Deep Learning
by Prince Waqas Khan, Yung-Cheol Byun and Namje Park
Sensors 2020, 20(10), 2990; https://doi.org/10.3390/s20102990 - 25 May 2020
Cited by 163 | Viewed by 13608
Abstract
Agriculture and livestock play a vital role in social and economic stability. Food safety and transparency in the food supply chain are a significant concern for many people. Internet of Things (IoT) and blockchain are gaining attention due to their success in versatile [...] Read more.
Agriculture and livestock play a vital role in social and economic stability. Food safety and transparency in the food supply chain are a significant concern for many people. Internet of Things (IoT) and blockchain are gaining attention due to their success in versatile applications. They generate a large amount of data that can be optimized and used efficiently by advanced deep learning (ADL) techniques. The importance of such innovations from the viewpoint of supply chain management is significant in different processes such as for broadened visibility, provenance, digitalization, disintermediation, and smart contracts. This article takes the secure IoT–blockchain data of Industry 4.0 in the food sector as a research object. Using ADL techniques, we propose a hybrid model based on recurrent neural networks (RNN). Therefore, we used long short-term memory (LSTM) and gated recurrent units (GRU) as a prediction model and genetic algorithm (GA) optimization jointly to optimize the parameters of the hybrid model. We select the optimal training parameters by GA and finally cascade LSTM with GRU. We evaluated the performance of the proposed system for a different number of users. This paper aims to help supply chain practitioners to take advantage of the state-of-the-art technologies; it will also help the industry to make policies according to the predictions of ADL. Full article
(This article belongs to the Special Issue Blockchain Security and Privacy for the Internet of Things)
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11 pages, 1358 KiB  
Article
SPR Biosensor Based on Polymer Multi-Mode Optical Waveguide and Nanoparticle Signal Enhancement
by Johanna-Gabriela Walter, Alina Eilers, Lourdes Shanika Malindi Alwis, Bernhard Wilhelm Roth and Kort Bremer
Sensors 2020, 20(10), 2889; https://doi.org/10.3390/s20102889 - 20 May 2020
Cited by 47 | Viewed by 5918
Abstract
We present a surface plasmon resonance (SPR) biosensor that is based on a planar-optical multi-mode (MM) polymer waveguide structure applied for the detection of biomolecules in the lower nano-molar (nM) range. The basic sensor shows a sensitivity of 608.6 nm/RIU when exposed to [...] Read more.
We present a surface plasmon resonance (SPR) biosensor that is based on a planar-optical multi-mode (MM) polymer waveguide structure applied for the detection of biomolecules in the lower nano-molar (nM) range. The basic sensor shows a sensitivity of 608.6 nm/RIU when exposed to refractive index changes with a measurement resolution of 4.3 × 10−3 RIU. By combining the SPR sensor with an aptamer-functionalized, gold-nanoparticle (AuNP)-enhanced sandwich assay, the detection of C-reactive protein (CRP) in a buffer solution was achieved with a response of 0.118 nm/nM. Due to the multi-mode polymer waveguide structure and the simple concept, the reported biosensor is well suited for low-cost disposable lab-on-a-chip applications and can be used with rather simple and economic devices. In particular, the sensor offers the potential for fast and multiplexed detection of several biomarkers on a single integrated platform. Full article
(This article belongs to the Collection Photonic Sensors)
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15 pages, 4764 KiB  
Article
YOLO-Based Simultaneous Target Detection and Classification in Automotive FMCW Radar Systems
by Woosuk Kim, Hyunwoong Cho, Jongseok Kim, Byungkwan Kim and Seongwook Lee
Sensors 2020, 20(10), 2897; https://doi.org/10.3390/s20102897 - 20 May 2020
Cited by 48 | Viewed by 6883
Abstract
This paper proposes a method to simultaneously detect and classify objects by using a deep learning model, specifically you only look once (YOLO), with pre-processed automotive radar signals. In conventional methods, the detection and classification in automotive radar systems are conducted in two [...] Read more.
This paper proposes a method to simultaneously detect and classify objects by using a deep learning model, specifically you only look once (YOLO), with pre-processed automotive radar signals. In conventional methods, the detection and classification in automotive radar systems are conducted in two successive stages; however, in the proposed method, the two stages are combined into one. To verify the effectiveness of the proposed method, we applied it to the actual radar data measured using our automotive radar sensor. According to the results, our proposed method can simultaneously detect targets and classify them with over 90% accuracy. In addition, it shows better performance in terms of detection and classification, compared with conventional methods such as density-based spatial clustering of applications with noise or the support vector machine. Moreover, the proposed method especially exhibits better performance when detecting and classifying a vehicle with a long body. Full article
(This article belongs to the Section Electronic Sensors)
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15 pages, 16733 KiB  
Article
Feasibility of a Wearable Reflectometric System for Sensing Skin Hydration
by Raissa Schiavoni, Giuseppina Monti, Emanuele Piuzzi, Luciano Tarricone, Annarita Tedesco, Egidio De Benedetto and Andrea Cataldo
Sensors 2020, 20(10), 2833; https://doi.org/10.3390/s20102833 - 16 May 2020
Cited by 35 | Viewed by 4931
Abstract
One of the major goals of Health 4.0 is to offer personalized care to patients, also through real-time, remote monitoring of their biomedical parameters. In this regard, wearable monitoring systems are crucial to deliver continuous appropriate care. For some biomedical parameters, there are [...] Read more.
One of the major goals of Health 4.0 is to offer personalized care to patients, also through real-time, remote monitoring of their biomedical parameters. In this regard, wearable monitoring systems are crucial to deliver continuous appropriate care. For some biomedical parameters, there are a number of well established systems that offer adequate solutions for real-time, continuous patient monitoring. On the other hand, monitoring skin hydration still remains a challenging task. The continuous monitoring of this physiological parameter is extremely important in several contexts, for example for athletes, sick people, workers in hostile environments or for the elderly. State-of-the-art systems, however, exhibit some limitations, especially related with the possibility of continuous, real-time monitoring. Starting from these considerations, in this work, the feasibility of an innovative time-domain reflectometry (TDR)-based wearable, skin hydration sensing system for real-time, continuous monitoring of skin hydration level was investigated. The applicability of the proposed system was demonstrated, first, through experimental tests on reference substances, then, directly on human skin. The obtained results demonstrate the TDR technique and the proposed system holds unexplored potential for the aforementioned purposes. Full article
(This article belongs to the Special Issue Wearable Devices and Sensors for Innovative Monitoring Systems in the 4.0 Era)
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21 pages, 547 KiB  
Article
Heart Rate Variability and Accelerometry as Classification Tools for Monitoring Perceived Stress Levels—A Pilot Study on Firefighters
by Michał Meina, Ewa Ratajczak, Maria Sadowska, Krzysztof Rykaczewski, Joanna Dreszer, Bibianna Bałaj, Stanisław Biedugnis, Wojciech Węgrzyński and Adam Krasuski
Sensors 2020, 20(10), 2834; https://doi.org/10.3390/s20102834 - 16 May 2020
Cited by 21 | Viewed by 5383
Abstract
Chronic stress is the main cause of health problems in high-risk jobs. Wearable sensors can become an ecologically valid method of stress level assessment in real-life applications. We sought to determine a non-invasive technique for objective stress monitoring. Data were collected from firefighters [...] Read more.
Chronic stress is the main cause of health problems in high-risk jobs. Wearable sensors can become an ecologically valid method of stress level assessment in real-life applications. We sought to determine a non-invasive technique for objective stress monitoring. Data were collected from firefighters during 24-h shifts using sensor belts equipped with a dry-lead electrocardiograph (ECG) and a three-axial accelerometer. Levels of stress experienced during fire incidents were evaluated via a brief self-assessment questionnaire. Types of physical activity were distinguished basing on accelerometer readings, and heart rate variability (HRV) time series were segmented accordingly into corresponding fragments. Those segments were classified as stress/no-stress conditions. Receiver Operating Characteristic (ROC) analysis showed true positive classification as stress condition for 15% of incidents (while maintaining almost zero False Positive Rate), which parallels the amount of truly stressful incidents reported in the questionnaires. These results show a firm correspondence between the perceived stress level and physiological data. Psychophysiological measurements are reliable indicators of stress even in ecological settings and appear promising for chronic stress monitoring in high-risk jobs, such as firefighting. Full article
(This article belongs to the Collection Sensors for Gait, Human Movement Analysis, and Health Monitoring)
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22 pages, 4327 KiB  
Review
IoT Wearable Sensors and Devices in Elderly Care: A Literature Review
by Thanos G. Stavropoulos, Asterios Papastergiou, Lampros Mpaltadoros, Spiros Nikolopoulos and Ioannis Kompatsiaris
Sensors 2020, 20(10), 2826; https://doi.org/10.3390/s20102826 - 16 May 2020
Cited by 177 | Viewed by 24583
Abstract
The increasing ageing global population is causing an upsurge in ailments related to old age, primarily dementia and Alzheimer’s disease, frailty, Parkinson’s, and cardiovascular disease, but also a general need for general eldercare as well as active and healthy ageing. In turn, there [...] Read more.
The increasing ageing global population is causing an upsurge in ailments related to old age, primarily dementia and Alzheimer’s disease, frailty, Parkinson’s, and cardiovascular disease, but also a general need for general eldercare as well as active and healthy ageing. In turn, there is a need for constant monitoring and assistance, intervention, and support, causing a considerable financial and human burden on individuals and their caregivers. Interconnected sensing technology, such as IoT wearables and devices, present a promising solution for objective, reliable, and remote monitoring, assessment, and support through ambient assisted living. This paper presents a review of such solutions including both earlier review studies and individual case studies, rapidly evolving in the last decade. In doing so, it examines and categorizes them according to common aspects of interest such as health focus, from specific ailments to general eldercare; IoT technologies, from wearables to smart home sensors; aims, from assessment to fall detection and indoor positioning to intervention; and experimental evaluation participants duration and outcome measures, from acceptability to accuracy. Statistics drawn from this categorization aim to outline the current state-of-the-art, as well as trends and effective practices for the future of effective, accessible, and acceptable eldercare with technology. Full article
(This article belongs to the Special Issue Smart Sensors for eHealth Applications)
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15 pages, 3607 KiB  
Article
Hollow-Core Photonic Crystal Fiber Mach–Zehnder Interferometer for Gas Sensing
by Kaveh Nazeri, Farid Ahmed, Vahid Ahsani, Hang-Eun Joe, Colin Bradley, Ehsan Toyserkani and Martin B. G. Jun
Sensors 2020, 20(10), 2807; https://doi.org/10.3390/s20102807 - 15 May 2020
Cited by 26 | Viewed by 4389
Abstract
A novel and compact interferometric refractive index (RI) point sensor is developed using hollow-core photonic crystal fiber (HC-PCF) and experimentally demonstrated for high sensitivity detection and measurement of pure gases. To construct the device, the sensing element fiber (HC-PCF) was placed between two [...] Read more.
A novel and compact interferometric refractive index (RI) point sensor is developed using hollow-core photonic crystal fiber (HC-PCF) and experimentally demonstrated for high sensitivity detection and measurement of pure gases. To construct the device, the sensing element fiber (HC-PCF) was placed between two single-mode fibers with airgaps at each side. Great measurement repeatability was shown in the cyclic test for the detection of various gases. The RI sensitivity of 4629 nm/RIU was demonstrated in the RI range of 1.0000347–1.000436 for the sensor with an HC-PCF length of 3.3 mm. The sensitivity of the proposed Mach–Zehnder interferometer (MZI) sensor increases when the length of the sensing element decreases. It is shown that response and recovery times of the proposed sensor inversely change with the length of HC-PCF. Besides, spatial frequency analysis for a wide range of air-gaps revealed information on the number and power distribution of modes. It is shown that the power is mainly carried by two dominant modes in the proposed structure. The proposed sensors have the potential to improve current technology’s ability to detect and quantify pure gases. Full article
(This article belongs to the Special Issue Fiber Optic Sensors in Chemical and Biological Applications)
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23 pages, 24525 KiB  
Article
Vulnerability Assessment of Buildings due to Land Subsidence Using InSAR Data in the Ancient Historical City of Pistoia (Italy)
by Pablo Ezquerro, Matteo Del Soldato, Lorenzo Solari, Roberto Tomás, Federico Raspini, Mattia Ceccatelli, José Antonio Fernández-Merodo, Nicola Casagli and Gerardo Herrera
Sensors 2020, 20(10), 2749; https://doi.org/10.3390/s20102749 - 12 May 2020
Cited by 38 | Viewed by 5991
Abstract
The launch of the medium resolution Synthetic Aperture Radar (SAR) Sentinel-1 constellation in 2014 has allowed public and private organizations to introduce SAR interferometry (InSAR) products as a valuable option in their monitoring systems. The massive stacks of displacement data resulting from the [...] Read more.
The launch of the medium resolution Synthetic Aperture Radar (SAR) Sentinel-1 constellation in 2014 has allowed public and private organizations to introduce SAR interferometry (InSAR) products as a valuable option in their monitoring systems. The massive stacks of displacement data resulting from the processing of large C-B and radar images can be used to highlight temporal and spatial deformation anomalies, and their detailed analysis and postprocessing to generate operative products for final users. In this work, the wide-area mapping capability of Sentinel-1 was used in synergy with the COSMO-SkyMed high resolution SAR data to characterize ground subsidence affecting the urban fabric of the city of Pistoia (Tuscany Region, central Italy). Line of sight velocities were decomposed on vertical and E–W components, observing slight horizontal movements towards the center of the subsidence area. Vertical displacements and damage field surveys allowed for the calculation of the probability of damage depending on the displacement velocity by means of fragility curves. Finally, these data were translated to damage probability and potential loss maps. These products are useful for urban planning and geohazard management, focusing on the identification of the most hazardous areas on which to concentrate efforts and resources. Full article
(This article belongs to the Special Issue Remote Sensing of Geohazards)
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15 pages, 7228 KiB  
Article
Examination of Multi-Receiver GPS/EGNOS Positioning with Kalman Filtering and Validation Based on CORS Stations
by Adam Ciećko, Mieczysław Bakuła, Grzegorz Grunwald and Janusz Ćwiklak
Sensors 2020, 20(9), 2732; https://doi.org/10.3390/s20092732 - 11 May 2020
Cited by 21 | Viewed by 4338
Abstract
This paper presents the concept of precise navigation based on SBAS technology and CORS stations. In a kinematic test, three rover Global Positioning System (GPS) receivers, properly spaced relatively to each other, were used in order to estimate reliable and redundant GPS/EGNOS positions. [...] Read more.
This paper presents the concept of precise navigation based on SBAS technology and CORS stations. In a kinematic test, three rover Global Positioning System (GPS) receivers, properly spaced relatively to each other, were used in order to estimate reliable and redundant GPS/EGNOS positions. Next, the Kalman filter was employed to give the final solution. It was proven that EGNOS positioning allows to obtain an accuracy in the range of about 0.5–1.5 m. The proposed solution involving the use of three mobile receivers and Kalman filtering allowed to reduce the 3D error to a level below 0.3 m. Such an accuracy was achieved using only GPS L1 code observations and EGNOS corrections. Additionally, a reliable monitoring of quality of GPS/EGNOS positioning in the test area based on CORS stations was presented. Full article
(This article belongs to the Special Issue GNSS Sensors in Aerial Navigation)
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10 pages, 1353 KiB  
Article
Multi-Addressed Fiber Bragg Structures for Microwave-Photonic Sensor Systems
by Oleg Morozov, Airat Sakhabutdinov, Vladimir Anfinogentov, Rinat Misbakhov, Artem Kuznetsov and Timur Agliullin
Sensors 2020, 20(9), 2693; https://doi.org/10.3390/s20092693 - 9 May 2020
Cited by 27 | Viewed by 3703
Abstract
The new theory and technique of Multi-Addressed Fiber Bragg Structure (MAFBS) usage in Microwave Photonics Sensor Systems (MPSS) is presented. This theory is the logical evolution of the theory of Addressed Fiber Bragg Structure (AFBS) usage as sensors in MPSS. The mathematical model [...] Read more.
The new theory and technique of Multi-Addressed Fiber Bragg Structure (MAFBS) usage in Microwave Photonics Sensor Systems (MPSS) is presented. This theory is the logical evolution of the theory of Addressed Fiber Bragg Structure (AFBS) usage as sensors in MPSS. The mathematical model of additive response from a single MAFBS is presented. The MAFBS is a special type of Fiber Bragg Gratings (FBG), the reflection spectrum of which has three (or more) narrow notches. The frequencies of narrow notches are located in the infrared range of electromagnetic spectrum, while differences between them are located in the microwave frequency range. All cross-differences between optical frequencies of single MAFBS are called the address frequencies set. When the additive optical response from a single MAFBS, passed through an optic filter with an oblique amplitude–frequency characteristic, is received on a photodetector, the complex electrical signal, which consists of all cross-frequency beatings of all optical frequencies, which are included in this optical signal, is taken at its output. This complex electrical signal at the photodetector’s output contains enough information to determine the central frequency shift of the MAFBS. The method of address frequencies analysis with the microwave-photonic measuring conversion method, which allows us to define the central frequency shift of a single MAFBS, is discussed in the work. Full article
(This article belongs to the Special Issue Fiber Bragg Grating Based Sensors and Systems)
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23 pages, 3702 KiB  
Review
How Reliable Is the Electrochemical Readout of MIP Sensors?
by Aysu Yarman and Frieder W. Scheller
Sensors 2020, 20(9), 2677; https://doi.org/10.3390/s20092677 - 8 May 2020
Cited by 52 | Viewed by 6246
Abstract
Electrochemical methods offer the simple characterization of the synthesis of molecularly imprinted polymers (MIPs) and the readouts of target binding. The binding of electroinactive analytes can be detected indirectly by their modulating effect on the diffusional permeability of a redox marker through thin [...] Read more.
Electrochemical methods offer the simple characterization of the synthesis of molecularly imprinted polymers (MIPs) and the readouts of target binding. The binding of electroinactive analytes can be detected indirectly by their modulating effect on the diffusional permeability of a redox marker through thin MIP films. However, this process generates an overall signal, which may include nonspecific interactions with the nonimprinted surface and adsorption at the electrode surface in addition to (specific) binding to the cavities. Redox-active low-molecular-weight targets and metalloproteins enable a more specific direct quantification of their binding to MIPs by measuring the faradaic current. The in situ characterization of enzymes, MIP-based mimics of redox enzymes or enzyme-labeled targets, is based on the indication of an electroactive product. This approach allows the determination of both the activity of the bio(mimetic) catalyst and of the substrate concentration. Full article
(This article belongs to the Special Issue Innovative Strategy of MIP Sensors on the Road to Practical Applications)
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25 pages, 1481 KiB  
Article
Machine Learning on Mainstream Microcontrollers
by Fouad Sakr, Francesco Bellotti, Riccardo Berta and Alessandro De Gloria
Sensors 2020, 20(9), 2638; https://doi.org/10.3390/s20092638 - 5 May 2020
Cited by 64 | Viewed by 8382
Abstract
This paper presents the Edge Learning Machine (ELM), a machine learning framework for edge devices, which manages the training phase on a desktop computer and performs inferences on microcontrollers. The framework implements, in a platform-independent C language, three supervised machine learning algorithms (Support [...] Read more.
This paper presents the Edge Learning Machine (ELM), a machine learning framework for edge devices, which manages the training phase on a desktop computer and performs inferences on microcontrollers. The framework implements, in a platform-independent C language, three supervised machine learning algorithms (Support Vector Machine (SVM) with a linear kernel, k-Nearest Neighbors (K-NN), and Decision Tree (DT)), and exploits STM X-Cube-AI to implement Artificial Neural Networks (ANNs) on STM32 Nucleo boards. We investigated the performance of these algorithms on six embedded boards and six datasets (four classifications and two regression). Our analysis—which aims to plug a gap in the literature—shows that the target platforms allow us to achieve the same performance score as a desktop machine, with a similar time latency. ANN performs better than the other algorithms in most cases, with no difference among the target devices. We observed that increasing the depth of an NN improves performance, up to a saturation level. k-NN performs similarly to ANN and, in one case, even better, but requires all the training sets to be kept in the inference phase, posing a significant memory demand, which can be afforded only by high-end edge devices. DT performance has a larger variance across datasets. In general, several factors impact performance in different ways across datasets. This highlights the importance of a framework like ELM, which is able to train and compare different algorithms. To support the developer community, ELM is released on an open-source basis. Full article
(This article belongs to the Special Issue Applications in Electronics Pervading Industry, Environment and Society – Sensing Systems and Pervasive Intelligence)
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8 pages, 1900 KiB  
Article
Design Rule of Mach-Zehnder Interferometer Sensors for Ultra-High Sensitivity
by Yiwei Xie, Ming Zhang and Daoxin Dai
Sensors 2020, 20(9), 2640; https://doi.org/10.3390/s20092640 - 5 May 2020
Cited by 33 | Viewed by 5347
Abstract
A design rule for a Mach-Zehnder interferometer (MZI) sensor is presented, allowing tunable sensitivity by appropriately choosing the MZI arm lengths according to the formula given in this paper. The present MZI sensor designed by this method can achieve an ultra-high sensitivity, which [...] Read more.
A design rule for a Mach-Zehnder interferometer (MZI) sensor is presented, allowing tunable sensitivity by appropriately choosing the MZI arm lengths according to the formula given in this paper. The present MZI sensor designed by this method can achieve an ultra-high sensitivity, which is much higher than any other traditional MZI sensors. An example is given with silicon-on-insulator (SOI) nanowires and the device sensitivity is as high as 106 nm/refractive-index -unit (or even higher), by choosing the MZI arms appropriately. This makes it possible for one to realize a low-cost optical sensing system with a detection limit as high as 10−6 refractive-index-unit, even when a cheap optical spectrum analyzer with low-resolution (e.g., 1 nm) is used for the wavelength-shift measurement. Full article
(This article belongs to the Section Optical Sensors)
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19 pages, 3275 KiB  
Article
Evaluation of Two Low-Cost Optical Particle Counters for the Measurement of Ambient Aerosol Scattering Coefficient and Ångström Exponent
by Krzysztof M. Markowicz and Michał T. Chiliński
Sensors 2020, 20(9), 2617; https://doi.org/10.3390/s20092617 - 4 May 2020
Cited by 19 | Viewed by 4438
Abstract
The aerosol scattering coefficient and Ångström exponent (AE) are important parameters in the understanding of aerosol optical properties and aerosol direct effect. These parameters are usually measured by a nephelometer network which is under-represented geographically; however, a rapid growth of air-pollution monitoring, using [...] Read more.
The aerosol scattering coefficient and Ångström exponent (AE) are important parameters in the understanding of aerosol optical properties and aerosol direct effect. These parameters are usually measured by a nephelometer network which is under-represented geographically; however, a rapid growth of air-pollution monitoring, using low-cost particle sensors, may extend observation networks. This paper presents the results of co-located measurements of aerosol optical properties, such as the aerosol scattering coefficient and the scattering AE, using low-cost sensors and using a scientific-grade polar Aurora 4000 nephelometer. A high Pearson correlation coefficient (0.94–0.96) between the low-cost particulate matter (PM) mass concentration and the aerosol scattering coefficient was found. For the PM10 mass concentration, the aerosol scattering coefficient relation is linear for the Dfrobot SEN0177 sensor and non-linear for the Alphasense OPC-N2 device. After regression analyses, both low-cost instruments provided the aerosol scattering coefficient with a similar mean square error difference (RMSE) of about 20 Mm−1, which corresponds to about 27% of the mean aerosol scattering coefficient. The relative uncertainty is independent of the pollution level. In addition, the ratio of aerosol number concentration between different bins showed a significant statistical (95% of confidence level) correlation with the scattering AE. For the SEN0177, the ratio of the particle number in bin 1 (radius of 0.15–0.25 µm) to bin 4 (radius of 1.25–2.5 µm) was a linear function of the scattering AE, with a Pearson correlation coefficient of 0.74. In the case of OPC-N2, the best correlation (r = 0.66) was found for the ratio between bin 1 (radius of 0.19–0.27 µm) and bin 2 (radius of 0.27–0.39 µm). Comparisons of an estimated scattering AE from a low-cost sensor with Aurora 4000 are given with the RMSE of 0.23–0.24, which corresponds to 16–19%. In addition, a three-year (2016–2019) observation by SEN0177 indicates that this sensor can be used to determine an annual cycle as well as a short-term variability. Full article
(This article belongs to the Special Issue Photonics-Based Sensors for Environment and Pollution Monitoring)
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12 pages, 1419 KiB  
Article
Blockchain-Based Healthcare Workflow for Tele-Medical Laboratory in Federated Hospital IoT Clouds
by Antonio Celesti, Armando Ruggeri, Maria Fazio, Antonino Galletta, Massimo Villari and Agata Romano
Sensors 2020, 20(9), 2590; https://doi.org/10.3390/s20092590 - 2 May 2020
Cited by 78 | Viewed by 7928
Abstract
In a pandemic situation such as that we are living at the time of writing of this paper due to the Covid-19 virus, the need of tele-healthcare service becomes dramatically fundamental to reduce the movement of patients, thence reducing the risk of infection. [...] Read more.
In a pandemic situation such as that we are living at the time of writing of this paper due to the Covid-19 virus, the need of tele-healthcare service becomes dramatically fundamental to reduce the movement of patients, thence reducing the risk of infection. Leveraging the recent Cloud computing and Internet of Things (IoT) technologies, this paper aims at proposing a tele-medical laboratory service where clinical exams are performed on patients directly in a hospital by technicians through IoT medical devices and results are automatically sent via the hospital Cloud to doctors of federated hospitals for validation and/or consultation. In particular, we discuss a distributed scenario where nurses, technicians and medical doctors belonging to different hospitals cooperate through their federated hospital Clouds to form a virtual health team able to carry out a healthcare workflow in secure fashion leveraging the intrinsic security features of the Blockchain technology. In particular, both public and hybrid Blockchain scenarios are discussed and assessed using the Ethereum platform. Full article
(This article belongs to the Special Issue Blockchain in the Internet of Things: Opportunities, Challenges and Solutions)
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37 pages, 7884 KiB  
Review
A Guideline for Effectively Synthesizing and Characterizing Magnetic Nanoparticles for Advancing Nanobiotechnology: A Review
by Mohammad Reza Zamani Kouhpanji and Bethanie J. H. Stadler
Sensors 2020, 20(9), 2554; https://doi.org/10.3390/s20092554 - 30 Apr 2020
Cited by 65 | Viewed by 5791
Abstract
The remarkable multimodal functionalities of magnetic nanoparticles, conferred by their size and morphology, are very important in resolving challenges slowing the progression of nanobiotechnology. The rapid and revolutionary expansion of magnetic nanoparticles in nanobiotechnology, especially in nanomedicine and therapeutics, demands an overview of [...] Read more.
The remarkable multimodal functionalities of magnetic nanoparticles, conferred by their size and morphology, are very important in resolving challenges slowing the progression of nanobiotechnology. The rapid and revolutionary expansion of magnetic nanoparticles in nanobiotechnology, especially in nanomedicine and therapeutics, demands an overview of the current state of the art for synthesizing and characterizing magnetic nanoparticles. In this review, we explain the synthesis routes for tailoring the size, morphology, composition, and magnetic properties of the magnetic nanoparticles. The pros and cons of the most popularly used characterization techniques for determining the aforementioned parameters, with particular focus on nanomedicine and biosensing applications, are discussed. Moreover, we provide numerous biomedical applications and highlight their challenges and requirements that must be met using the magnetic nanoparticles to achieve the most effective outcomes. Finally, we conclude this review by providing an insight towards resolving the persisting challenges and the future directions. This review should be an excellent source of information for beginners in this field who are looking for a groundbreaking start but they have been overwhelmed by the volume of literature. Full article
(This article belongs to the Special Issue Biosensors with Magnetic Nanocomponents)
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16 pages, 2643 KiB  
Article
UAV and Machine Learning Based Refinement of a Satellite-Driven Vegetation Index for Precision Agriculture
by Vittorio Mazzia, Lorenzo Comba, Aleem Khaliq, Marcello Chiaberge and Paolo Gay
Sensors 2020, 20(9), 2530; https://doi.org/10.3390/s20092530 - 29 Apr 2020
Cited by 82 | Viewed by 8590
Abstract
Precision agriculture is considered to be a fundamental approach in pursuing a low-input, high-efficiency, and sustainable kind of agriculture when performing site-specific management practices. To achieve this objective, a reliable and updated description of the local status of crops is required. Remote sensing, [...] Read more.
Precision agriculture is considered to be a fundamental approach in pursuing a low-input, high-efficiency, and sustainable kind of agriculture when performing site-specific management practices. To achieve this objective, a reliable and updated description of the local status of crops is required. Remote sensing, and in particular satellite-based imagery, proved to be a valuable tool in crop mapping, monitoring, and diseases assessment. However, freely available satellite imagery with low or moderate resolutions showed some limits in specific agricultural applications, e.g., where crops are grown by rows. Indeed, in this framework, the satellite’s output could be biased by intra-row covering, giving inaccurate information about crop status. This paper presents a novel satellite imagery refinement framework, based on a deep learning technique which exploits information properly derived from high resolution images acquired by unmanned aerial vehicle (UAV) airborne multispectral sensors. To train the convolutional neural network, only a single UAV-driven dataset is required, making the proposed approach simple and cost-effective. A vineyard in Serralunga d’Alba (Northern Italy) was chosen as a case study for validation purposes. Refined satellite-driven normalized difference vegetation index (NDVI) maps, acquired in four different periods during the vine growing season, were shown to better describe crop status with respect to raw datasets by correlation analysis and ANOVA. In addition, using a K-means based classifier, 3-class vineyard vigor maps were profitably derived from the NDVI maps, which are a valuable tool for growers. Full article
(This article belongs to the Special Issue Metrology for Agriculture and Forestry 2019)
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34 pages, 4149 KiB  
Review
Edge Machine Learning for AI-Enabled IoT Devices: A Review
by Massimo Merenda, Carlo Porcaro and Demetrio Iero
Sensors 2020, 20(9), 2533; https://doi.org/10.3390/s20092533 - 29 Apr 2020
Cited by 251 | Viewed by 30607
Abstract
In a few years, the world will be populated by billions of connected devices that will be placed in our homes, cities, vehicles, and industries. Devices with limited resources will interact with the surrounding environment and users. Many of these devices will be [...] Read more.
In a few years, the world will be populated by billions of connected devices that will be placed in our homes, cities, vehicles, and industries. Devices with limited resources will interact with the surrounding environment and users. Many of these devices will be based on machine learning models to decode meaning and behavior behind sensors’ data, to implement accurate predictions and make decisions. The bottleneck will be the high level of connected things that could congest the network. Hence, the need to incorporate intelligence on end devices using machine learning algorithms. Deploying machine learning on such edge devices improves the network congestion by allowing computations to be performed close to the data sources. The aim of this work is to provide a review of the main techniques that guarantee the execution of machine learning models on hardware with low performances in the Internet of Things paradigm, paving the way to the Internet of Conscious Things. In this work, a detailed review on models, architecture, and requirements on solutions that implement edge machine learning on Internet of Things devices is presented, with the main goal to define the state of the art and envisioning development requirements. Furthermore, an example of edge machine learning implementation on a microcontroller will be provided, commonly regarded as the machine learning “Hello World”. Full article
(This article belongs to the Special Issue Sensors and Smart Devices at the Edge: IoT Meets Edge Computing)
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18 pages, 951 KiB  
Review
A Review of IoT Sensing Applications and Challenges Using RFID and Wireless Sensor Networks
by Hugo Landaluce, Laura Arjona, Asier Perallos, Francisco Falcone, Ignacio Angulo and Florian Muralter
Sensors 2020, 20(9), 2495; https://doi.org/10.3390/s20092495 - 28 Apr 2020
Cited by 230 | Viewed by 19567
Abstract
Radio frequency identification (RFID) and wireless sensors networks (WSNs) are two fundamental pillars that enable the Internet of Things (IoT). RFID systems are able to identify and track devices, whilst WSNs cooperate to gather and provide information from interconnected sensors. This involves challenges, [...] Read more.
Radio frequency identification (RFID) and wireless sensors networks (WSNs) are two fundamental pillars that enable the Internet of Things (IoT). RFID systems are able to identify and track devices, whilst WSNs cooperate to gather and provide information from interconnected sensors. This involves challenges, for example, in transforming RFID systems with identification capabilities into sensing and computational platforms, as well as considering them as architectures of wirelessly connected sensing tags. This, together with the latest advances in WSNs and with the integration of both technologies, has resulted in the opportunity to develop novel IoT applications. This paper presents a review of these two technologies and the obstacles and challenges that need to be overcome. Some of these challenges are the efficiency of the energy harvesting, communication interference, fault tolerance, higher capacities to handling data processing, cost feasibility, and an appropriate integration of these factors. Additionally, two emerging trends in IoT are reviewed: the combination of RFID and WSNs in order to exploit their advantages and complement their limitations, and wearable sensors, which enable new promising IoT applications. Full article
(This article belongs to the Special Issue RFID and Wireless Sensor Networks: Recent Advances in the Design of IoT Applications)
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34 pages, 825 KiB  
Review
A Survey of Context-Aware Access Control Mechanisms for Cloud and Fog Networks: Taxonomy and Open Research Issues
by A. S. M. Kayes, Rudri Kalaria, Iqbal H. Sarker, Md. Saiful Islam, Paul A. Watters, Alex Ng, Mohammad Hammoudeh, Shahriar Badsha and Indika Kumara
Sensors 2020, 20(9), 2464; https://doi.org/10.3390/s20092464 - 27 Apr 2020
Cited by 55 | Viewed by 7530
Abstract
Over the last few decades, the proliferation of the Internet of Things (IoT) has produced an overwhelming flow of data and services, which has shifted the access control paradigm from a fixed desktop environment to dynamic cloud environments. Fog computing is associated with [...] Read more.
Over the last few decades, the proliferation of the Internet of Things (IoT) has produced an overwhelming flow of data and services, which has shifted the access control paradigm from a fixed desktop environment to dynamic cloud environments. Fog computing is associated with a new access control paradigm to reduce the overhead costs by moving the execution of application logic from the centre of the cloud data sources to the periphery of the IoT-oriented sensor networks. Indeed, accessing information and data resources from a variety of IoT sources has been plagued with inherent problems such as data heterogeneity, privacy, security and computational overheads. This paper presents an extensive survey of security, privacy and access control research, while highlighting several specific concerns in a wide range of contextual conditions (e.g., spatial, temporal and environmental contexts) which are gaining a lot of momentum in the area of industrial sensor and cloud networks. We present different taxonomies, such as contextual conditions and authorization models, based on the key issues in this area and discuss the existing context-sensitive access control approaches to tackle the aforementioned issues. With the aim of reducing administrative and computational overheads in the IoT sensor networks, we propose a new generation of Fog-Based Context-Aware Access Control (FB-CAAC) framework, combining the benefits of the cloud, IoT and context-aware computing; and ensuring proper access control and security at the edge of the end-devices. Our goal is not only to control context-sensitive access to data resources in the cloud, but also to move the execution of an application logic from the cloud-level to an intermediary-level where necessary, through adding computational nodes at the edge of the IoT sensor network. A discussion of some open research issues pertaining to context-sensitive access control to data resources is provided, including several real-world case studies. We conclude the paper with an in-depth analysis of the research challenges that have not been adequately addressed in the literature and highlight directions for future work that has not been well aligned with currently available research. Full article
(This article belongs to the Special Issue Security, Privacy, and Trustworthiness of Sensor Networks and Internet of Things)
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11 pages, 3501 KiB  
Article
Sensitivity Improvement of a Surface Plasmon Resonance Sensor Based on Two-Dimensional Materials Hybrid Structure in Visible Region: A Theoretical Study
by Zhining Lin, Shujing Chen and Chengyou Lin
Sensors 2020, 20(9), 2445; https://doi.org/10.3390/s20092445 - 25 Apr 2020
Cited by 43 | Viewed by 3628
Abstract
In this paper, we propose a surface plasmon resonance (SPR) sensor based on two-dimensional (2D) materials (graphene, MoS2, WS2 and WSe2) hybrid structure, and theoretically investigate its sensitivity improvement in the visible region. The thickness of metal (Au, [...] Read more.
In this paper, we propose a surface plasmon resonance (SPR) sensor based on two-dimensional (2D) materials (graphene, MoS2, WS2 and WSe2) hybrid structure, and theoretically investigate its sensitivity improvement in the visible region. The thickness of metal (Au, Ag or Cu) and the layer number of each 2D material are optimized using genetic algorithms to obtain the highest sensitivity for a specific wavelength of incident light. Then, the sensitivities of proposed SPR sensors with different metal films at various wavelengths are compared. An Ag-based SPR sensor exhibits a higher sensitivity than an Au- or Cu-based one at most wavelengths in the visible region. In addition, the sensitivity of the proposed SPR sensor varies obviously with the wavelength of incident light, and shows a maximum value of 159, 194 or 155°/RIU for Au, Ag or Cu, respectively. It is demonstrated that the sensitivity of the SPR sensor based on 2D materials’ hybrid structure can be further improved by optimizing the wavelength of incident light. Full article
(This article belongs to the Section Optical Sensors)
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26 pages, 18576 KiB  
Article
An IoT Platform Based on Microservices and Serverless Paradigms for Smart Farming Purposes
by Sergio Trilles, Alberto González-Pérez and Joaquín Huerta
Sensors 2020, 20(8), 2418; https://doi.org/10.3390/s20082418 - 24 Apr 2020
Cited by 62 | Viewed by 9248
Abstract
Nowadays, the concept of “Everything is connected to Everything” has spread to reach increasingly diverse scenarios, due to the benefits of constantly being able to know, in real-time, the status of your factory, your city, your health or your smallholding. This wide variety [...] Read more.
Nowadays, the concept of “Everything is connected to Everything” has spread to reach increasingly diverse scenarios, due to the benefits of constantly being able to know, in real-time, the status of your factory, your city, your health or your smallholding. This wide variety of scenarios creates different challenges such as the heterogeneity of IoT devices, support for large numbers of connected devices, reliable and safe systems, energy efficiency and the possibility of using this system by third-parties in other scenarios. A transversal middleware in all IoT solutions is called an IoT platform. the IoT platform is a piece of software that works like a kind of “glue” to combine platforms and orchestrate capabilities that connect devices, users and applications/services in a “cyber-physical” world. In this way, the IoT platform can help solve the challenges listed above. This paper proposes an IoT agnostic architecture, highlighting the role of the IoT platform, within a broader ecosystem of interconnected tools, aiming at increasing scalability, stability, interoperability and reusability. For that purpose, different paradigms of computing will be used, such as microservices architecture and serverless computing. Additionally, a technological proposal of the architecture, called SEnviro Connect, is presented. This proposal is validated in the IoT scenario of smart farming, where five IoT devices (SEnviro nodes) have been deployed to improve wine production. A comprehensive performance evaluation is carried out to guarantee a scalable and stable platform. Full article
(This article belongs to the Special Issue Smart Agricultural Applications with Internet of Things)
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15 pages, 2571 KiB  
Article
Effect of the Elastomer Matrix on Thermoplastic Elastomer-Based Strain Sensor Fiber Composites
by Antonia Georgopoulou, Claudia Kummerlöwe and Frank Clemens
Sensors 2020, 20(8), 2399; https://doi.org/10.3390/s20082399 - 23 Apr 2020
Cited by 19 | Viewed by 3540
Abstract
In this study, a thermoplastic elastomer sensor fiber was embedded in an elastomer matrix. The effect of the matrix material on the sensor properties and the piezoresistive behavior of the single fiber-matrix composite system was investigated. For all composites, cycling test (dynamic test) [...] Read more.
In this study, a thermoplastic elastomer sensor fiber was embedded in an elastomer matrix. The effect of the matrix material on the sensor properties and the piezoresistive behavior of the single fiber-matrix composite system was investigated. For all composites, cycling test (dynamic test) and the relaxation behavior at different strains (quasi-static test) were investigated. In all cases, dynamic properties and quasi-static significantly changed after embedding, compared to the pure fiber. The composite with the silicone elastomer PDMS (Polydimethylsiloxane) as matrix material exhibited deviation from linear response of the resistivity at low strains and proved an unsuitable choice compared to natural rubber. The addition of a spring construct in the embedded sensor fiber natural rubber composite improved the linearity at low strains but increased the mechanical and electrical hysteresis of the soft matter sensor composite. Using pre-vulcanized natural rubber improved linearity at low strains and reduced significantly the stress and relative resistance relaxation as well as the resistance hysteresis, especially if the resistance remained low. In both cases of the pre-vulcanized rubber and the spring structure, the piezoresistive behavior was improved, and at the same time, the stiffness of the system was increased indicating that using a stiffer matrix can be a strategy for improving the sensor properties. Full article
(This article belongs to the Section Sensor Materials)
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19 pages, 12592 KiB  
Article
Ultra-Wideband Diversity MIMO Antenna System for Future Mobile Handsets
by Naser Ojaroudi Parchin, Haleh Jahanbakhsh Basherlou, Yasir I. A. Al-Yasir, Ahmed M. Abdulkhaleq and Raed A. Abd-Alhameed
Sensors 2020, 20(8), 2371; https://doi.org/10.3390/s20082371 - 22 Apr 2020
Cited by 26 | Viewed by 4724
Abstract
A new ultra-wideband (UWB) multiple-input/multiple-output (MIMO) antenna system is proposed for future smartphones. The structure of the design comprises four identical pairs of compact microstrip-fed slot antennas with polarization diversity function that are placed symmetrically at different edge corners of the smartphone mainboard. [...] Read more.
A new ultra-wideband (UWB) multiple-input/multiple-output (MIMO) antenna system is proposed for future smartphones. The structure of the design comprises four identical pairs of compact microstrip-fed slot antennas with polarization diversity function that are placed symmetrically at different edge corners of the smartphone mainboard. Each antenna pair consists of an open-ended circular-ring slot radiator fed by two independently semi-arc-shaped microstrip-feeding lines exhibiting the polarization diversity characteristic. Therefore, in total, the proposed smartphone antenna design contains four horizontally-polarized and four vertically-polarized elements. The characteristics of the single-element dual-polarized UWB antenna and the proposed UWB-MIMO smartphone antenna are examined while using both experimental and simulated results. An impedance bandwidth of 2.5–10.2 GHz with 121% fractional bandwidth (FBW) is achieved for each element. However, for S11 ≤ −6 dB, this value is more than 130% (2.2–11 GHz). The proposed UWB-MIMO smartphone antenna system offers good isolation, dual-polarized function, full radiation coverage, and sufficient efficiency. Besides, the calculated diversity performances of the design in terms of the envelope correlation coefficient (ECC) and total active reflection coefficient (TARC) are very low over the entire operating band. Full article
(This article belongs to the Special Issue Antenna Design for 5G and Beyond)
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13 pages, 3030 KiB  
Article
Development of an Aptamer Based Luminescent Optical Fiber Sensor for the Continuous Monitoring of Hg2+ in Aqueous Media
by Nerea De Acha, César Elosúa and Francisco J. Arregui
Sensors 2020, 20(8), 2372; https://doi.org/10.3390/s20082372 - 22 Apr 2020
Cited by 21 | Viewed by 3432
Abstract
A fluorescent optical fiber sensor for the detection of mercury (Hg2+) ions in aqueous solutions is presented in this work. The sensor was based on a fluorophore-labeled thymine (T)-rich oligodeoxyribonucleotide (ON) sequence that was directly immobilized onto the tip of a [...] Read more.
A fluorescent optical fiber sensor for the detection of mercury (Hg2+) ions in aqueous solutions is presented in this work. The sensor was based on a fluorophore-labeled thymine (T)-rich oligodeoxyribonucleotide (ON) sequence that was directly immobilized onto the tip of a tapered optical fiber. In the presence of mercury ions, the formation of T–Hg2+-T mismatches quenches the fluorescence emission by the labeled fluorophore, which enables the measurement of Hg2+ ions in aqueous solutions. Thus, in contrast to commonly designed sensors, neither a fluorescence quencher nor a complementary ON sequence is required. The sensor presented a response time of 24.8 seconds toward 5 × 10−12 M Hg2+. It also showed both good reversibility (higher than the 95.8%) and selectivity: the I0/I variation was 10 times higher for Hg2+ ions than for Mn2+ ions. Other contaminants examined (Co2+, Ag+, Cd2+, Ni2+, Ca2+, Pb2+, Mn2+, Zn2+, Fe3+, and Cu2+) presented an even lower interference. The limit of detection of the sensor was 4.73 × 10−13 M Hg2+ in buffer solution and 9.03 × 10−13 M Hg2+ in ultrapure water, and was also able to detect 5 × 10−12 M Hg2+ in tap water. Full article
(This article belongs to the Special Issue Calibration of Chemical Sensors Based on Photoluminescence)
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18 pages, 3566 KiB  
Article
Privacy-Preserving Overgrid: Secure Data Collection for the Smart Grid
by Daniele Croce, Fabrizio Giuliano, Ilenia Tinnirello and Laura Giarré
Sensors 2020, 20(8), 2249; https://doi.org/10.3390/s20082249 - 16 Apr 2020
Cited by 8 | Viewed by 3078
Abstract
In this paper, we present a privacy-preserving scheme for Overgrid, a fully distributed peer-to-peer (P2P) architecture designed to automatically control and implement distributed Demand Response (DR) schemes in a community of smart buildings with energy generation and storage capabilities. To monitor the power [...] Read more.
In this paper, we present a privacy-preserving scheme for Overgrid, a fully distributed peer-to-peer (P2P) architecture designed to automatically control and implement distributed Demand Response (DR) schemes in a community of smart buildings with energy generation and storage capabilities. To monitor the power consumption of the buildings, while respecting the privacy of the users, we extend our previous Overgrid algorithms to provide privacy preserving data aggregation (PP-Overgrid). This new technique combines a distributed data aggregation scheme with the Secure Multi-Party Computation paradigm. First, we use the energy profiles of hundreds of buildings, classifying the amount of “flexible” energy consumption, i.e., the quota which could be potentially exploited for DR programs. Second, we consider renewable energy sources and apply the DR scheme to match the flexible consumption with the available energy. Finally, to show the feasibility of our approach, we validate the PP-Overgrid algorithm in simulation for a large network of smart buildings. Full article
(This article belongs to the Special Issue Sensor Based Smart Grid in Internet of Things Era)
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17 pages, 6799 KiB  
Article
Concrete Crack Monitoring Using a Novel Strain Transfer Model for Distributed Fiber Optics Sensors
by Antoine Bassil, Xavier Chapeleau, Dominique Leduc and Odile Abraham
Sensors 2020, 20(8), 2220; https://doi.org/10.3390/s20082220 - 15 Apr 2020
Cited by 60 | Viewed by 7217
Abstract
In this paper, we study the strain transfer mechanism between a host material and an optical fiber. A new analytical model handling imperfect bonding between layers is proposed. A general expression of the crack-induced strain transfer from fractured concrete material to optical fiber [...] Read more.
In this paper, we study the strain transfer mechanism between a host material and an optical fiber. A new analytical model handling imperfect bonding between layers is proposed. A general expression of the crack-induced strain transfer from fractured concrete material to optical fiber is established in the case of a multilayer system. This new strain transfer model is examined through performing wedge splitting tests on concrete specimens instrumented with embedded and surface-mounted fiber optic cables. The experimental results showed the validity of the crack-induced strain expression fitted to the distributed strains measured using an Optical Backscattering Reflectometry (OBR) system. As a result, precise estimations of the crack openings next to the optical cable location were achieved, as well as the monitoring of the optical cable response through following the strain lag parameter. Full article
(This article belongs to the Section Optical Sensors)
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16 pages, 915 KiB  
Review
Recent Development on the Electrochemical Detection of Selected Pesticides: A Focused Review
by Jafar Safaa Noori, John Mortensen and Alemnew Geto
Sensors 2020, 20(8), 2221; https://doi.org/10.3390/s20082221 - 15 Apr 2020
Cited by 70 | Viewed by 7859
Abstract
Pesticides are heavily used in agriculture to protect crops from diseases, insects, and weeds. However, only a fraction of the used pesticides reaches the target and the rest slips through the soil, causing the contamination of ground- and surface water resources. Given the [...] Read more.
Pesticides are heavily used in agriculture to protect crops from diseases, insects, and weeds. However, only a fraction of the used pesticides reaches the target and the rest slips through the soil, causing the contamination of ground- and surface water resources. Given the emerging interest in the on-site detection of analytes that can replace traditional chromatographic techniques, alternative methods for pesticide measuring have recently encountered remarkable attention. This review gives a focused overview of the literature related to the electrochemical detection of selected pesticides. Here, we focus on the electrochemical detection of three important pesticides; glyphosate, lindane and bentazone using a variety of electrochemical detection techniques, electrode materials, electrolyte media, and sample matrix. The review summarizes the different electrochemical studies and provides an overview of the analytical performances reported such as; the limits of detection and linearity range. This article highlights the advancements in pesticide detection of the selected pesticides using electrochemical methods and point towards the challenges and needed efforts to achieve electrochemical detection suitable for on-site applications. Full article
(This article belongs to the Section Electronic Sensors)
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26 pages, 2231 KiB  
Article
Towards a Remote Monitoring of Patient Vital Signs Based on IoT-Based Blockchain Integrity Management Platforms in Smart Hospitals
by Faisal Jamil, Shabir Ahmad, Naeem Iqbal and Do-Hyeun Kim
Sensors 2020, 20(8), 2195; https://doi.org/10.3390/s20082195 - 13 Apr 2020
Cited by 206 | Viewed by 19309
Abstract
Over the past several years, many healthcare applications have been developed to enhance the healthcare industry. Recent advancements in information technology and blockchain technology have revolutionized electronic healthcare research and industry. The innovation of miniaturized healthcare sensors for monitoring patient vital signs has [...] Read more.
Over the past several years, many healthcare applications have been developed to enhance the healthcare industry. Recent advancements in information technology and blockchain technology have revolutionized electronic healthcare research and industry. The innovation of miniaturized healthcare sensors for monitoring patient vital signs has improved and secured the human healthcare system. The increase in portable health devices has enhanced the quality of health-monitoring status both at an activity/fitness level for self-health tracking and at a medical level, providing more data to clinicians with potential for earlier diagnosis and guidance of treatment. When sharing personal medical information, data security and comfort are essential requirements for interaction with and collection of electronic medical records. However, it is hard for current systems to meet these requirements because they have inconsistent security policies and access control structures. The new solutions should be directed towards improving data access, and should be managed by the government in terms of privacy and security requirements to ensure the reliability of data for medical purposes. Blockchain paves the way for a revolution in the traditional pharmaceutical industry and benefits from unique features such as privacy and transparency of data. In this paper, we propose a novel platform for monitoring patient vital signs using smart contracts based on blockchain. The proposed system is designed and developed using hyperledger fabric, which is an enterprise-distributed ledger framework for developing blockchain-based applications. This approach provides several benefits to the patients, such as an extensive, immutable history log, and global access to medical information from anywhere at any time. The Libelium e-Health toolkit is used to acquire physiological data. The performance of the designed and developed system is evaluated in terms of transaction per second, transaction latency, and resource utilization using a standard benchmark tool known as Hyperledger Caliper. It is found that the proposed system outperforms the traditional health care system for monitoring patient data. Full article
(This article belongs to the Special Issue Blockchain Security and Privacy for the Internet of Things)
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18 pages, 1337 KiB  
Article
Edge Computing Resource Allocation for Dynamic Networks: The DRUID-NET Vision and Perspective
by Dimitrios Dechouniotis, Nikolaos Athanasopoulos, Aris Leivadeas, Nathalie Mitton, Raphael Jungers and Symeon Papavassiliou
Sensors 2020, 20(8), 2191; https://doi.org/10.3390/s20082191 - 13 Apr 2020
Cited by 29 | Viewed by 4671
Abstract
The potential offered by the abundance of sensors, actuators, and communications in the Internet of Things (IoT) era is hindered by the limited computational capacity of local nodes. Several key challenges should be addressed to optimally and jointly exploit the network, computing, and [...] Read more.
The potential offered by the abundance of sensors, actuators, and communications in the Internet of Things (IoT) era is hindered by the limited computational capacity of local nodes. Several key challenges should be addressed to optimally and jointly exploit the network, computing, and storage resources, guaranteeing at the same time feasibility for time-critical and mission-critical tasks. We propose the DRUID-NET framework to take upon these challenges by dynamically distributing resources when the demand is rapidly varying. It includes analytic dynamical modeling of the resources, offered workload, and networking environment, incorporating phenomena typically met in wireless communications and mobile edge computing, together with new estimators of time-varying profiles. Building on this framework, we aim to develop novel resource allocation mechanisms that explicitly include service differentiation and context-awareness, being capable of guaranteeing well-defined Quality of Service (QoS) metrics. DRUID-NET goes beyond the state of the art in the design of control algorithms by incorporating resource allocation mechanisms to the decision strategy itself. To achieve these breakthroughs, we combine tools from Automata and Graph theory, Machine Learning, Modern Control Theory, and Network Theory. DRUID-NET constitutes the first truly holistic, multidisciplinary approach that extends recent, albeit fragmented results from all aforementioned fields, thus bridging the gap between efforts of different communities. Full article
(This article belongs to the Special Issue Optimization and Communication in UAV Networks)
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20 pages, 741 KiB  
Review
A Review of Visual-LiDAR Fusion based Simultaneous Localization and Mapping
by César Debeunne and Damien Vivet
Sensors 2020, 20(7), 2068; https://doi.org/10.3390/s20072068 - 7 Apr 2020
Cited by 238 | Viewed by 23137
Abstract
Autonomous navigation requires both a precise and robust mapping and localization solution. In this context, Simultaneous Localization and Mapping (SLAM) is a very well-suited solution. SLAM is used for many applications including mobile robotics, self-driving cars, unmanned aerial vehicles, or autonomous underwater vehicles. [...] Read more.
Autonomous navigation requires both a precise and robust mapping and localization solution. In this context, Simultaneous Localization and Mapping (SLAM) is a very well-suited solution. SLAM is used for many applications including mobile robotics, self-driving cars, unmanned aerial vehicles, or autonomous underwater vehicles. In these domains, both visual and visual-IMU SLAM are well studied, and improvements are regularly proposed in the literature. However, LiDAR-SLAM techniques seem to be relatively the same as ten or twenty years ago. Moreover, few research works focus on vision-LiDAR approaches, whereas such a fusion would have many advantages. Indeed, hybridized solutions offer improvements in the performance of SLAM, especially with respect to aggressive motion, lack of light, or lack of visual features. This study provides a comprehensive survey on visual-LiDAR SLAM. After a summary of the basic idea of SLAM and its implementation, we give a complete review of the state-of-the-art of SLAM research, focusing on solutions using vision, LiDAR, and a sensor fusion of both modalities. Full article
(This article belongs to the Special Issue Autonomous Mobile Robots: Real-Time Sensing, Navigation, and Control)
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24 pages, 5501 KiB  
Article
LoRaFarM: A LoRaWAN-Based Smart Farming Modular IoT Architecture
by Gaia Codeluppi, Antonio Cilfone, Luca Davoli and Gianluigi Ferrari
Sensors 2020, 20(7), 2028; https://doi.org/10.3390/s20072028 - 4 Apr 2020
Cited by 117 | Viewed by 17883
Abstract
Presently, the adoption of Internet of Things (IoT)-related technologies in the Smart Farming domain is rapidly emerging. The ultimate goal is to collect, monitor, and effectively employ relevant data for agricultural processes, with the purpose of achieving an optimized and more environmentally sustainable [...] Read more.
Presently, the adoption of Internet of Things (IoT)-related technologies in the Smart Farming domain is rapidly emerging. The ultimate goal is to collect, monitor, and effectively employ relevant data for agricultural processes, with the purpose of achieving an optimized and more environmentally sustainable agriculture. In this paper, a low-cost, modular, and Long-Range Wide-Area Network (LoRaWAN)-based IoT platform, denoted as “LoRaWAN-based Smart Farming Modular IoT Architecture” (LoRaFarM), and aimed at improving the management of generic farms in a highly customizable way, is presented. The platform, built around a core middleware, is easily extensible with ad-hoc low-level modules (feeding the middleware with data coming from the sensors deployed in the farm) or high-level modules (providing advanced functionalities to the farmer). The proposed platform has been evaluated in a real farm in Italy, collecting environmental data (air/soil temperature and humidity) related to the growth of farm products (namely grapes and greenhouse vegetables) over a period of three months. A web-based visualization tool for the collected data is also presented, to validate the LoRaFarM architecture. Full article
(This article belongs to the Special Issue Metrology for Agriculture and Forestry 2019)
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17 pages, 684 KiB  
Article
Caching Transient Contents in Vehicular Named Data Networking: A Performance Analysis
by Marica Amadeo, Claudia Campolo, Giuseppe Ruggeri, Gianmarco Lia and Antonella Molinaro
Sensors 2020, 20(7), 1985; https://doi.org/10.3390/s20071985 - 2 Apr 2020
Cited by 28 | Viewed by 3508
Abstract
Named Data Networking (NDN) is a promising communication paradigm for the challenging vehicular ad hoc environment. In particular, the built-in pervasive caching capability was shown to be essential for effective data delivery in presence of short-lived and intermittent connectivity. Existing studies have however [...] Read more.
Named Data Networking (NDN) is a promising communication paradigm for the challenging vehicular ad hoc environment. In particular, the built-in pervasive caching capability was shown to be essential for effective data delivery in presence of short-lived and intermittent connectivity. Existing studies have however not considered the fact that multiple vehicular contents can be transient, i.e., they expire after a certain time period since they were generated, the so-called FreshnessPeriod in NDN. In this paper, we study the effects of caching transient contents in Vehicular NDN and present a simple yet effective freshness-driven caching decision strategy that vehicles can implement autonomously. Performance evaluation in ndnSIM shows that the FreshnessPeriod is a crucial parameter that deeply influences the cache hit ratio and, consequently, the data dissemination performance. Full article
(This article belongs to the Special Issue Vehicular Sensor Networks: Applications, Advances and Challenges)
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12 pages, 2264 KiB  
Article
A Syringe-Based Biosensor to Rapidly Detect Low Levels of Escherichia Coli (ECOR13) in Drinking Water Using Engineered Bacteriophages
by Troy C. Hinkley, Spencer Garing, Paras Jain, John Williford, Anne-Laure M. Le Ny, Kevin P. Nichols, Joseph E. Peters, Joey N. Talbert and Sam R. Nugen
Sensors 2020, 20(7), 1953; https://doi.org/10.3390/s20071953 - 31 Mar 2020
Cited by 17 | Viewed by 4119
Abstract
A sanitized drinking water supply is an unconditional requirement for public health and the overall prosperity of humanity. Potential microbial and chemical contaminants of drinking water have been identified by a joint effort between the World Health Organization (WHO) and the United Nations [...] Read more.
A sanitized drinking water supply is an unconditional requirement for public health and the overall prosperity of humanity. Potential microbial and chemical contaminants of drinking water have been identified by a joint effort between the World Health Organization (WHO) and the United Nations Children’s Fund (UNICEF), who together establish guidelines that define, in part, that the presence of Escherichia coli (E. coli) in drinking water is an indication of inadequate sanitation and a significant health risk. As E. coli is a nearly ubiquitous resident of mammalian gastrointestinal tracts, no detectable counts in 100 mL of drinking water is the standard used worldwide as an indicator of sanitation. The currently accepted EPA method relies on filtration, followed by growth on selective media, and requires 24–48 h from sample to results. In response, we developed a rapid bacteriophage-based detection assay with detection limit capabilities comparable to traditional methods in less than a quarter of the time. We coupled membrane filtration with selective enrichment using genetically engineered bacteriophages to identify less than 20 colony forming units (CFU) E. coli in 100 mL drinking water within 5 h. The combination of membrane filtration with phage infection produced a novel assay that demonstrated a rapid, selective, and sensitive detection of an indicator organism in large volumes of drinking water as recommended by the leading world regulatory authorities. Full article
(This article belongs to the Section Biosensors)
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