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Editor’s Choice Articles

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

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29 pages, 2695 KiB  
Review
A Systematic Review of IoT Solutions for Smart Farming
by Emerson Navarro, Nuno Costa and António Pereira
Sensors 2020, 20(15), 4231; https://doi.org/10.3390/s20154231 - 29 Jul 2020
Cited by 247 | Viewed by 36022
Abstract
The world population growth is increasing the demand for food production. Furthermore, the reduction of the workforce in rural areas and the increase in production costs are challenges for food production nowadays. Smart farming is a farm management concept that may use Internet [...] Read more.
The world population growth is increasing the demand for food production. Furthermore, the reduction of the workforce in rural areas and the increase in production costs are challenges for food production nowadays. Smart farming is a farm management concept that may use Internet of Things (IoT) to overcome the current challenges of food production. This work uses the preferred reporting items for systematic reviews (PRISMA) methodology to systematically review the existing literature on smart farming with IoT. The review aims to identify the main devices, platforms, network protocols, processing data technologies and the applicability of smart farming with IoT to agriculture. The review shows an evolution in the way data is processed in recent years. Traditional approaches mostly used data in a reactive manner. In more recent approaches, however, new technological developments allowed the use of data to prevent crop problems and to improve the accuracy of crop diagnosis. Full article
(This article belongs to the Special Issue IoT for Smart Food and Farming)
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20 pages, 8702 KiB  
Article
Pavement Crack Detection from Mobile Laser Scanning Point Clouds Using a Time Grid
by Mianqing Zhong, Lichun Sui, Zhihua Wang and Dongming Hu
Sensors 2020, 20(15), 4198; https://doi.org/10.3390/s20154198 - 28 Jul 2020
Cited by 40 | Viewed by 6405
Abstract
This paper presents a novel algorithm for detecting pavement cracks from mobile laser scanning (MLS) data. The algorithm losslessly transforms MLS data into a regular grid structure to adopt the proven image-based methods of crack extraction. To address the problem of lacking topology, [...] Read more.
This paper presents a novel algorithm for detecting pavement cracks from mobile laser scanning (MLS) data. The algorithm losslessly transforms MLS data into a regular grid structure to adopt the proven image-based methods of crack extraction. To address the problem of lacking topology, this study assigns a two-dimensional index for each laser point depending on its scanning angle or acquisition time. Next, crack candidates are identified by integrating the differential intensity and height changes from their neighbors. Then, morphology filtering, a thinning algorithm, and the Freeman codes serve for the extraction of the edge and skeleton of the crack curves. Further than the other studies, this work quantitatively evaluates crack shape parameters: crack direction, width, length, and area, from the extracted crack points. The F1 scores of the quantity of the transverse, longitudinal, and oblique cracks correctly extracted from the test data reached 96.55%, 87.09%, and 81.48%, respectively. In addition, the average accuracy of the crack width and length exceeded 0.812 and 0.897. Experimental results demonstrate that the proposed approach is robust for detecting pavement cracks in a complex road surface status. The proposed method is also promising in serving the extraction of other on-road objects. Full article
(This article belongs to the Special Issue Mobile Multi-Sensors in Positioning, Navigation, and Mapping Applications)
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16 pages, 6976 KiB  
Article
A Variable Data Fusion Approach for Electromechanical Impedance-Based Damage Detection
by Shishir Kumar Singh, Rohan Soman, Tomasz Wandowski and Pawel Malinowski
Sensors 2020, 20(15), 4204; https://doi.org/10.3390/s20154204 - 28 Jul 2020
Cited by 23 | Viewed by 3707
Abstract
There is continuing research in the area of structural health monitoring (SHM) as it may allow a reduction in maintenance costs as well as lifetime extension. The search for a low-cost health monitoring system that is able to detect small levels of damage [...] Read more.
There is continuing research in the area of structural health monitoring (SHM) as it may allow a reduction in maintenance costs as well as lifetime extension. The search for a low-cost health monitoring system that is able to detect small levels of damage is still on-going. The present study is one more step in this direction. This paper describes a data fusion technique by combining the information for robust damage detection using the electromechanical impedance (EMI) method. The EMI method is commonly used for damage detection due to its sensitivity to low levels of damage. In this paper, the information of resistance (R) and conductance (G) is studied in a selected frequency band and a novel data fusion approach is proposed. A novel fused parameter (F) is developed by combining the information from G and R. The difference in the new metric under different damage conditions is then quantified using established indices such as the root mean square deviation (RMSD) index, mean absolute percentage deviation (MAPD), and root mean square deviation using k-th state as the reference (RMSDk). The paper presents an application of the new metric for detection of damage in three structures, namely, a thin aluminum (Al) plate with increasing damage severity (simulated with a drilled hole of increasing size), a glass fiber reinforced polymer (GFRP) composite beam with increasing delamination and another GFRP plate with impact-induced damage scenarios. Based on the experimental results, it is apparent that the variable F increases the robustness of the damage detection as compared to the quantities R and G. Full article
(This article belongs to the Special Issue Smart Sensors for Damage Detection)
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20 pages, 6310 KiB  
Article
Development of Synchronized High-Sensitivity Wireless Accelerometer for Structural Health Monitoring
by Shaik Althaf Veluthedath Shajihan, Raymond Chow, Kirill Mechitov, Yuguang Fu, Tu Hoang and Billie F. Spencer
Sensors 2020, 20(15), 4169; https://doi.org/10.3390/s20154169 - 27 Jul 2020
Cited by 30 | Viewed by 7902
Abstract
The use of digital accelerometers featuring high sensitivity and low noise levels in wireless smart sensors (WSSs) is becoming increasingly common for structural health monitoring (SHM) applications. Improvements in the design of Micro Electro-Mechanical System (MEMS) based digital accelerometers allow for high resolution [...] Read more.
The use of digital accelerometers featuring high sensitivity and low noise levels in wireless smart sensors (WSSs) is becoming increasingly common for structural health monitoring (SHM) applications. Improvements in the design of Micro Electro-Mechanical System (MEMS) based digital accelerometers allow for high resolution sensing required for SHM with low power consumption suitable for WSSs. However, new approaches are needed to synchronize data from these sensors. Data synchronization is essential in wireless smart sensor networks (WSSNs) for accurate condition assessment of structures and reduced false-positive indications of damage. Efforts to achieve synchronized data sampling from multiple WSS nodes with digital accelerometers have been lacking, primarily because these sensors feature an internal Analog to Digital Converter (ADC) to which the host platform has no direct access. The result is increased uncertainty in the ADC startup time and thus worse synchronization among sensors. In this study, a high-sensitivity digital accelerometer is integrated with a next-generation WSS platform, the Xnode. An adaptive iterative algorithm is used to characterize these delays without the need for a dedicated evaluation setup and hardware-level access to the ADC. Extensive tests are conducted to evaluate the performance of the accelerometer experimentally. Overall time-synchronization achieved is under 15 µs, demonstrating the efficacy of this approach for synchronization of critical SHM applications. Full article
(This article belongs to the Special Issue Toward Data-Driven Structural Health Monitoring: New Approaches and Sensor-Based Methods)
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22 pages, 1782 KiB  
Review
Detection and Classification of Multirotor Drones in Radar Sensor Networks: A Review
by Angelo Coluccia, Gianluca Parisi and Alessio Fascista
Sensors 2020, 20(15), 4172; https://doi.org/10.3390/s20154172 - 27 Jul 2020
Cited by 101 | Viewed by 14020
Abstract
Thanks to recent technological advances, a new generation of low-cost, small, unmanned aerial vehicles (UAVs) is available. Small UAVs, often called drones, are enabling unprecedented applications but, at the same time, new threats are arising linked to their possible misuse (e.g., drug smuggling, [...] Read more.
Thanks to recent technological advances, a new generation of low-cost, small, unmanned aerial vehicles (UAVs) is available. Small UAVs, often called drones, are enabling unprecedented applications but, at the same time, new threats are arising linked to their possible misuse (e.g., drug smuggling, terrorist attacks, espionage). In this paper, the main challenges related to the problem of drone identification are discussed, which include detection, possible verification, and classification. An overview of the most relevant technologies is provided, which in modern surveillance systems are composed into a network of spatially-distributed sensors to ensure full coverage of the monitored area. More specifically, the main focus is on the frequency modulated continuous wave (FMCW) radar sensor, which is a key technology also due to its low cost and capability to work at relatively long distances, as well as strong robustness to illumination and weather conditions. This paper provides a review of the existing literature on the most promising approaches adopted in the different phases of the identification process, i.e., detection of the possible presence of drones, target verification, and classification. Full article
(This article belongs to the Special Issue Sensor Network Signal Processing)
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18 pages, 6015 KiB  
Article
Extended Kalman Filter (EKF) Design for Vehicle Position Tracking Using Reliability Function of Radar and Lidar
by Taeklim Kim and Tae-Hyoung Park
Sensors 2020, 20(15), 4126; https://doi.org/10.3390/s20154126 - 24 Jul 2020
Cited by 98 | Viewed by 14245
Abstract
Detection and distance measurement using sensors is not always accurate. Sensor fusion makes up for this shortcoming by reducing inaccuracies. This study, therefore, proposes an extended Kalman filter (EKF) that reflects the distance characteristics of lidar and radar sensors. The sensor characteristics of [...] Read more.
Detection and distance measurement using sensors is not always accurate. Sensor fusion makes up for this shortcoming by reducing inaccuracies. This study, therefore, proposes an extended Kalman filter (EKF) that reflects the distance characteristics of lidar and radar sensors. The sensor characteristics of the lidar and radar over distance were analyzed, and a reliability function was designed to extend the Kalman filter to reflect distance characteristics. The accuracy of position estimation was improved by identifying the sensor errors according to distance. Experiments were conducted using real vehicles, and a comparative experiment was done combining sensor fusion using a fuzzy, adaptive measure noise and Kalman filter. Experimental results showed that the study’s method produced accurate distance estimations. Full article
(This article belongs to the Special Issue Sensors and Sensor's Fusion in Autonomous Vehicles)
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65 pages, 11440 KiB  
Review
A Review of Acoustic Impedance Matching Techniques for Piezoelectric Sensors and Transducers
by Vivek T. Rathod
Sensors 2020, 20(14), 4051; https://doi.org/10.3390/s20144051 - 21 Jul 2020
Cited by 196 | Viewed by 35259
Abstract
The coupling of waves between the piezoelectric generators, detectors, and propagating media is challenging due to mismatch in the acoustic properties. The mismatch leads to the reverberation of waves within the transducer, heating, low signal-to-noise ratio, and signal distortion. Acoustic impedance matching increases [...] Read more.
The coupling of waves between the piezoelectric generators, detectors, and propagating media is challenging due to mismatch in the acoustic properties. The mismatch leads to the reverberation of waves within the transducer, heating, low signal-to-noise ratio, and signal distortion. Acoustic impedance matching increases the coupling largely. This article presents standard methods to match the acoustic impedance of the piezoelectric sensors, actuators, and transducers with the surrounding wave propagation media. Acoustic matching methods utilizing active and passive materials have been discussed. Special materials such as nanocomposites, metamaterials, and metasurfaces as emerging materials have been presented. Emphasis is placed throughout the article to differentiate the difference between electric and acoustic impedance matching and the relation between the two. Comparison of various techniques is made with the discussion on capabilities, advantages, and disadvantages. Acoustic impedance matching for specific and uncommon applications has also been covered. Full article
(This article belongs to the Section Electronic Sensors)
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16 pages, 4758 KiB  
Article
Sensing the Generation of Intracellular Free Electrons Using the Inactive Catalytic Subunit of Cytochrome P450s as a Sink
by Damilare D. Akintade and Bhabatosh Chaudhuri
Sensors 2020, 20(14), 4050; https://doi.org/10.3390/s20144050 - 21 Jul 2020
Cited by 8 | Viewed by 3283
Abstract
Cytochrome P450 reductase (CPR) abstracts electrons from Nicotinamide adenine dinucleotide phosphate H (NADPH), transferring them to an active Cytochrome P450 (CYP) site to provide a functional CYP. In the present study, a yeast strain was genetically engineered to delete the endogenous CPR gene. [...] Read more.
Cytochrome P450 reductase (CPR) abstracts electrons from Nicotinamide adenine dinucleotide phosphate H (NADPH), transferring them to an active Cytochrome P450 (CYP) site to provide a functional CYP. In the present study, a yeast strain was genetically engineered to delete the endogenous CPR gene. A human CYP expressed in a CPR-null (yRD−) strain was inactive. It was queried if Bax—which induces apoptosis in yeast and human cells by generating reactive oxygen species (ROS)—substituted for the absence of CPR. Since Bax-generated ROS stems from an initial release of electrons, is it possible for these released electrons to be captured by an inactive CYP to make it active once again? In this study, yeast cells that did not contain any CPR activity (i.e., because the yeasts’ CPR gene was completely deleted) were used to show that (a) human CYPs produced within CPR-null (yRD-) yeast cells were inactive and (b) low levels of the pro-apoptotic human Bax protein could activate inactive human CYPs within this yeast cells. Surprisingly, Bax activated three inactive CYP proteins, confirming that it could compensate for CPR’s absence within yeast cells. These findings could be useful in research, development of bioassays, bioreactors, biosensors, and disease diagnosis, among others. Full article
(This article belongs to the Section Biosensors)
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36 pages, 10030 KiB  
Review
Micromachined Accelerometers with Sub-µg/√Hz Noise Floor: A Review
by Chen Wang, Fang Chen, Yuan Wang, Sina Sadeghpour, Chenxi Wang, Mathieu Baijot, Rui Esteves, Chun Zhao, Jian Bai, Huafeng Liu and Michael Kraft
Sensors 2020, 20(14), 4054; https://doi.org/10.3390/s20144054 - 21 Jul 2020
Cited by 77 | Viewed by 13033
Abstract
This paper reviews the research and development of micromachined accelerometers with a noise floor lower than 1 µg/√Hz. Firstly, the basic working principle of micromachined accelerometers is introduced. Then, different methods of reducing the noise floor of micromachined accelerometers are analyzed. Different types [...] Read more.
This paper reviews the research and development of micromachined accelerometers with a noise floor lower than 1 µg/√Hz. Firstly, the basic working principle of micromachined accelerometers is introduced. Then, different methods of reducing the noise floor of micromachined accelerometers are analyzed. Different types of micromachined accelerometers with a noise floor below 1 µg/√Hz are discussed. Such sensors can mainly be categorized into: (i) micromachined accelerometers with a low spring constant; (ii) with a large proof mass; (iii) with a high quality factor; (iv) with a low noise interface circuit; (v) with sensing schemes leading to a high scale factor. Finally, the characteristics of various micromachined accelerometers and their trends are discussed and investigated. Full article
(This article belongs to the Special Issue Feature Papers in Physical Sensors Section 2020)
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63 pages, 3618 KiB  
Review
Review of Microfluidic Devices and Imaging Techniques for Fluid Flow Study in Porous Geomaterials
by Amir Jahanbakhsh, Krystian L. Wlodarczyk, Duncan P. Hand, Robert R. J. Maier and M. Mercedes Maroto-Valer
Sensors 2020, 20(14), 4030; https://doi.org/10.3390/s20144030 - 20 Jul 2020
Cited by 52 | Viewed by 12457
Abstract
Understanding transport phenomena and governing mechanisms of different physical and chemical processes in porous media has been a critical research area for decades. Correlating fluid flow behaviour at the micro-scale with macro-scale parameters, such as relative permeability and capillary pressure, is key to [...] Read more.
Understanding transport phenomena and governing mechanisms of different physical and chemical processes in porous media has been a critical research area for decades. Correlating fluid flow behaviour at the micro-scale with macro-scale parameters, such as relative permeability and capillary pressure, is key to understanding the processes governing subsurface systems, and this in turn allows us to improve the accuracy of modelling and simulations of transport phenomena at a large scale. Over the last two decades, there have been significant developments in our understanding of pore-scale processes and modelling of complex underground systems. Microfluidic devices (micromodels) and imaging techniques, as facilitators to link experimental observations to simulation, have greatly contributed to these achievements. Although several reviews exist covering separately advances in one of these two areas, we present here a detailed review integrating recent advances and applications in both micromodels and imaging techniques. This includes a comprehensive analysis of critical aspects of fabrication techniques of micromodels, and the most recent advances such as embedding fibre optic sensors in micromodels for research applications. To complete the analysis of visualization techniques, we have thoroughly reviewed the most applicable imaging techniques in the area of geoscience and geo-energy. Moreover, the integration of microfluidic devices and imaging techniques was highlighted as appropriate. In this review, we focus particularly on four prominent yet very wide application areas, namely “fluid flow in porous media”, “flow in heterogeneous rocks and fractures”, “reactive transport, solute and colloid transport”, and finally “porous media characterization”. In summary, this review provides an in-depth analysis of micromodels and imaging techniques that can help to guide future research in the in-situ visualization of fluid flow in porous media. Full article
(This article belongs to the Section Sensing and Imaging)
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21 pages, 11804 KiB  
Article
A Highly Reliable, 5.8 GHz DSRC Wake-Up Receiver with an Intelligent Digital Controller for an ETC System
by Imran Ali, Muhammad Asif, Muhammad Riaz Ur Rehman, Danial Khan, Huo Yingge, Sung Jin Kim, YoungGun Pu, Sang-Sun Yoo and Kang-Yoon Lee
Sensors 2020, 20(14), 4012; https://doi.org/10.3390/s20144012 - 19 Jul 2020
Cited by 6 | Viewed by 5043
Abstract
In this article, a highly reliable radio frequency (RF) wake-up receiver (WuRx) is presented for electronic toll collection (ETC) applications. An intelligent digital controller (IDC) is proposed as the final stage for improving WuRx reliability and replacing complex analog blocks. With IDC, high [...] Read more.
In this article, a highly reliable radio frequency (RF) wake-up receiver (WuRx) is presented for electronic toll collection (ETC) applications. An intelligent digital controller (IDC) is proposed as the final stage for improving WuRx reliability and replacing complex analog blocks. With IDC, high reliability and accuracy are achieved by sensing and ensuring the successive, configurable number of wake-up signal cycles before enabling power-hungry RF transceiver. The IDC and range communication (RC) oscillator current consumption is reduced by a presented self-hibernation technique during the non-wake-up period. For accommodating wake-up signal frequency variation and enhancing WuRx accuracy, a digital hysteresis is incorporated. To avoid uncertain conditions during poor and false wake-up, a watch-dog timer for IDC self-recovery is integrated. During wake-up, the digital controller consumes 34.62 nW power and draws 38.47 nA current from a 0.9 V supply. In self-hibernation mode, its current reduces to 9.7 nA. It is fully synthesizable and needs 809 gates for its implementation in a 130 nm CMOS process with a 94 × 82 µm2 area. The WuRx measured power consumption is 2.48 µW, has −46 dBm sensitivity, and a 0.484 mm² chip area. Full article
(This article belongs to the Special Issue Integrated Circuits and Systems for Smart Sensory Applications)
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21 pages, 6654 KiB  
Article
Using UAV Photogrammetry to Analyse Changes in the Coastal Zone Based on the Sopot Tombolo (Salient) Measurement Project
by Pawel Burdziakowski, Cezary Specht, Pawel S. Dabrowski, Mariusz Specht, Oktawia Lewicka and Artur Makar
Sensors 2020, 20(14), 4000; https://doi.org/10.3390/s20144000 - 18 Jul 2020
Cited by 39 | Viewed by 4289
Abstract
The main factors influencing the shape of the beach, shoreline and seabed include undulation, wind and coastal currents. These phenomena cause continuous and multidimensional changes in the shape of the seabed and the Earth’s surface, and when they occur in an area of [...] Read more.
The main factors influencing the shape of the beach, shoreline and seabed include undulation, wind and coastal currents. These phenomena cause continuous and multidimensional changes in the shape of the seabed and the Earth’s surface, and when they occur in an area of intense human activity, they should be constantly monitored. In 2018 and 2019, several measurement campaigns took place in the littoral zone in Sopot, related to the intensive uplift of the seabed and beach caused by the tombolo phenomenon. In this research, a unique combination of bathymetric data obtained from an unmanned surface vessel, photogrammetric data obtained from unmanned aerial vehicles and ground laser scanning were used, along with geodetic data from precision measurements with receivers of global satellite navigation systems. This paper comprehensively presents photogrammetric measurements made from unmanned aerial vehicles during these campaigns. It describes in detail the problems in reconstruction within the water areas, analyses the accuracy of various photogrammetric measurement techniques, proposes a statistical method of data filtration and presents the changes that occurred within the studies area. The work ends with an interpretation of the causes of changes in the land part of the littoral zone and a summary of the obtained results. Full article
(This article belongs to the Special Issue Sensors and Sensor's Fusion in Autonomous Vehicles)
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20 pages, 5142 KiB  
Article
A Spatially Distributed Fiber-Optic Temperature Sensor for Applications in the Steel Industry
by Muhammad Roman, Damilola Balogun, Yiyang Zhuang, Rex E. Gerald II, Laura Bartlett, Ronald J. O’Malley and Jie Huang
Sensors 2020, 20(14), 3900; https://doi.org/10.3390/s20143900 - 13 Jul 2020
Cited by 43 | Viewed by 5617
Abstract
This paper presents a spatially distributed fiber-optic sensor system designed for demanding applications, like temperature measurements in the steel industry. The sensor system employed optical frequency domain reflectometry (OFDR) to interrogate Rayleigh backscattering signals in single-mode optical fibers. Temperature measurements employing the OFDR [...] Read more.
This paper presents a spatially distributed fiber-optic sensor system designed for demanding applications, like temperature measurements in the steel industry. The sensor system employed optical frequency domain reflectometry (OFDR) to interrogate Rayleigh backscattering signals in single-mode optical fibers. Temperature measurements employing the OFDR system were compared with conventional thermocouple measurements, accentuating the spatially distributed sensing capability of the fiber-optic system. Experiments were designed and conducted to test the spatial thermal mapping capability of the fiber-optic temperature measurement system. Experimental simulations provided evidence that the optical fiber system could resolve closely spaced temperature features, due to the high spatial resolution and fast measurement rates of the OFDR system. The ability of the fiber-optic system to perform temperature measurements in a metal casting was tested by monitoring aluminum solidification in a sand mold. The optical fiber, encased in a stainless steel tube, survived both mechanically and optically at temperatures exceeding 700 °C. The ability to distinguish between closely spaced temperature features that generate information-rich thermal maps opens up many applications in the steel industry. Full article
(This article belongs to the Section Optical Sensors)
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18 pages, 9938 KiB  
Article
Wavefront Aberration Sensor Based on a Multichannel Diffractive Optical Element
by Svetlana N. Khonina, Sergey V. Karpeev and Alexey P. Porfirev
Sensors 2020, 20(14), 3850; https://doi.org/10.3390/s20143850 - 10 Jul 2020
Cited by 42 | Viewed by 3752
Abstract
We propose a new type of a wavefront aberration sensor, that is, a Zernike matched multichannel diffractive optical filter, which performs consistent filtering of phase distributions corresponding to Zernike polynomials. The sensitivity of the new sensor is theoretically estimated. Based on the theory, [...] Read more.
We propose a new type of a wavefront aberration sensor, that is, a Zernike matched multichannel diffractive optical filter, which performs consistent filtering of phase distributions corresponding to Zernike polynomials. The sensitivity of the new sensor is theoretically estimated. Based on the theory, we develop recommendations for its application. Test wavefronts formed using a spatial light modulator are experimentally investigated. The applicability of the new sensor for the fine-tuning of a laser collimator is assessed. Full article
(This article belongs to the Special Issue Sensors Based on Diffraction Structures)
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12 pages, 2856 KiB  
Article
Antiresonant Hollow-Core Fiber-Based Dual Gas Sensor for Detection of Methane and Carbon Dioxide in the Near- and Mid-Infrared Regions
by Piotr Jaworski, Paweł Kozioł, Karol Krzempek, Dakun Wu, Fei Yu, Piotr Bojęś, Grzegorz Dudzik, Meisong Liao, Krzysztof Abramski and Jonathan Knight
Sensors 2020, 20(14), 3813; https://doi.org/10.3390/s20143813 - 8 Jul 2020
Cited by 74 | Viewed by 7050
Abstract
In this work, we present for the first time a laser-based dual gas sensor utilizing a silica-based Antiresonant Hollow-Core Fiber (ARHCF) operating in the Near- and Mid-Infrared spectral region. A 1-m-long fiber with an 84-µm diameter air-core was implemented as a low-volume absorption [...] Read more.
In this work, we present for the first time a laser-based dual gas sensor utilizing a silica-based Antiresonant Hollow-Core Fiber (ARHCF) operating in the Near- and Mid-Infrared spectral region. A 1-m-long fiber with an 84-µm diameter air-core was implemented as a low-volume absorption cell in a sensor configuration utilizing the simple and well-known Wavelength Modulation Spectroscopy (WMS) method. The fiber was filled with a mixture of methane (CH4) and carbon dioxide (CO2), and a simultaneous detection of both gases was demonstrated targeting their transitions at 3.334 µm and 1.574 µm, respectively. Due to excellent guidance properties of the fiber and low background noise, the proposed sensor reached a detection limit down to 24 parts-per-billion by volume for CH4 and 144 parts-per-million by volume for CO2. The obtained results confirm the suitability of ARHCF for efficient use in gas sensing applications for over a broad spectral range. Thanks to the demonstrated low loss, such fibers with lengths of over one meter can be used for increasing the laser-gas molecules interaction path, substituting bulk optics-based multipass cells, while delivering required flexibility, compactness, reliability and enhancement in the sensor’s sensitivity. Full article
(This article belongs to the Section Optical Sensors)
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27 pages, 6057 KiB  
Article
Intuitive Development to Examine Collaborative IoT Supply Chain System Underlying Privacy and Security Levels and Perspective Powering through Proactive Blockchain
by Aamir Shahzad, Kaiwen Zhang and Abdelouahed Gherbi
Sensors 2020, 20(13), 3760; https://doi.org/10.3390/s20133760 - 5 Jul 2020
Cited by 35 | Viewed by 4412
Abstract
Undoubtedly, the supply chain management (SCM) system is an important part of many organizations worldwide; over time, the technologies used to manage a supply chain ecosystem have, therefore, a great impact on businesses’ effectiveness. Among others, numerous developments have been made that targeted [...] Read more.
Undoubtedly, the supply chain management (SCM) system is an important part of many organizations worldwide; over time, the technologies used to manage a supply chain ecosystem have, therefore, a great impact on businesses’ effectiveness. Among others, numerous developments have been made that targeted to have robust supply chain systems to efficiently manage the growing demands of various supplies, considering the underlying requirements and main challenges such as scalability, specifically privacy and security, of various business networks. Internet of things (IoT) comes with a solution to manage a complex, scalable supply chain system, but to provide and attain enough security during information exchange, along with keeping the privacy of its users, is the great inherent challenge of IoT. To fulfill these limitations, this study designs and models a scaled IoT-based supply chain (IoT-SC) system, comprising several operations and participants, and deploys mechanisms to leverage the security, mainly confidentially, integrity, authentication (CIA), and a digital signature scheme to leverage potentially secured non-repudiation security service for the worst-case scenario, and to leverage privacy to keep users sensitive personal and location information protected against adversarial entities to the IoT-SC system. Indeed, a scaled IoT-SC system certainly opens new challenges to manage privacy and security while communicating. Therefore, in the IoT-SC system, each transaction writes from edge computing nodes to the IoT-SC controller is thoroughly examined to ensure the proposed solutions in bi-directional communication, and their robustness against adversarial behaviors. Future research works, employing blockchain and its integrations, are detailed as paces to accelerate the privacy and security of the IoT-SC system, for example, migrating IoT-centric computing to an immutable, decentralized platform. Full article
(This article belongs to the Section Sensor Networks)
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13 pages, 1582 KiB  
Article
Single-Shot 3D Shape Reconstruction Using Structured Light and Deep Convolutional Neural Networks
by Hieu Nguyen, Yuzeng Wang and Zhaoyang Wang
Sensors 2020, 20(13), 3718; https://doi.org/10.3390/s20133718 - 3 Jul 2020
Cited by 109 | Viewed by 10745
Abstract
Single-shot 3D imaging and shape reconstruction has seen a surge of interest due to the ever-increasing evolution in sensing technologies. In this paper, a robust single-shot 3D shape reconstruction technique integrating the structured light technique with the deep convolutional neural networks (CNNs) is [...] Read more.
Single-shot 3D imaging and shape reconstruction has seen a surge of interest due to the ever-increasing evolution in sensing technologies. In this paper, a robust single-shot 3D shape reconstruction technique integrating the structured light technique with the deep convolutional neural networks (CNNs) is proposed. The input of the technique is a single fringe-pattern image, and the output is the corresponding depth map for 3D shape reconstruction. The essential training and validation datasets with high-quality 3D ground-truth labels are prepared by using a multi-frequency fringe projection profilometry technique. Unlike the conventional 3D shape reconstruction methods which involve complex algorithms and intensive computation to determine phase distributions or pixel disparities as well as depth map, the proposed approach uses an end-to-end network architecture to directly carry out the transformation of a 2D image to its corresponding 3D depth map without extra processing. In the approach, three CNN-based models are adopted for comparison. Furthermore, an accurate structured-light-based 3D imaging dataset used in this paper is made publicly available. Experiments have been conducted to demonstrate the validity and robustness of the proposed technique. It is capable of satisfying various 3D shape reconstruction demands in scientific research and engineering applications. Full article
(This article belongs to the Special Issue Recent Advances in Depth Sensors and Applications)
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26 pages, 1431 KiB  
Article
Towards a Secure Thermal-Energy Aware Routing Protocol in Wireless Body Area Network Based on Blockchain Technology
by Zeinab Shahbazi and Yung-Cheol Byun
Sensors 2020, 20(12), 3604; https://doi.org/10.3390/s20123604 - 26 Jun 2020
Cited by 82 | Viewed by 7750
Abstract
The emergence of biomedical sensor devices, wireless communication, and innovation in other technologies for healthcare applications result in the evolution of a new area of research that is termed as Wireless Body Area Networks (WBANs). WBAN originates from Wireless Sensor Networks (WSNs), which [...] Read more.
The emergence of biomedical sensor devices, wireless communication, and innovation in other technologies for healthcare applications result in the evolution of a new area of research that is termed as Wireless Body Area Networks (WBANs). WBAN originates from Wireless Sensor Networks (WSNs), which are used for implementing many healthcare systems integrated with networks and wireless devices to ensure remote healthcare monitoring. WBAN is a network of wearable devices implanted in or on the human body. The main aim of WBAN is to collect the human vital signs/physiological data (like ECG, body temperature, EMG, glucose level, etc.) round-the-clock from patients that demand secure, optimal and efficient routing techniques. The efficient, secure, and reliable designing of routing protocol is a difficult task in WBAN due to its diverse characteristic and restraints, such as energy consumption and temperature-rise of implanted sensors. The two significant constraints, overheating of nodes and energy efficiency must be taken into account while designing a reliable blockchain-enabled WBAN routing protocol. The purpose of this study is to achieve stability and efficiency in the routing of WBAN through managing temperature and energy limitations. Moreover, the blockchain provides security, transparency, and lightweight solution for the interoperability of physiological data with other medical personnel in the healthcare ecosystem. In this research work, the blockchain-based Adaptive Thermal-/Energy-Aware Routing (ATEAR) protocol for WBAN is proposed. Temperature rise, energy consumption, and throughput are the evaluation metrics considered to analyze the performance of ATEAR for data transmission. In contrast, transaction throughput, latency, and resource utilization are used to investigate the outcome of the blockchain system. Hyperledger Caliper, a benchmarking tool, is used to evaluate the performance of the blockchain system in terms of CPU utilization, memory, and memory utilization. The results show that by preserving residual energy and avoiding overheated nodes as forwarders, high throughput is achieved with the ultimate increase of the network lifetime. Castalia, a simulation tool, is used to evaluate the performance of the proposed protocol, and its comparison is made with Multipath Ring Routing Protocol (MRRP), thermal-aware routing algorithm (TARA), and Shortest-Hop (SHR). Evaluation results illustrate that the proposed protocol performs significantly better in balancing of temperature (to avoid damaging heat effect on the body tissues) and energy consumption (to prevent the replacement of battery and to increase the embedded sensor node life) with efficient data transmission achieving a high throughput value. Full article
(This article belongs to the Special Issue Recent Advances of Blockchain Technologies in Sensor Networks)
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27 pages, 1649 KiB  
Article
Positioning Performance Limits of GNSS Meta-Signals and HO-BOC Signals
by Lorenzo Ortega, Daniel Medina, Jordi Vilà-Valls, François Vincent and Eric Chaumette
Sensors 2020, 20(12), 3586; https://doi.org/10.3390/s20123586 - 25 Jun 2020
Cited by 12 | Viewed by 4263
Abstract
Global Navigation Satellite Systems (GNSS) are the main source of position, navigation, and timing (PNT) information and will be a key player in the next-generation intelligent transportation systems and safety-critical applications, but several limitations need to be overcome to meet the stringent performance [...] Read more.
Global Navigation Satellite Systems (GNSS) are the main source of position, navigation, and timing (PNT) information and will be a key player in the next-generation intelligent transportation systems and safety-critical applications, but several limitations need to be overcome to meet the stringent performance requirements. One of the open issues is how to provide precise PNT solutions in harsh propagation environments. Under nominal conditions, the former is typically achieved by exploiting carrier phase information through precise positioning techniques, but these methods are very sensitive to the quality of phase observables. Another option that is gaining interest in the scientific community is the use of large bandwidth signals, which allow obtaining a better baseband resolution, and therefore more precise code-based observables. Two options may be considered: (i) high-order binary offset carrier (HO-BOC) modulations or (ii) the concept of GNSS meta-signals. In this contribution, we assess the time-delay and phase maximum likelihood (ML) estimation performance limits of such signals, together with the performance translation into the position domain, considering single point positioning (SPP) and RTK solutions, being an important missing point in the literature. A comprehensive discussion is provided on the estimators’ behavior, the corresponding ML threshold regions, the impact of good and bad satellite constellation geometries, and final conclusions on the best candidates, which may lead to precise solutions under harsh conditions. It is found that if the receiver is constrained by the receiver bandwidth, the best choices are the L1-M or E6-Public Regulated Service (PRS) signals. If the receiver is able to operate at 60 MHz, it is recommended to exploit the full-bandwidth Galileo E5 signal. In terms of robustness and performance, if the receiver can operate at 135 MHz, the best choice is to use the GNSS meta-signals E5 + E6 or B2 + B3, which provide the best overall performances regardless of the positioning method used, the satellite constellation geometry, or the propagation conditions. Full article
(This article belongs to the Special Issue Recent Advances in GNSS-based High Precision Positioning Technology: Part I)
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15 pages, 8787 KiB  
Letter
Real-Time Moving Object Detection in High-Resolution Video Sensing
by Haidi Zhu, Haoran Wei, Baoqing Li, Xiaobing Yuan and Nasser Kehtarnavaz
Sensors 2020, 20(12), 3591; https://doi.org/10.3390/s20123591 - 25 Jun 2020
Cited by 61 | Viewed by 6203
Abstract
This paper addresses real-time moving object detection with high accuracy in high-resolution video frames. A previously developed framework for moving object detection is modified to enable real-time processing of high-resolution images. First, a computationally efficient method is employed, which detects moving regions on [...] Read more.
This paper addresses real-time moving object detection with high accuracy in high-resolution video frames. A previously developed framework for moving object detection is modified to enable real-time processing of high-resolution images. First, a computationally efficient method is employed, which detects moving regions on a resized image while maintaining moving regions on the original image with mapping coordinates. Second, a light backbone deep neural network in place of a more complex one is utilized. Third, the focal loss function is employed to alleviate the imbalance between positive and negative samples. The results of the extensive experimentations conducted indicate that the modified framework developed in this paper achieves a processing rate of 21 frames per second with 86.15% accuracy on the dataset SimitMovingDataset, which contains high-resolution images of the size 1920 × 1080. Full article
(This article belongs to the Section Sensor Networks)
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18 pages, 3643 KiB  
Article
A Human Support Robot for the Cleaning and Maintenance of Door Handles Using a Deep-Learning Framework
by Balakrishnan Ramalingam, Jia Yin, Mohan Rajesh Elara, Yokhesh Krishnasamy Tamilselvam, Madan Mohan Rayguru, M. A. Viraj J. Muthugala and Braulio Félix Gómez
Sensors 2020, 20(12), 3543; https://doi.org/10.3390/s20123543 - 23 Jun 2020
Cited by 68 | Viewed by 11095
Abstract
The role of mobile robots for cleaning and sanitation purposes is increasing worldwide. Disinfection and hygiene are two integral parts of any safe indoor environment, and these factors become more critical in COVID-19-like pandemic situations. Door handles are highly sensitive contact points that [...] Read more.
The role of mobile robots for cleaning and sanitation purposes is increasing worldwide. Disinfection and hygiene are two integral parts of any safe indoor environment, and these factors become more critical in COVID-19-like pandemic situations. Door handles are highly sensitive contact points that are prone to be contamination. Automation of the door-handle cleaning task is not only important for ensuring safety, but also to improve efficiency. This work proposes an AI-enabled framework for automating cleaning tasks through a Human Support Robot (HSR). The overall cleaning process involves mobile base motion, door-handle detection, and control of the HSR manipulator for the completion of the cleaning tasks. The detection part exploits a deep-learning technique to classify the image space, and provides a set of coordinates for the robot. The cooperative control between the spraying and wiping is developed in the Robotic Operating System. The control module uses the information obtained from the detection module to generate a task/operational space for the robot, along with evaluating the desired position to actuate the manipulators. The complete strategy is validated through numerical simulations, and experiments on a Toyota HSR platform. Full article
(This article belongs to the Section Sensor Networks)
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21 pages, 4606 KiB  
Review
Graphene Plasmonics in Sensor Applications: A Review
by Shinpei Ogawa, Shoichiro Fukushima and Masaaki Shimatani
Sensors 2020, 20(12), 3563; https://doi.org/10.3390/s20123563 - 23 Jun 2020
Cited by 62 | Viewed by 8223
Abstract
Surface plasmon polaritons (SPPs) can be generated in graphene at frequencies in the mid-infrared to terahertz range, which is not possible using conventional plasmonic materials such as noble metals. Moreover, the lifetime and confinement volume of such SPPs are much longer and smaller, [...] Read more.
Surface plasmon polaritons (SPPs) can be generated in graphene at frequencies in the mid-infrared to terahertz range, which is not possible using conventional plasmonic materials such as noble metals. Moreover, the lifetime and confinement volume of such SPPs are much longer and smaller, respectively, than those in metals. For these reasons, graphene plasmonics has potential applications in novel plasmonic sensors and various concepts have been proposed. This review paper examines the potential of such graphene plasmonics with regard to the development of novel high-performance sensors. The theoretical background is summarized and the intrinsic nature of graphene plasmons, interactions between graphene and SPPs induced by metallic nanostructures and the electrical control of SPPs by adjusting the Fermi level of graphene are discussed. Subsequently, the development of optical sensors, biological sensors and important components such as absorbers/emitters and reconfigurable optical mirrors for use in new sensor systems are reviewed. Finally, future challenges related to the fabrication of graphene-based devices as well as various advanced optical devices incorporating other two-dimensional materials are examined. This review is intended to assist researchers in both industry and academia in the design and development of novel sensors based on graphene plasmonics. Full article
(This article belongs to the Collection Advances in Metamaterials or Plasmonics-Based Sensors)
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24 pages, 7285 KiB  
Article
Image-Processing-Based Low-Cost Fault Detection Solution for End-of-Line ECUs in Automotive Manufacturing
by Adrian Korodi, Denis Anitei, Alexandru Boitor and Ioan Silea
Sensors 2020, 20(12), 3520; https://doi.org/10.3390/s20123520 - 22 Jun 2020
Cited by 18 | Viewed by 6479
Abstract
The manufacturing industry is continuously researching and developing strategies and solutions to increase product quality and to decrease production time and costs. The approach is always targeting more automated, traceable, and supervised production, minimizing the impact of the human factor. In the automotive [...] Read more.
The manufacturing industry is continuously researching and developing strategies and solutions to increase product quality and to decrease production time and costs. The approach is always targeting more automated, traceable, and supervised production, minimizing the impact of the human factor. In the automotive industry, the Electronic Control Unit (ECU) manufacturing ends with complex testing, the End-of-Line (EoL) products being afterwards sent to client companies. This paper proposes an image-processing-based low-cost fault detection (IP-LC-FD) solution for the EoL ECUs, aiming for high-quality and fast detection. The IP-LC-FD solution approaches the problem of determining, on the manufacturing line, the correct mounting of the pins in the locations of each connector of the ECU module, respectively, other defects as missing or extra pins, damaged clips, or surface cracks. The IP-LC-FD system is a hardware–software structure, based on Raspberry Pi microcomputers, Pi cameras, respectively, Python and OpenCV environments. This paper presents the two main stages of the research, the experimental model, and the prototype. The rapid integration into the production line represented an important goal, meaning the accomplishment of the specific hard acceptance requirements regarding both performance and functionality. The solution was implemented and tested as an experimental model and prototype in a real industrial environment, proving excellent results. Full article
(This article belongs to the Section Fault Diagnosis & Sensors)
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32 pages, 9734 KiB  
Review
Enzyme-Based Biosensors: Tackling Electron Transfer Issues
by Paolo Bollella and Evgeny Katz
Sensors 2020, 20(12), 3517; https://doi.org/10.3390/s20123517 - 21 Jun 2020
Cited by 128 | Viewed by 10289
Abstract
This review summarizes the fundamentals of the phenomenon of electron transfer (ET) reactions occurring in redox enzymes that were widely employed for the development of electroanalytical devices, like biosensors, and enzymatic fuel cells (EFCs). A brief introduction on the ET observed in proteins/enzymes [...] Read more.
This review summarizes the fundamentals of the phenomenon of electron transfer (ET) reactions occurring in redox enzymes that were widely employed for the development of electroanalytical devices, like biosensors, and enzymatic fuel cells (EFCs). A brief introduction on the ET observed in proteins/enzymes and its paradigms (e.g., classification of ET mechanisms, maximal distance at which is observed direct electron transfer, etc.) are given. Moreover, the theoretical aspects related to direct electron transfer (DET) are resumed as a guideline for newcomers to the field. Snapshots on the ET theory formulated by Rudolph A. Marcus and on the mathematical model used to calculate the ET rate constant formulated by Laviron are provided. Particular attention is devoted to the case of glucose oxidase (GOx) that has been erroneously classified as an enzyme able to transfer electrons directly. Thereafter, all tools available to investigate ET issues are reported addressing the discussions toward the development of new methodology to tackle ET issues. In conclusion, the trends toward upcoming practical applications are suggested as well as some directions in fundamental studies of bioelectrochemistry. Full article
(This article belongs to the Special Issue Biosensors – Recent Advances and Future Challenges)
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58 pages, 21886 KiB  
Review
Wireless Power Transfer Techniques for Implantable Medical Devices: A Review
by Sadeque Reza Khan, Sumanth Kumar Pavuluri, Gerard Cummins and Marc P. Y. Desmulliez
Sensors 2020, 20(12), 3487; https://doi.org/10.3390/s20123487 - 19 Jun 2020
Cited by 218 | Viewed by 24114
Abstract
Wireless power transfer (WPT) systems have become increasingly suitable solutions for the electrical powering of advanced multifunctional micro-electronic devices such as those found in current biomedical implants. The design and implementation of high power transfer efficiency WPT systems are, however, challenging. The size [...] Read more.
Wireless power transfer (WPT) systems have become increasingly suitable solutions for the electrical powering of advanced multifunctional micro-electronic devices such as those found in current biomedical implants. The design and implementation of high power transfer efficiency WPT systems are, however, challenging. The size of the WPT system, the separation distance between the outside environment and location of the implanted medical device inside the body, the operating frequency and tissue safety due to power dissipation are key parameters to consider in the design of WPT systems. This article provides a systematic review of the wide range of WPT systems that have been investigated over the last two decades to improve overall system performance. The various strategies implemented to transfer wireless power in implantable medical devices (IMDs) were reviewed, which includes capacitive coupling, inductive coupling, magnetic resonance coupling and, more recently, acoustic and optical powering methods. The strengths and limitations of all these techniques are benchmarked against each other and particular emphasis is placed on comparing the implanted receiver size, the WPT distance, power transfer efficiency and tissue safety presented by the resulting systems. Necessary improvements and trends of each WPT techniques are also indicated per specific IMD. Full article
(This article belongs to the Special Issue Smart IoT Systems for Pervasive Healthcare)
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18 pages, 1154 KiB  
Article
An Efficient Distributed Area Division Method for Cooperative Monitoring Applications with Multiple UAVs
by José Joaquín Acevedo, Ivan Maza, Anibal Ollero and Begoña C. Arrue
Sensors 2020, 20(12), 3448; https://doi.org/10.3390/s20123448 - 18 Jun 2020
Cited by 13 | Viewed by 3404
Abstract
This article addresses the area division problem in a distributed manner providing a solution for cooperative monitoring missions with multiple UAVs. Starting from a sub-optimal area division, a distributed online algorithm is presented to accelerate the convergence of the system to the optimal [...] Read more.
This article addresses the area division problem in a distributed manner providing a solution for cooperative monitoring missions with multiple UAVs. Starting from a sub-optimal area division, a distributed online algorithm is presented to accelerate the convergence of the system to the optimal solution, following a frequency-based approach. Based on the “coordination variables” concept and on a strict neighborhood relation to share information (left, right, above and below neighbors), this technique defines a distributed division protocol to determine coherently the size and shape of the sub-area assigned to each UAV. Theoretically, the convergence time of the proposed solution depends linearly on the number of UAVs. Validation results, comparing the proposed approach with other distributed techniques, are provided to evaluate and analyze its performance following a convergence time criterion. Full article
(This article belongs to the Special Issue UAV-Based Smart Sensor Systems and Applications)
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15 pages, 2119 KiB  
Article
Layered Double Hydroxide-Modified Organic Electrochemical Transistor for Glucose and Lactate Biosensing
by Isacco Gualandi, Marta Tessarolo, Federica Mariani, Danilo Arcangeli, Luca Possanzini, Domenica Tonelli, Beatrice Fraboni and Erika Scavetta
Sensors 2020, 20(12), 3453; https://doi.org/10.3390/s20123453 - 18 Jun 2020
Cited by 53 | Viewed by 5876
Abstract
Biosensors based on Organic Electrochemical Transistors (OECTs) are developed for the selective detection of glucose and lactate. The transistor architecture provides signal amplification (gain) with respect to the simple amperometric response. The biosensors are based on a poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) channel and the gate [...] Read more.
Biosensors based on Organic Electrochemical Transistors (OECTs) are developed for the selective detection of glucose and lactate. The transistor architecture provides signal amplification (gain) with respect to the simple amperometric response. The biosensors are based on a poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) channel and the gate electrode is functionalised with glucose oxidase (GOx) or lactate oxidase (LOx) enzymes, which are immobilised within a Ni/Al Layered Double Hydroxide (LDH) through a one-step electrodeposition procedure. The here-designed OECT architecture allows minimising the required amount of enzyme during electrodeposition. The output signal of the biosensor is the drain current (Id), which decreases as the analyte concentration increases. In the optimised conditions, the biosensor responds to glucose in the range of 0.1–8.0 mM with a limit of detection (LOD) of 0.02 mM. Two regimes of proportionality are observed. For concentrations lower than 1.0 mM, a linear response is obtained with a mean gain of 360, whereas for concentrations higher than 1.0 mM, Id is proportional to the logarithm of glucose concentration, with a gain of 220. For lactate detection, the biosensor response is linear in the whole concentration range (0.05–8.0 mM). A LOD of 0.04 mM is reached, with a net gain equal to 400. Full article
(This article belongs to the Special Issue New Generation of Electrochemical Sensors)
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13 pages, 2927 KiB  
Article
Development of Taste Sensor to Detect Non-Charged Bitter Substances
by Jumpei Yoshimatsu, Kiyoshi Toko, Yusuke Tahara, Misaki Ishida, Masaaki Habara, Hidekazu Ikezaki, Honami Kojima, Saeri Ikegami, Miyako Yoshida and Takahiro Uchida
Sensors 2020, 20(12), 3455; https://doi.org/10.3390/s20123455 - 18 Jun 2020
Cited by 26 | Viewed by 5278
Abstract
A taste sensor with lipid/polymer membranes is one of the devices that can evaluate taste objectively. However, the conventional taste sensor cannot measure non-charged bitter substances, such as caffeine contained in coffee, because the taste sensor uses the potentiometric measurement based mainly on [...] Read more.
A taste sensor with lipid/polymer membranes is one of the devices that can evaluate taste objectively. However, the conventional taste sensor cannot measure non-charged bitter substances, such as caffeine contained in coffee, because the taste sensor uses the potentiometric measurement based mainly on change in surface electric charge density of the membrane. In this study, we aimed at the detection of typical non-charged bitter substances such as caffeine, theophylline and theobromine included in beverages and pharmaceutical products. The developed sensor is designed to detect the change in the membrane potential by using a kind of allosteric mechanism of breaking an intramolecular hydrogen bond between the carboxy group and hydroxy group of aromatic carboxylic acid (i.e., hydroxy-, dihydroxy-, and trihydroxybenzoic acids) when non-charged bitter substances are bound to the hydroxy group. As a result of surface modification by immersing the sensor electrode in a modification solution in which 2,6-dihydroxybenzoic acid was dissolved, it was confirmed that the sensor response increased with the concentration of caffeine as well as allied substances. The threshold and increase tendency were consistent with those of human senses. The detection mechanism is discussed by taking into account intramolecular and intermolecular hydrogen bonds, which cause allostery. These findings suggest that it is possible to evaluate bitterness caused by non-charged bitter substances objectively by using the taste sensor with allosteric mechanism. Full article
(This article belongs to the Section Chemical Sensors)
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11 pages, 1643 KiB  
Article
Intelligent Data Management and Security in Cloud Computing
by Lidia Ogiela, Marek R. Ogiela and Hoon Ko
Sensors 2020, 20(12), 3458; https://doi.org/10.3390/s20123458 - 18 Jun 2020
Cited by 52 | Viewed by 4897
Abstract
This paper will present the authors’ own techniques of secret data management and protection, with particular attention paid to techniques securing data services. Among the solutions discussed, there will be information-sharing protocols dedicated to the tasks of secret (confidential) data sharing. Such solutions [...] Read more.
This paper will present the authors’ own techniques of secret data management and protection, with particular attention paid to techniques securing data services. Among the solutions discussed, there will be information-sharing protocols dedicated to the tasks of secret (confidential) data sharing. Such solutions will be presented in an algorithmic form, aimed at solving the tasks of protecting and securing data against unauthorized acquisition. Data-sharing protocols will execute the tasks of securing a special type of information, i.e., data services. The area of data protection will be defined for various levels, within which will be executed the tasks of data management and protection. The authors’ solution concerning securing data with the use of cryptographic threshold techniques used to split the secret among a specified group of secret trustees, simultaneously enhanced by the application of linguistic methods of description of the shared secret, forms a new class of protocols, i.e., intelligent linguistic threshold schemes. The solutions presented in this paper referring to the service management and securing will be dedicated to various levels of data management. These levels could be differentiated both in the structure of a given entity and in its environment. There is a special example thereof, i.e., the cloud management processes. These will also be subject to the assessment of feasibility of application of the discussed protocols in these areas. Presented solutions will be based on the application of an innovative approach, in which we can use a special formal graph for the creation of a secret representation, which can then be divided and transmitted over a distributed network. Full article
(This article belongs to the Special Issue Selected Papers from the 11-th International Conference on Intelligent Networking and Collaborative Systems (INCoS-2019) and the 22nd International Conference on Network-Based Information Systems (NBiS-2019))
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13 pages, 3974 KiB  
Article
Magnetic Bioreactor for Magneto-, Mechano- and Electroactive Tissue Engineering Strategies
by Nelson Castro, Margarida M. Fernandes, Clarisse Ribeiro, Vítor Correia, Rikardo Minguez and Senentxu Lanceros-Méndez
Sensors 2020, 20(12), 3340; https://doi.org/10.3390/s20123340 - 12 Jun 2020
Cited by 32 | Viewed by 5093
Abstract
Biomimetic bioreactor systems are increasingly being developed for tissue engineering applications, due to their ability to recreate the native cell/tissue microenvironment. Regarding bone-related diseases and considering the piezoelectric nature of bone, piezoelectric scaffolds electromechanically stimulated by a bioreactor, providing the stimuli to the [...] Read more.
Biomimetic bioreactor systems are increasingly being developed for tissue engineering applications, due to their ability to recreate the native cell/tissue microenvironment. Regarding bone-related diseases and considering the piezoelectric nature of bone, piezoelectric scaffolds electromechanically stimulated by a bioreactor, providing the stimuli to the cells, allows a biomimetic approach and thus, mimicking the required microenvironment for effective growth and differentiation of bone cells. In this work, a bioreactor has been designed and built allowing to magnetically stimulate magnetoelectric scaffolds and therefore provide mechanical and electrical stimuli to the cells through magnetomechanical or magnetoelectrical effects, depending on the piezoelectric nature of the scaffold. While mechanical bioreactors need direct application of the stimuli on the scaffolds, the herein proposed magnetic bioreactors allow for a remote stimulation without direct contact with the material. Thus, the stimuli application (23 mT at a frequency of 0.3 Hz) to cells seeded on the magnetoelectric, leads to an increase in cell viability of almost 30% with respect to cell culture under static conditions. This could be valuable to mimic what occurs in the human body and for application in immobilized patients. Thus, special emphasis has been placed on the control, design and modeling parameters governing the bioreactor as well as its functional mechanism. Full article
(This article belongs to the Special Issue Electronics for Sensors)
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23 pages, 704 KiB  
Review
Internet of Robotic Things in Smart Domains: Applications and Challenges
by Laura Romeo, Antonio Petitti, Roberto Marani and Annalisa Milella
Sensors 2020, 20(12), 3355; https://doi.org/10.3390/s20123355 - 12 Jun 2020
Cited by 115 | Viewed by 17067
Abstract
With the advent of the Fourth Industrial Revolution, Internet of Things (IoT) and robotic systems are closely cooperating, reshaping their relations and managing to develop new-generation devices. Such disruptive technology corresponds to the backbone of the so-called Industry 4.0. The integration of robotic [...] Read more.
With the advent of the Fourth Industrial Revolution, Internet of Things (IoT) and robotic systems are closely cooperating, reshaping their relations and managing to develop new-generation devices. Such disruptive technology corresponds to the backbone of the so-called Industry 4.0. The integration of robotic agents and IoT leads to the concept of the Internet of Robotic Things, in which innovation in digital systems is drawing new possibilities in both industrial and research fields, covering several domains such as manufacturing, agriculture, health, surveillance, and education, to name but a few. In this manuscript, the state-of-the-art of IoRT applications is outlined, aiming to mark their impact on several research fields, and focusing on the main open challenges of the integration of robotic technologies into smart spaces. IoRT technologies and applications are also discussed to underline their influence in everyday life, inducing the need for more research into remote and automated applications. Full article
(This article belongs to the Special Issue Robot and Sensor Networks for Environmental Monitoring)
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28 pages, 1397 KiB  
Review
MRI Segmentation and Classification of Human Brain Using Deep Learning for Diagnosis of Alzheimer’s Disease: A Survey
by Nagaraj Yamanakkanavar, Jae Young Choi and Bumshik Lee
Sensors 2020, 20(11), 3243; https://doi.org/10.3390/s20113243 - 7 Jun 2020
Cited by 163 | Viewed by 17148
Abstract
Many neurological diseases and delineating pathological regions have been analyzed, and the anatomical structure of the brain researched with the aid of magnetic resonance imaging (MRI). It is important to identify patients with Alzheimer’s disease (AD) early so that preventative measures can be [...] Read more.
Many neurological diseases and delineating pathological regions have been analyzed, and the anatomical structure of the brain researched with the aid of magnetic resonance imaging (MRI). It is important to identify patients with Alzheimer’s disease (AD) early so that preventative measures can be taken. A detailed analysis of the tissue structures from segmented MRI leads to a more accurate classification of specific brain disorders. Several segmentation methods to diagnose AD have been proposed with varying complexity. Segmentation of the brain structure and classification of AD using deep learning approaches has gained attention as it can provide effective results over a large set of data. Hence, deep learning methods are now preferred over state-of-the-art machine learning methods. We aim to provide an outline of current deep learning-based segmentation approaches for the quantitative analysis of brain MRI for the diagnosis of AD. Here, we report how convolutional neural network architectures are used to analyze the anatomical brain structure and diagnose AD, discuss how brain MRI segmentation improves AD classification, describe the state-of-the-art approaches, and summarize their results using publicly available datasets. Finally, we provide insight into current issues and discuss possible future research directions in building a computer-aided diagnostic system for AD. Full article
(This article belongs to the Section Biomedical Sensors)
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24 pages, 4632 KiB  
Article
Design and Intensive Experimental Evaluation of an Enhanced Visible Light Communication System for Automotive Applications
by Sebastian-Andrei Avătămăniței, Alin-Mihai Căilean, Adrian Done, Mihai Dimian, Valentin Popa and Marius Prelipceanu
Sensors 2020, 20(11), 3190; https://doi.org/10.3390/s20113190 - 4 Jun 2020
Cited by 15 | Viewed by 4191
Abstract
As the interest toward communication-based vehicle safety applications is increasing, the development of secure wireless communication techniques has become an important research area. In this context, the article addresses issues that are related to the use of the visible light communication (VLC) technology [...] Read more.
As the interest toward communication-based vehicle safety applications is increasing, the development of secure wireless communication techniques has become an important research area. In this context, the article addresses issues that are related to the use of the visible light communication (VLC) technology in vehicular applications. Thus, it provides an extensive presentation concerning the main challenges and issues that are associated to vehicular VLC applications and of some of the existing VLC solutions. Moreover, the article presents the aspects related to the design and intensive experimental evaluation of a new automotive VLC system. The experimental evaluation performed in indoor and outdoor conditions shows that the proposed system can achieve communication distances up to 50 m and bit error ratio (BER) lower than 10−6, while being exposed to optical and weather perturbations. This article provides important evidence concerning the snowfall effect on middle to long range outdoor VLC, as the proposed VLC system was also evaluated in snowfall conditions. Accordingly, the experimental evaluation showed that snowfall and heavy gust could increase bit error rate by up to 10,000 times. Even so, this article provides encouraging evidence that VLC systems will soon be able to reliably support V2X communications. Full article
(This article belongs to the Special Issue State-of-the-Art Indoor and Outdoor Visible Light Communications (VLC) Applications and Systems)
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18 pages, 3710 KiB  
Review
A Review of Bolt Tightening Force Measurement and Loosening Detection
by Rusong Miao, Ruili Shen, Songhan Zhang and Songling Xue
Sensors 2020, 20(11), 3165; https://doi.org/10.3390/s20113165 - 2 Jun 2020
Cited by 112 | Viewed by 12404
Abstract
Pre-stressed bolted joints are widely used in civil structures and industries. The tightening force of a bolt is crucial to the reliability of the joint connection. Loosening or over-tightening of a bolt may lead to connectors slipping or bolt strength failure, which are [...] Read more.
Pre-stressed bolted joints are widely used in civil structures and industries. The tightening force of a bolt is crucial to the reliability of the joint connection. Loosening or over-tightening of a bolt may lead to connectors slipping or bolt strength failure, which are both harmful to the main structure. In most practical cases it is extremely difficult, even impossible, to install the bolts to ensure there is a precise tension force during the construction phase. Furthermore, it is inevitable that the bolts will loosen due to long-term usage under high stress. The identification of bolt tension is therefore of great significance for monitoring the health of existing structures. This paper reviews state-of-the-art research on bolt tightening force measurement and loosening detection, including fundamental theories, algorithms, experimental set-ups, and practical applications. In general, methods based on the acoustoelastic principle are capable of calculating the value of bolt axial stress if both the time of incident wave and reflected wave can be clearly recognized. The relevant commercial instrument has been developed and its algorithm will be briefly introduced. Methods based on contact dynamic phenomena such as wave energy attenuation, high-order harmonics, sidebands, and impedance, are able to correlate interface stiffness and the clamping force of bolted joints with respective dynamic indicators. Therefore, they are able to detect or quantify bolt tightness. The related technologies will be reviewed in detail. Potential challenges and research trends will also be discussed. Full article
(This article belongs to the Section Fault Diagnosis & Sensors)
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19 pages, 3806 KiB  
Article
Strain Transfer in Surface-Bonded Optical Fiber Sensors
by Francesco Falcetelli, Leonardo Rossi, Raffaella Di Sante and Gabriele Bolognini
Sensors 2020, 20(11), 3100; https://doi.org/10.3390/s20113100 - 30 May 2020
Cited by 71 | Viewed by 5836
Abstract
Fiber optic sensors represent one of the most promising technologies for the monitoring of various engineering structures. A major challenge in the field is to analyze and predict the strain transfer to the fiber core reliably. Many authors developed analytical models of a [...] Read more.
Fiber optic sensors represent one of the most promising technologies for the monitoring of various engineering structures. A major challenge in the field is to analyze and predict the strain transfer to the fiber core reliably. Many authors developed analytical models of a coated optical fiber, assuming null strain at the ends of the bonding length. However, this configuration only partially reflects real experimental setups in which the cable structure can be more complex and the strains do not drastically reduce to zero. In this study, a novel strain transfer model for surface-bonded sensing cables with multilayered structure was developed. The analytical model was validated both experimentally and numerically, considering two surface-mounted cable prototypes with three different bonding lengths and five load cases. The results demonstrated the capability of the model to predict the strain profile and, differently from the available strain transfer models, that the strain values at the extremities of the bonded fiber length are not null. Full article
(This article belongs to the Special Issue Fiber Optic Sensing Technology)
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24 pages, 943 KiB  
Article
IoT-Blockchain Enabled Optimized Provenance System for Food Industry 4.0 Using Advanced Deep Learning
by Prince Waqas Khan, Yung-Cheol Byun and Namje Park
Sensors 2020, 20(10), 2990; https://doi.org/10.3390/s20102990 - 25 May 2020
Cited by 218 | Viewed by 16303
Abstract
Agriculture and livestock play a vital role in social and economic stability. Food safety and transparency in the food supply chain are a significant concern for many people. Internet of Things (IoT) and blockchain are gaining attention due to their success in versatile [...] Read more.
Agriculture and livestock play a vital role in social and economic stability. Food safety and transparency in the food supply chain are a significant concern for many people. Internet of Things (IoT) and blockchain are gaining attention due to their success in versatile applications. They generate a large amount of data that can be optimized and used efficiently by advanced deep learning (ADL) techniques. The importance of such innovations from the viewpoint of supply chain management is significant in different processes such as for broadened visibility, provenance, digitalization, disintermediation, and smart contracts. This article takes the secure IoT–blockchain data of Industry 4.0 in the food sector as a research object. Using ADL techniques, we propose a hybrid model based on recurrent neural networks (RNN). Therefore, we used long short-term memory (LSTM) and gated recurrent units (GRU) as a prediction model and genetic algorithm (GA) optimization jointly to optimize the parameters of the hybrid model. We select the optimal training parameters by GA and finally cascade LSTM with GRU. We evaluated the performance of the proposed system for a different number of users. This paper aims to help supply chain practitioners to take advantage of the state-of-the-art technologies; it will also help the industry to make policies according to the predictions of ADL. Full article
(This article belongs to the Special Issue Blockchain Security and Privacy for the Internet of Things)
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11 pages, 1358 KiB  
Article
SPR Biosensor Based on Polymer Multi-Mode Optical Waveguide and Nanoparticle Signal Enhancement
by Johanna-Gabriela Walter, Alina Eilers, Lourdes Shanika Malindi Alwis, Bernhard Wilhelm Roth and Kort Bremer
Sensors 2020, 20(10), 2889; https://doi.org/10.3390/s20102889 - 20 May 2020
Cited by 58 | Viewed by 7270
Abstract
We present a surface plasmon resonance (SPR) biosensor that is based on a planar-optical multi-mode (MM) polymer waveguide structure applied for the detection of biomolecules in the lower nano-molar (nM) range. The basic sensor shows a sensitivity of 608.6 nm/RIU when exposed to [...] Read more.
We present a surface plasmon resonance (SPR) biosensor that is based on a planar-optical multi-mode (MM) polymer waveguide structure applied for the detection of biomolecules in the lower nano-molar (nM) range. The basic sensor shows a sensitivity of 608.6 nm/RIU when exposed to refractive index changes with a measurement resolution of 4.3 × 10−3 RIU. By combining the SPR sensor with an aptamer-functionalized, gold-nanoparticle (AuNP)-enhanced sandwich assay, the detection of C-reactive protein (CRP) in a buffer solution was achieved with a response of 0.118 nm/nM. Due to the multi-mode polymer waveguide structure and the simple concept, the reported biosensor is well suited for low-cost disposable lab-on-a-chip applications and can be used with rather simple and economic devices. In particular, the sensor offers the potential for fast and multiplexed detection of several biomarkers on a single integrated platform. Full article
(This article belongs to the Collection Photonic Sensors)
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15 pages, 4764 KiB  
Article
YOLO-Based Simultaneous Target Detection and Classification in Automotive FMCW Radar Systems
by Woosuk Kim, Hyunwoong Cho, Jongseok Kim, Byungkwan Kim and Seongwook Lee
Sensors 2020, 20(10), 2897; https://doi.org/10.3390/s20102897 - 20 May 2020
Cited by 59 | Viewed by 8473
Abstract
This paper proposes a method to simultaneously detect and classify objects by using a deep learning model, specifically you only look once (YOLO), with pre-processed automotive radar signals. In conventional methods, the detection and classification in automotive radar systems are conducted in two [...] Read more.
This paper proposes a method to simultaneously detect and classify objects by using a deep learning model, specifically you only look once (YOLO), with pre-processed automotive radar signals. In conventional methods, the detection and classification in automotive radar systems are conducted in two successive stages; however, in the proposed method, the two stages are combined into one. To verify the effectiveness of the proposed method, we applied it to the actual radar data measured using our automotive radar sensor. According to the results, our proposed method can simultaneously detect targets and classify them with over 90% accuracy. In addition, it shows better performance in terms of detection and classification, compared with conventional methods such as density-based spatial clustering of applications with noise or the support vector machine. Moreover, the proposed method especially exhibits better performance when detecting and classifying a vehicle with a long body. Full article
(This article belongs to the Section Electronic Sensors)
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22 pages, 4327 KiB  
Review
IoT Wearable Sensors and Devices in Elderly Care: A Literature Review
by Thanos G. Stavropoulos, Asterios Papastergiou, Lampros Mpaltadoros, Spiros Nikolopoulos and Ioannis Kompatsiaris
Sensors 2020, 20(10), 2826; https://doi.org/10.3390/s20102826 - 16 May 2020
Cited by 250 | Viewed by 33689
Abstract
The increasing ageing global population is causing an upsurge in ailments related to old age, primarily dementia and Alzheimer’s disease, frailty, Parkinson’s, and cardiovascular disease, but also a general need for general eldercare as well as active and healthy ageing. In turn, there [...] Read more.
The increasing ageing global population is causing an upsurge in ailments related to old age, primarily dementia and Alzheimer’s disease, frailty, Parkinson’s, and cardiovascular disease, but also a general need for general eldercare as well as active and healthy ageing. In turn, there is a need for constant monitoring and assistance, intervention, and support, causing a considerable financial and human burden on individuals and their caregivers. Interconnected sensing technology, such as IoT wearables and devices, present a promising solution for objective, reliable, and remote monitoring, assessment, and support through ambient assisted living. This paper presents a review of such solutions including both earlier review studies and individual case studies, rapidly evolving in the last decade. In doing so, it examines and categorizes them according to common aspects of interest such as health focus, from specific ailments to general eldercare; IoT technologies, from wearables to smart home sensors; aims, from assessment to fall detection and indoor positioning to intervention; and experimental evaluation participants duration and outcome measures, from acceptability to accuracy. Statistics drawn from this categorization aim to outline the current state-of-the-art, as well as trends and effective practices for the future of effective, accessible, and acceptable eldercare with technology. Full article
(This article belongs to the Special Issue Smart Sensors for eHealth Applications)
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15 pages, 16733 KiB  
Article
Feasibility of a Wearable Reflectometric System for Sensing Skin Hydration
by Raissa Schiavoni, Giuseppina Monti, Emanuele Piuzzi, Luciano Tarricone, Annarita Tedesco, Egidio De Benedetto and Andrea Cataldo
Sensors 2020, 20(10), 2833; https://doi.org/10.3390/s20102833 - 16 May 2020
Cited by 37 | Viewed by 5787
Abstract
One of the major goals of Health 4.0 is to offer personalized care to patients, also through real-time, remote monitoring of their biomedical parameters. In this regard, wearable monitoring systems are crucial to deliver continuous appropriate care. For some biomedical parameters, there are [...] Read more.
One of the major goals of Health 4.0 is to offer personalized care to patients, also through real-time, remote monitoring of their biomedical parameters. In this regard, wearable monitoring systems are crucial to deliver continuous appropriate care. For some biomedical parameters, there are a number of well established systems that offer adequate solutions for real-time, continuous patient monitoring. On the other hand, monitoring skin hydration still remains a challenging task. The continuous monitoring of this physiological parameter is extremely important in several contexts, for example for athletes, sick people, workers in hostile environments or for the elderly. State-of-the-art systems, however, exhibit some limitations, especially related with the possibility of continuous, real-time monitoring. Starting from these considerations, in this work, the feasibility of an innovative time-domain reflectometry (TDR)-based wearable, skin hydration sensing system for real-time, continuous monitoring of skin hydration level was investigated. The applicability of the proposed system was demonstrated, first, through experimental tests on reference substances, then, directly on human skin. The obtained results demonstrate the TDR technique and the proposed system holds unexplored potential for the aforementioned purposes. Full article
(This article belongs to the Special Issue Wearable Devices and Sensors for Innovative Monitoring Systems in the 4.0 Era)
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21 pages, 547 KiB  
Article
Heart Rate Variability and Accelerometry as Classification Tools for Monitoring Perceived Stress Levels—A Pilot Study on Firefighters
by Michał Meina, Ewa Ratajczak, Maria Sadowska, Krzysztof Rykaczewski, Joanna Dreszer, Bibianna Bałaj, Stanisław Biedugnis, Wojciech Węgrzyński and Adam Krasuski
Sensors 2020, 20(10), 2834; https://doi.org/10.3390/s20102834 - 16 May 2020
Cited by 25 | Viewed by 6414
Abstract
Chronic stress is the main cause of health problems in high-risk jobs. Wearable sensors can become an ecologically valid method of stress level assessment in real-life applications. We sought to determine a non-invasive technique for objective stress monitoring. Data were collected from firefighters [...] Read more.
Chronic stress is the main cause of health problems in high-risk jobs. Wearable sensors can become an ecologically valid method of stress level assessment in real-life applications. We sought to determine a non-invasive technique for objective stress monitoring. Data were collected from firefighters during 24-h shifts using sensor belts equipped with a dry-lead electrocardiograph (ECG) and a three-axial accelerometer. Levels of stress experienced during fire incidents were evaluated via a brief self-assessment questionnaire. Types of physical activity were distinguished basing on accelerometer readings, and heart rate variability (HRV) time series were segmented accordingly into corresponding fragments. Those segments were classified as stress/no-stress conditions. Receiver Operating Characteristic (ROC) analysis showed true positive classification as stress condition for 15% of incidents (while maintaining almost zero False Positive Rate), which parallels the amount of truly stressful incidents reported in the questionnaires. These results show a firm correspondence between the perceived stress level and physiological data. Psychophysiological measurements are reliable indicators of stress even in ecological settings and appear promising for chronic stress monitoring in high-risk jobs, such as firefighting. Full article
(This article belongs to the Collection Sensors for Gait, Human Movement Analysis, and Health Monitoring)
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15 pages, 3607 KiB  
Article
Hollow-Core Photonic Crystal Fiber Mach–Zehnder Interferometer for Gas Sensing
by Kaveh Nazeri, Farid Ahmed, Vahid Ahsani, Hang-Eun Joe, Colin Bradley, Ehsan Toyserkani and Martin B. G. Jun
Sensors 2020, 20(10), 2807; https://doi.org/10.3390/s20102807 - 15 May 2020
Cited by 30 | Viewed by 5181
Abstract
A novel and compact interferometric refractive index (RI) point sensor is developed using hollow-core photonic crystal fiber (HC-PCF) and experimentally demonstrated for high sensitivity detection and measurement of pure gases. To construct the device, the sensing element fiber (HC-PCF) was placed between two [...] Read more.
A novel and compact interferometric refractive index (RI) point sensor is developed using hollow-core photonic crystal fiber (HC-PCF) and experimentally demonstrated for high sensitivity detection and measurement of pure gases. To construct the device, the sensing element fiber (HC-PCF) was placed between two single-mode fibers with airgaps at each side. Great measurement repeatability was shown in the cyclic test for the detection of various gases. The RI sensitivity of 4629 nm/RIU was demonstrated in the RI range of 1.0000347–1.000436 for the sensor with an HC-PCF length of 3.3 mm. The sensitivity of the proposed Mach–Zehnder interferometer (MZI) sensor increases when the length of the sensing element decreases. It is shown that response and recovery times of the proposed sensor inversely change with the length of HC-PCF. Besides, spatial frequency analysis for a wide range of air-gaps revealed information on the number and power distribution of modes. It is shown that the power is mainly carried by two dominant modes in the proposed structure. The proposed sensors have the potential to improve current technology’s ability to detect and quantify pure gases. Full article
(This article belongs to the Special Issue Fiber Optic Sensors in Chemical and Biological Applications)
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23 pages, 24525 KiB  
Article
Vulnerability Assessment of Buildings due to Land Subsidence Using InSAR Data in the Ancient Historical City of Pistoia (Italy)
by Pablo Ezquerro, Matteo Del Soldato, Lorenzo Solari, Roberto Tomás, Federico Raspini, Mattia Ceccatelli, José Antonio Fernández-Merodo, Nicola Casagli and Gerardo Herrera
Sensors 2020, 20(10), 2749; https://doi.org/10.3390/s20102749 - 12 May 2020
Cited by 47 | Viewed by 7121
Abstract
The launch of the medium resolution Synthetic Aperture Radar (SAR) Sentinel-1 constellation in 2014 has allowed public and private organizations to introduce SAR interferometry (InSAR) products as a valuable option in their monitoring systems. The massive stacks of displacement data resulting from the [...] Read more.
The launch of the medium resolution Synthetic Aperture Radar (SAR) Sentinel-1 constellation in 2014 has allowed public and private organizations to introduce SAR interferometry (InSAR) products as a valuable option in their monitoring systems. The massive stacks of displacement data resulting from the processing of large C-B and radar images can be used to highlight temporal and spatial deformation anomalies, and their detailed analysis and postprocessing to generate operative products for final users. In this work, the wide-area mapping capability of Sentinel-1 was used in synergy with the COSMO-SkyMed high resolution SAR data to characterize ground subsidence affecting the urban fabric of the city of Pistoia (Tuscany Region, central Italy). Line of sight velocities were decomposed on vertical and E–W components, observing slight horizontal movements towards the center of the subsidence area. Vertical displacements and damage field surveys allowed for the calculation of the probability of damage depending on the displacement velocity by means of fragility curves. Finally, these data were translated to damage probability and potential loss maps. These products are useful for urban planning and geohazard management, focusing on the identification of the most hazardous areas on which to concentrate efforts and resources. Full article
(This article belongs to the Special Issue Remote Sensing of Geohazards)
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15 pages, 7228 KiB  
Article
Examination of Multi-Receiver GPS/EGNOS Positioning with Kalman Filtering and Validation Based on CORS Stations
by Adam Ciećko, Mieczysław Bakuła, Grzegorz Grunwald and Janusz Ćwiklak
Sensors 2020, 20(9), 2732; https://doi.org/10.3390/s20092732 - 11 May 2020
Cited by 24 | Viewed by 4970
Abstract
This paper presents the concept of precise navigation based on SBAS technology and CORS stations. In a kinematic test, three rover Global Positioning System (GPS) receivers, properly spaced relatively to each other, were used in order to estimate reliable and redundant GPS/EGNOS positions. [...] Read more.
This paper presents the concept of precise navigation based on SBAS technology and CORS stations. In a kinematic test, three rover Global Positioning System (GPS) receivers, properly spaced relatively to each other, were used in order to estimate reliable and redundant GPS/EGNOS positions. Next, the Kalman filter was employed to give the final solution. It was proven that EGNOS positioning allows to obtain an accuracy in the range of about 0.5–1.5 m. The proposed solution involving the use of three mobile receivers and Kalman filtering allowed to reduce the 3D error to a level below 0.3 m. Such an accuracy was achieved using only GPS L1 code observations and EGNOS corrections. Additionally, a reliable monitoring of quality of GPS/EGNOS positioning in the test area based on CORS stations was presented. Full article
(This article belongs to the Special Issue GNSS Sensors in Aerial Navigation)
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10 pages, 1353 KiB  
Article
Multi-Addressed Fiber Bragg Structures for Microwave-Photonic Sensor Systems
by Oleg Morozov, Airat Sakhabutdinov, Vladimir Anfinogentov, Rinat Misbakhov, Artem Kuznetsov and Timur Agliullin
Sensors 2020, 20(9), 2693; https://doi.org/10.3390/s20092693 - 9 May 2020
Cited by 41 | Viewed by 4335
Abstract
The new theory and technique of Multi-Addressed Fiber Bragg Structure (MAFBS) usage in Microwave Photonics Sensor Systems (MPSS) is presented. This theory is the logical evolution of the theory of Addressed Fiber Bragg Structure (AFBS) usage as sensors in MPSS. The mathematical model [...] Read more.
The new theory and technique of Multi-Addressed Fiber Bragg Structure (MAFBS) usage in Microwave Photonics Sensor Systems (MPSS) is presented. This theory is the logical evolution of the theory of Addressed Fiber Bragg Structure (AFBS) usage as sensors in MPSS. The mathematical model of additive response from a single MAFBS is presented. The MAFBS is a special type of Fiber Bragg Gratings (FBG), the reflection spectrum of which has three (or more) narrow notches. The frequencies of narrow notches are located in the infrared range of electromagnetic spectrum, while differences between them are located in the microwave frequency range. All cross-differences between optical frequencies of single MAFBS are called the address frequencies set. When the additive optical response from a single MAFBS, passed through an optic filter with an oblique amplitude–frequency characteristic, is received on a photodetector, the complex electrical signal, which consists of all cross-frequency beatings of all optical frequencies, which are included in this optical signal, is taken at its output. This complex electrical signal at the photodetector’s output contains enough information to determine the central frequency shift of the MAFBS. The method of address frequencies analysis with the microwave-photonic measuring conversion method, which allows us to define the central frequency shift of a single MAFBS, is discussed in the work. Full article
(This article belongs to the Special Issue Fiber Bragg Grating Based Sensors and Systems)
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23 pages, 3702 KiB  
Review
How Reliable Is the Electrochemical Readout of MIP Sensors?
by Aysu Yarman and Frieder W. Scheller
Sensors 2020, 20(9), 2677; https://doi.org/10.3390/s20092677 - 8 May 2020
Cited by 68 | Viewed by 7582
Abstract
Electrochemical methods offer the simple characterization of the synthesis of molecularly imprinted polymers (MIPs) and the readouts of target binding. The binding of electroinactive analytes can be detected indirectly by their modulating effect on the diffusional permeability of a redox marker through thin [...] Read more.
Electrochemical methods offer the simple characterization of the synthesis of molecularly imprinted polymers (MIPs) and the readouts of target binding. The binding of electroinactive analytes can be detected indirectly by their modulating effect on the diffusional permeability of a redox marker through thin MIP films. However, this process generates an overall signal, which may include nonspecific interactions with the nonimprinted surface and adsorption at the electrode surface in addition to (specific) binding to the cavities. Redox-active low-molecular-weight targets and metalloproteins enable a more specific direct quantification of their binding to MIPs by measuring the faradaic current. The in situ characterization of enzymes, MIP-based mimics of redox enzymes or enzyme-labeled targets, is based on the indication of an electroactive product. This approach allows the determination of both the activity of the bio(mimetic) catalyst and of the substrate concentration. Full article
(This article belongs to the Special Issue Innovative Strategy of MIP Sensors on the Road to Practical Applications)
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25 pages, 1481 KiB  
Article
Machine Learning on Mainstream Microcontrollers
by Fouad Sakr, Francesco Bellotti, Riccardo Berta and Alessandro De Gloria
Sensors 2020, 20(9), 2638; https://doi.org/10.3390/s20092638 - 5 May 2020
Cited by 83 | Viewed by 10655
Abstract
This paper presents the Edge Learning Machine (ELM), a machine learning framework for edge devices, which manages the training phase on a desktop computer and performs inferences on microcontrollers. The framework implements, in a platform-independent C language, three supervised machine learning algorithms (Support [...] Read more.
This paper presents the Edge Learning Machine (ELM), a machine learning framework for edge devices, which manages the training phase on a desktop computer and performs inferences on microcontrollers. The framework implements, in a platform-independent C language, three supervised machine learning algorithms (Support Vector Machine (SVM) with a linear kernel, k-Nearest Neighbors (K-NN), and Decision Tree (DT)), and exploits STM X-Cube-AI to implement Artificial Neural Networks (ANNs) on STM32 Nucleo boards. We investigated the performance of these algorithms on six embedded boards and six datasets (four classifications and two regression). Our analysis—which aims to plug a gap in the literature—shows that the target platforms allow us to achieve the same performance score as a desktop machine, with a similar time latency. ANN performs better than the other algorithms in most cases, with no difference among the target devices. We observed that increasing the depth of an NN improves performance, up to a saturation level. k-NN performs similarly to ANN and, in one case, even better, but requires all the training sets to be kept in the inference phase, posing a significant memory demand, which can be afforded only by high-end edge devices. DT performance has a larger variance across datasets. In general, several factors impact performance in different ways across datasets. This highlights the importance of a framework like ELM, which is able to train and compare different algorithms. To support the developer community, ELM is released on an open-source basis. Full article
(This article belongs to the Special Issue Applications in Electronics Pervading Industry, Environment and Society – Sensing Systems and Pervasive Intelligence)
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8 pages, 1900 KiB  
Article
Design Rule of Mach-Zehnder Interferometer Sensors for Ultra-High Sensitivity
by Yiwei Xie, Ming Zhang and Daoxin Dai
Sensors 2020, 20(9), 2640; https://doi.org/10.3390/s20092640 - 5 May 2020
Cited by 36 | Viewed by 6678
Abstract
A design rule for a Mach-Zehnder interferometer (MZI) sensor is presented, allowing tunable sensitivity by appropriately choosing the MZI arm lengths according to the formula given in this paper. The present MZI sensor designed by this method can achieve an ultra-high sensitivity, which [...] Read more.
A design rule for a Mach-Zehnder interferometer (MZI) sensor is presented, allowing tunable sensitivity by appropriately choosing the MZI arm lengths according to the formula given in this paper. The present MZI sensor designed by this method can achieve an ultra-high sensitivity, which is much higher than any other traditional MZI sensors. An example is given with silicon-on-insulator (SOI) nanowires and the device sensitivity is as high as 106 nm/refractive-index -unit (or even higher), by choosing the MZI arms appropriately. This makes it possible for one to realize a low-cost optical sensing system with a detection limit as high as 10−6 refractive-index-unit, even when a cheap optical spectrum analyzer with low-resolution (e.g., 1 nm) is used for the wavelength-shift measurement. Full article
(This article belongs to the Section Optical Sensors)
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19 pages, 3275 KiB  
Article
Evaluation of Two Low-Cost Optical Particle Counters for the Measurement of Ambient Aerosol Scattering Coefficient and Ångström Exponent
by Krzysztof M. Markowicz and Michał T. Chiliński
Sensors 2020, 20(9), 2617; https://doi.org/10.3390/s20092617 - 4 May 2020
Cited by 22 | Viewed by 5236
Abstract
The aerosol scattering coefficient and Ångström exponent (AE) are important parameters in the understanding of aerosol optical properties and aerosol direct effect. These parameters are usually measured by a nephelometer network which is under-represented geographically; however, a rapid growth of air-pollution monitoring, using [...] Read more.
The aerosol scattering coefficient and Ångström exponent (AE) are important parameters in the understanding of aerosol optical properties and aerosol direct effect. These parameters are usually measured by a nephelometer network which is under-represented geographically; however, a rapid growth of air-pollution monitoring, using low-cost particle sensors, may extend observation networks. This paper presents the results of co-located measurements of aerosol optical properties, such as the aerosol scattering coefficient and the scattering AE, using low-cost sensors and using a scientific-grade polar Aurora 4000 nephelometer. A high Pearson correlation coefficient (0.94–0.96) between the low-cost particulate matter (PM) mass concentration and the aerosol scattering coefficient was found. For the PM10 mass concentration, the aerosol scattering coefficient relation is linear for the Dfrobot SEN0177 sensor and non-linear for the Alphasense OPC-N2 device. After regression analyses, both low-cost instruments provided the aerosol scattering coefficient with a similar mean square error difference (RMSE) of about 20 Mm−1, which corresponds to about 27% of the mean aerosol scattering coefficient. The relative uncertainty is independent of the pollution level. In addition, the ratio of aerosol number concentration between different bins showed a significant statistical (95% of confidence level) correlation with the scattering AE. For the SEN0177, the ratio of the particle number in bin 1 (radius of 0.15–0.25 µm) to bin 4 (radius of 1.25–2.5 µm) was a linear function of the scattering AE, with a Pearson correlation coefficient of 0.74. In the case of OPC-N2, the best correlation (r = 0.66) was found for the ratio between bin 1 (radius of 0.19–0.27 µm) and bin 2 (radius of 0.27–0.39 µm). Comparisons of an estimated scattering AE from a low-cost sensor with Aurora 4000 are given with the RMSE of 0.23–0.24, which corresponds to 16–19%. In addition, a three-year (2016–2019) observation by SEN0177 indicates that this sensor can be used to determine an annual cycle as well as a short-term variability. Full article
(This article belongs to the Special Issue Photonics-Based Sensors for Environment and Pollution Monitoring)
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12 pages, 1419 KiB  
Article
Blockchain-Based Healthcare Workflow for Tele-Medical Laboratory in Federated Hospital IoT Clouds
by Antonio Celesti, Armando Ruggeri, Maria Fazio, Antonino Galletta, Massimo Villari and Agata Romano
Sensors 2020, 20(9), 2590; https://doi.org/10.3390/s20092590 - 2 May 2020
Cited by 100 | Viewed by 9101
Abstract
In a pandemic situation such as that we are living at the time of writing of this paper due to the Covid-19 virus, the need of tele-healthcare service becomes dramatically fundamental to reduce the movement of patients, thence reducing the risk of infection. [...] Read more.
In a pandemic situation such as that we are living at the time of writing of this paper due to the Covid-19 virus, the need of tele-healthcare service becomes dramatically fundamental to reduce the movement of patients, thence reducing the risk of infection. Leveraging the recent Cloud computing and Internet of Things (IoT) technologies, this paper aims at proposing a tele-medical laboratory service where clinical exams are performed on patients directly in a hospital by technicians through IoT medical devices and results are automatically sent via the hospital Cloud to doctors of federated hospitals for validation and/or consultation. In particular, we discuss a distributed scenario where nurses, technicians and medical doctors belonging to different hospitals cooperate through their federated hospital Clouds to form a virtual health team able to carry out a healthcare workflow in secure fashion leveraging the intrinsic security features of the Blockchain technology. In particular, both public and hybrid Blockchain scenarios are discussed and assessed using the Ethereum platform. Full article
(This article belongs to the Special Issue Blockchain in the Internet of Things: Opportunities, Challenges and Solutions)
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