Sensors

12 pages, 2335 KiB

Open AccessEditor’s ChoiceArticle

Light Drone-Based Application to Assess Soil Tillage Quality Parameters

by Roberto Fanigliulo, Francesca Antonucci, Simone Figorilli, Daniele Pochi, Federico Pallottino, Laura Fornaciari, Renato Grilli and Corrado Costa

Sensors 2020, 20(3), 728; https://doi.org/10.3390/s20030728 - 28 Jan 2020

Cited by 20 | Viewed by 4835

Abstract

The evaluation of soil tillage quality parameters, such as cloddiness and surface roughness produced by tillage tools, is based on traditional methods ranging, respectively, from manual or mechanical sieving of ground samples to handheld rulers, non-contact devices or Precision Agriculture technics, such as [...] Read more.

The evaluation of soil tillage quality parameters, such as cloddiness and surface roughness produced by tillage tools, is based on traditional methods ranging, respectively, from manual or mechanical sieving of ground samples to handheld rulers, non-contact devices or Precision Agriculture technics, such as laser profile meters. The aim of the study was to compare traditional methods of soil roughness and cloddiness assessment (laser profile meter and manual sieving), with light drone RGB 3D imaging techniques for the evaluation of different tillage methods (ploughed, harrowed and grassed). Light drone application was able to replicate the results obtained by the traditional methods, introducing advantages in terms of time, repeatability and analysed surface while reducing the human error during the data collection on the one hand and allowing a labour-intensive field monitoring solution for digital farming on the other. Indeed, the profilometer positioning introduces errors and may lead to false reading due to limited data collection. Future work could be done in order to streamline the data processing operation and so to produce a practical application ready to use and stimulate the adoption of new evaluation indices of soil cloddiness, such as Entropy and the Angular Second Moment (ASM), which seem more suitable than the classic ones to achieved data referred to more extended surfaces. Full article

(This article belongs to the Section Optical Sensors)

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16 pages, 3157 KiB

Open AccessEditor’s ChoiceArticle

Multi-Parameter Sensing in a Multimode Self-Interference Micro-Ring Resonator by Machine Learning

by Dong Hu, Chang-ling Zou, Hongliang Ren, Jin Lu, Zichun Le, Yali Qin, Shunqin Guo, Chunhua Dong and Weisheng Hu

Sensors 2020, 20(3), 709; https://doi.org/10.3390/s20030709 - 28 Jan 2020

Cited by 26 | Viewed by 5301

Abstract

A universal multi-parameter sensing scheme based on a self-interference micro-ring resonator (SIMRR) is proposed. Benefit from the special intensity sensing mechanism, the SIMRR allows multimode sensing in a wide range of wavelengths but immune from frequency noise. To process the multiple mode spectra [...] Read more.

A universal multi-parameter sensing scheme based on a self-interference micro-ring resonator (SIMRR) is proposed. Benefit from the special intensity sensing mechanism, the SIMRR allows multimode sensing in a wide range of wavelengths but immune from frequency noise. To process the multiple mode spectra that are dependent on multiple parameters, we adopt the machine learning algorithm instead of massive asymptotic solutions of resonators. Employing the proposed multi-mode sensing approach, a two-parameter SIMRR sensor is designed. Assuming that two gases have different wavelength dependence of refractive indices, the feasibility and effectiveness of the two-parameter sensing strategy are verified numerically. Moreover, the dependence of parameter estimation accuracy on the laser intensity noises is also investigated. The numerical results indicate that our scheme of multi-parameter sensing in a multimode SIMRR holds great potential for practical high-sensitive sensing platforms compared with the single-mode sensing based on whispering gallery mode (WGM) resonators. Full article

(This article belongs to the Special Issue Optical–Resonant Microsensors)

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25 pages, 11187 KiB

Open AccessEditor’s ChoiceArticle

Video Image Enhancement and Machine Learning Pipeline for Underwater Animal Detection and Classification at Cabled Observatories

by Vanesa Lopez-Vazquez, Jose Manuel Lopez-Guede, Simone Marini, Emanuela Fanelli, Espen Johnsen and Jacopo Aguzzi

Sensors 2020, 20(3), 726; https://doi.org/10.3390/s20030726 - 28 Jan 2020

Cited by 47 | Viewed by 7872

Abstract

An understanding of marine ecosystems and their biodiversity is relevant to sustainable use of the goods and services they offer. Since marine areas host complex ecosystems, it is important to develop spatially widespread monitoring networks capable of providing large amounts of multiparametric information, [...] Read more.

An understanding of marine ecosystems and their biodiversity is relevant to sustainable use of the goods and services they offer. Since marine areas host complex ecosystems, it is important to develop spatially widespread monitoring networks capable of providing large amounts of multiparametric information, encompassing both biotic and abiotic variables, and describing the ecological dynamics of the observed species. In this context, imaging devices are valuable tools that complement other biological and oceanographic monitoring devices. Nevertheless, large amounts of images or movies cannot all be manually processed, and autonomous routines for recognizing the relevant content, classification, and tagging are urgently needed. In this work, we propose a pipeline for the analysis of visual data that integrates video/image annotation tools for defining, training, and validation of datasets with video/image enhancement and machine and deep learning approaches. Such a pipeline is required to achieve good performance in the recognition and classification tasks of mobile and sessile megafauna, in order to obtain integrated information on spatial distribution and temporal dynamics. A prototype implementation of the analysis pipeline is provided in the context of deep-sea videos taken by one of the fixed cameras at the LoVe Ocean Observatory network of Lofoten Islands (Norway) at 260 m depth, in the Barents Sea, which has shown good classification results on an independent test dataset with an accuracy value of 76.18% and an area under the curve (AUC) value of 87.59%. Full article

(This article belongs to the Special Issue Imaging Sensor Systems for Analyzing Subsea Environment and Life)

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25 pages, 3135 KiB

Open AccessEditor’s ChoiceArticle

Mobile Synchronization Recovery for Ultrasonic Indoor Positioning

by Riccardo Carotenuto, Massimo Merenda, Demetrio Iero and Francesco G. Della Corte

Sensors 2020, 20(3), 702; https://doi.org/10.3390/s20030702 - 27 Jan 2020

Cited by 28 | Viewed by 3444

Abstract

The growing interest for indoor position-based applications and services, as well as ubiquitous computing and location aware information, have led to increasing efforts toward the development of positioning techniques. Many applications require accurate positioning or tracking of people and assets inside buildings, and [...] Read more.

The growing interest for indoor position-based applications and services, as well as ubiquitous computing and location aware information, have led to increasing efforts toward the development of positioning techniques. Many applications require accurate positioning or tracking of people and assets inside buildings, and some market sectors are waiting for such technologies for starting a fast growth. Ultrasonic systems have already been shown to possess the desired positioning accuracy and refresh rate. However, they still require accurate synchronization between ultrasound emitters and receivers to work properly. Usually, synchronization is carried out through radio frequency (RF) signals, adding system complexity and raising the cost. In this work, this limit is overcome by introducing a novel self-synchronizing indoor positioning technique. Ultrasonic signals travel from emitters placed at fixed reference positions to any number of mobile devices (MD). The travelled distance is computed from the time of flight (TOF), which requires in turn synchronism between emitter and receiver. It is shown that this synchronism can be indirectly estimated from the time difference of arrival (TDOA) of the ultrasonic signals. The obtained positioning information is private, in the sense that the positioning infrastructure is not aware of the number or identity of the MDs that use it. Computer simulations and experimental results obtained in a typical office room are provided. Full article

(This article belongs to the Section Electronic Sensors)

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15 pages, 5221 KiB

Open AccessEditor’s ChoiceArticle

Hand Gesture Recognition Using Compact CNN via Surface Electromyography Signals

by Lin Chen, Jianting Fu, Yuheng Wu, Haochen Li and Bin Zheng

Sensors 2020, 20(3), 672; https://doi.org/10.3390/s20030672 - 26 Jan 2020

Cited by 142 | Viewed by 10460

Abstract

By training the deep neural network model, the hidden features in Surface Electromyography(sEMG) signals can be extracted. The motion intention of the human can be predicted by analysis of sEMG. However, the models recently proposed by researchers often have a large number of [...] Read more.

By training the deep neural network model, the hidden features in Surface Electromyography(sEMG) signals can be extracted. The motion intention of the human can be predicted by analysis of sEMG. However, the models recently proposed by researchers often have a large number of parameters. Therefore, we designed a compact Convolution Neural Network (CNN) model, which not only improves the classification accuracy but also reduces the number of parameters in the model. Our proposed model was validated on the Ninapro DB5 Dataset and the Myo Dataset. The classification accuracy of gesture recognition achieved good results. Full article

(This article belongs to the Special Issue Advanced Computational Intelligence for Object Detection, Feature Extraction and Recognition in Smart Sensor Environments)

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23 pages, 565 KiB

Open AccessEditor’s ChoiceReview

Inertial Sensor-Based Lower Limb Joint Kinematics: A Methodological Systematic Review

by Ive Weygers, Manon Kok, Marco Konings, Hans Hallez, Henri De Vroey and Kurt Claeys

Sensors 2020, 20(3), 673; https://doi.org/10.3390/s20030673 - 26 Jan 2020

Cited by 89 | Viewed by 10753

Abstract

The use of inertial measurement units (IMUs) has gained popularity for the estimation of lower limb kinematics. However, implementations in clinical practice are still lacking. The aim of this review is twofold—to evaluate the methodological requirements for IMU-based joint kinematic estimation to be [...] Read more.

The use of inertial measurement units (IMUs) has gained popularity for the estimation of lower limb kinematics. However, implementations in clinical practice are still lacking. The aim of this review is twofold—to evaluate the methodological requirements for IMU-based joint kinematic estimation to be applicable in a clinical setting, and to suggest future research directions. Studies within the PubMed, Web Of Science and EMBASE databases were screened for eligibility, based on the following inclusion criteria: (1) studies must include a methodological description of how kinematic variables were obtained for the lower limb, (2) kinematic data must have been acquired by means of IMUs, (3) studies must have validated the implemented method against a golden standard reference system. Information on study characteristics, signal processing characteristics and study results was assessed and discussed. This review shows that methods for lower limb joint kinematics are inherently application dependent. Sensor restrictions are generally compensated with biomechanically inspired assumptions and prior information. Awareness of the possible adaptations in the IMU-based kinematic estimates by incorporating such prior information and assumptions is necessary, before drawing clinical decisions. Future research should focus on alternative validation methods, subject-specific IMU-based biomechanical joint models and disturbed movement patterns in real-world settings. Full article

(This article belongs to the Special Issue Inertial Sensors)

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15 pages, 3180 KiB

Open AccessEditor’s ChoiceArticle

SeisMote: A Multi-Sensor Wireless Platform for Cardiovascular Monitoring in Laboratory, Daily Life, and Telemedicine

by Marco Di Rienzo, Giovannibattista Rizzo, Zeynep Melike Işilay and Prospero Lombardi

Sensors 2020, 20(3), 680; https://doi.org/10.3390/s20030680 - 26 Jan 2020

Cited by 30 | Viewed by 5093

Abstract

This article presents a new wearable platform, SeisMote, for the monitoring of cardiovascular function in controlled conditions and daily life. It consists of a wireless network of sensorized nodes providing simultaneous multiple measures of electrocardiogram (ECG), acceleration, rotational velocity, and photoplethysmogram (PPG) from [...] Read more.

This article presents a new wearable platform, SeisMote, for the monitoring of cardiovascular function in controlled conditions and daily life. It consists of a wireless network of sensorized nodes providing simultaneous multiple measures of electrocardiogram (ECG), acceleration, rotational velocity, and photoplethysmogram (PPG) from different body areas. A custom low-power transmission protocol was developed to allow the concomitant real-time monitoring of 32 signals (16 bit @200 Hz) from up to 12 nodes with a jitter in the among-node time synchronization lower than 0.2 ms. The BluetoothLE protocol may be used when only a single node is needed. Data can also be collected in the off-line mode. Seismocardiogram and pulse transit times can be derived from the collected data to obtain additional information on cardiac mechanics and vascular characteristics. The employment of the system in the field showed recordings without data gaps caused by transmission errors, and the duration of each battery charge exceeded 16 h. The system is currently used to investigate strategies of hemodynamic regulation in different vascular districts (through a multisite assessment of ECG and PPG) and to study the propagation of precordial vibrations along the thorax. The single-node version is presently exploited to monitor cardiac patients during telerehabilitation. Full article

(This article belongs to the Special Issue Wearable and Nearable Biosensors and Systems for Healthcare)

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16 pages, 25191 KiB

Open AccessEditor’s ChoiceArticle

LoRaWAN for Smart City IoT Deployments: A Long Term Evaluation

by Philip J. Basford, Florentin M. J. Bulot, Mihaela Apetroaie-Cristea, Simon J. Cox and Steven J. Ossont

Sensors 2020, 20(3), 648; https://doi.org/10.3390/s20030648 - 23 Jan 2020

Cited by 96 | Viewed by 10151

Abstract

LoRaWAN is a Low-Power Wide Area Network (LPWAN) technology designed for Internet of Things (IoT) deployments; this paper presents experiences from deploying a city-scale LoRaWAN network across Southampton, UK. This network was deployed to support an installation of air quality monitors and to [...] Read more.

LoRaWAN is a Low-Power Wide Area Network (LPWAN) technology designed for Internet of Things (IoT) deployments; this paper presents experiences from deploying a city-scale LoRaWAN network across Southampton, UK. This network was deployed to support an installation of air quality monitors and to explore the capabilities of LoRaWAN. This deployment uses a mixture of commercial off-the-shelf gateways and custom gateways. These gateway locations were chosen based on network access, site permission and accessibility, and are not necessarily the best locations theoretically. Over 135,000 messages have been transmitted by the twenty devices analysed. Over the course of the complete deployment,

72.4

% of the messages were successfully received by the data server. Of the messages that were received, 99% were received within 10

s

of transmission. We conclude that LoRaWAN is an applicable communication technology for city-scale air quality monitoring and other smart city applications. Full article

(This article belongs to the Special Issue Selected Papers from the 3rd Global IoT Summit)

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21 pages, 1341 KiB

Open AccessEditor’s ChoiceArticle

An IoT Architecture for Water Resource Management in Agroindustrial Environments: A Case Study in Almería (Spain)

by Manuel Muñoz, Juan D. Gil, Lidia Roca, Francisco Rodríguez and Manuel Berenguel

Sensors 2020, 20(3), 596; https://doi.org/10.3390/s20030596 - 21 Jan 2020

Cited by 29 | Viewed by 5785

Abstract

The current agricultural water panorama in many Mediterranean countries is composed by desalination facilities, wells (frequently overexploited), the water public utility network, and several consumer agents with different water needs. This distributed water network requires centralized management methods for its proper use, which [...] Read more.

The current agricultural water panorama in many Mediterranean countries is composed by desalination facilities, wells (frequently overexploited), the water public utility network, and several consumer agents with different water needs. This distributed water network requires centralized management methods for its proper use, which are difficult to implement as the different agents are usually geographically separated. In this sense, the use of enabling technologies such as the Internet of Things can be essential to the proper operation of these agroindustrial systems. In this paper, an Internet of Things cloud architecture based on the FIWARE standard is proposed for interconnecting the several agents that make up the agroindustrial system. In addition, this architecture includes an efficient management method based on a model predictive control technique, which is aimed at minimizing operating costs. A case study inspired by three real facilities located in Almería (southeast of Spain) is used as the simulation test bed. The obtained results show how around 75% of the total operating costs can be saved with the application of the proposed approach, which could be very significant to decrease the costs of desalinated water and, therefore, to maintain the sustainability of the agricultural system. Full article

(This article belongs to the Special Issue Selected Papers from the 3rd Global IoT Summit)

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19 pages, 1999 KiB

Open AccessEditor’s ChoiceArticle

Predictive Maintenance of Boiler Feed Water Pumps Using SCADA Data

by Marek Moleda, Alina Momot and Dariusz Mrozek

Sensors 2020, 20(2), 571; https://doi.org/10.3390/s20020571 - 20 Jan 2020

Cited by 30 | Viewed by 11132

Abstract

IoT enabled predictive maintenance allows companies in the energy sector to identify potential problems in the production devices far before the failure occurs. In this paper, we propose a method for early detection of faults in boiler feed pumps using existing measurements currently [...] Read more.

IoT enabled predictive maintenance allows companies in the energy sector to identify potential problems in the production devices far before the failure occurs. In this paper, we propose a method for early detection of faults in boiler feed pumps using existing measurements currently captured by control devices. In the experimental part, we work on real measurement data and events from a coal fired power plant. The main research objective is to implement a model that detects deviations from the normal operation state based on regression and to check which events or failures can be detected by it. The presented technique allows the creation of a predictive system working on the basis of the available data with a minimal requirement of expert knowledge, in particular the knowledge related to the categorization of failures and the exact time of their occurrence, which is sometimes difficult to identify. The paper shows that with modern technologies, such as the Internet of Things, big data, and cloud computing, it is possible to integrate automation systems, designed in the past only to control the production process, with IT systems that make all processes more efficient through the use of advanced analytic tools. Full article

(This article belongs to the Special Issue Advanced Sensors and Signal Processing of Sensor Data: Recent Advances and Applications)

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17 pages, 4209 KiB

Open AccessEditor’s ChoiceArticle

A Multi-Parametric Wearable System to Monitor Neck Movements and Respiratory Frequency of Computer Workers

by Daniela Lo Presti, Arianna Carnevale, Jessica D’Abbraccio, Luca Massari, Carlo Massaroni, Riccardo Sabbadini, Martina Zaltieri, Joshua Di Tocco, Marco Bravi, Sandra Miccinilli, Silvia Sterzi, Umile G. Longo, Vincenzo Denaro, Michele A. Caponero, Domenico Formica, Calogero M. Oddo and Emiliano Schena

Sensors 2020, 20(2), 536; https://doi.org/10.3390/s20020536 - 18 Jan 2020

Cited by 60 | Viewed by 5560

Abstract

Musculoskeletal disorders are the most common form of occupational ill-health. Neck pain is one of the most prevalent musculoskeletal disorders experienced by computer workers. Wrong postural habits and non-compliance of the workstation to ergonomics guidelines are the leading causes of neck pain. These [...] Read more.

Musculoskeletal disorders are the most common form of occupational ill-health. Neck pain is one of the most prevalent musculoskeletal disorders experienced by computer workers. Wrong postural habits and non-compliance of the workstation to ergonomics guidelines are the leading causes of neck pain. These factors may also alter respiratory functions. Health and safety interventions can reduce neck pain and, more generally, the symptoms of musculoskeletal disorders and reduce the consequent economic burden. In this work, a multi-parametric wearable system based on two fiber Bragg grating sensors is proposed for monitoring neck movements and breathing activity of computer workers. The sensing elements were positioned on the neck, in the frontal and sagittal planes, to monitor: (i) flexion-extension and axial rotation repetitions, and (ii) respiratory frequency. In this pilot study, five volunteers were enrolled and performed five repetitions of both flexion-extension and axial rotation, and ten breaths of both quite breathing and tachypnea. Results showed the good performances of the proposed system in monitoring the aforementioned parameters when compared to optical reference systems. The wearable system is able to well-match the trend in time of the neck movements (both flexion-extension and axial rotation) and to estimate mean and breath-by-breath respiratory frequency values with percentage errors ≤6.09% and ≤1.90%, during quiet breathing and tachypnea, respectively. Full article

(This article belongs to the Collection Respiratory Monitoring for Healthcare, Sport and Physical Activity: Sensors, Techniques and Applications)

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18 pages, 8540 KiB

Open AccessEditor’s ChoiceArticle

Design and Implementation of a Smart Traffic Signal Control System for Smart City Applications

by Wei-Hsun Lee and Chi-Yi Chiu

Sensors 2020, 20(2), 508; https://doi.org/10.3390/s20020508 - 16 Jan 2020

Cited by 107 | Viewed by 29128

Abstract

Infrastructure supporting vehicular network (V2X) capability is the key factor to the success of smart city because it enables many smart transportation services. In order to reduce the traffic congestion and improve the public transport efficiency, many intelligent transportation systems (ITS) need to [...] Read more.

Infrastructure supporting vehicular network (V2X) capability is the key factor to the success of smart city because it enables many smart transportation services. In order to reduce the traffic congestion and improve the public transport efficiency, many intelligent transportation systems (ITS) need to be developed. In this paper, a smart traffic signal control (STSC) system is designed and implemented, it supports several smart city transportation applications including emergency vehicle signal preemption (EVSP), public transport signal priority (TSP), adaptive traffic signal control (ATSC), eco-driving supporting, and message broadcasting. The roadside unit (RSU) controller is the core of the proposed STSC system, where the system architecture, middleware, control algorithms, and peripheral modules are detailed discussed in this paper. It is compatible with existed traffic signal controller so that it can be fast and cost−effectively deployed. A new traffic signal scheme is specially designed for the EVSP scenario, it can inform all the drivers near the intersection regarding which direction the emergency vehicle (EV) is approaching, smoothing the traffic flow, and enhancing the safety. EVSP scenario and the related control algorithms are implemented in this work; integration test and field test are performed to demonstrate the STSC system. Full article

(This article belongs to the Special Issue Architectures and Platforms for Smart and Sustainable Cities)

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18 pages, 951 KiB

Open AccessEditor’s ChoiceReview

Innovations in Electrodermal Activity Data Collection and Signal Processing: A Systematic Review

by Hugo F. Posada-Quintero and Ki H. Chon

Sensors 2020, 20(2), 479; https://doi.org/10.3390/s20020479 - 15 Jan 2020

Cited by 238 | Viewed by 20305

Abstract

The electrodermal activity (EDA) signal is an electrical manifestation of the sympathetic innervation of the sweat glands. EDA has a history in psychophysiological (including emotional or cognitive stress) research since 1879, but it was not until recent years that researchers began using EDA [...] Read more.

The electrodermal activity (EDA) signal is an electrical manifestation of the sympathetic innervation of the sweat glands. EDA has a history in psychophysiological (including emotional or cognitive stress) research since 1879, but it was not until recent years that researchers began using EDA for pathophysiological applications like the assessment of fatigue, pain, sleepiness, exercise recovery, diagnosis of epilepsy, neuropathies, depression, and so forth. The advent of new devices and applications for EDA has increased the development of novel signal processing techniques, creating a growing pool of measures derived mathematically from the EDA. For many years, simply computing the mean of EDA values over a period was used to assess arousal. Much later, researchers found that EDA contains information not only in the slow changes (tonic component) that the mean value represents, but also in the rapid or phasic changes of the signal. The techniques that have ensued have intended to provide a more sophisticated analysis of EDA, beyond the traditional tonic/phasic decomposition of the signal. With many researchers from the social sciences, engineering, medicine, and other areas recently working with EDA, it is timely to summarize and review the recent developments and provide an updated and synthesized framework for all researchers interested in incorporating EDA into their research. Full article

(This article belongs to the Special Issue Skin Sensors)

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22 pages, 611 KiB

Open AccessEditor’s ChoiceReview

Survey on Wireless Technology Trade-Offs for the Industrial Internet of Things

by Amina Seferagić, Jeroen Famaey, Eli De Poorter and Jeroen Hoebeke

Sensors 2020, 20(2), 488; https://doi.org/10.3390/s20020488 - 15 Jan 2020

Cited by 75 | Viewed by 8313

Abstract

Aside from vast deployment cost reduction, Industrial Wireless Sensor and Actuator Networks (IWSAN) introduce a new level of industrial connectivity. Wireless connection of sensors and actuators in industrial environments not only enables wireless monitoring and actuation, it also enables coordination of production stages, [...] Read more.

Aside from vast deployment cost reduction, Industrial Wireless Sensor and Actuator Networks (IWSAN) introduce a new level of industrial connectivity. Wireless connection of sensors and actuators in industrial environments not only enables wireless monitoring and actuation, it also enables coordination of production stages, connecting mobile robots and autonomous transport vehicles, as well as localization and tracking of assets. All these opportunities already inspired the development of many wireless technologies in an effort to fully enable Industry 4.0. However, different technologies significantly differ in performance and capabilities, none being capable of supporting all industrial use cases. When designing a network solution, one must be aware of the capabilities and the trade-offs that prospective technologies have. This paper evaluates the technologies potentially suitable for IWSAN solutions covering an entire industrial site with limited infrastructure cost and discusses their trade-offs in an effort to provide information for choosing the most suitable technology for the use case of interest. The comparative discussion presented in this paper aims to enable engineers to choose the most suitable wireless technology for their specific IWSAN deployment. Full article

(This article belongs to the Special Issue Real-Time Sensor Networks and Systems for the Industrial IoT)

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12 pages, 5585 KiB

Open AccessEditor’s ChoiceArticle

Fused-Deposition-Material 3D-Printing Procedure and Algorithm Avoiding Use of Any Supports

by Gianluca Barile, Alfiero Leoni, Mirco Muttillo, Romina Paolucci, Gianfranco Fazzini and Leonardo Pantoli

Sensors 2020, 20(2), 470; https://doi.org/10.3390/s20020470 - 14 Jan 2020

Cited by 4 | Viewed by 7251

Abstract

The three-dimensional printing of complex shapes without using supporting structures is the most attractive factor of merit in current additive manufacturing because it allows to drastically reduce printing time, and ideally nullify postprocessing and waste material. In this work, we present an innovative [...] Read more.

The three-dimensional printing of complex shapes without using supporting structures is the most attractive factor of merit in current additive manufacturing because it allows to drastically reduce printing time, and ideally nullify postprocessing and waste material. In this work, we present an innovative procedure and algorithm (Print on Air, PoA) for additive manufacturing that, relying on sensing systems embedded into the three-dimensional (3D) printer (e.g., temperature and speed sensors), aims at generating a printing sequence capable of a self-sustaining bridge and overhang structures. This feature was achieved by splitting the actual floating area of the layer where the aforementioned structures are in many subsections. Each is generated with a negligible floating surface and printed in a well-determined sequence with accurate temperature and speed profiles. Therefore, each subsection is formed without the need for scaffolding, simultaneously acting as a supporting structure for the following subsection. The array of subsections constitutes the actual bridge or overhang structure. The proposed method can be used for any object, including very long bridges or convex surfaces. The revolutionary method is here reported and evaluated in order to show its applicability in any condition. Although the study was conducted in a Fused Deposition Material (FDM) environment, it can certainly be adapted to other manufacturing environments with adequate modifications. Full article

(This article belongs to the Special Issue Selected papers from the 2019 IEEE International Worshop on Metrology for Industry 4.0 and IoT)

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14 pages, 2054 KiB

Open AccessEditor’s ChoiceArticle

An Assessment of Surface Water Detection Methods for Water Resource Management in the Nigerien Sahel

by Kelsey Herndon, Rebekke Muench, Emil Cherrington and Robert Griffin

Sensors 2020, 20(2), 431; https://doi.org/10.3390/s20020431 - 12 Jan 2020

Cited by 45 | Viewed by 5609

Abstract

Water is a scarce, but essential resource in the Sahel. Rainfed ephemeral ponds and lakes that dot the landscape are necessary to the livelihoods of smallholder farmers and pastoralists who rely on these resources to irrigate crops and hydrate cattle. The remote location [...] Read more.

Water is a scarce, but essential resource in the Sahel. Rainfed ephemeral ponds and lakes that dot the landscape are necessary to the livelihoods of smallholder farmers and pastoralists who rely on these resources to irrigate crops and hydrate cattle. The remote location and dispersed nature of these water bodies limits typical methods of monitoring, such as with gauges; fortunately, remote sensing offers a quick and cost-effective means of regularly measuring surface water extent in these isolated regions. Dozens of operational methods exist to use remote sensing to identify waterbodies, however, their performance when identifying surface water in the semi-arid Sahel has not been well-documented and the limitations of these methods for the region are not well understood. Here, we evaluate two global dynamic surface water datasets, fifteen spectral indices developed to classify surface water extent, and three simple decision tree methods created specifically to identify surface water in semi-arid environments. We find that the existing global surface water datasets effectively minimize false positives, but greatly underestimate the presence and extent of smaller, more turbid water bodies that are essential to local livelihoods, an important limitation in their use for monitoring water availability. Three of fifteen spectral indices exhibited both high accuracy and threshold stability when evaluated over different areas and seasons. The three simple decision tree methods had mixed performance, with only one having an overall accuracy that compared to the best performing spectral indices. We find that while global surface water datasets may be appropriate for analysis at the global scale, other methods calibrated to the local environment may provide improved performance for more localized water monitoring needs. Full article

(This article belongs to the Special Issue Applications of Remote Sensing Data in Water Resources Management)

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25 pages, 7519 KiB

Open AccessEditor’s ChoiceArticle

Accuracy of the Dynamic Acoustic Map in a Large City Generated by Fixed Monitoring Units

by Roberto Benocci, Chiara Confalonieri, Hector Eduardo Roman, Fabio Angelini and Giovanni Zambon

Sensors 2020, 20(2), 412; https://doi.org/10.3390/s20020412 - 11 Jan 2020

Cited by 27 | Viewed by 3273

Abstract

DYNAMAP, a European Life project, aims at giving a real image of the noise generated by vehicular traffic in urban areas developing a dynamic acoustic map based on a limited number of low-cost permanent noise monitoring stations. The system has been implemented in [...] Read more.

DYNAMAP, a European Life project, aims at giving a real image of the noise generated by vehicular traffic in urban areas developing a dynamic acoustic map based on a limited number of low-cost permanent noise monitoring stations. The system has been implemented in two pilot areas located in the agglomeration of Milan (Italy) and along the Motorway A90 (Rome-Italy). The paper reports the final assessment of the system installed in the pilot area of Milan. Traffic noise data collected by the monitoring stations, each one representative of a number of roads (groups) sharing similar characteristics (e.g., daily traffic flow), are used to build-up a “real-time” noise map. In particular, we focused on the results of the testing campaign (21 sites distributed over the pilot area and 24 h duration of each recording). It allowed evaluating the accuracy and reliability of the system by comparing the predicted noise level of DYNAMAP with field measurements in randomly selected sites. To this end, a statistical analysis has been implemented to determine the error associated with such prediction, and to optimize the system by developing a correction procedure aimed at keeping the error below some acceptable threshold. The steps and the results of this procedure are given in detail. It is shown that it is possible to describe a complex road network on the basis of a statistical approach, complemented by empirical data, within a threshold of 3 dB provided that the traffic flow model achieves a comparable accuracy within each single groups of roads in the network. Full article

(This article belongs to the Special Issue Smart Wireless Acoustic Sensor Network Design for Noise Monitoring in Smart Cities)

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22 pages, 5866 KiB

Open AccessEditor’s ChoiceArticle

Algorithm with Patterned Singular Value Approach for Highly Reliable Autonomous Star Identification

by Kiduck Kim and Hyochoong Bang

Sensors 2020, 20(2), 374; https://doi.org/10.3390/s20020374 - 9 Jan 2020

Cited by 8 | Viewed by 2879

Abstract

In the work reported in this paper, a lost-in-space star pattern identification algorithm for agile spacecraft was studied. Generally, the operation of a star tracker is known to exhibit serious degradation or even failure during fast attitude maneuvers. While tracking methods are widely [...] Read more.

In the work reported in this paper, a lost-in-space star pattern identification algorithm for agile spacecraft was studied. Generally, the operation of a star tracker is known to exhibit serious degradation or even failure during fast attitude maneuvers. While tracking methods are widely used solutions to handle the dynamic conditions, they require prior information about the initial orientation. Therefore, the tracking methods may not be adequate for autonomy of attitude and control systems. In this paper a novel autonomous identification method for dynamic conditions is proposed. Additional constraints are taken into account that can significantly decrease the number of stars imaged and the centroid accuracy. A strategy combining two existing classes for star pattern identification is proposed. The new approach is intended to provide a unique way to determine the identity of stars that promises robustness against noise and rapid identification. Moreover, representative algorithms implemented in actual space applications were utilized as counterparts to analyze the performance of the proposed method in various scenarios. Numerical simulations show that the proposed method is not only highly robust against positional noise and false stars, but also guarantees fast run-time, which is appropriate for high-speed applications. Full article

(This article belongs to the Special Issue Sensor Systems for Satellite Attitude Determination)

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10 pages, 3334 KiB

Open AccessEditor’s ChoiceArticle

A Novel Piezoresistive MEMS Pressure Sensors Based on Temporary Bonding Technology

by Peishuai Song, Chaowei Si, Mingliang Zhang, Yongmei Zhao, Yurong He, Wen Liu and Xiaodong Wang

Sensors 2020, 20(2), 337; https://doi.org/10.3390/s20020337 - 7 Jan 2020

Cited by 26 | Viewed by 6598

Abstract

A miniature piezoresistive pressure sensor fabricated by temporary bonding technology was reported in this paper. The sensing membrane was formed on the device layer of an SOI (Silicon-On-Insulator) wafer, which was bonded to borosilicate glass (Borofloat 33, BF33) wafer for supporting before releasing [...] Read more.

A miniature piezoresistive pressure sensor fabricated by temporary bonding technology was reported in this paper. The sensing membrane was formed on the device layer of an SOI (Silicon-On-Insulator) wafer, which was bonded to borosilicate glass (Borofloat 33, BF33) wafer for supporting before releasing with Cu-Cu bonding after boron doping and electrode patterning. The handle layer was bonded to another BF33 wafer after thinning and etching. Finally, the substrate BF33 wafer was thinned by chemical mechanical polishing (CMP) to reduce the total device thickness. The copper temporary bonding layer was removed by acid solution after dicing to release the sensing membrane. The chip area of the fabricated pressure sensor was of 1600 μm × 650 μm × 104 μm, and the size of a sensing membrane was of 100 μm × 100 μm × 2 μm. A higher sensitivity of 36 μV/(V∙kPa) in the range of 0–180 kPa was obtained. By further reducing the width, the fabricated miniature pressure sensor could be easily mounted in a medical catheter for the blood pressure measurement. Full article

(This article belongs to the Section Sensor Materials)

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24 pages, 4287 KiB

Open AccessEditor’s ChoiceArticle

Enhancing the Sensor Node Localization Algorithm Based on Improved DV-Hop and DE Algorithms in Wireless Sensor Networks

by Dezhi Han, Yunping Yu, Kuan-Ching Li and Rodrigo Fernandes de Mello

Sensors 2020, 20(2), 343; https://doi.org/10.3390/s20020343 - 7 Jan 2020

Cited by 59 | Viewed by 4212

Abstract

The Distance Vector-Hop (DV-Hop) algorithm is the most well-known range-free localization algorithm based on the distance vector routing protocol in wireless sensor networks; however, it is widely known that its localization accuracy is limited. In this paper, DEIDV-Hop is proposed, an enhanced wireless [...] Read more.

The Distance Vector-Hop (DV-Hop) algorithm is the most well-known range-free localization algorithm based on the distance vector routing protocol in wireless sensor networks; however, it is widely known that its localization accuracy is limited. In this paper, DEIDV-Hop is proposed, an enhanced wireless sensor node localization algorithm based on the differential evolution (DE) and improved DV-Hop algorithms, which improves the problem of potential error about average distance per hop. Introduced into the random individuals of mutation operation that increase the diversity of the population, random mutation is infused to enhance the search stagnation and premature convergence of the DE algorithm. On the basis of the generated individual, the social learning part of the Particle Swarm (PSO) algorithm is embedded into the crossover operation that accelerates the convergence speed as well as improves the optimization result of the algorithm. The improved DE algorithm is applied to obtain the global optimal solution corresponding to the estimated location of the unknown node. Among the four different network environments, the simulation results show that the proposed algorithm has smaller localization errors and more excellent stability than previous ones. Still, it is promising for application scenarios with higher localization accuracy and stability requirements. Full article

(This article belongs to the Special Issue Trends on Edge Computing and Artificial Intelligence for Next Generation Sensor Networks)

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14 pages, 591 KiB

Open AccessEditor’s ChoiceArticle

Distributed Optical Fiber-Based Approach for Soil–Structure Interaction

by Nissrine Boujia, Franziska Schmidt, Christophe Chevalier, Dominique Siegert and Damien Pham Van Bang

Sensors 2020, 20(1), 321; https://doi.org/10.3390/s20010321 - 6 Jan 2020

Cited by 10 | Viewed by 4630

Abstract

Scour is a hydraulic risk threatening the stability of bridges in fluvial and coastal areas. Therefore, developing permanent and real-time monitoring techniques is crucial. Recent advances in strain measurements using fiber optic sensors allow new opportunities for scour monitoring. In this study, the [...] Read more.

Scour is a hydraulic risk threatening the stability of bridges in fluvial and coastal areas. Therefore, developing permanent and real-time monitoring techniques is crucial. Recent advances in strain measurements using fiber optic sensors allow new opportunities for scour monitoring. In this study, the innovative optical frequency domain reflectometry (OFDR) was used to evaluate the effect of scour by performing distributed strain measurements along a rod under static lateral loads. An analytical analysis based on the Winkler model of the soil was carefully established and used to evaluate the accuracy of the fiber optic sensors and helped interpret the measurements results. Dynamic tests were also performed and results from static and dynamic tests were compared using an equivalent cantilever model. Full article

(This article belongs to the Special Issue Optical Sensors for Structural Health Monitoring)

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17 pages, 981 KiB

Open AccessEditor’s ChoiceArticle

A Comparative Analysis of Machine/Deep Learning Models for Parking Space Availability Prediction

by Faraz Malik Awan, Yasir Saleem, Roberto Minerva and Noel Crespi

Sensors 2020, 20(1), 322; https://doi.org/10.3390/s20010322 - 6 Jan 2020

Cited by 78 | Viewed by 9317

Abstract

Machine/Deep Learning (ML/DL) techniques have been applied to large data sets in order to extract relevant information and for making predictions. The performance and the outcomes of different ML/DL algorithms may vary depending upon the data sets being used, as well as on [...] Read more.

Machine/Deep Learning (ML/DL) techniques have been applied to large data sets in order to extract relevant information and for making predictions. The performance and the outcomes of different ML/DL algorithms may vary depending upon the data sets being used, as well as on the suitability of algorithms to the data and the application domain under consideration. Hence, determining which ML/DL algorithm is most suitable for a specific application domain and its related data sets would be a key advantage. To respond to this need, a comparative analysis of well-known ML/DL techniques, including Multilayer Perceptron, K-Nearest Neighbors, Decision Tree, Random Forest, and Voting Classifier (or the Ensemble Learning Approach) for the prediction of parking space availability has been conducted. This comparison utilized Santander’s parking data set, initiated while working on the H2020 WISE-IoT project. The data set was used in order to evaluate the considered algorithms and to determine the one offering the best prediction. The results of this analysis show that, regardless of the data set size, the less complex algorithms like Decision Tree, Random Forest, and KNN outperform complex algorithms such as Multilayer Perceptron, in terms of higher prediction accuracy, while providing comparable information for the prediction of parking space availability. In addition, in this paper, we are providing Top-K parking space recommendations on the basis of distance between current position of vehicles and free parking spots. Full article

(This article belongs to the Special Issue Sensor Systems in Smart Environments)

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26 pages, 9504 KiB

Open AccessEditor’s ChoiceArticle

Vehicle Trajectory Prediction and Collision Warning via Fusion of Multisensors and Wireless Vehicular Communications

by Minjin Baek, Donggi Jeong, Dongho Choi and Sangsun Lee

Sensors 2020, 20(1), 288; https://doi.org/10.3390/s20010288 - 4 Jan 2020

Cited by 53 | Viewed by 7313

Abstract

Driver inattention is one of the leading causes of traffic crashes worldwide. Providing the driver with an early warning prior to a potential collision can significantly reduce the fatalities and level of injuries associated with vehicle collisions. In order to monitor the vehicle [...] Read more.

Driver inattention is one of the leading causes of traffic crashes worldwide. Providing the driver with an early warning prior to a potential collision can significantly reduce the fatalities and level of injuries associated with vehicle collisions. In order to monitor the vehicle surroundings and predict collisions, on-board sensors such as radar, lidar, and cameras are often used. However, the driving environment perception based on these sensors can be adversely affected by a number of factors such as weather and solar irradiance. In addition, potential dangers cannot be detected if the target is located outside the limited field-of-view of the sensors, or if the line of sight to the target is occluded. In this paper, we propose an approach for designing a vehicle collision warning system based on fusion of multisensors and wireless vehicular communications. A high-level fusion of radar, lidar, camera, and wireless vehicular communication data was performed to predict the trajectories of remote targets and generate an appropriate warning to the driver prior to a possible collision. We implemented and evaluated the proposed vehicle collision system in virtual driving environments, which consisted of a vehicle–vehicle collision scenario and a vehicle–pedestrian collision scenario. Full article

(This article belongs to the Special Issue Intelligent Vehicles)

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21 pages, 1089 KiB

Open AccessEditor’s ChoiceArticle

Impact of SCHC Compression and Fragmentation in LPWAN: A Case Study with LoRaWAN

by Jesus Sanchez-Gomez, Jorge Gallego-Madrid, Ramon Sanchez-Iborra, Jose Santa and Antonio F. Skarmeta

Sensors 2020, 20(1), 280; https://doi.org/10.3390/s20010280 - 3 Jan 2020

Cited by 31 | Viewed by 5284

Abstract

The dawn of the Internet of Things (IoT) paradigm has brought about a series of novel services never imagined until recently. However, certain deployments such as those employing Low-Power Wide-Area Network (LPWAN)-based technologies may present severe network restrictions in terms of throughput and [...] Read more.

The dawn of the Internet of Things (IoT) paradigm has brought about a series of novel services never imagined until recently. However, certain deployments such as those employing Low-Power Wide-Area Network (LPWAN)-based technologies may present severe network restrictions in terms of throughput and supported packet length. This situation prompts the isolation of LPWAN systems on islands with limited interoperability with the Internet. For that reason, the IETF’s LPWAN working group has proposed a Static Context Header Compression (SCHC) scheme that permits compression and fragmentation of and IPv6/UDP/CoAP packets with the aim of making them suitable for transmission over the restricted links of LPWANs. Given the impact that such a solution can have in many IoT scenarios, this paper addresses its real evaluation in terms not only of latency and delivery ratio improvements, as a consequence of different compression and fragmentation levels, but also of the overhead in end node resources and useful payload sent per fragment. This has been carried out with the implementation of middleware and using a real testbed implementation of a LoRaWAN-to-IPv6 architecture together with a publish/subscribe broker for CoAP. The attained results show the advantages of SCHC, and sustain discussion regarding the impact of different SCHC and LoRaWAN configurations on the performance. It is highlighted that necessary end node resources are low as compared to the benefit of delivering long IPv6 packets over the LPWAN links. In turn, fragmentation can impose a lack of efficiency in terms of data and energy and, hence, a cross-layer solution is needed in order to obtain the best throughput of the network. Full article

(This article belongs to the Special Issue Pub/Sub Solutions for IoT)

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19 pages, 7293 KiB

Open AccessEditor’s ChoiceArticle

Fusion of Spectroscopy and Cobalt Electrochemistry Data for Estimating Phosphate Concentration in Hydroponic Solution

by Dae-Hyun Jung, Hak-Jin Kim, Hyoung Seok Kim, Jaeyoung Choi, Jeong Do Kim and Soo Hyun Park

Sensors 2019, 19(11), 2596; https://doi.org/10.3390/s19112596 - 7 Jun 2019

Cited by 16 | Viewed by 5395

Abstract

Phosphate is a key element affecting plant growth. Therefore, the accurate determination of phosphate concentration in hydroponic nutrient solutions is essential for providing a balanced set of nutrients to plants within a suitable range. This study aimed to develop a data fusion approach [...] Read more.

Phosphate is a key element affecting plant growth. Therefore, the accurate determination of phosphate concentration in hydroponic nutrient solutions is essential for providing a balanced set of nutrients to plants within a suitable range. This study aimed to develop a data fusion approach for determining phosphate concentrations in a paprika nutrient solution. As a conventional multivariate analysis approach using spectral data, partial least squares regression (PLSR) and principal components regression (PCR) models were developed using 56 samples for calibration and 24 samples for evaluation. The R² values of estimation models using PCR and PLSR ranged from 0.44 to 0.64. Furthermore, an estimation model using raw electromotive force (EMF) data from cobalt electrodes gave R² values of 0.58–0.71. To improve the model performance, a data fusion method was developed to estimate phosphate concentration using near infrared (NIR) spectral and cobalt electrochemical data. Raw EMF data from cobalt electrodes and principle component values from the spectral data were combined. Results of calibration and evaluation tests using an artificial neural network estimation model showed that R² = 0.90 and 0.89 and root mean square error (RMSE) = 96.70 and 119.50 mg/L, respectively. These values are sufficiently high for application to measuring phosphate concentration in hydroponic solutions. Full article

(This article belongs to the Special Issue Ion Selective Electrodes and Optodes)

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19 pages, 6019 KiB

Open AccessEditor’s ChoiceArticle

Deep CT to MR Synthesis Using Paired and Unpaired Data

by Cheng-Bin Jin, Hakil Kim, Mingjie Liu, Wonmo Jung, Seongsu Joo, Eunsik Park, Young Saem Ahn, In Ho Han, Jae Il Lee and Xuenan Cui

Sensors 2019, 19(10), 2361; https://doi.org/10.3390/s19102361 - 22 May 2019

Cited by 138 | Viewed by 9881

Abstract

Magnetic resonance (MR) imaging plays a highly important role in radiotherapy treatment planning for the segmentation of tumor volumes and organs. However, the use of MR is limited, owing to its high cost and the increased use of metal implants for patients. This [...] Read more.

Magnetic resonance (MR) imaging plays a highly important role in radiotherapy treatment planning for the segmentation of tumor volumes and organs. However, the use of MR is limited, owing to its high cost and the increased use of metal implants for patients. This study is aimed towards patients who are contraindicated owing to claustrophobia and cardiac pacemakers, and many scenarios in which only computed tomography (CT) images are available, such as emergencies, situations lacking an MR scanner, and situations in which the cost of obtaining an MR scan is prohibitive. From medical practice, our approach can be adopted as a screening method by radiologists to observe abnormal anatomical lesions in certain diseases that are difficult to diagnose by CT. The proposed approach can estimate an MR image based on a CT image using paired and unpaired training data. In contrast to existing synthetic methods for medical imaging, which depend on sparse pairwise-aligned data or plentiful unpaired data, the proposed approach alleviates the rigid registration of paired training, and overcomes the context-misalignment problem of unpaired training. A generative adversarial network was trained to transform two-dimensional (2D) brain CT image slices into 2D brain MR image slices, combining the adversarial, dual cycle-consistent, and voxel-wise losses. Qualitative and quantitative comparisons against independent paired and unpaired training methods demonstrated the superiority of our approach. Full article

(This article belongs to the Special Issue Biomedical Imaging and Sensing)

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39 pages, 11559 KiB

Open AccessEditor’s ChoiceReview

Tapered Optical Fibre Sensors: Current Trends and Future Perspectives

by Sergiy Korposh, Stephen W. James, Seung-Woo Lee and Ralph P. Tatam

Sensors 2019, 19(10), 2294; https://doi.org/10.3390/s19102294 - 17 May 2019

Cited by 131 | Viewed by 15420

Abstract

The development of reliable, affordable and efficient sensors is a key step in providing tools for efficient monitoring of critical environmental parameters. This review focuses on the use of tapered optical fibres as an environmental sensing platform. Tapered fibres allow access to the [...] Read more.

The development of reliable, affordable and efficient sensors is a key step in providing tools for efficient monitoring of critical environmental parameters. This review focuses on the use of tapered optical fibres as an environmental sensing platform. Tapered fibres allow access to the evanescent wave of the propagating mode, which can be exploited to facilitate chemical sensing by spectroscopic evaluation of the medium surrounding the optical fibre, by measurement of the refractive index of the medium, or by coupling to other waveguides formed of chemically sensitive materials. In addition, the reduced diameter of the tapered section of the optical fibre can offer benefits when measuring physical parameters such as strain and temperature. A review of the basic sensing platforms implemented using tapered optical fibres and their application for development of fibre-optic physical, chemical and bio-sensors is presented. Full article

(This article belongs to the Special Issue Sensors for Emerging Environmental Markers and Contaminants)

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11 pages, 706 KiB

Open AccessEditor’s ChoiceArticle

Asymptotically Optimal Deployment of Drones for Surveillance and Monitoring

by Andrey V. Savkin and Hailong Huang

Sensors 2019, 19(9), 2068; https://doi.org/10.3390/s19092068 - 3 May 2019

Cited by 40 | Viewed by 5453

Abstract

This paper studies the problem of placing a set of drones for surveillance of a ground region. The main goal is to determine the minimum number of drones necessary to be deployed at a given altitude to monitor the region. An easily implementable [...] Read more.

This paper studies the problem of placing a set of drones for surveillance of a ground region. The main goal is to determine the minimum number of drones necessary to be deployed at a given altitude to monitor the region. An easily implementable algorithm to estimate the minimum number of drones and determine their locations is developed. Moreover, it is proved that this algorithm is asymptotically optimal in the sense that the ratio of the number of drones required by this algorithm and the minimum number of drones converges to one as the area of the ground region tends to infinity. The proof is based on Kershner’s theorem from combinatorial geometry. Illustrative examples and comparisons with other existing methods show the efficiency of the developed algorithm. Full article

(This article belongs to the Special Issue Deployment and Navigation of Aerial Drones for Surveillance and Monitoring)

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26 pages, 2330 KiB

Open AccessEditor’s ChoiceReview

Review on Wearable Technology Sensors Used in Consumer Sport Applications

by Gobinath Aroganam, Nadarajah Manivannan and David Harrison

Sensors 2019, 19(9), 1983; https://doi.org/10.3390/s19091983 - 28 Apr 2019

Cited by 225 | Viewed by 35536

Abstract

This review paper discusses the trends and projections for wearable technology in the consumer sports sector (excluding professional sport). Analyzing the role of wearable technology for different users and why there is such a need for these devices in everyday lives. It shows [...] Read more.

This review paper discusses the trends and projections for wearable technology in the consumer sports sector (excluding professional sport). Analyzing the role of wearable technology for different users and why there is such a need for these devices in everyday lives. It shows how different sensors are influential in delivering a variety of readings that are useful in many ways regarding sport attributes. Wearables are increasing in function, and through integrating technology, users are gathering more data about themselves. The amount of wearable technology available is broad, each having its own role to play in different industries. Inertial measuring unit (IMU) and Global Positioning System (GPS) sensors are predominantly present in sport wearables but can be programmed for different needs. In this review, the differences are displayed to show which sensors are compatible and which ones can evolve sensor technology for sport applications. Full article

(This article belongs to the Special Issue Wearable Wireless Sensors)

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19 pages, 407 KiB

Open AccessEditor’s ChoiceArticle

Towards Deep-Learning-Driven Intrusion Detection for the Internet of Things

by Geethapriya Thamilarasu and Shiven Chawla

Sensors 2019, 19(9), 1977; https://doi.org/10.3390/s19091977 - 27 Apr 2019

Cited by 202 | Viewed by 10666

Abstract

Cyber-attacks on the Internet of Things (IoT) are growing at an alarming rate as devices, applications, and communication networks are becoming increasingly connected and integrated. When attacks on IoT networks go undetected for longer periods, it affects availability of critical systems for end [...] Read more.

Cyber-attacks on the Internet of Things (IoT) are growing at an alarming rate as devices, applications, and communication networks are becoming increasingly connected and integrated. When attacks on IoT networks go undetected for longer periods, it affects availability of critical systems for end users, increases the number of data breaches and identity theft, drives up the costs and impacts the revenue. It is imperative to detect attacks on IoT systems in near real time to provide effective security and defense. In this paper, we develop an intelligent intrusion-detection system tailored to the IoT environment. Specifically, we use a deep-learning algorithm to detect malicious traffic in IoT networks. The detection solution provides security as a service and facilitates interoperability between various network communication protocols used in IoT. We evaluate our proposed detection framework using both real-network traces for providing a proof of concept, and using simulation for providing evidence of its scalability. Our experimental results confirm that the proposed intrusion-detection system can detect real-world intrusions effectively. Full article

(This article belongs to the Special Issue Security and Privacy in Internet of Things)

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9 pages, 2611 KiB

Open AccessEditor’s ChoiceArticle

Sperm-Cultured Gate Ion-Sensitive Field-Effect Transistor for Non-Optical and Live Monitoring of Sperm Capacitation

by Akiko Saito and Toshiya Sakata

Sensors 2019, 19(8), 1784; https://doi.org/10.3390/s19081784 - 14 Apr 2019

Cited by 12 | Viewed by 3635

Abstract

We have successfully monitored the effect of progesterone and Ca²⁺ on artificially induced sperm capacitation in a real-time, noninvasive and label-free manner using an ion-sensitive field-effect transistor (ISFET) sensor. The sperm activity can be electrically detected as a change in pH generated [...] Read more.

We have successfully monitored the effect of progesterone and Ca²⁺ on artificially induced sperm capacitation in a real-time, noninvasive and label-free manner using an ion-sensitive field-effect transistor (ISFET) sensor. The sperm activity can be electrically detected as a change in pH generated by sperm respiration based on the principle of the ISFET sensor. Upon adding mouse sperm to the gate of the ISFET sensor in the culture medium with progesterone, the pH decreases with an increasing concentration of progesterone from 1 to 40 μM. This is because progesterone induces Ca²⁺ influx into spermatozoa and triggers multiple Ca²⁺-dependent physiological responses, which subsequently activates sperm respiration. Moreover, this pH response of the ISFET sensor is not observed for a Ca²⁺-free medium even when progesterone is introduced, which means that Ca²⁺ influx is necessary for sperm activation that results in sperm capacitation. Thus, a platform based on the ISFET sensor system can provide a simple method of evaluating artificially induced sperm capacitation in the field of male infertility treatment. Full article

(This article belongs to the Special Issue Potentiometric Bio/Chemical Sensing)

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17 pages, 6151 KiB

Open AccessEditor’s ChoiceArticle

A Smart Wireless Ear-Worn Device for Cardiovascular and Sweat Parameter Monitoring During Physical Exercise: Design and Performance Results

by Bruno Gil, Salzitsa Anastasova and Guang Z. Yang

Sensors 2019, 19(7), 1616; https://doi.org/10.3390/s19071616 - 4 Apr 2019

Cited by 40 | Viewed by 6859

Abstract

Wearable biomedical technology has gained much support lately as devices have become more affordable to the general public and they can easily interact with mobile phones and other platforms. The feasibility and accuracy of the data generated by these devices so as to [...] Read more.

Wearable biomedical technology has gained much support lately as devices have become more affordable to the general public and they can easily interact with mobile phones and other platforms. The feasibility and accuracy of the data generated by these devices so as to replace the standard medical methods in use today is still under scrutiny. In this paper, we present an ear-worn device to measure cardiovascular and sweat parameters during physical exercise. ECG bipolar recordings capture the electric potential around both ears, whereas sweat rate is estimated by the impedance method over one segment of tissue closer to the left ear, complemented by the measurement of the lactate and pH levels using amperiometric and potentiometric sensors, respectively. Together with head acceleration, the acquired data is sent to a mobile phone via BLE, enabling extended periods of signal recording. Results obtained by the device have shown a SNR level of 18 dB for the ECG signal recorded around the ears, a THD value of −20.46 dB for the excitation signal involved in impedance measurements, sweat conductivity of 0.08 S/m at 1 kHz and sensitivities of 50 mV/pH and 0.8 μA/mM for the pH and lactate acquisition channels, respectively. Testing of the device was performed in human subjects during indoors cycling with characteristic level changes. Full article

(This article belongs to the Special Issue Non-Invasive Biomedical Sensors)

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17 pages, 980 KiB

Open AccessEditor’s ChoiceReview

Validity and Reliability of Wearable Sensors for Joint Angle Estimation: A Systematic Review

by Isabelle Poitras, Frédérique Dupuis, Mathieu Bielmann, Alexandre Campeau-Lecours, Catherine Mercier, Laurent J. Bouyer and Jean-Sébastien Roy

Sensors 2019, 19(7), 1555; https://doi.org/10.3390/s19071555 - 31 Mar 2019

Cited by 171 | Viewed by 12155

Abstract

Motion capture systems are recognized as the gold standard for joint angle calculation. However, studies using these systems are restricted to laboratory settings for technical reasons, which may lead to findings that are not representative of real-life context. Recently developed commercial and home-made [...] Read more.

Motion capture systems are recognized as the gold standard for joint angle calculation. However, studies using these systems are restricted to laboratory settings for technical reasons, which may lead to findings that are not representative of real-life context. Recently developed commercial and home-made inertial measurement sensors (M/IMU) are potentially good alternatives to the laboratory-based systems, and recent technology improvements required a synthesis of the current evidence. The aim of this systematic review was to determine the criterion validity and reliability of M/IMU for each body joint and for tasks of different levels of complexity. Five different databases were screened (Pubmed, Cinhal, Embase, Ergonomic abstract, and Compendex). Two evaluators performed independent selection, quality assessment (consensus-based standards for the selection of health measurement instruments [COSMIN] and quality appraisal tools), and data extraction. Forty-two studies were included. Reported validity varied according to task complexity (higher validity for simple tasks) and the joint evaluated (better validity for lower limb joints). More studies on reliability are needed to make stronger conclusions, as the number of studies addressing this psychometric property was limited. M/IMU should be considered as a valid tool to assess whole body range of motion, but further studies are needed to standardize technical procedures to obtain more accurate data. Full article

(This article belongs to the Special Issue Wearable Sensors for Gait and Motion Analysis 2018)

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11 pages, 3022 KiB

Open AccessEditor’s ChoiceArticle

A Simple Procedure to Assess Limit of Detection for Multisensor Systems

by Ekaterina Oleneva, Maria Khaydukova, Julia Ashina, Irina Yaroshenko, Igor Jahatspanian, Andrey Legin and Dmitry Kirsanov

Sensors 2019, 19(6), 1359; https://doi.org/10.3390/s19061359 - 18 Mar 2019

Cited by 31 | Viewed by 5939

Abstract

Currently, there are no established procedures for limit of detection (LOD) evaluation in multisensor system studies, which complicates their correct comparison with other analytical techniques and hinders further development of the method. In this study we propose a simple and visually comprehensible approach [...] Read more.

Currently, there are no established procedures for limit of detection (LOD) evaluation in multisensor system studies, which complicates their correct comparison with other analytical techniques and hinders further development of the method. In this study we propose a simple and visually comprehensible approach for LOD estimation in multisensor analysis. The suggested approach is based on the assessment of evolution of mean relative error values in calibration series with growing analyte concentration. The LOD value is estimated as the concentration starting from which MRE values become stable from sample to sample. This intuitive procedure was successfully tested with a variety of real data from potentiometric multisensor systems. Full article

(This article belongs to the Special Issue Multivariate Data Analysis for Sensors and Sensor Arrays)

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23 pages, 1904 KiB

Open AccessEditor’s ChoiceReview

Advanced Micro- and Nano-Gas Sensor Technology: A Review

by Haleh Nazemi, Aashish Joseph, Jaewoo Park and Arezoo Emadi

Sensors 2019, 19(6), 1285; https://doi.org/10.3390/s19061285 - 14 Mar 2019

Cited by 383 | Viewed by 32866

Abstract

Micro- and nano-sensors lie at the heart of critical innovation in fields ranging from medical to environmental sciences. In recent years, there has been a significant improvement in sensor design along with the advances in micro- and nano-fabrication technology and the use of [...] Read more.

Micro- and nano-sensors lie at the heart of critical innovation in fields ranging from medical to environmental sciences. In recent years, there has been a significant improvement in sensor design along with the advances in micro- and nano-fabrication technology and the use of newly designed materials, leading to the development of high-performance gas sensors. Advanced micro- and nano-fabrication technology enables miniaturization of these sensors into micro-sized gas sensor arrays while maintaining the sensing performance. These capabilities facilitate the development of miniaturized integrated gas sensor arrays that enhance both sensor sensitivity and selectivity towards various analytes. In the past, several micro- and nano-gas sensors have been proposed and investigated where each type of sensor exhibits various advantages and limitations in sensing resolution, operating power, response, and recovery time. This paper presents an overview of the recent progress made in a wide range of gas-sensing technology. The sensing functionalizing materials, the advanced micro-machining fabrication methods, as well as their constraints on the sensor design, are discussed. The sensors’ working mechanisms and their structures and configurations are reviewed. Finally, the future development outlook and the potential applications made feasible by each category of the sensors are discussed. Full article

(This article belongs to the Section Physical Sensors)

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28 pages, 6510 KiB

Open AccessEditor’s ChoiceReview

Electrochemical Deposition of Nanomaterials for Electrochemical Sensing

by Domenica Tonelli, Erika Scavetta and Isacco Gualandi

Sensors 2019, 19(5), 1186; https://doi.org/10.3390/s19051186 - 8 Mar 2019

Cited by 125 | Viewed by 11609

Abstract

The most commonly used methods to electrodeposit nanomaterials on conductive supports or to obtain electrosynthesis nanomaterials are described. Au, layered double hydroxides (LDHs), metal oxides, and polymers are the classes of compounds taken into account. The electrochemical approach for the synthesis allows one [...] Read more.

The most commonly used methods to electrodeposit nanomaterials on conductive supports or to obtain electrosynthesis nanomaterials are described. Au, layered double hydroxides (LDHs), metal oxides, and polymers are the classes of compounds taken into account. The electrochemical approach for the synthesis allows one to obtain nanostructures with well-defined morphologies, even without the use of a template, and of variable sizes simply by controlling the experimental synthesis conditions. In fact, parameters such as current density, applied potential (constant, pulsed or ramp) and duration of the synthesis play a key role in determining the shape and size of the resulting nanostructures. This review aims to describe the most recent applications in the field of electrochemical sensors of the considered nanomaterials and special attention is devoted to the analytical figures of merit of the devices. Full article

(This article belongs to the Special Issue Nanostructured Surfaces in Sensing Systems)

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22 pages, 812 KiB

Open AccessEditor’s ChoiceReview

Visible Light Communication: A System Perspective—Overview and Challenges

by Saeed Ur Rehman, Shakir Ullah, Peter Han Joo Chong, Sira Yongchareon and Dan Komosny

Sensors 2019, 19(5), 1153; https://doi.org/10.3390/s19051153 - 7 Mar 2019

Cited by 171 | Viewed by 17897

Abstract

Visible light communication (VLC) is a new paradigm that could revolutionise the future of wireless communication. In VLC, information is transmitted through modulating the visible light spectrum (400–700 nm) that is used for illumination. Analytical and experimental work has shown the potential of [...] Read more.

Visible light communication (VLC) is a new paradigm that could revolutionise the future of wireless communication. In VLC, information is transmitted through modulating the visible light spectrum (400–700 nm) that is used for illumination. Analytical and experimental work has shown the potential of VLC to provide high-speed data communication with the added advantage of improved energy efficiency and communication security/privacy. VLC is still in the early phase of research. There are fewer review articles published on this topic mostly addressing the physical layer research. Unlike other reviews, this article gives a system prespective of VLC along with the survey on existing literature and potential challenges toward the implementation and integration of VLC. Full article

(This article belongs to the Special Issue Advanced Technologies on Green Radio Networks)

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9 pages, 4172 KiB

Open AccessEditor’s ChoiceArticle

Formation of Interstitial Hot-Spots Using the Reduced Gap-Size between Plasmonic Microbeads Pattern for Surface-Enhanced Raman Scattering Analysis

by Taeksu Lee, Sanghee Jung, Soongeun Kwon, Woochang Kim, Jinsung Park, Hyungjun Lim and JaeJong Lee

Sensors 2019, 19(5), 1046; https://doi.org/10.3390/s19051046 - 1 Mar 2019

Cited by 16 | Viewed by 3228

Abstract

To achieve an effective surface-enhanced Raman scattering (SERS) sensor with periodically distributed “hot spots” on wafer-scale substrates, we propose a hybrid approach combining physical nano-imprint lithography and a chemical deposition method to form a silver microbead array. Nano-imprint lithography (NIL) can lead to [...] Read more.

To achieve an effective surface-enhanced Raman scattering (SERS) sensor with periodically distributed “hot spots” on wafer-scale substrates, we propose a hybrid approach combining physical nano-imprint lithography and a chemical deposition method to form a silver microbead array. Nano-imprint lithography (NIL) can lead to mass-production and high throughput, but is not appropriate for generating strong “hot-spots.” However, when we apply electrochemical deposition to an NIL substrate and the reaction time was increased to 45 s, periodical “hot-spots” between the microbeads were generated on the substrates. It contributed to increasing the enhancement factor (EF) and lowering the detection limit of the substrates to 4.40 × 10⁶ and 1.0 × 10⁻¹¹ M, respectively. In addition, this synthetic method exhibited good substrate-to-substrate reproducibility (RSD < 9.4%). Our research suggests a new opportunity for expanding the SERS application. Full article

(This article belongs to the Special Issue SERS Sensing)

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46 pages, 13356 KiB

Open AccessEditor’s ChoiceReview

EM-Wave Biosensors: A Review of RF, Microwave, mm-Wave and Optical Sensing

by Parikha Mehrotra, Baibhab Chatterjee and Shreyas Sen

Sensors 2019, 19(5), 1013; https://doi.org/10.3390/s19051013 - 27 Feb 2019

Cited by 137 | Viewed by 18085

Abstract

This article presents a broad review on optical, radio-frequency (RF), microwave (MW), millimeter wave (mmW) and terahertz (THz) biosensors. Biomatter-wave interaction modalities are considered over a wide range of frequencies and applications such as detection of cancer biomarkers, biotin, neurotransmitters and heart rate [...] Read more.

This article presents a broad review on optical, radio-frequency (RF), microwave (MW), millimeter wave (mmW) and terahertz (THz) biosensors. Biomatter-wave interaction modalities are considered over a wide range of frequencies and applications such as detection of cancer biomarkers, biotin, neurotransmitters and heart rate are presented in detail. By treating biological tissue as a dielectric substance, having a unique dielectric signature, it can be characterized by frequency dependent parameters such as permittivity and conductivity. By observing the unique permittivity spectrum, cancerous cells can be distinguished from healthy ones or by measuring the changes in permittivity, concentration of medically relevant biomolecules such as glucose, neurotransmitters, vitamins and proteins, ailments and abnormalities can be detected. In case of optical biosensors, any change in permittivity is transduced to a change in optical properties such as photoluminescence, interference pattern, reflection intensity and reflection angle through techniques like quantum dots, interferometry, surface enhanced raman scattering or surface plasmon resonance. Conversely, in case of RF, MW, mmW and THz biosensors, capacitive sensing is most commonly employed where changes in permittivity are reflected as changes in capacitance, through components like interdigitated electrodes, resonators and microstrip structures. In this paper, interactions of EM waves with biomatter are considered, with an emphasis on a clear demarcation of various modalities, their underlying principles and applications. Full article

(This article belongs to the Special Issue RF, Microwave and mm Wave Sensors and Applicators for Chemical, Biological and Medical Applications)

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14 pages, 2752 KiB

Open AccessEditor’s ChoiceArticle

The Effects of Housing Environments on the Performance of Activity-Recognition Systems Using Wi-Fi Channel State Information: An Exploratory Study

by Hoonyong Lee, Changbum R. Ahn, Nakjung Choi, Toseung Kim and Hyunsoo Lee

Sensors 2019, 19(5), 983; https://doi.org/10.3390/s19050983 - 26 Feb 2019

Cited by 29 | Viewed by 5999

Abstract

Recently, device-free human activity–monitoring systems using commercial Wi-Fi devices have demonstrated a great potential to support smart home environments. These systems exploit Channel State Information (CSI), which represents how human activities–based environmental changes affect the Wi-Fi signals propagating through physical space. However, given [...] Read more.

Recently, device-free human activity–monitoring systems using commercial Wi-Fi devices have demonstrated a great potential to support smart home environments. These systems exploit Channel State Information (CSI), which represents how human activities–based environmental changes affect the Wi-Fi signals propagating through physical space. However, given that Wi-Fi signals either penetrate through an obstacle or are reflected by the obstacle, there is a high chance that the housing environment would have a great impact on the performance of a CSI-based activity-recognition system. In this context, this paper examines whether and to what extent housing environment affects the performance of the CSI-based activity recognition systems. Activities in daily living (ADL)–recognition systems were implemented in two typical housing environments representative of the United States and South Korea: a wood-frame apartment (Unit A) and a reinforced concrete-frame apartment (Unit B), respectively. The experimental results show that housing environments, combined with various environmental factors (i.e., structural building materials, surrounding Wi-Fi interference, housing layout, and population density), generate a significant difference in the accuracy of the applied CSI-based ADL-recognition systems. This outcome provides insights into how such ADL systems should be configured for various home environments. Full article

(This article belongs to the Special Issue Sensor Technology for Smart Homes)

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25 pages, 10305 KiB

Open AccessEditor’s ChoiceArticle

Deep Learning-Based Framework for In Vivo Identification of Glioblastoma Tumor using Hyperspectral Images of Human Brain

by Himar Fabelo, Martin Halicek, Samuel Ortega, Maysam Shahedi, Adam Szolna, Juan F. Piñeiro, Coralia Sosa, Aruma J. O’Shanahan, Sara Bisshopp, Carlos Espino, Mariano Márquez, María Hernández, David Carrera, Jesús Morera, Gustavo M. Callico, Roberto Sarmiento and Baowei Fei

Sensors 2019, 19(4), 920; https://doi.org/10.3390/s19040920 - 22 Feb 2019

Cited by 111 | Viewed by 8350

Abstract

The main goal of brain cancer surgery is to perform an accurate resection of the tumor, preserving as much normal brain tissue as possible for the patient. The development of a non-contact and label-free method to provide reliable support for tumor resection in [...] Read more.

The main goal of brain cancer surgery is to perform an accurate resection of the tumor, preserving as much normal brain tissue as possible for the patient. The development of a non-contact and label-free method to provide reliable support for tumor resection in real-time during neurosurgical procedures is a current clinical need. Hyperspectral imaging is a non-contact, non-ionizing, and label-free imaging modality that can assist surgeons during this challenging task without using any contrast agent. In this work, we present a deep learning-based framework for processing hyperspectral images of in vivo human brain tissue. The proposed framework was evaluated by our human image database, which includes 26 in vivo hyperspectral cubes from 16 different patients, among which 258,810 pixels were labeled. The proposed framework is able to generate a thematic map where the parenchymal area of the brain is delineated and the location of the tumor is identified, providing guidance to the operating surgeon for a successful and precise tumor resection. The deep learning pipeline achieves an overall accuracy of 80% for multiclass classification, improving the results obtained with traditional support vector machine (SVM)-based approaches. In addition, an aid visualization system is presented, where the final thematic map can be adjusted by the operating surgeon to find the optimal classification threshold for the current situation during the surgical procedure. Full article

(This article belongs to the Special Issue Advanced Spectroscopy, Imaging and Sensing in Biomedicine)

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19 pages, 5536 KiB

Open AccessEditor’s ChoiceArticle

Slotted ALOHA on LoRaWAN-Design, Analysis, and Deployment

by Tommaso Polonelli, Davide Brunelli, Achille Marzocchi and Luca Benini

Sensors 2019, 19(4), 838; https://doi.org/10.3390/s19040838 - 18 Feb 2019

Cited by 130 | Viewed by 9126

Abstract

LoRaWAN is one of the most promising standards for long-range sensing applications. However, the high number of end devices expected in at-scale deployment, combined with the absence of an effective synchronization scheme, challenge the scalability of this standard. In this paper, we present [...] Read more.

LoRaWAN is one of the most promising standards for long-range sensing applications. However, the high number of end devices expected in at-scale deployment, combined with the absence of an effective synchronization scheme, challenge the scalability of this standard. In this paper, we present an approach to increase network throughput through a Slotted-ALOHA overlay on LoRaWAN networks. To increase the single channel capacity, we propose to regulate the communication of LoRaWAN networks using a Slotted-ALOHA variant on the top of the Pure-ALOHA approach used by the standard; thus, no modification in pre-existing libraries is necessary. Our method is based on an innovative synchronization service that is suitable for low-cost wireless sensor nodes. We modelled the LoRaWAN channel with extensive measurement on hardware platforms, and we quantified the impact of tuning parameters on physical and medium access control layers, as well as the packet collision rate. Results show that Slotted-ALOHA supported by our synchronization service significantly improves the performance of traditional LoRaWAN networks regarding packet loss rate and network throughput. Full article

(This article belongs to the Special Issue Low Energy Wireless Sensor Networks: Protocols, Architectures and Solutions)

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45 pages, 6190 KiB

Open AccessEditor’s ChoiceReview

The Progress of Glucose Monitoring—A Review of Invasive to Minimally and Non-Invasive Techniques, Devices and Sensors

by Wilbert Villena Gonzales, Ahmed Toaha Mobashsher and Amin Abbosh

Sensors 2019, 19(4), 800; https://doi.org/10.3390/s19040800 - 15 Feb 2019

Cited by 363 | Viewed by 48887

Abstract

Current glucose monitoring methods for the ever-increasing number of diabetic people around the world are invasive, painful, time-consuming, and a constant burden for the household budget. The non-invasive glucose monitoring technology overcomes these limitations, for which this topic is significantly being researched and [...] Read more.

Current glucose monitoring methods for the ever-increasing number of diabetic people around the world are invasive, painful, time-consuming, and a constant burden for the household budget. The non-invasive glucose monitoring technology overcomes these limitations, for which this topic is significantly being researched and represents an exciting and highly sought after market for many companies. This review aims to offer an up-to-date report on the leading technologies for non-invasive (NI) and minimally-invasive (MI) glucose monitoring sensors, devices currently available in the market, regulatory framework for accuracy assessment, new approaches currently under study by representative groups and developers, and algorithm types for signal enhancement and value prediction. The review also discusses the future trend of glucose detection by analyzing the usage of the different bands in the electromagnetic spectrum. The review concludes that the adoption and use of new technologies for glucose detection is unavoidable and closer to become a reality. Full article

(This article belongs to the Special Issue Electromagnetic Medical Sensing)

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14 pages, 4886 KiB

Open AccessEditor’s ChoiceArticle

Waste Coffee Ground Biochar: A Material for Humidity Sensors

by Pravin Jagdale, Daniele Ziegler, Massimo Rovere, Jean Marc Tulliani and Alberto Tagliaferro

Sensors 2019, 19(4), 801; https://doi.org/10.3390/s19040801 - 15 Feb 2019

Cited by 48 | Viewed by 9633

Abstract

Worldwide consumption of coffee exceeds 11 billion tons/year. Used coffee grounds end up as landfill. However, the unique structural properties of its porous surface make coffee grounds popular for the adsorption of gaseous molecules. In the present work, we demonstrate the use of [...] Read more.

Worldwide consumption of coffee exceeds 11 billion tons/year. Used coffee grounds end up as landfill. However, the unique structural properties of its porous surface make coffee grounds popular for the adsorption of gaseous molecules. In the present work, we demonstrate the use of coffee grounds as a potential and cheap source for biochar carbon. The produced coffee ground biochar (CGB) was investigated as a sensing material for developing humidity sensors. CGB was fully characterized by using laser granulometry, X-ray diffraction (XRD), Raman spectroscopy, field emission-scanning electron microscopy (FESEM), X-ray photoelectron spectroscopy (XPS), thermogravimetric analysis (TGA) and the Brunnauer Emmett Teller (BET) technique in order to acquire a complete understanding of its structural and surface properties and composition. Subsequently humidity sensors were screen printed using an ink-containing CGB with polyvinyl butyral (PVB) acting as a temporary binder and ethylene glycol monobutyral ether, Emflow, as an organic vehicle so that the proper rheological characteristics were achieved. Screen-printed films were the heated at 300 °C in air. Humidity tests were performed under a flow of 1.7 L/min in the relative humidity range 0–100% at room temperature. The initial impedance of the film was 25.2 ± 0.15 MΩ which changes to 12.3 MΩ under 98% humidity exposure. A sensor response was observed above 20% relative humidity (RH). Both the response and recovery times were reasonably fast (less than 2 min). Full article

(This article belongs to the Special Issue Functional Materials for the Applications of Advanced Gas Sensors)

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14 pages, 2699 KiB

Open AccessEditor’s ChoiceArticle

Enhanced Hydrogen Detection in ppb-Level by Electrospun SnO₂-Loaded ZnO Nanofibers

by Jae-Hyoung Lee, Jin-Young Kim, Jae-Hun Kim and Sang Sub Kim

Sensors 2019, 19(3), 726; https://doi.org/10.3390/s19030726 - 11 Feb 2019

Cited by 39 | Viewed by 5289

Abstract

High-performance hydrogen sensors are important in many industries to effectively address safety concerns related to the production, delivering, storage and use of H₂ gas. Herein, we present a highly sensitive hydrogen gas sensor based on SnO₂-loaded ZnO nanofibers (NFs). The [...] Read more.

High-performance hydrogen sensors are important in many industries to effectively address safety concerns related to the production, delivering, storage and use of H₂ gas. Herein, we present a highly sensitive hydrogen gas sensor based on SnO₂-loaded ZnO nanofibers (NFs). The xSnO₂-loaded (x = 0.05, 0.1 and 0.15) ZnO NFs were fabricated using an electrospinning technique followed by calcination at high temperature. Microscopic analyses demonstrated the formation of NFs with expected morphology and chemical composition. Hydrogen sensing studies were performed at various temperatures and the optimal working temperature was selected as 300 °C. The optimal gas sensor (0.1 SnO₂ loaded ZnO NFs) not only showed a high response to 50 ppb hydrogen gas, but also showed an excellent selectivity to hydrogen gas. The excellent performance of the gas sensor to hydrogen gas was mainly related to the formation of SnO₂-ZnO heterojunctions and the metallization effect of ZnO. Full article

(This article belongs to the Section Chemical Sensors)

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35 pages, 10607 KiB

Open AccessFeature PaperEditor’s ChoiceReview

Layer-by-Layer Nano-assembly: A Powerful Tool for Optical Fiber Sensing Applications

by Pedro J. Rivero, Javier Goicoechea and Francisco J. Arregui

Sensors 2019, 19(3), 683; https://doi.org/10.3390/s19030683 - 7 Feb 2019

Cited by 52 | Viewed by 7043

Abstract

The ability to tune the composition of nanostructured thin films is a hot topic for the design of functional coatings with advanced properties for sensing applications. The control of the structure at the nanoscale level enables an improvement of intrinsic properties (optical, chemical [...] Read more.

The ability to tune the composition of nanostructured thin films is a hot topic for the design of functional coatings with advanced properties for sensing applications. The control of the structure at the nanoscale level enables an improvement of intrinsic properties (optical, chemical or physical) in comparison with the traditional bulk materials. In this sense, among all the known nanofabrication techniques, the layer-by-layer (LbL) nano-assembly method is a flexible, easily-scalable and versatile approach which makes possible precise control of the coating thickness, composition and structure. The development of sensitive nanocoatings has shown an exceptional growth in optical fiber sensing applications due to their self-assembling ability with oppositely charged components in order to obtain a multilayer structure. This nanoassembly technique is a powerful tool for the incorporation of a wide variety of species (polyelectrolytes, metal/metal oxide nanoparticles, hybrid particles, luminescent materials, dyes or biomolecules) in the resultant multilayer structure for the design of high-performance optical fiber sensors. In this work we present a review of applications related to optical fiber sensors based on advanced LbL coatings in two related research areas of great interest for the scientific community, namely chemical sensing (pH, gases and volatile organic compounds detection) as well as biological/biochemical sensing (proteins, immunoglobulins, antibodies or DNA detection). Full article

(This article belongs to the Special Issue Nanostructured Surfaces in Sensing Systems)

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17 pages, 5284 KiB

Open AccessEditor’s ChoiceArticle

An Improved Routing Schema with Special Clustering Using PSO Algorithm for Heterogeneous Wireless Sensor Network

by Jin Wang, Yu Gao, Wei Liu, Arun Kumar Sangaiah and Hye-Jin Kim

Sensors 2019, 19(3), 671; https://doi.org/10.3390/s19030671 - 7 Feb 2019

Cited by 208 | Viewed by 8678

Abstract

Energy efficiency and energy balancing are crucial research issues as per routing protocol designing for self-organized wireless sensor networks (WSNs). Many literatures used the clustering algorithm to achieve energy efficiency and energy balancing, however, there are usually energy holes near the cluster heads [...] Read more.

Energy efficiency and energy balancing are crucial research issues as per routing protocol designing for self-organized wireless sensor networks (WSNs). Many literatures used the clustering algorithm to achieve energy efficiency and energy balancing, however, there are usually energy holes near the cluster heads (CHs) because of the heavy burden of forwarding. As the clustering problem in lossy WSNs is proved to be a NP-hard problem, many metaheuristic algorithms are utilized to solve the problem. In this paper, a special clustering method called Energy Centers Searching using Particle Swarm Optimization (EC-PSO) is presented to avoid these energy holes and search energy centers for CHs selection. During the first period, the CHs are elected using geometric method. After the energy of the network is heterogeneous, EC-PSO is adopted for clustering. Energy centers are searched using an improved PSO algorithm and nodes close to the energy center are elected as CHs. Additionally, a protection mechanism is also used to prevent low energy nodes from being the forwarder and a mobile data collector is introduced to gather the data. We conduct numerous simulations to illustrate that our presented EC-PSO outperforms than some similar works in terms of network lifetime enhancement and energy utilization ratio. Full article

(This article belongs to the Special Issue Recent Advances in Data Mining and Information Fusion in Wireless Sensors Networks)

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34 pages, 5506 KiB

Open AccessEditor’s ChoiceReview

Fluorescent Sensors for the Detection of Heavy Metal Ions in Aqueous Media

by Nerea De Acha, César Elosúa, Jesús M. Corres and Francisco J. Arregui

Sensors 2019, 19(3), 599; https://doi.org/10.3390/s19030599 - 31 Jan 2019

Cited by 179 | Viewed by 15243

Abstract

Due to the risks that water contamination implies for human health and environmental protection, monitoring the quality of water is a major concern of the present era. Therefore, in recent years several efforts have been dedicated to the development of fast, sensitive, and [...] Read more.

Due to the risks that water contamination implies for human health and environmental protection, monitoring the quality of water is a major concern of the present era. Therefore, in recent years several efforts have been dedicated to the development of fast, sensitive, and selective sensors for the detection of heavy metal ions. In particular, fluorescent sensors have gained in popularity due to their interesting features, such as high specificity, sensitivity, and reversibility. Thus, this review is devoted to the recent advances in fluorescent sensors for the monitoring of these contaminants, and special focus is placed on those devices based on fluorescent aptasensors, quantum dots, and organic dyes. Full article

(This article belongs to the Special Issue Optical Chemical Nanosensors)

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12 pages, 17892 KiB

Open AccessEditor’s ChoiceArticle

Embedded Smart Antenna for Non-Destructive Testing and Evaluation (NDT&E) of Moisture Content and Deterioration in Concrete

by Kah Hou Teng, Patryk Kot, Magomed Muradov, Andy Shaw, Khalid Hashim, Michaela Gkantou and Ahmed Al-Shamma’a

Sensors 2019, 19(3), 547; https://doi.org/10.3390/s19030547 - 28 Jan 2019

Cited by 68 | Viewed by 6883

Abstract

Concrete failure will lead to serious safety concerns in the performance of a building structure. It is one of the biggest challenges for engineers to inspect and maintain the quality of concrete throughout the service years in order to prevent structural deterioration. To [...] Read more.

Concrete failure will lead to serious safety concerns in the performance of a building structure. It is one of the biggest challenges for engineers to inspect and maintain the quality of concrete throughout the service years in order to prevent structural deterioration. To date, a lot of research is ongoing to develop different instruments to inspect concrete quality. Detection of moisture ingress is important in the structural monitoring of concrete. This paper presents a novel sensing technique using a smart antenna for the non-destructive evaluation of moisture content and deterioration inspection in concrete blocks. Two different standard concrete samples (United Kingdom and Malaysia) were investigated in this research. An electromagnetic (EM) sensor was designed and embedded inside the concrete to detect the moisture content within the structure. In addition, CST microwave studio was used to validate the theoretical model of the EM sensor against the test data. The results demonstrated that the EM sensor at 2.45 GHz is capable of detecting the moisture content in the concrete with linear regression of R² = 0.9752. Furthermore, identification of different mix ratios of concrete were successfully demonstrated in this paper. In conclusion, the EM sensor is capable of detecting moisture content non-destructively and could be a potential technique for maintenance and quality control of the building performance. Full article

(This article belongs to the Special Issue RF Technology for Sensor Applications)

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17 pages, 32838 KiB

Open AccessEditor’s ChoiceArticle

Comparing UAV-Based Technologies and RGB-D Reconstruction Methods for Plant Height and Biomass Monitoring on Grass Ley

by Victor P. Rueda-Ayala, José M. Peña, Mats Höglind, José M. Bengochea-Guevara and Dionisio Andújar

Sensors 2019, 19(3), 535; https://doi.org/10.3390/s19030535 - 28 Jan 2019

Cited by 67 | Viewed by 9138

Abstract

Pastures are botanically diverse and difficult to characterize. Digital modeling of pasture biomass and quality by non-destructive methods can provide highly valuable support for decision-making. This study aimed to evaluate aerial and on-ground methods to characterize grass ley fields, estimating plant height, biomass [...] Read more.

Pastures are botanically diverse and difficult to characterize. Digital modeling of pasture biomass and quality by non-destructive methods can provide highly valuable support for decision-making. This study aimed to evaluate aerial and on-ground methods to characterize grass ley fields, estimating plant height, biomass and volume, using digital grass models. Two fields were sampled, one timothy-dominant and the other ryegrass-dominant. Both sensing systems allowed estimation of biomass, volume and plant height, which were compared with ground truth, also taking into consideration basic economical aspects. To obtain ground-truth data for validation, 10 plots of 1 m² were manually and destructively sampled on each field. The studied systems differed in data resolution, thus in estimation capability. There was a reasonably good agreement between the UAV-based, the RGB-D-based estimates and the manual height measurements on both fields. RGB-D-based estimation correlated well with ground truth of plant height (

R^{2} > 0.80

) for both fields, and with dry biomass (

R^{2} = 0.88

), only for the timothy field. RGB-D-based estimation of plant volume for ryegrass showed a high agreement (

R^{2} = 0.87

). The UAV-based system showed a weaker estimation capability for plant height and dry biomass (

R^{2} < 0.6

). UAV-systems are more affordable, easier to operate and can cover a larger surface. On-ground techniques with RGB-D cameras can produce highly detailed models, but with more variable results than UAV-based models. On-ground RGB-D data can be effectively analysed with open source software, which is a cost reduction advantage, compared with aerial image analysis. Since the resolution for agricultural operations does not need fine identification the end-details of the grass plants, the use of aerial platforms could result a better option in grasslands. Full article

(This article belongs to the Special Issue Emerging Sensor Technology in Agriculture)

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