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Sensors, Volume 17, Issue 6 (June 2017)

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Open AccessArticle Development of Diamond and Silicon MEMS Sensor Arrays with Integrated Readout for Vapor Detection
Sensors 2017, 17(6), 1163; doi:10.3390/s17061163
Received: 31 March 2017 / Revised: 12 May 2017 / Accepted: 12 May 2017 / Published: 24 May 2017
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Abstract
This paper reports on the development of an autonomous instrument based on an array of eight resonant microcantilevers for vapor detection. The fabricated sensors are label-free devices, allowing chemical and biological functionalization. In this work, sensors based on an array of silicon and
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This paper reports on the development of an autonomous instrument based on an array of eight resonant microcantilevers for vapor detection. The fabricated sensors are label-free devices, allowing chemical and biological functionalization. In this work, sensors based on an array of silicon and synthetic diamond microcantilevers are sensitized with polymeric films for the detection of analytes. The main advantage of the proposed system is that sensors can be easily changed for another application or for cleaning since the developed gas cell presents removable electrical connections. We report the successful application of our electronic nose approach to detect 12 volatile organic compounds. Moreover, the response pattern of the cantilever arrays is interpreted via principal component analysis (PCA) techniques in order to identify samples. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in France 2016)
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Open AccessArticle Natural Inspired Intelligent Visual Computing and Its Application to Viticulture
Sensors 2017, 17(6), 1186; doi:10.3390/s17061186
Received: 16 February 2017 / Revised: 28 April 2017 / Accepted: 2 May 2017 / Published: 23 May 2017
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Abstract
This paper presents an investigation of natural inspired intelligent computing and its corresponding application towards visual information processing systems for viticulture. The paper has three contributions: (1) a review of visual information processing applications for viticulture; (2) the development of natural inspired computing
[...] Read more.
This paper presents an investigation of natural inspired intelligent computing and its corresponding application towards visual information processing systems for viticulture. The paper has three contributions: (1) a review of visual information processing applications for viticulture; (2) the development of natural inspired computing algorithms based on artificial immune system (AIS) techniques for grape berry detection; and (3) the application of the developed algorithms towards real-world grape berry images captured in natural conditions from vineyards in Australia. The AIS algorithms in (2) were developed based on a nature-inspired clonal selection algorithm (CSA) which is able to detect the arcs in the berry images with precision, based on a fitness model. The arcs detected are then extended to perform the multiple arcs and ring detectors information processing for the berry detection application. The performance of the developed algorithms were compared with traditional image processing algorithms like the circular Hough transform (CHT) and other well-known circle detection methods. The proposed AIS approach gave a Fscore of 0.71 compared with Fscores of 0.28 and 0.30 for the CHT and a parameter-free circle detection technique (RPCD) respectively. Full article
(This article belongs to the Special Issue System-Integrated Intelligence and Intelligent Systems)
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Open AccessArticle Multimodal Bio-Inspired Tactile Sensing Module for Surface Characterization
Sensors 2017, 17(6), 1187; doi:10.3390/s17061187
Received: 31 March 2017 / Revised: 12 May 2017 / Accepted: 17 May 2017 / Published: 23 May 2017
Cited by 1 | PDF Full-text (6117 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Robots are expected to recognize the properties of objects in order to handle them safely and efficiently in a variety of applications, such as health and elder care, manufacturing, or high-risk environments. This paper explores the issue of surface characterization by monitoring the
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Robots are expected to recognize the properties of objects in order to handle them safely and efficiently in a variety of applications, such as health and elder care, manufacturing, or high-risk environments. This paper explores the issue of surface characterization by monitoring the signals acquired by a novel bio-inspired tactile probe in contact with ridged surfaces. The tactile module comprises a nine Degree of Freedom Microelectromechanical Magnetic, Angular Rate, and Gravity system (9-DOF MEMS MARG) and a deep MEMS pressure sensor embedded in a compliant structure that mimics the function and the organization of mechanoreceptors in human skin as well as the hardness of the human skin. When the modules tip slides over a surface, the MARG unit vibrates and the deep pressure sensor captures the overall normal force exerted. The module is evaluated in two experiments. The first experiment compares the frequency content of the data collected in two setups: one when the module is mounted over a linear motion carriage that slides four grating patterns at constant velocities; the second when the module is carried by a robotic finger in contact with the same grating patterns while performing a sliding motion, similar to the exploratory motion employed by humans to detect object roughness. As expected, in the linear setup, the magnitude spectrum of the sensors’ output shows that the module can detect the applied stimuli with frequencies ranging from 3.66 Hz to 11.54 Hz with an overall maximum error of ±0.1 Hz. The second experiment shows how localized features extracted from the data collected by the robotic finger setup over seven synthetic shapes can be used to classify them. The classification method consists on applying multiscale principal components analysis prior to the classification with a multilayer neural network. Achieved accuracies from 85.1% to 98.9% for the various sensor types demonstrate the usefulness of traditional MEMS as tactile sensors embedded into flexible substrates. Full article
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Open AccessArticle An Iterative Distortion Compensation Algorithm for Camera Calibration Based on Phase Target
Sensors 2017, 17(6), 1188; doi:10.3390/s17061188
Received: 21 March 2017 / Revised: 11 May 2017 / Accepted: 18 May 2017 / Published: 23 May 2017
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Abstract
Camera distortion is a critical factor affecting the accuracy of camera calibration. A conventional calibration approach cannot satisfy the requirement of a measurement system demanding high calibration accuracy due to the inaccurate distortion compensation. This paper presents a novel camera calibration method with
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Camera distortion is a critical factor affecting the accuracy of camera calibration. A conventional calibration approach cannot satisfy the requirement of a measurement system demanding high calibration accuracy due to the inaccurate distortion compensation. This paper presents a novel camera calibration method with an iterative distortion compensation algorithm. The initial parameters of the camera are calibrated by full-field camera pixels and the corresponding points on a phase target. An iterative algorithm is proposed to compensate for the distortion. A 2D fitting and interpolation method is also developed to enhance the accuracy of the phase target. Compared to the conventional calibration method, the proposed method does not rely on a distortion mathematical model, and is stable and effective in terms of complex distortion conditions. Both the simulation work and experimental results show that the proposed calibration method is more than 100% more accurate than the conventional calibration method. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Atmospheric Sampling on Ascension Island Using Multirotor UAVs
Sensors 2017, 17(6), 1189; doi:10.3390/s17061189
Received: 15 November 2016 / Revised: 9 May 2017 / Accepted: 15 May 2017 / Published: 23 May 2017
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Abstract
As part of an NERC-funded project investigating the southern methane anomaly, a team drawn from the Universities of Bristol, Birmingham and Royal Holloway flew small unmanned multirotors from Ascension Island for the purposes of atmospheric sampling. The objective of these flights was to
[...] Read more.
As part of an NERC-funded project investigating the southern methane anomaly, a team drawn from the Universities of Bristol, Birmingham and Royal Holloway flew small unmanned multirotors from Ascension Island for the purposes of atmospheric sampling. The objective of these flights was to collect air samples from below, within and above a persistent atmospheric feature, the Trade Wind Inversion, in order to characterise methane concentrations and their isotopic composition. These parameters allow the methane in the different air masses to be tied to different source locations, which can be further analysed using back trajectory atmospheric computer modelling. This paper describes the campaigns as a whole including the design of the bespoke eight rotor aircraft and the operational requirements that were needed in order to collect targeted multiple air samples up to 2.5 km above the ground level in under 20 min of flight time. Key features of the system described include real-time feedback of temperature and humidity, as well as system health data. This enabled detailed targeting of the air sampling design to be realised and planned during the flight mission on the downward leg, a capability that is invaluable in the presence of uncertainty in the pre-flight meteorological data. Environmental considerations are also outlined together with the flight plans that were created in order to rapidly fly vertical transects of the atmosphere whilst encountering changing wind conditions. Two sampling campaigns were carried out in September 2014 and July 2015 with over one hundred high altitude sampling missions. Lessons learned are given throughout, including those associated with operating in the testing environment encountered on Ascension Island. Full article
(This article belongs to the Special Issue UAV-Based Remote Sensing)
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Open AccessArticle Sensors and Actuators on Determining Parameters for Being Considered in Selection of Elastomers for Biomimetic Hands
Sensors 2017, 17(6), 1190; doi:10.3390/s17061190
Received: 20 April 2017 / Revised: 18 May 2017 / Accepted: 19 May 2017 / Published: 23 May 2017
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Abstract
In this paper, the authors present a new methodology to study the viscoelastic behaviour of the human finger. The methodology is based on experimental research consisting of a finger’s indentation with a small steel cylindrical object for various indentation speeds. The tests were
[...] Read more.
In this paper, the authors present a new methodology to study the viscoelastic behaviour of the human finger. The methodology is based on experimental research consisting of a finger’s indentation with a small steel cylindrical object for various indentation speeds. The tests were realized on a CETR UMT-2 Tribometer for indentation speed between 0.02 mm/s and 4 mm/s with a normal load of up to 22 N. Using the force–deformation diagrams recorded at the smallest indentation speed determined the elastic modulus of the human finger according to an adapted Hertzian model. By considering the increasing of the indentation force with indentation speed, the viscous component of the human finger was evidenced. The power dissipated in the finger tissue as a result of the prehension process has been obtained as a function of indentation speed and indentation depth. In addition, a general equation for the prehension force as a function of indentation speed and indentation depth has been obtained. The results of this study will be relevant for selection of the specific elastomers used in biomimetic hands. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Thermal Characterization of Dynamic Silicon Cantilever Array Sensors by Digital Holographic Microscopy
Sensors 2017, 17(6), 1191; doi:10.3390/s17061191
Received: 2 May 2017 / Revised: 17 May 2017 / Accepted: 19 May 2017 / Published: 23 May 2017
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Abstract
In this paper, we apply a digital holographic microscope (DHM) in conjunction with stroboscopic acquisition synchronization. Here, the temperature-dependent decrease of the first resonance frequency (S1(T)) and Young’s elastic modulus (E1(T)) of silicon
[...] Read more.
In this paper, we apply a digital holographic microscope (DHM) in conjunction with stroboscopic acquisition synchronization. Here, the temperature-dependent decrease of the first resonance frequency (S1(T)) and Young’s elastic modulus (E1(T)) of silicon micromechanical cantilever sensors (MCSs) are measured. To perform these measurements, the MCSs are uniformly heated from T0 = 298 K to T = 450 K while being externally actuated with a piezo-actuator in a certain frequency range close to their first resonance frequencies. At each temperature, the DHM records the time-sequence of the 3D topographies for the given frequency range. Such holographic data allow for the extracting of the out-of-plane vibrations at any relevant area of the MCSs. Next, the Bode and Nyquist diagrams are used to determine the resonant frequencies with a precision of 0.1 Hz. Our results show that the decrease of resonance frequency is a direct consequence of the reduction of the silicon elastic modulus upon heating. The measured temperature dependence of the Young’s modulus is in very good accordance with the previously-reported values, validating the reliability and applicability of this method for micromechanical sensing applications. Full article
(This article belongs to the Special Issue MEMS and Nano-Sensors)
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Open AccessArticle A High-Sensitive Pressure Sensor Using a Single-Mode Fiber Embedded Microbubble with Thin Film Characteristics
Sensors 2017, 17(6), 1192; doi:10.3390/s17061192
Received: 15 December 2016 / Revised: 4 May 2017 / Accepted: 16 May 2017 / Published: 23 May 2017
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Abstract
A new fiber pressure sensor is proposed and analyzed in this paper. A commercial arc fusion splicer and pressure-assisted arc discharge technology are used here to fabricate a silica hollow microbubble from a common glass tube with the characteristics of a thin film.
[...] Read more.
A new fiber pressure sensor is proposed and analyzed in this paper. A commercial arc fusion splicer and pressure-assisted arc discharge technology are used here to fabricate a silica hollow microbubble from a common glass tube with the characteristics of a thin film. Then the single mode fiber is embedded into the microbubble to form a fiber Fabry–Perot interferometer by measuring the reflected interference spectrum from the fiber tip and microbubble end. As the wall thickness of the micro-bubble can reach up to several micrometers, it can then be used for measuring the outer pressure with high sensitivity. The fabrication method has the merits of being simple, low in cost, and is easy to control. Experimental results show that its pressure sensitivity can reach 164.56 pm/kPa and the temperature sensitivity can reach 4 pm/°C. Therefore, it also has the advantage of being insensitive to temperature fluctuation. Full article
(This article belongs to the Special Issue Recent Advances in Fiber Bragg Grating Sensing)
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Open AccessArticle LoRa Scalability: A Simulation Model Based on Interference Measurements
Sensors 2017, 17(6), 1193; doi:10.3390/s17061193
Received: 27 March 2017 / Revised: 15 May 2017 / Accepted: 19 May 2017 / Published: 23 May 2017
Cited by 2 | PDF Full-text (1130 KB) | HTML Full-text | XML Full-text
Abstract
LoRa is a long-range, low power, low bit rate and single-hop wireless communication technology. It is intended to be used in Internet of Things (IoT) applications involving battery-powered devices with low throughput requirements. A LoRaWAN network consists of multiple end nodes that communicate
[...] Read more.
LoRa is a long-range, low power, low bit rate and single-hop wireless communication technology. It is intended to be used in Internet of Things (IoT) applications involving battery-powered devices with low throughput requirements. A LoRaWAN network consists of multiple end nodes that communicate with one or more gateways. These gateways act like a transparent bridge towards a common network server. The amount of end devices and their throughput requirements will have an impact on the performance of the LoRaWAN network. This study investigates the scalability in terms of the number of end devices per gateway of single-gateway LoRaWAN deployments. First, we determine the intra-technology interference behavior with two physical end nodes, by checking the impact of an interfering node on a transmitting node. Measurements show that even under concurrent transmission, one of the packets can be received under certain conditions. Based on these measurements, we create a simulation model for assessing the scalability of a single gateway LoRaWAN network. We show that when the number of nodes increases up to 1000 per gateway, the losses will be up to 32%. In such a case, pure Aloha will have around 90% losses. However, when the duty cycle of the application layer becomes lower than the allowed radio duty cycle of 1%, losses will be even lower. We also show network scalability simulation results for some IoT use cases based on real data. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle In-Process Atomic-Force Microscopy (AFM) Based Inspection
Sensors 2017, 17(6), 1194; doi:10.3390/s17061194
Received: 23 March 2017 / Revised: 2 May 2017 / Accepted: 19 May 2017 / Published: 31 May 2017
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Abstract
A new in-process atomic-force microscopy (AFM) based inspection is presented for nanolithography to compensate for any deviation such as instantaneous degradation of the lithography probe tip. Traditional method used the AFM probes for lithography work and retract to inspect the obtained feature but
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A new in-process atomic-force microscopy (AFM) based inspection is presented for nanolithography to compensate for any deviation such as instantaneous degradation of the lithography probe tip. Traditional method used the AFM probes for lithography work and retract to inspect the obtained feature but this practice degrades the probe tip shape and hence, affects the measurement quality. This paper suggests a second dedicated lithography probe that is positioned back-to-back to the AFM probe under two synchronized controllers to correct any deviation in the process compared to specifications. This method shows that the quality improvement of the nanomachining, in progress probe tip wear, and better understanding of nanomachining. The system is hosted in a recently developed nanomanipulator for educational and research purposes. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle A Monitoring System for Laying Hens That Uses a Detection Sensor Based on Infrared Technology and Image Pattern Recognition
Sensors 2017, 17(6), 1195; doi:10.3390/s17061195
Received: 27 January 2017 / Revised: 20 April 2017 / Accepted: 20 May 2017 / Published: 24 May 2017
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Abstract
In Italy, organic egg production farms use free-range housing systems with a big outdoor area and a flock of no more than 500 hens. With additional devices and/or farming procedures, the whole flock could be forced to stay in the outdoor area for
[...] Read more.
In Italy, organic egg production farms use free-range housing systems with a big outdoor area and a flock of no more than 500 hens. With additional devices and/or farming procedures, the whole flock could be forced to stay in the outdoor area for a limited time of the day. As a consequence, ozone treatments of housing areas could be performed in order to reduce the levels of atmospheric ammonia and bacterial load without risks, due by its toxicity, both for hens and workers. However, an automatic monitoring system, and a sensor able to detect the presence of animals, would be necessary. For this purpose, a first sensor was developed but some limits, related to the time necessary to detect a hen, were observed. In this study, significant improvements, for this sensor, are proposed. They were reached by an image pattern recognition technique that was applied to thermografic images acquired from the housing system. An experimental group of seven laying hens was selected for the tests, carried out for three weeks. The first week was used to set-up the sensor. Different templates, to use for the pattern recognition, were studied and different floor temperature shifts were investigated. At the end of these evaluations, a template of elliptical shape, and sizes of 135 × 63 pixels, was chosen. Furthermore, a temperature shift of one degree was selected to calculate, for each image, a color background threshold to apply in the following field tests. Obtained results showed an improvement of the sensor detection accuracy that reached values of sensitivity and specificity of 95.1% and 98.7%. In addition, the range of time necessary to detect a hen, or classify a case, was reduced at two seconds. This result could allow the sensor to control a bigger area of the housing system. Thus, the resulting monitoring system could allow to perform the sanitary treatments without risks both for animals and humans. Full article
(This article belongs to the Special Issue Infrared Detectors)
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Open AccessArticle Thermochemical Humidity Detection in Harsh or Non-Steady Environments
Sensors 2017, 17(6), 1196; doi:10.3390/s17061196
Received: 25 March 2017 / Revised: 9 May 2017 / Accepted: 18 May 2017 / Published: 24 May 2017
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Abstract
We present a new method of chemical quantification utilizing thermal analysis for the detection of relative humidity. By measuring the temperature change of a hydrophilically-modified temperature sensing element vs. a hydrophobically-modified reference element, the total heat from chemical interactions in the sensing element
[...] Read more.
We present a new method of chemical quantification utilizing thermal analysis for the detection of relative humidity. By measuring the temperature change of a hydrophilically-modified temperature sensing element vs. a hydrophobically-modified reference element, the total heat from chemical interactions in the sensing element can be measured and used to calculate a change in relative humidity. We have probed the concept by assuming constant temperature streams, and having constant reference humidity (~0% in this case). The concept has been probed with the two methods presented here: (1) a thermistor-based method and (2) a thermographic method. For the first method, a hydrophilically-modified thermistor was used, and a detection range of 0–75% relative humidity was demonstrated. For the second method, a hydrophilically-modified disposable surface (sensing element) and thermal camera were used, and thermal signatures for different relative humidity were demonstrated. These new methods offer opportunities in either chemically harsh environments or in rapidly changing environments. For sensing humidity in a chemically harsh environment, a hydrophilically-modified thermistor can provide a sensing method, eliminating the exposure of metallic contacts, which can be easily corroded by the environment. On the other hand, the thermographic method can be applied with a disposable non-contact sensing element, which is a low-cost upkeep option in environments where damage or fouling is inevitable. In addition, for environments that are rapidly changing, the thermographic method could potentially provide a very rapid humidity measurement as the chemical interactions are rapid and their changes are easily quantified. Full article
(This article belongs to the Special Issue Humidity Sensors)
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Open AccessArticle Diazonium Salt-Based Surface-Enhanced Raman Spectroscopy Nanosensor: Detection and Quantitation of Aromatic Hydrocarbons in Water Samples
Sensors 2017, 17(6), 1198; doi:10.3390/s17061198
Received: 31 March 2017 / Revised: 11 May 2017 / Accepted: 16 May 2017 / Published: 24 May 2017
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Abstract
Here, we present a surface-enhanced Raman spectroscopy (SERS) nanosensor for environmental pollutants detection. This study was conducted on three polycyclic aromatic hydrocarbons (PAHs): benzo[a]pyrene (BaP), fluoranthene (FL), and naphthalene (NAP). SERS substrates were chemically functionalized using 4-dodecyl benzenediazonium-tetrafluoroborate and SERS analyses were conducted
[...] Read more.
Here, we present a surface-enhanced Raman spectroscopy (SERS) nanosensor for environmental pollutants detection. This study was conducted on three polycyclic aromatic hydrocarbons (PAHs): benzo[a]pyrene (BaP), fluoranthene (FL), and naphthalene (NAP). SERS substrates were chemically functionalized using 4-dodecyl benzenediazonium-tetrafluoroborate and SERS analyses were conducted to detect the pollutants alone and in mixtures. Compounds were first measured in water-methanol (9:1 volume ratio) samples. Investigation on solutions containing concentrations ranging from 10−6 g L−1 to 10−3 g L−1 provided data to plot calibration curves and to determine the performance of the sensor. The calculated limit of detection (LOD) was 0.026 mg L−1 (10−7 mol L−1) for BaP, 0.064 mg L−1 (3.2 × 10−7 mol L−1) for FL, and 3.94 mg L−1 (3.1 × 10−5 mol L−1) for NAP, respectively. The correlation between the calculated LOD values and the octanol-water partition coefficient (Kow) of the investigated PAHs suggests that the developed nanosensor is particularly suitable for detecting highly non-polar PAH compounds. Measurements conducted on a mixture of the three analytes (i) demonstrated the ability of the developed technology to detect and identify the three analytes in the mixture; (ii) provided the exact quantitation of pollutants in a mixture. Moreover, we optimized the surface regeneration step for the nanosensor. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in France 2016)
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Open AccessArticle A Simple Drain Current Model for MOS Transistors with the Lorentz Force Effect
Sensors 2017, 17(6), 1199; doi:10.3390/s17061199
Received: 24 March 2017 / Revised: 17 May 2017 / Accepted: 18 May 2017 / Published: 24 May 2017
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Abstract
A novel concept of drain current modelling in rectangular normal MOS transistors with the Lorentz force has been proposed for the first time. The single-drain MOS transistor is qualified as a magnetic sensor. To create the Lorentz force, a DC loop current is
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A novel concept of drain current modelling in rectangular normal MOS transistors with the Lorentz force has been proposed for the first time. The single-drain MOS transistor is qualified as a magnetic sensor. To create the Lorentz force, a DC loop current is applied through an on-chip metal loop around the device, and the relation between the applied loop current and the created magnetic field is assumed to be linear in nature. The drain current of the MOS transistor is reduced with the applied Lorentz force from both directions. This change in the drain current is ascribed to a change in mobility in the strong inversion region, and a change in mobility of around 4.45% is observed. To model this change, a set of novel drain current equations, under the Lorentz force, for the strong inversion region has been proposed. A satisfactory agreement of an average error of less than 2% between the measured and the calculated drain currents under the magnetic field created by an on-chip metal loop is achieved. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Biomechanical Modeling of Pterygium Radiation Surgery: A Retrospective Case Study
Sensors 2017, 17(6), 1200; doi:10.3390/s17061200
Received: 31 March 2017 / Revised: 17 May 2017 / Accepted: 19 May 2017 / Published: 24 May 2017
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Abstract
Pterygium is a vascularized, invasive transformation on the anterior corneal surface that can be treated by Strontium-/Yttrium90 beta irradiation. Finite element modeling was used to analyze the biomechanical effects governing the treatment, and to help understand clinically observed changes in corneal astigmatism. Results
[...] Read more.
Pterygium is a vascularized, invasive transformation on the anterior corneal surface that can be treated by Strontium-/Yttrium90 beta irradiation. Finite element modeling was used to analyze the biomechanical effects governing the treatment, and to help understand clinically observed changes in corneal astigmatism. Results suggested that irradiation-induced pulling forces on the anterior corneal surface can cause astigmatism, as well as central corneal flattening. Finite element modeling of corneal biomechanics closely predicted the postoperative corneal surface (astigmatism error −0.01D; central curvature error −0.16D), and can help in understanding beta irradiation treatment. Numerical simulations have the potential to preoperatively predict corneal shape and function changes, and help to improve corneal treatments. Full article
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Open AccessArticle The Effects of Dithiothreitol on DNA
Sensors 2017, 17(6), 1201; doi:10.3390/s17061201
Received: 13 March 2017 / Revised: 17 May 2017 / Accepted: 18 May 2017 / Published: 24 May 2017
PDF Full-text (1162 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
With the novel possibilities for detecting molecules of interest with extreme sensitivity also comes the risk of encountering hitherto negligible sources of error. In life science, such sources of error might be the broad variety of additives such as dithiothreitol (DTT) used to
[...] Read more.
With the novel possibilities for detecting molecules of interest with extreme sensitivity also comes the risk of encountering hitherto negligible sources of error. In life science, such sources of error might be the broad variety of additives such as dithiothreitol (DTT) used to preserve enzyme stability during in vitro reactions. Using two different assays that can sense strand interruptions in double stranded DNA, we here show that DTT is able to introduce nicks in the DNA backbone. DTT was furthermore shown to facilitate the immobilization of fluorescent DNA on an NHS-ester functionalized glass surface. Such reactions may in particular impact the readout from single molecule detection studies and other ultrasensitive assays. This was highlighted by the finding that DTT markedly decreased the signal to noise ratio in a DNA sensor based assay with single molecule resolution. Full article
(This article belongs to the Special Issue Genosensing)
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Open AccessArticle The Effect of Leaf Stacking on Leaf Reflectance and Vegetation Indices Measured by Contact Probe during the Season
Sensors 2017, 17(6), 1202; doi:10.3390/s17061202
Received: 13 February 2017 / Revised: 18 May 2017 / Accepted: 18 May 2017 / Published: 24 May 2017
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Abstract
The aims of the study were: (i) to compare leaf reflectance in visible (VIS) (400–700 nm), near-infrared (NIR) (740–1140 nm) and short-wave infrared (SWIR) (2000–2400 nm) spectral ranges measured monthly by a contact probe on a single leaf and a stack of five
[...] Read more.
The aims of the study were: (i) to compare leaf reflectance in visible (VIS) (400–700 nm), near-infrared (NIR) (740–1140 nm) and short-wave infrared (SWIR) (2000–2400 nm) spectral ranges measured monthly by a contact probe on a single leaf and a stack of five leaves (measurement setup (MS)) of two broadleaved tree species during the vegetative season; and (ii) to test if and how selected vegetation indices differ under these two MS. In VIS, the pigment-related spectral region, the effect of MS on reflectance was negligible. The major influence of MS on reflectance was detected in NIR (up to 25%), the structure-related spectral range; and weaker effect in SWIR, the water-related spectral range. Vegetation indices involving VIS wavelengths were independent of MS while indices combining wavelengths from both VIS and NIR were MS-affected throughout the season. The effect of leaf stacking contributed to weakening the correlation between the leaf chlorophyll content and selected vegetation indices due to a higher leaf mass per area of the leaf sample. The majority of MS-affected indices were better correlated with chlorophyll content in both species in comparison with MS-unaffected indices. Therefore, in terms of monitoring leaf chlorophyll content using the contact probe reflectance measurement, these MS-affected indices should be used with caution, as discussed in the paper. If the vegetation indices are used for assessment of plant physiological status in various times of the vegetative season, then it is essential to take into consideration their possible changes induced by the particular contact probe measurement setup regarding the leaf stacking. Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle Amorphous In–Ga–Zn–O Powder with High Gas Selectivity towards Wide Range Concentration of C2H5OH
Sensors 2017, 17(6), 1203; doi:10.3390/s17061203
Received: 5 April 2017 / Revised: 9 May 2017 / Accepted: 20 May 2017 / Published: 24 May 2017
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Abstract
Amorphous indium gallium zinc oxide (a-IGZO) powder was prepared by typical solution-based process and post-annealing process. The sample was used as sensor for detecting C2H5OH, H2, and CO. Gas-sensing performance was found to be highly sensitive to
[...] Read more.
Amorphous indium gallium zinc oxide (a-IGZO) powder was prepared by typical solution-based process and post-annealing process. The sample was used as sensor for detecting C2H5OH, H2, and CO. Gas-sensing performance was found to be highly sensitive to C2H5OH gas in a wide range of concentration (0.5–1250 ppm) with the response of 2.0 towards 0.5 ppm and 89.2 towards 1250 ppm. Obvious difference of response towards C2H5OH, H2, and CO was found that the response e.g., was 33.20, 6.64, and 2.84 respectively at the concentration of 200 ppm. The response time and recovery time of was 32 s and 14 s respectively towards 200 ppm concentration of C2H5OH gas under heating voltage of 6.5 V. Full article
(This article belongs to the Section Chemical Sensors)
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Open AccessArticle A New Calibration Method for Commercial RGB-D Sensors
Sensors 2017, 17(6), 1204; doi:10.3390/s17061204
Received: 1 March 2017 / Revised: 9 May 2017 / Accepted: 20 May 2017 / Published: 24 May 2017
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Abstract
Commercial RGB-D sensors such as Kinect and Structure Sensors have been widely used in the game industry, where geometric fidelity is not of utmost importance. For applications in which high quality 3D is required, i.e., 3D building models of centimeter‑level accuracy, accurate and
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Commercial RGB-D sensors such as Kinect and Structure Sensors have been widely used in the game industry, where geometric fidelity is not of utmost importance. For applications in which high quality 3D is required, i.e., 3D building models of centimeter‑level accuracy, accurate and reliable calibrations of these sensors are required. This paper presents a new model for calibrating the depth measurements of RGB-D sensors based on the structured light concept. Additionally, a new automatic method is proposed for the calibration of all RGB-D parameters, including internal calibration parameters for all cameras, the baseline between the infrared and RGB cameras, and the depth error model. When compared with traditional calibration methods, this new model shows a significant improvement in depth precision for both near and far ranges. Full article
(This article belongs to the Special Issue Indoor LiDAR/Vision Systems)
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Open AccessArticle Evaluation and Comparison of the Processing Methods of Airborne Gravimetry Concerning the Errors Effects on Downward Continuation Results: Case Studies in Louisiana (USA) and the Tibetan Plateau (China)
Sensors 2017, 17(6), 1205; doi:10.3390/s17061205
Received: 4 April 2017 / Revised: 11 May 2017 / Accepted: 20 May 2017 / Published: 25 May 2017
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Abstract
Gravity data gaps in mountainous areas are nowadays often filled in with the data from airborne gravity surveys. Because of the errors caused by the airborne gravimeter sensors, and because of rough flight conditions, such errors cannot be completely eliminated. The precision of
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Gravity data gaps in mountainous areas are nowadays often filled in with the data from airborne gravity surveys. Because of the errors caused by the airborne gravimeter sensors, and because of rough flight conditions, such errors cannot be completely eliminated. The precision of the gravity disturbances generated by the airborne gravimetry is around 3–5 mgal. A major obstacle in using airborne gravimetry are the errors caused by the downward continuation. In order to improve the results the external high-accuracy gravity information e.g., from the surface data can be used for high frequency correction, while satellite information can be applying for low frequency correction. Surface data may be used to reduce the systematic errors, while regularization methods can reduce the random errors in downward continuation. Airborne gravity surveys are sometimes conducted in mountainous areas and the most extreme area of the world for this type of survey is the Tibetan Plateau. Since there are no high-accuracy surface gravity data available for this area, the above error minimization method involving the external gravity data cannot be used. We propose a semi-parametric downward continuation method in combination with regularization to suppress the systematic error effect and the random error effect in the Tibetan Plateau; i.e., without the use of the external high-accuracy gravity data. We use a Louisiana airborne gravity dataset from the USA National Oceanic and Atmospheric Administration (NOAA) to demonstrate that the new method works effectively. Furthermore, and for the Tibetan Plateau we show that the numerical experiment is also successfully conducted using the synthetic Earth Gravitational Model 2008 (EGM08)-derived gravity data contaminated with the synthetic errors. The estimated systematic errors generated by the method are close to the simulated values. In addition, we study the relationship between the downward continuation altitudes and the error effect. The analysis results show that the proposed semi-parametric method combined with regularization is efficient to address such modelling problems. Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle A Novel Complex-Coefficient In-Band Interference Suppression Algorithm for Cognitive Ultra-Wide Band Wireless Sensors Networks
Sensors 2017, 17(6), 1206; doi:10.3390/s17061206
Received: 11 March 2017 / Revised: 15 May 2017 / Accepted: 19 May 2017 / Published: 25 May 2017
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Abstract
With the rapid development of wireless communication systems and electronic techniques, the limited frequency spectrum resources are shared with various wireless devices, leading to a crowded and challenging coexistence circumstance. Cognitive radio (CR) and ultra-wide band (UWB), as sophisticated wireless techniques, have been
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With the rapid development of wireless communication systems and electronic techniques, the limited frequency spectrum resources are shared with various wireless devices, leading to a crowded and challenging coexistence circumstance. Cognitive radio (CR) and ultra-wide band (UWB), as sophisticated wireless techniques, have been considered as significant solutions to solve the harmonious coexistence issues. UWB wireless sensors can share the spectrum with primary user (PU) systems without harmful interference. The in-band interference of UWB systems should be considered because such interference can severely affect the transmissions of UWB wireless systems. In order to solve the in-band interference issues for UWB wireless sensor networks (WSN), a novel in-band narrow band interferences (NBIs) elimination scheme is proposed in this paper. The proposed narrow band interferences suppression scheme is based on a novel complex-coefficient adaptive notch filter unit with a single constrained zero-pole pair. Moreover, in order to reduce the computation complexity of the proposed scheme, an adaptive complex-coefficient iterative method based on two-order Taylor series is designed. To cope with multiple narrow band interferences, a linear cascaded high order adaptive filter and a cyclic cascaded high order matrix adaptive filter (CCHOMAF) interference suppression algorithm based on the basic adaptive notch filter unit are also presented. The theoretical analysis and numerical simulation results indicate that the proposed CCHOMAF algorithm can achieve better performance in terms of average bit error rate for UWB WSNs. The proposed in-band NBIs elimination scheme can significantly improve the reception performance of low-cost and low-power UWB wireless systems. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle Traffic Sign Detection System for Locating Road Intersections and Roundabouts: The Chilean Case
Sensors 2017, 17(6), 1207; doi:10.3390/s17061207
Received: 2 January 2017 / Revised: 16 May 2017 / Accepted: 22 May 2017 / Published: 25 May 2017
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Abstract
This paper presents a traffic sign detection method for signs close to road intersections and roundabouts, such as stop and yield (give way) signs. The proposed method relies on statistical templates built using color information for both segmentation and classification. The segmentation method
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This paper presents a traffic sign detection method for signs close to road intersections and roundabouts, such as stop and yield (give way) signs. The proposed method relies on statistical templates built using color information for both segmentation and classification. The segmentation method uses the RGB-normalized (ErEgEb) color space for ROIs (Regions of Interest) generation based on a chromaticity filter, where templates at 10 scales are applied to the entire image. Templates consider the mean and standard deviation of normalized color of the traffic signs to build thresholding intervals where the expected color should lie for a given sign. The classification stage employs the information of the statistical templates over YCbCr and ErEgEb color spaces, for which the background has been previously removed by using a probability function that models the probability that the pixel corresponds to a sign given its chromaticity values. This work includes an analysis of the detection rate as a function of the distance between the vehicle and the sign. Such information is useful to validate the robustness of the approach and is often not included in the existing literature. The detection rates, as a function of distance, are compared to those of the well-known Viola–Jones method. The results show that for distances less than 48 m, the proposed method achieves a detection rate of 87.5 % and 95.4 % for yield and stop signs, respectively. For distances less than 30 m, the detection rate is 100 % for both signs. The Viola–Jones approach has detection rates below 20 % for distances between 30 and 48 m, and barely improves in the 20–30 m range with detection rates of up to 60 % . Thus, the proposed method provides a robust alternative for intersection detection that relies on statistical color-based templates instead of shape information. The experiments employed videos of traffic signs taken in several streets of Santiago, Chile, using a research platform implemented at the Robotics and Automation Laboratory of PUC to develop driver assistance systems. Full article
(This article belongs to the Special Issue Sensors for Transportation)
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Open AccessArticle A Max-Flow Based Algorithm for Connected Target Coverage with Probabilistic Sensors
Sensors 2017, 17(6), 1208; doi:10.3390/s17061208
Received: 7 April 2017 / Revised: 10 May 2017 / Accepted: 19 May 2017 / Published: 25 May 2017
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Abstract
Coverage is a fundamental issue in the research field of wireless sensor networks (WSNs). Connected target coverage discusses the sensor placement to guarantee the needs of both coverage and connectivity. Existing works largely leverage on the Boolean disk model, which is only a
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Coverage is a fundamental issue in the research field of wireless sensor networks (WSNs). Connected target coverage discusses the sensor placement to guarantee the needs of both coverage and connectivity. Existing works largely leverage on the Boolean disk model, which is only a coarse approximation to the practical sensing model. In this paper, we focus on the connected target coverage issue based on the probabilistic sensing model, which can characterize the quality of coverage more accurately. In the probabilistic sensing model, sensors are only be able to detect a target with certain probability. We study the collaborative detection probability of target under multiple sensors. Armed with the analysis of collaborative detection probability, we further formulate the minimum ϵ-connected target coverage problem, aiming to minimize the number of sensors satisfying the requirements of both coverage and connectivity. We map it into a flow graph and present an approximation algorithm called the minimum vertices maximum flow algorithm (MVMFA) with provable time complex and approximation ratios. To evaluate our design, we analyze the performance of MVMFA theoretically and also conduct extensive simulation studies to demonstrate the effectiveness of our proposed algorithm. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle Amorphous SiC/c-ZnO-Based Quasi-Lamb Mode Sensor for Liquid Environments
Sensors 2017, 17(6), 1209; doi:10.3390/s17061209
Received: 1 April 2017 / Revised: 15 May 2017 / Accepted: 23 May 2017 / Published: 25 May 2017
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Abstract
The propagation of the quasi-Lamb modes along a-SiC/ZnO thin composite plates was modeled and analysed with the aim to design a sensor able to detect the changes in parameters of a liquid environment, such as added mass and viscosity changes. The modes propagation
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The propagation of the quasi-Lamb modes along a-SiC/ZnO thin composite plates was modeled and analysed with the aim to design a sensor able to detect the changes in parameters of a liquid environment, such as added mass and viscosity changes. The modes propagation was modeled by numerically solving the system of coupled electro-mechanical field equations in three media. The mode shape, the power flow, the phase velocity, and the electroacoustic coupling efficiency (K2) of the modes were calculated, specifically addressing the design of enhanced-coupling, microwave frequency sensors for applications in probing the solid/liquid interface. Three modes were identified that have predominant longitudinal polarization, high phase velocity, and quite good K2: the fundamental quasi symmetric mode (qS0) and two higher order quasi-longitudinal modes (qL1 and qL2) with a dominantly longitudinal displacement component in one plate side. The velocity and attenuation of these modes were calculated for different liquid viscosities and added mass, and the gravimetric and viscosity sensitivities of both the phase velocity and attenuation were theoretically calculated. The present study highlights the feasibility of the a-SiC/ZnO acoustic waveguides for the development of high-frequency, integrated-circuit compatible electroacoustic devices suitable for working in a liquid environment. Full article
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Open AccessArticle Mapping Winter Wheat with Multi-Temporal SAR and Optical Images in an Urban Agricultural Region
Sensors 2017, 17(6), 1210; doi:10.3390/s17061210
Received: 7 April 2017 / Revised: 21 May 2017 / Accepted: 21 May 2017 / Published: 25 May 2017
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Abstract
Winter wheat is the second largest food crop in China. It is important to obtain reliable winter wheat acreage to guarantee the food security for the most populous country in the world. This paper focuses on assessing the feasibility of in-season winter wheat
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Winter wheat is the second largest food crop in China. It is important to obtain reliable winter wheat acreage to guarantee the food security for the most populous country in the world. This paper focuses on assessing the feasibility of in-season winter wheat mapping and investigating potential classification improvement by using SAR (Synthetic Aperture Radar) images, optical images, and the integration of both types of data in urban agricultural regions with complex planting structures in Southern China. Both SAR (Sentinel-1A) and optical (Landsat-8) data were acquired, and classification using different combinations of Sentinel-1A-derived information and optical images was performed using a support vector machine (SVM) and a random forest (RF) method. The interference coherence and texture images were obtained and used to assess the effect of adding them to the backscatter intensity images on the classification accuracy. The results showed that the use of four Sentinel-1A images acquired before the jointing period of winter wheat can provide satisfactory winter wheat classification accuracy, with an F1 measure of 87.89%. The combination of SAR and optical images for winter wheat mapping achieved the best F1 measure–up to 98.06%. The SVM was superior to RF in terms of the overall accuracy and the kappa coefficient, and was faster than RF, while the RF classifier was slightly better than SVM in terms of the F1 measure. In addition, the classification accuracy can be effectively improved by adding the texture and coherence images to the backscatter intensity data. Full article
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Open AccessArticle Excimer Laser Surgery: Biometrical Iris Eye Recognition with Cyclorotational Control Eye Tracker System
Sensors 2017, 17(6), 1211; doi:10.3390/s17061211
Received: 26 March 2017 / Revised: 22 May 2017 / Accepted: 23 May 2017 / Published: 25 May 2017
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Abstract
A prospective comparative study assessing the importance of the intra-operative dynamic rotational tracking—especially in the treatment of astigmatisms in corneal refractive Excimer laser correction—concerning clinical outcomes is presented. The cyclotorsion from upright to supine position was measured using iris image comparison. The Group
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A prospective comparative study assessing the importance of the intra-operative dynamic rotational tracking—especially in the treatment of astigmatisms in corneal refractive Excimer laser correction—concerning clinical outcomes is presented. The cyclotorsion from upright to supine position was measured using iris image comparison. The Group 1 of patients was additionally treated with cyclorotational control and Group 2 only with X-Y control. Significant differences were observed between the groups regarding the mean postoperative cylinder refraction (p < 0.05). The mean cyclotorsion can be calculated to 3.75° with a standard deviation of 3.1°. The total range of torsion was from −14.9° to +12.6°. Re-treatment rate was 2.2% in Group 1 and 8.2% in Group 2, which is highly significant (p < 0.01). The investigation confirms that the dynamic rotational tracking system used for LASIK results in highly predictable refraction quality with significantly less postoperative re-treatments. Full article
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Open AccessArticle Automatic Detection of Driver Fatigue Using Driving Operation Information for Transportation Safety
Sensors 2017, 17(6), 1212; doi:10.3390/s17061212
Received: 19 April 2017 / Revised: 19 May 2017 / Accepted: 24 May 2017 / Published: 25 May 2017
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Abstract
Fatigued driving is a major cause of road accidents. For this reason, the method in this paper is based on the steering wheel angles (SWA) and yaw angles (YA) information under real driving conditions to detect drivers’ fatigue levels. It analyzes the operation
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Fatigued driving is a major cause of road accidents. For this reason, the method in this paper is based on the steering wheel angles (SWA) and yaw angles (YA) information under real driving conditions to detect drivers’ fatigue levels. It analyzes the operation features of SWA and YA under different fatigue statuses, then calculates the approximate entropy (ApEn) features of a short sliding window on time series. Using the nonlinear feature construction theory of dynamic time series, with the fatigue features as input, designs a “2-6-6-3” multi-level back propagation (BP) Neural Networks classifier to realize the fatigue detection. An approximately 15-h experiment is carried out on a real road, and the data retrieved are segmented and labeled with three fatigue levels after expert evaluation, namely “awake”, “drowsy” and “very drowsy”. The average accuracy of 88.02% in fatigue identification was achieved in the experiment, endorsing the value of the proposed method for engineering applications. Full article
(This article belongs to the Special Issue Sensors for Transportation)
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Open AccessArticle LOCALI: Calibration-Free Systematic Localization Approach for Indoor Positioning
Sensors 2017, 17(6), 1213; doi:10.3390/s17061213
Received: 15 March 2017 / Revised: 20 May 2017 / Accepted: 22 May 2017 / Published: 25 May 2017
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Abstract
Recent advancements in indoor positioning systems are based on infrastructure-free solutions, aimed at improving the location accuracy in complex indoor environments without the use of specialized resources. A popular infrastructure-free solution for indoor positioning is a calibration-based positioning, commonly known as fingerprinting. Fingerprinting
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Recent advancements in indoor positioning systems are based on infrastructure-free solutions, aimed at improving the location accuracy in complex indoor environments without the use of specialized resources. A popular infrastructure-free solution for indoor positioning is a calibration-based positioning, commonly known as fingerprinting. Fingerprinting solutions require extensive and error-free surveys of environments to build radio-map databases, which play a key role in position estimation. Fingerprinting also requires random updates of the database, when there are significant changes in the environment or a decrease in the accuracy. The calibration of the fingerprinting database is a time-consuming and laborious effort that prevents the extensive adoption of this technique. In this paper, we present a systematic LOCALIzation approach, “LOCALI”, for indoor positioning, which does not require a calibration database and extensive updates. The LOCALI exploits the floor plan/wall map of the environment to estimate the target position by generating radio maps by integrating path-losses over certain trajectories in complex indoor environments, where triangulation using time information or the received signal strength level is highly erroneous due to the fading effects caused by multi-path propagation or absorption by environmental elements or varying antenna alignment. Experimental results demonstrate that by using the map information and environmental parameters, a significant level of accuracy in indoor positioning can be achieved. Moreover, this process requires considerably lesser effort compared to the calibration-based techniques. Full article
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Open AccessArticle DeepMap+: Recognizing High-Level Indoor Semantics Using Virtual Features and Samples Based on a Multi-Length Window Framework
Sensors 2017, 17(6), 1214; doi:10.3390/s17061214
Received: 25 February 2017 / Revised: 21 May 2017 / Accepted: 22 May 2017 / Published: 26 May 2017
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Abstract
Existing indoor semantic recognition schemes are mostly capable of discovering patterns through smartphone sensing, but it is hard to recognize rich enough high-level indoor semantics for map enhancement. In this work we present DeepMap+, an automatical inference system for recognizing high-level indoor semantics
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Existing indoor semantic recognition schemes are mostly capable of discovering patterns through smartphone sensing, but it is hard to recognize rich enough high-level indoor semantics for map enhancement. In this work we present DeepMap+, an automatical inference system for recognizing high-level indoor semantics using complex human activities with wrist-worn sensing. DeepMap+ is the first deep computation system using deep learning (DL) based on a multi-length window framework to enrich the data source. Furthermore, we propose novel methods of increasing virtual features and virtual samples for DeepMap+ to better discover hidden patterns of complex hand gestures. We have performed 23 high-level indoor semantics (including public facilities and functional zones) and collected wrist-worn data at a Wal-Mart supermarket. The experimental results show that our proposed methods can effectively improve the classification accuracy. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Internal Model-Based Robust Tracking Control Design for the MEMS Electromagnetic Micromirror
Sensors 2017, 17(6), 1215; doi:10.3390/s17061215
Received: 3 April 2017 / Revised: 22 May 2017 / Accepted: 23 May 2017 / Published: 26 May 2017
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Abstract
The micromirror based on micro-electro-mechanical systems (MEMS) technology is widely employed in different areas, such as scanning, imaging and optical switching. This paper studies the MEMS electromagnetic micromirror for scanning or imaging application. In these application scenarios, the micromirror is required to track
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The micromirror based on micro-electro-mechanical systems (MEMS) technology is widely employed in different areas, such as scanning, imaging and optical switching. This paper studies the MEMS electromagnetic micromirror for scanning or imaging application. In these application scenarios, the micromirror is required to track the command sinusoidal signal, which can be converted to an output regulation problem theoretically. In this paper, based on the internal model principle, the output regulation problem is solved by designing a robust controller that is able to force the micromirror to track the command signal accurately. The proposed controller relies little on the accuracy of the model. Further, the proposed controller is implemented, and its effectiveness is examined by experiments. The experimental results demonstrate that the performance of the proposed controller is satisfying. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle LEM Characterization of Synthetic Jet Actuators Driven by Piezoelectric Element: A Review
Sensors 2017, 17(6), 1216; doi:10.3390/s17061216
Received: 6 March 2017 / Revised: 28 April 2017 / Accepted: 17 May 2017 / Published: 26 May 2017
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Abstract
In the last decades, Synthetic jet actuators have gained much interest among the flow control techniques due to their short response time, high jet velocity and absence of traditional piping, which matches the requirements of reduced size and low weight. A synthetic jet
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In the last decades, Synthetic jet actuators have gained much interest among the flow control techniques due to their short response time, high jet velocity and absence of traditional piping, which matches the requirements of reduced size and low weight. A synthetic jet is generated by the diaphragm oscillation (generally driven by a piezoelectric element) in a relatively small cavity, producing periodic cavity pressure variations associated with cavity volume changes. The pressured air exhausts through an orifice, converting diaphragm electrodynamic energy into jet kinetic energy. This review paper considers the development of various Lumped-Element Models (LEMs) as practical tools to design and manufacture the actuators. LEMs can quickly predict device performances such as the frequency response in terms of diaphragm displacement, cavity pressure and jet velocity, as well as the efficiency of energy conversion of input Joule power into useful kinetic power of air jet. The actuator performance is also analyzed by varying typical geometric parameters such as cavity height and orifice diameter and length, through a suited dimensionless form of the governing equations. A comprehensive and detailed physical modeling aimed to evaluate the device efficiency is introduced, shedding light on the different stages involved in the process. Overall, the influence of the coupling degree of the two oscillators, the diaphragm and the Helmholtz frequency, on the device performance is discussed throughout the paper. Full article
(This article belongs to the Special Issue Piezoelectric Micro- and Nano-Devices)
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Open AccessArticle A Smart Power Electronic Multiconverter for the Residential Sector
Sensors 2017, 17(6), 1217; doi:10.3390/s17061217
Received: 16 March 2017 / Revised: 19 May 2017 / Accepted: 23 May 2017 / Published: 26 May 2017
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Abstract
The future of the grid includes distributed generation and smart grid technologies. Demand Side Management (DSM) systems will also be essential to achieve a high level of reliability and robustness in power systems. To do that, expanding the Advanced Metering Infrastructure (AMI) and
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The future of the grid includes distributed generation and smart grid technologies. Demand Side Management (DSM) systems will also be essential to achieve a high level of reliability and robustness in power systems. To do that, expanding the Advanced Metering Infrastructure (AMI) and Energy Management Systems (EMS) are necessary. The trend direction is towards the creation of energy resource hubs, such as the smart community concept. This paper presents a smart multiconverter system for residential/housing sector with a Hybrid Energy Storage System (HESS) consisting of supercapacitor and battery, and with local photovoltaic (PV) energy source integration. The device works as a distributed energy unit located in each house of the community, receiving active power set-points provided by a smart community EMS. This central EMS is responsible for managing the active energy flows between the electricity grid, renewable energy sources, storage equipment and loads existing in the community. The proposed multiconverter is responsible for complying with the reference active power set-points with proper power quality; guaranteeing that the local PV modules operate with a Maximum Power Point Tracking (MPPT) algorithm; and extending the lifetime of the battery thanks to a cooperative operation of the HESS. A simulation model has been developed in order to show the detailed operation of the system. Finally, a prototype of the multiconverter platform has been implemented and some experimental tests have been carried out to validate it. Full article
(This article belongs to the Special Issue Advances in Sensors for Sustainable Smart Cities and Smart Buildings)
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Open AccessArticle Modelling and Optimization of Four-Segment Shielding Coils of Current Transformers
Sensors 2017, 17(6), 1218; doi:10.3390/s17061218
Received: 22 March 2017 / Revised: 25 April 2017 / Accepted: 22 May 2017 / Published: 26 May 2017
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Abstract
Applying shielding coils is a practical way to protect current transformers (CTs) for large-capacity generators from the intensive magnetic interference produced by adjacent bus-bars. The aim of this study is to build a simple analytical model for the shielding coils, from which the
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Applying shielding coils is a practical way to protect current transformers (CTs) for large-capacity generators from the intensive magnetic interference produced by adjacent bus-bars. The aim of this study is to build a simple analytical model for the shielding coils, from which the optimization of the shielding coils can be calculated effectively. Based on an existing stray flux model, a new analytical model for the leakage flux of partial coils is presented, and finite element method-based simulations are carried out to develop empirical equations for the core-pickup factors of the models. Using the flux models, a model of the common four-segment shielding coils is derived. Furthermore, a theoretical analysis is carried out on the optimal performance of the four-segment shielding coils in a typical six-bus-bars scenario. It turns out that the “all parallel” shielding coils with a 45° starting position have the best shielding performance, whereas the “separated loop” shielding coils with a 0° starting position feature the lowest heating value. Physical experiments were performed, which verified all the models and the conclusions proposed in the paper. In addition, for shielding coils with other than the four-segment configuration, the analysis process will generally be the same. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Corrugated-Diaphragm Based Fiber Laser Hydrophone with Sub-100 μPa/Hz1/2 Resolution
Sensors 2017, 17(6), 1219; doi:10.3390/s17061219
Received: 18 April 2017 / Revised: 16 May 2017 / Accepted: 23 May 2017 / Published: 26 May 2017
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Abstract
In this work, a beat-frequency encoded fiber laser hydrophone is developed for high-resolution acoustic detection by using an elastic corrugated diaphragm. The diaphragm is center-supported by the fiber. Incident acoustic waves deform the diaphragm and induce a concentrated lateral load on the laser
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In this work, a beat-frequency encoded fiber laser hydrophone is developed for high-resolution acoustic detection by using an elastic corrugated diaphragm. The diaphragm is center-supported by the fiber. Incident acoustic waves deform the diaphragm and induce a concentrated lateral load on the laser cavity. The acoustically induced perturbation changes local optical phases and frequency-modulates the radio-frequency beat signal between two orthogonal lasing modes of the cavity. Theoretical analysis reveals that a higher corrugation-depth/thickness ratio or larger diaphragm area can provide higher transduction efficiency. The experimentally achieved average sensitivity in beat-frequency variation is 185.7 kHz/Pa over a bandwidth of 1 kHz. The detection capability can be enhanced by shortening the cavity length to enhance the signal-to-noise ratio. The minimum detectable acoustic pressure reaches 74 µPa/Hz1/2 at 1 kHz, which is comparable to the zeroth order sea noise. Full article
(This article belongs to the Special Issue Fiber Bragg Grating Based Sensors)
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Open AccessArticle Development of a Flexible Artificial Lateral Line Canal System for Hydrodynamic Pressure Detection
Sensors 2017, 17(6), 1220; doi:10.3390/s17061220
Received: 16 February 2017 / Revised: 10 May 2017 / Accepted: 24 May 2017 / Published: 26 May 2017
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Abstract
Surface mounted ‘smart skin’ can enhance the situational and environmental awareness of marine vehicles, which requires flexible, reliable, and light-weight hydrodynamic pressure sensors. Inspired by the lateral line canal system in fish, we developed an artificial lateral line (ALL) canal system by integrating
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Surface mounted ‘smart skin’ can enhance the situational and environmental awareness of marine vehicles, which requires flexible, reliable, and light-weight hydrodynamic pressure sensors. Inspired by the lateral line canal system in fish, we developed an artificial lateral line (ALL) canal system by integrating cantilevered flow-sensing elements in a polydimethylsiloxane (PDMS) canal. Polypropylene and polyvinylidene fluoride (PVDF) layers were laminated together to form the cantilevered flow-sensing elements. Both the ALL canal system and its superficial counterpart were characterized using a dipole vibration source. Experimental results showed that the peak frequencies of both the canal and superficial sensors were approximately 110 Hz, which was estimated to be the resonance frequency of the cantilevered flow-sensing element. The proposed ALL canal system demonstrated high-pass filtering capabilities to attenuate low-frequency stimulus and a pressure gradient detection limit of approximately 11 Pa/m at a frequency of 115 ± 1 Hz. Because of its structural flexibility and noise immunity, the proposed ALL canal system shows significant potential for underwater robotics applications. Full article
(This article belongs to the Special Issue Piezoelectric Micro- and Nano-Devices)
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Open AccessArticle Time Series Data Analysis of Wireless Sensor Network Measurements of Temperature
Sensors 2017, 17(6), 1221; doi:10.3390/s17061221
Received: 21 February 2017 / Revised: 8 May 2017 / Accepted: 23 May 2017 / Published: 26 May 2017
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Abstract
Wireless sensor networks have gained significant traction in environmental signal monitoring and analysis. The cost or lifetime of the system typically depends on the frequency at which environmental phenomena are monitored. If sampling rates are reduced, energy is saved. Using empirical datasets collected
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Wireless sensor networks have gained significant traction in environmental signal monitoring and analysis. The cost or lifetime of the system typically depends on the frequency at which environmental phenomena are monitored. If sampling rates are reduced, energy is saved. Using empirical datasets collected from environmental monitoring sensor networks, this work performs time series analyses of measured temperature time series. Unlike previous works which have concentrated on suppressing the transmission of some data samples by time-series analysis but still maintaining high sampling rates, this work investigates reducing the sampling rate (and sensor wake up rate) and looks at the effects on accuracy. Results show that the sampling period of the sensor can be increased up to one hour while still allowing intermediate and future states to be estimated with interpolation RMSE less than 0.2 °C and forecasting RMSE less than 1 °C. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle A Multiple Sensors Platform Method for Power Line Inspection Based on a Large Unmanned Helicopter
Sensors 2017, 17(6), 1222; doi:10.3390/s17061222
Received: 31 March 2017 / Revised: 20 May 2017 / Accepted: 22 May 2017 / Published: 26 May 2017
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Abstract
Many theoretical and experimental studies have been carried out in order to improve the efficiency and reduce labor for power line inspection, but problems related to stability, efficiency, and comprehensiveness still exist. This paper presents a multiple sensors platform method for overhead power
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Many theoretical and experimental studies have been carried out in order to improve the efficiency and reduce labor for power line inspection, but problems related to stability, efficiency, and comprehensiveness still exist. This paper presents a multiple sensors platform method for overhead power line inspection based on the use of a large unmanned helicopter. Compared with the existing methods, multiple sensors can realize synchronized inspection on all power line components and surrounding objects within one sortie. Flight safety of unmanned helicopter, scheduling of sensors and exact tracking on power line components are very important aspects when using the proposed multiple sensors platform, therefore this paper introduces in detail the planning method for the flight path of the unmanned helicopter and tasks of the sensors before inspecting power lines, and the method used for tracking power lines and insulators automatically during the inspection process. To validate the method, experiments on a transmission line at Qingyuan in Guangdong Province were carried out, the results show that the proposed method is effective for power line inspection. Full article
(This article belongs to the Special Issue Multi-Sensor Integration and Fusion)
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Open AccessArticle Complete Tri-Axis Magnetometer Calibration with a Gyro Auxiliary
Sensors 2017, 17(6), 1223; doi:10.3390/s17061223
Received: 30 March 2017 / Revised: 22 May 2017 / Accepted: 24 May 2017 / Published: 26 May 2017
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Abstract
Magnetometers combined with inertial sensors are widely used for orientation estimation, and calibrations are necessary to achieve high accuracy. This paper presents a complete tri-axis magnetometer calibration algorithm with a gyro auxiliary. The magnetic distortions and sensor errors, including the misalignment error between
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Magnetometers combined with inertial sensors are widely used for orientation estimation, and calibrations are necessary to achieve high accuracy. This paper presents a complete tri-axis magnetometer calibration algorithm with a gyro auxiliary. The magnetic distortions and sensor errors, including the misalignment error between the magnetometer and assembled platform, are compensated after calibration. With the gyro auxiliary, the magnetometer linear interpolation outputs are calculated, and the error parameters are evaluated under linear operations of magnetometer interpolation outputs. The simulation and experiment are performed to illustrate the efficiency of the algorithm. After calibration, the heading errors calculated by magnetometers are reduced to 0.5° (1σ). This calibration algorithm can also be applied to tri-axis accelerometers whose error model is similar to tri-axis magnetometers. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Comparison Study between RMS and Edge Detection Image Processing Algorithms for a Pulsed Laser UWPI (Ultrasonic Wave Propagation Imaging)-Based NDT Technique
Sensors 2017, 17(6), 1224; doi:10.3390/s17061224
Received: 13 March 2017 / Revised: 15 May 2017 / Accepted: 25 May 2017 / Published: 26 May 2017
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Abstract
In this study, a non-contact laser ultrasonic propagation imaging technique was applied to detect the damage of plate-like structures. Lamb waves were generated by an Nd:YAG pulse laser system, while a galvanometer-based laser scanner was used to scan the preliminarily designated area. The
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In this study, a non-contact laser ultrasonic propagation imaging technique was applied to detect the damage of plate-like structures. Lamb waves were generated by an Nd:YAG pulse laser system, while a galvanometer-based laser scanner was used to scan the preliminarily designated area. The signals of the structural responses were measured using a piezoelectric sensor attached on the front or back side of the plates. The obtained responses were analyzed by calculating the root mean square (RMS) values to achieve the visualization of structural defects such as crack, corrosion, and so on. If the propagating waves encounter the damage, the waves are scattered at the damage and the energy of the scattered waves can be expressed by the RMS values. In this study, notch and corrosion were artificially formed on aluminum plates and were considered as structural defects. The notches were created with different depths and angles on the aluminum plates, and the corrosion damage was formed with different depths and areas. To visualize the damage more clearly, edge detection methodologies were applied to the RMS images and the feasibility of the methods was investigated. The results showed that most of the edge detection methods were good at detecting the shape and/or the size of the damage while they had poor performance of detecting the depth of the damage. Full article
(This article belongs to the Special Issue Intelligent Sensing Technologies for Nondestructive Evaluation)
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Open AccessArticle DOA Finding with Support Vector Regression Based Forward–Backward Linear Prediction
Sensors 2017, 17(6), 1225; doi:10.3390/s17061225
Received: 19 April 2017 / Revised: 22 May 2017 / Accepted: 24 May 2017 / Published: 27 May 2017
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Abstract
Direction-of-arrival (DOA) estimation has drawn considerable attention in array signal processing, particularly with coherent signals and a limited number of snapshots. Forward–backward linear prediction (FBLP) is able to directly deal with coherent signals. Support vector regression (SVR) is robust with small samples. This
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Direction-of-arrival (DOA) estimation has drawn considerable attention in array signal processing, particularly with coherent signals and a limited number of snapshots. Forward–backward linear prediction (FBLP) is able to directly deal with coherent signals. Support vector regression (SVR) is robust with small samples. This paper proposes the combination of the advantages of FBLP and SVR in the estimation of DOAs of coherent incoming signals with low snapshots. The performance of the proposed method is validated with numerical simulations in coherent scenarios, in terms of different angle separations, numbers of snapshots, and signal-to-noise ratios (SNRs). Simulation results show the effectiveness of the proposed method. Full article
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Open AccessArticle Adaptive Data Aggregation and Compression to Improve Energy Utilization in Solar-Powered Wireless Sensor Networks
Sensors 2017, 17(6), 1226; doi:10.3390/s17061226
Received: 17 April 2017 / Revised: 17 May 2017 / Accepted: 24 May 2017 / Published: 27 May 2017
Cited by 3 | PDF Full-text (578 KB) | HTML Full-text | XML Full-text
Abstract
A node in a solar-powered wireless sensor network (WSN) collects energy when the sun shines and stores it in a battery or capacitor for use when no solar power is available, in particular at night. In our scheme, each tiny node in a
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A node in a solar-powered wireless sensor network (WSN) collects energy when the sun shines and stores it in a battery or capacitor for use when no solar power is available, in particular at night. In our scheme, each tiny node in a WSN periodically determines its energy budget, which takes into account its residual energy, and its likely acquisition and consumption. If it expects to acquire more energy than it can store, the data which has it has sensed is aggregated with data from other nodes, compressed, and transmitted. Otherwise, the node continues to sense data, but turns off its wireless communication to reduce energy consumption. We compared several schemes by simulation. Our scheme reduced the number of nodes forced to black out due to lack of energy so that more data arrives at the sink node. Full article
(This article belongs to the Special Issue Wireless Rechargeable Sensor Networks)
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Open AccessArticle A Protocol Layer Trust-Based Intrusion Detection Scheme for Wireless Sensor Networks
Sensors 2017, 17(6), 1227; doi:10.3390/s17061227
Received: 29 March 2017 / Revised: 12 May 2017 / Accepted: 24 May 2017 / Published: 27 May 2017
Cited by 1 | PDF Full-text (5528 KB) | HTML Full-text | XML Full-text
Abstract
This article proposes a protocol layer trust-based intrusion detection scheme for wireless sensor networks. Unlike existing work, the trust value of a sensor node is evaluated according to the deviations of key parameters at each protocol layer considering the attacks initiated at different
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This article proposes a protocol layer trust-based intrusion detection scheme for wireless sensor networks. Unlike existing work, the trust value of a sensor node is evaluated according to the deviations of key parameters at each protocol layer considering the attacks initiated at different protocol layers will inevitably have impacts on the parameters of the corresponding protocol layers. For simplicity, the paper mainly considers three aspects of trustworthiness, namely physical layer trust, media access control layer trust and network layer trust. The per-layer trust metrics are then combined to determine the overall trust metric of a sensor node. The performance of the proposed intrusion detection mechanism is then analyzed using the t-distribution to derive analytical results of false positive and false negative probabilities. Numerical analytical results, validated by simulation results, are presented in different attack scenarios. It is shown that the proposed protocol layer trust-based intrusion detection scheme outperforms a state-of-the-art scheme in terms of detection probability and false probability, demonstrating its usefulness for detecting cross-layer attacks. Full article
(This article belongs to the Special Issue Smart Communication Protocols and Algorithms for Sensor Networks)
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Open AccessArticle Underwater Depth and Temperature Sensing Based on Fiber Optic Technology for Marine and Fresh Water Applications
Sensors 2017, 17(6), 1228; doi:10.3390/s17061228
Received: 13 April 2017 / Revised: 24 May 2017 / Accepted: 24 May 2017 / Published: 27 May 2017
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Abstract
Oceanic conditions play an important role in determining the effects of climate change and these effects can be monitored through the changes in the physical properties of sea water. In fact, Oceanographers use various probes for measuring the properties within the water column.
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Oceanic conditions play an important role in determining the effects of climate change and these effects can be monitored through the changes in the physical properties of sea water. In fact, Oceanographers use various probes for measuring the properties within the water column. CTDs (Conductivity, Temperature and Depth) provide profiles of physical and chemical parameters of the water column. A CTD device consists of Conductivity (C), Temperature (T) and Depth (D) probes to monitor the water column changes with respect to relative depth. An optical fibre-based point sensor used as a combined pressure (depth) and temperature sensor and the sensor system are described. Measurements accruing from underwater trials of a miniature sensor for pressure (depth) and temperature in the ocean and in fresh water are reported. The sensor exhibits excellent stability and its performance is shown to be comparable with the Sea-Bird Scientific commercial sensor: SBE9Plus. Full article
(This article belongs to the Special Issue Marine Sensing)
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Open AccessArticle Evaluation of Feature Extraction and Recognition for Activity Monitoring and Fall Detection Based on Wearable sEMG Sensors
Sensors 2017, 17(6), 1229; doi:10.3390/s17061229
Received: 17 March 2017 / Revised: 6 May 2017 / Accepted: 23 May 2017 / Published: 27 May 2017
Cited by 2 | PDF Full-text (7099 KB) | HTML Full-text | XML Full-text
Abstract
As an essential subfield of context awareness, activity awareness, especially daily activity monitoring and fall detection, plays a significant role for elderly or frail people who need assistance in their daily activities. This study investigates the feature extraction and pattern recognition of surface
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As an essential subfield of context awareness, activity awareness, especially daily activity monitoring and fall detection, plays a significant role for elderly or frail people who need assistance in their daily activities. This study investigates the feature extraction and pattern recognition of surface electromyography (sEMG), with the purpose of determining the best features and classifiers of sEMG for daily living activities monitoring and fall detection. This is done by a serial of experiments. In the experiments, four channels of sEMG signal from wireless, wearable sensors located on lower limbs are recorded from three subjects while they perform seven activities of daily living (ADL). A simulated trip fall scenario is also considered with a custom-made device attached to the ankle. With this experimental setting, 15 feature extraction methods of sEMG, including time, frequency, time/frequency domain and entropy, are analyzed based on class separability and calculation complexity, and five classification methods, each with 15 features, are estimated with respect to the accuracy rate of recognition and calculation complexity for activity monitoring and fall detection. It is shown that a high accuracy rate of recognition and a minimal calculation time for daily activity monitoring and fall detection can be achieved in the current experimental setting. Specifically, the Wilson Amplitude (WAMP) feature performs the best, and the classifier Gaussian Kernel Support Vector Machine (GK-SVM) with Permutation Entropy (PE) or WAMP results in the highest accuracy for activity monitoring with recognition rates of 97.35% and 96.43%. For fall detection, the classifier Fuzzy Min-Max Neural Network (FMMNN) has the best sensitivity and specificity at the cost of the longest calculation time, while the classifier Gaussian Kernel Fisher Linear Discriminant Analysis (GK-FDA) with the feature WAMP guarantees a high sensitivity (98.70%) and specificity (98.59%) with a short calculation time (65.586 ms), making it a possible choice for pre-impact fall detection. The thorough quantitative comparison of the features and classifiers in this study supports the feasibility of a wireless, wearable sEMG sensor system for automatic activity monitoring and fall detection. Full article
(This article belongs to the Section Biosensors)
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Open AccessArticle Location-Enhanced Activity Recognition in Indoor Environments Using Off the Shelf Smart Watch Technology and BLE Beacons
Sensors 2017, 17(6), 1230; doi:10.3390/s17061230
Received: 2 April 2017 / Revised: 17 May 2017 / Accepted: 19 May 2017 / Published: 27 May 2017
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Abstract
Activity recognition in indoor spaces benefits context awareness and improves the efficiency of applications related to personalised health monitoring, building energy management, security and safety. The majority of activity recognition frameworks, however, employ a network of specialised building sensors or a network of
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Activity recognition in indoor spaces benefits context awareness and improves the efficiency of applications related to personalised health monitoring, building energy management, security and safety. The majority of activity recognition frameworks, however, employ a network of specialised building sensors or a network of body-worn sensors. As this approach suffers with respect to practicality, we propose the use of commercial off-the-shelf devices. In this work, we design and evaluate an activity recognition system composed of a smart watch, which is enhanced with location information coming from Bluetooth Low Energy (BLE) beacons. We evaluate the performance of this approach for a variety of activities performed in an indoor laboratory environment, using four supervised machine learning algorithms. Our experimental results indicate that our location-enhanced activity recognition system is able to reach a classification accuracy ranging from 92% to 100%, while without location information classification accuracy it can drop to as low as 50% in some cases, depending on the window size chosen for data segmentation. Full article
(This article belongs to the Special Issue Smart Sensing Technologies for Personalised Coaching)
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Open AccessArticle A Compact Magnetic Field-Based Obstacle Detection and Avoidance System for Miniature Spherical Robots
Sensors 2017, 17(6), 1231; doi:10.3390/s17061231
Received: 20 April 2017 / Revised: 23 May 2017 / Accepted: 24 May 2017 / Published: 28 May 2017
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Abstract
Due to their efficient locomotion and natural tolerance to hazardous environments, spherical robots have wide applications in security surveillance, exploration of unknown territory and emergency response. Numerous studies have been conducted on the driving mechanism, motion planning and trajectory tracking methods of spherical
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Due to their efficient locomotion and natural tolerance to hazardous environments, spherical robots have wide applications in security surveillance, exploration of unknown territory and emergency response. Numerous studies have been conducted on the driving mechanism, motion planning and trajectory tracking methods of spherical robots, yet very limited studies have been conducted regarding the obstacle avoidance capability of spherical robots. Most of the existing spherical robots rely on the “hit and run” technique, which has been argued to be a reasonable strategy because spherical robots have an inherent ability to recover from collisions. Without protruding components, they will not become stuck and can simply roll back after running into bstacles. However, for small scale spherical robots that contain sensitive surveillance sensors and cannot afford to utilize heavy protective shells, the absence of obstacle avoidance solutions would leave the robot at the mercy of potentially dangerous obstacles. In this paper, a compact magnetic field-based obstacle detection and avoidance system has been developed for miniature spherical robots. It utilizes a passive magnetic field so that the system is both compact and power efficient. The proposed system can detect not only the presence, but also the approaching direction of a ferromagnetic obstacle, therefore, an intelligent avoidance behavior can be generated by adapting the trajectory tracking method with the detection information. Design optimization is conducted to enhance the obstacle detection performance and detailed avoidance strategies are devised. Experimental results are also presented for validation purposes. Full article
(This article belongs to the Special Issue Magnetic Sensors and Their Applications)
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Open AccessArticle History-Based Response Threshold Model for Division of Labor in Multi-Agent Systems
Sensors 2017, 17(6), 1232; doi:10.3390/s17061232
Received: 31 March 2017 / Revised: 16 May 2017 / Accepted: 25 May 2017 / Published: 28 May 2017
Cited by 2 | PDF Full-text (755 KB) | HTML Full-text | XML Full-text
Abstract
Dynamic task allocation is a necessity in a group of robots. Each member should decide its own task such that it is most commensurate with its current state in the overall system. In this work, the response threshold model is applied to a
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Dynamic task allocation is a necessity in a group of robots. Each member should decide its own task such that it is most commensurate with its current state in the overall system. In this work, the response threshold model is applied to a dynamic foraging task. Each robot employs a task switching function based on the local task demand obtained from the surrounding environment, and no communication occurs between the robots. Each individual member has a constant-sized task demand history that reflects the global demand. In addition, it has response threshold values for all of the tasks and manages the task switching process depending on the stimuli of the task demands. The robot then determines the task to be executed to regulate the overall division of labor. This task selection induces a specialized tendency for performing a specific task and regulates the division of labor. In particular, maintaining a history of the task demands is very effective for the dynamic foraging task. Various experiments are performed using a simulation with multiple robots, and the results show that the proposed algorithm is more effective as compared to the conventional model. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle Performance of BDS-3: Measurement Quality Analysis, Precise Orbit and Clock Determination
Sensors 2017, 17(6), 1233; doi:10.3390/s17061233
Received: 12 March 2017 / Revised: 25 May 2017 / Accepted: 25 May 2017 / Published: 28 May 2017
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Abstract
Since 2015, China has successfully launched five experimental BeiDou global navigation system (BDS-3) satellites for expanding the regional system to global coverage. An initial performance assessment and characterization analysis of the BDS-3 is presented. Twenty days of tracking data have been collected from
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Since 2015, China has successfully launched five experimental BeiDou global navigation system (BDS-3) satellites for expanding the regional system to global coverage. An initial performance assessment and characterization analysis of the BDS-3 is presented. Twenty days of tracking data have been collected from eleven monitoring stations. The tracking characteristics and measurement quality are analyzed and compared with the regional BDS (BDS-2) in terms of observed carrier-to-noise density ratio, pseudo-range multipath, and noise. The preliminary results suggest that the measurement quality of BDS-3 outperforms the BDS-2 for the same type of satellites. In addition, the analysis of multipath combinations reveals that the problem of satellite-induced code biases found in BDS-2 seems to have been solved for BDS-3. Precise orbit and clock determination are carried out and evaluated. The orbit overlap comparison show a precision of 2–6 dm in 3D root mean square (RMS) and 6–14 cm in the radial component for experimental BDS-3 satellites. External validations with satellite laser ranging (SLR) show residual RMS on the level of 1–3 dm. Finally, the performance of the new-generation onboard atomic clocks is evaluated and results confirm an increased stability compared to BDS-2 satellite clocks. Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle High Resolution Full-Aperture ISAR Processing through Modified Doppler History Based Motion Compensation
Sensors 2017, 17(6), 1234; doi:10.3390/s17061234
Received: 25 March 2017 / Revised: 24 May 2017 / Accepted: 26 May 2017 / Published: 28 May 2017
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Abstract
A high resolution inverse synthetic aperture radar (ISAR) technique is presented using modified Doppler history based motion compensation. To this purpose, a novel wideband ISAR system is developed that accommodates parametric processing over extended aperture length. The proposed method is derived from an
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A high resolution inverse synthetic aperture radar (ISAR) technique is presented using modified Doppler history based motion compensation. To this purpose, a novel wideband ISAR system is developed that accommodates parametric processing over extended aperture length. The proposed method is derived from an ISAR-to-SAR approach that makes use of high resolution spotlight SAR and sub-aperture recombination. It is dedicated to wide aperture ISAR imaging and exhibits robust performance against unstable targets having non-linear motions. We demonstrate that the Doppler histories of the full aperture ISAR echoes from disturbed targets are efficiently retrieved with good fitting models. Experiments have been conducted on real aircraft targets and the feasibility of the full aperture ISAR processing is verified through the acquisition of high resolution ISAR imagery. Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle Study of ZnS Nanostructures Based Electrochemical and Photoelectrochemical Biosensors for Uric Acid Detection
Sensors 2017, 17(6), 1235; doi:10.3390/s17061235
Received: 15 April 2017 / Revised: 14 May 2017 / Accepted: 18 May 2017 / Published: 28 May 2017
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Abstract
Uric acid (UA) is a kind of purine metabolism product and important in clinical diagnosis. In this work, we present a study of ZnS nanostructures-based electrochemical and photoelectrochemical biosensors for UA detection. Through a simple hydrothermal method and varying the ratio of reaction
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Uric acid (UA) is a kind of purine metabolism product and important in clinical diagnosis. In this work, we present a study of ZnS nanostructures-based electrochemical and photoelectrochemical biosensors for UA detection. Through a simple hydrothermal method and varying the ratio of reaction solvents, we obtained ZnS nanomaterials of one-dimensional to three-dimensional morphologies and they were characterized using field emission scanning electron microscopy (FESEM) and X-ray diffraction (XRD). To fabricate the UA biosensor and study the effect of material morphology on its performance, ZnS nanomaterials were deposited on indium tin oxide (ITO) conducting glass and then coated with uricase by physical absorption. Three kinds of working electrodes were characterized by cyclic voltammetry method. The effect of material morphology on performance of UA detection was investigated via amperometric response based electrochemical method based on enzymatic reaction. The ZnS urchin-like nanostructures electrode shows better sensitivity compared with those made of nanoparticles and nanoflakes because of its high surface-area-to-volume ratio. The photoelectrochemical method for detection of UA was also studied. The sensitivity was increased 5 times after irradiation of 300 nm UV light. These results indicate that ZnS nanostructures are good candidate materials for developing enzyme-based UA biosensors. Full article
(This article belongs to the Section Biosensors)
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Open AccessArticle Denoising Algorithm for CFA Image Sensors Considering Inter-Channel Correlation
Sensors 2017, 17(6), 1236; doi:10.3390/s17061236
Received: 1 May 2017 / Revised: 25 May 2017 / Accepted: 26 May 2017 / Published: 28 May 2017
PDF Full-text (4817 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, a spatio-spectral-temporal filter considering an inter-channel correlation is proposed for the denoising of a color filter array (CFA) sequence acquired by CCD/CMOS image sensors. Owing to the alternating under-sampled grid of the CFA pattern, the inter-channel correlation must be considered
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In this paper, a spatio-spectral-temporal filter considering an inter-channel correlation is proposed for the denoising of a color filter array (CFA) sequence acquired by CCD/CMOS image sensors. Owing to the alternating under-sampled grid of the CFA pattern, the inter-channel correlation must be considered in the direct denoising process. The proposed filter is applied in the spatial, spectral, and temporal domain, considering the spatio-tempo-spectral correlation. First, nonlocal means (NLM) spatial filtering with patch-based difference (PBD) refinement is performed by considering both the intra-channel correlation and inter-channel correlation to overcome the spatial resolution degradation occurring with the alternating under-sampled pattern. Second, a motion-compensated temporal filter that employs inter-channel correlated motion estimation and compensation is proposed to remove the noise in the temporal domain. Then, a motion adaptive detection value controls the ratio of the spatial filter and the temporal filter. The denoised CFA sequence can thus be obtained without motion artifacts. Experimental results for both simulated and real CFA sequences are presented with visual and numerical comparisons to several state-of-the-art denoising methods combined with a demosaicing method. Experimental results confirmed that the proposed frameworks outperformed the other techniques in terms of the objective criteria and subjective visual perception in CFA sequences. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Generalized Chirp Scaling Combined with Baseband Azimuth Scaling Algorithm for Large Bandwidth Sliding Spotlight SAR Imaging
Sensors 2017, 17(6), 1237; doi:10.3390/s17061237
Received: 13 February 2017 / Revised: 16 May 2017 / Accepted: 26 May 2017 / Published: 29 May 2017
Cited by 1 | PDF Full-text (4416 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents an efficient and precise imaging algorithm for the large bandwidth sliding spotlight synthetic aperture radar (SAR). The existing sub-aperture processing method based on the baseband azimuth scaling (BAS) algorithm cannot cope with the high order phase coupling along the range
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This paper presents an efficient and precise imaging algorithm for the large bandwidth sliding spotlight synthetic aperture radar (SAR). The existing sub-aperture processing method based on the baseband azimuth scaling (BAS) algorithm cannot cope with the high order phase coupling along the range and azimuth dimensions. This coupling problem causes defocusing along the range and azimuth dimensions. This paper proposes a generalized chirp scaling (GCS)-BAS processing algorithm, which is based on the GCS algorithm. It successfully mitigates the deep focus along the range dimension of a sub-aperture of the large bandwidth sliding spotlight SAR, as well as high order phase coupling along the range and azimuth dimensions. Additionally, the azimuth focusing can be achieved by this azimuth scaling method. Simulation results demonstrate the ability of the GCS-BAS algorithm to process the large bandwidth sliding spotlight SAR data. It is proven that great improvements of the focus depth and imaging accuracy are obtained via the GCS-BAS algorithm. Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle Corrosivity Sensor for Exposed Pipelines Based on Wireless Energy Transfer
Sensors 2017, 17(6), 1238; doi:10.3390/s17061238
Received: 13 April 2017 / Revised: 22 May 2017 / Accepted: 25 May 2017 / Published: 30 May 2017
Cited by 1 | PDF Full-text (6511 KB) | HTML Full-text | XML Full-text
Abstract
External corrosion was identified as one of the main causes of pipeline failures worldwide. A solution that addresses the issue of detecting and quantifying corrosivity of environment for application to existing exposed pipelines has been developed. It consists of a sensing array made
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External corrosion was identified as one of the main causes of pipeline failures worldwide. A solution that addresses the issue of detecting and quantifying corrosivity of environment for application to existing exposed pipelines has been developed. It consists of a sensing array made of an assembly of thin strips of pipeline steel and a circuit that provides a visual sensor reading to the operator. The proposed sensor is passive and does not require a constant power supply. Circuit design was validated through simulations and lab experiments. Accelerated corrosion experiment was conducted to confirm the feasibility of the proposed corrosivity sensor design. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Multi-Site Simultaneous Time-Resolved Photometry with a Low Cost Electro-Optics System
Sensors 2017, 17(6), 1239; doi:10.3390/s17061239
Received: 22 February 2017 / Revised: 18 May 2017 / Accepted: 24 May 2017 / Published: 30 May 2017
PDF Full-text (2508 KB) | HTML Full-text | XML Full-text
Abstract
Sunlight reflected off of resident space objects can be used as an optical signal for astrometric orbit determination and for deducing geometric information about the object. With the increasing population of small satellites and debris in low Earth orbit, photometry is a powerful
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Sunlight reflected off of resident space objects can be used as an optical signal for astrometric orbit determination and for deducing geometric information about the object. With the increasing population of small satellites and debris in low Earth orbit, photometry is a powerful tool in operational support of space missions, whether for anomaly resolution or object identification. To accurately determine size, shape, spin rate, status of deployables, or attitude information of an unresolved resident space object, multi-hertz sample rate photometry is required to capture the relatively rapid changes in brightness that these objects can exhibit. OSCOM, which stands for Optical tracking and Spectral characterization of CubeSats for Operational Missions, is a low cost and portable telescope system capable of time-resolved small satellite photometry, and is field deployable on short notice for simultaneous observation from multiple sites. We present the electro-optical design principles behind OSCOM and light curves of the 1.5 U DICE-2 CubeSat and simultaneous observations of the main body of the ASTRO-H satellite after its fragmentation event. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Vital Sign Monitoring and Mobile Phone Usage Detection Using IR-UWB Radar for Intended Use in Car Crash Prevention
Sensors 2017, 17(6), 1240; doi:10.3390/s17061240
Received: 23 March 2017 / Revised: 20 May 2017 / Accepted: 25 May 2017 / Published: 30 May 2017
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Abstract
In order to avoid car crashes, active safety systems are becoming more and more important. Many crashes are caused due to driver drowsiness or mobile phone usage. Detecting the drowsiness of the driver is very important for the safety of a car. Monitoring
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In order to avoid car crashes, active safety systems are becoming more and more important. Many crashes are caused due to driver drowsiness or mobile phone usage. Detecting the drowsiness of the driver is very important for the safety of a car. Monitoring of vital signs such as respiration rate and heart rate is important to determine the occurrence of driver drowsiness. In this paper, robust vital signs monitoring through impulse radio ultra-wideband (IR-UWB) radar is discussed. We propose a new algorithm that can estimate the vital signs even if there is motion caused by the driving activities. We analyzed the whole fast time vital detection region and found the signals at those fast time locations that have useful information related to the vital signals. We segmented those signals into sub-signals and then constructed the desired vital signal using the correlation method. In this way, the vital signs of the driver can be monitored noninvasively, which can be used by researchers to detect the drowsiness of the driver which is related to the vital signs i.e., respiration and heart rate. In addition, texting on a mobile phone during driving may cause visual, manual or cognitive distraction of the driver. In order to reduce accidents caused by a distracted driver, we proposed an algorithm that can detect perfectly a driver's mobile phone usage even if there are various motions of the driver in the car or changes in background objects. These novel techniques, which monitor vital signs associated with drowsiness and detect phone usage before a driver makes a mistake, may be very helpful in developing techniques for preventing a car crash. Full article
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Open AccessArticle Using Color, Texture and Object-Based Image Analysis of Multi-Temporal Camera Data to Monitor Soil Aggregate Breakdown
Sensors 2017, 17(6), 1241; doi:10.3390/s17061241
Received: 23 March 2017 / Revised: 18 May 2017 / Accepted: 25 May 2017 / Published: 30 May 2017
PDF Full-text (12259 KB) | HTML Full-text | XML Full-text
Abstract
Remote sensing has shown its potential to assess soil properties and is a fast and non-destructive method for monitoring soil surface changes. In this paper, we monitor soil aggregate breakdown under natural conditions. From November 2014 to February 2015, images and weather data
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Remote sensing has shown its potential to assess soil properties and is a fast and non-destructive method for monitoring soil surface changes. In this paper, we monitor soil aggregate breakdown under natural conditions. From November 2014 to February 2015, images and weather data were collected on a daily basis from five soils susceptible to detachment (Silty Loam with various organic matter content, Loam and Sandy Loam). Three techniques that vary in image processing complexity and user interaction were tested for the ability of monitoring aggregate breakdown. Considering that the soil surface roughness causes shadow cast, the blue/red band ratio is utilized to observe the soil aggregate changes. Dealing with images with high spatial resolution, image texture entropy, which reflects the process of soil aggregate breakdown, is used. In addition, the Huang thresholding technique, which allows estimation of the image area occupied by soil aggregate, is performed. Our results show that all three techniques indicate soil aggregate breakdown over time. The shadow ratio shows a gradual change over time with no details related to weather conditions. Both the entropy and the Huang thresholding technique show variations of soil aggregate breakdown responding to weather conditions. Using data obtained with a regular camera, we found that freezing–thawing cycles are the cause of soil aggregate breakdown. Full article
(This article belongs to the Special Issue Precision Agriculture and Remote Sensing Data Fusion)
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Open AccessArticle Belief Interval of Dempster-Shafer Theory for Line-of-Sight Identification in Indoor Positioning Applications
Sensors 2017, 17(6), 1242; doi:10.3390/s17061242
Received: 8 March 2017 / Revised: 9 May 2017 / Accepted: 23 May 2017 / Published: 30 May 2017
PDF Full-text (5705 KB) | HTML Full-text | XML Full-text
Abstract
Location data are among the most widely used contextual data in context-aware and ubiquitous computing applications. Numerous systems with distinct deployment costs and levels of positioning accuracy have been developed over the past decade for indoor positioning purposes. The most useful method focuses
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Location data are among the most widely used contextual data in context-aware and ubiquitous computing applications. Numerous systems with distinct deployment costs and levels of positioning accuracy have been developed over the past decade for indoor positioning purposes. The most useful method focuses on the received signal strength (RSS) and provides a set of signal transmission access points. Furthermore, most positioning systems are based on non-line-of-sight (NLOS) rather than line-of-sight (LOS) conditions, and this cause ranging errors for location predictions. Hence, manually compiling a fingerprint database measuring RSS involves high costs and is thus impractical in online prediction environments. In our proposed method, a comparison method is derived on the basis of belief intervals, as proposed in Dempster-Shafer theory, and the signal features are characterized on the LOS and NLOS conditions for different field experiments. The system performance levels were examined with different features and under different environments through robust testing and by using several widely used machine learning methods. The results showed that the proposed method can not only retain positioning accuracy but also save computation time in location predictions. Full article
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Open AccessArticle Extraction of Rice Phenological Differences under Heavy Metal Stress Using EVI Time-Series from HJ-1A/B Data
Sensors 2017, 17(6), 1243; doi:10.3390/s17061243
Received: 1 April 2017 / Revised: 3 May 2017 / Accepted: 26 May 2017 / Published: 30 May 2017
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Abstract
An effective method to monitor heavy metal stress in crops is of critical importance to assure agricultural production and food security. Phenology, as a sensitive indicator of environmental change, can respond to heavy metal stress in crops and remote sensing is an effective
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An effective method to monitor heavy metal stress in crops is of critical importance to assure agricultural production and food security. Phenology, as a sensitive indicator of environmental change, can respond to heavy metal stress in crops and remote sensing is an effective method to detect plant phenological changes. This study focused on identifying the rice phenological differences under varied heavy metal stress using EVI (enhanced vegetation index) time-series, which was obtained from HJ-1A/B CCD images and fitted with asymmetric Gaussian model functions. We extracted three phenological periods using first derivative analysis: the tillering period, heading period, and maturation period; and constructed two kinds of metrics with phenological characteristics: date-intervals and time-integrated EVI, to explore the rice phenological differences under mild and severe stress levels. Results indicated that under severe stress the values of the metrics for presenting rice phenological differences in the experimental areas of heavy metal stress were smaller than the ones under mild stress. This finding represents a new method for monitoring heavy metal contamination through rice phenology. Full article
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Open AccessArticle The Lateral Tracking Control for the Intelligent Vehicle Based on Adaptive PID Neural Network
Sensors 2017, 17(6), 1244; doi:10.3390/s17061244
Received: 15 April 2017 / Revised: 19 May 2017 / Accepted: 19 May 2017 / Published: 30 May 2017
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Abstract
The intelligent vehicle is a complicated nonlinear system, and the design of a path tracking controller is one of the key technologies in intelligent vehicle research. This paper mainly designs a lateral control dynamic model of the intelligent vehicle, which is used for
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The intelligent vehicle is a complicated nonlinear system, and the design of a path tracking controller is one of the key technologies in intelligent vehicle research. This paper mainly designs a lateral control dynamic model of the intelligent vehicle, which is used for lateral tracking control. Firstly, the vehicle dynamics model (i.e., transfer function) is established according to the vehicle parameters. Secondly, according to the vehicle steering control system and the CARMA (Controlled Auto-Regression and Moving-Average) model, a second-order control system model is built. Using forgetting factor recursive least square estimation (FFRLS), the system parameters are identified. Finally, a neural network PID (Proportion Integral Derivative) controller is established for lateral path tracking control based on the vehicle model and the steering system model. Experimental simulation results show that the proposed model and algorithm have the high real-time and robustness in path tracing control. This provides a certain theoretical basis for intelligent vehicle autonomous navigation tracking control, and lays the foundation for the vertical and lateral coupling control. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle Smartphone-Based pH Sensor for Home Monitoring of Pulmonary Exacerbations in Cystic Fibrosis
Sensors 2017, 17(6), 1245; doi:10.3390/s17061245
Received: 10 April 2017 / Revised: 15 May 2017 / Accepted: 23 May 2017 / Published: 30 May 2017
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Abstract
Currently, Cystic Fibrosis (CF) patients lack the ability to track their lung health at home, relying instead on doctor checkups leading to delayed treatment and lung damage. By leveraging the ubiquity of the smartphone to lower costs and increase portability, a smartphone-based peripheral
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Currently, Cystic Fibrosis (CF) patients lack the ability to track their lung health at home, relying instead on doctor checkups leading to delayed treatment and lung damage. By leveraging the ubiquity of the smartphone to lower costs and increase portability, a smartphone-based peripheral pH measurement device was designed to attach directly to the headphone port to harvest power and communicate with a smartphone application. This platform was tested using prepared pH buffers and sputum samples from CF patients. The system matches within ~0.03 pH of a benchtop pH meter while fully powering itself and communicating with a Samsung Galaxy S3 smartphone paired with either a glass or Iridium Oxide (IrOx) electrode. The IrOx electrodes were found to have 25% higher sensitivity than the glass probes at the expense of larger drift and matrix sensitivity that can be addressed with proper calibration. The smartphone-based platform has been demonstrated as a portable replacement for laboratory pH meters, and supports both highly robust glass probes and the sensitive and miniature IrOx electrodes with calibration. This tool can enable more frequent pH sputum tracking for CF patients to help detect the onset of pulmonary exacerbation to provide timely and appropriate treatment before serious damage occurs. Full article
(This article belongs to the Special Issue Biomedical Sensors and Systems 2017)
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Open AccessArticle An Improved Compressive Sensing and Received Signal Strength-Based Target Localization Algorithm with Unknown Target Population for Wireless Local Area Networks
Sensors 2017, 17(6), 1246; doi:10.3390/s17061246
Received: 10 March 2017 / Revised: 18 May 2017 / Accepted: 22 May 2017 / Published: 30 May 2017
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Abstract
In this paper a two-phase compressive sensing (CS) and received signal strength (RSS)-based target localization approach is proposed to improve position accuracy by dealing with the unknown target population and the effect of grid dimensions on position error. In the coarse localization phase,
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In this paper a two-phase compressive sensing (CS) and received signal strength (RSS)-based target localization approach is proposed to improve position accuracy by dealing with the unknown target population and the effect of grid dimensions on position error. In the coarse localization phase, by formulating target localization as a sparse signal recovery problem, grids with recovery vector components greater than a threshold are chosen as the candidate target grids. In the fine localization phase, by partitioning each candidate grid, the target position in a grid is iteratively refined by using the minimum residual error rule and the least-squares technique. When all the candidate target grids are iteratively partitioned and the measurement matrix is updated, the recovery vector is re-estimated. Threshold-based detection is employed again to determine the target grids and hence the target population. As a consequence, both the target population and the position estimation accuracy can be significantly improved. Simulation results demonstrate that the proposed approach achieves the best accuracy among all the algorithms compared. Full article
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Open AccessArticle Frequency Domain Analysis of Sensor Data for Event Classification in Real-Time Robot Assisted Deburring
Sensors 2017, 17(6), 1247; doi:10.3390/s17061247
Received: 30 March 2017 / Revised: 17 May 2017 / Accepted: 26 May 2017 / Published: 30 May 2017
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Abstract
Process monitoring using indirect methods relies on the usage of sensors. Using sensors to acquire vital process related information also presents itself with the problem of big data management and analysis. Due to uncertainty in the frequency of events occurring, a higher sampling
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Process monitoring using indirect methods relies on the usage of sensors. Using sensors to acquire vital process related information also presents itself with the problem of big data management and analysis. Due to uncertainty in the frequency of events occurring, a higher sampling rate is often used in real-time monitoring applications to increase the chances of capturing and understanding all possible events related to the process. Advanced signal processing methods are used to further decipher meaningful information from the acquired data. In this research work, power spectrum density (PSD) of sensor data acquired at sampling rates between 40–51.2 kHz was calculated and the corelation between PSD and completed number of cycles/passes is presented. Here, the progress in number of cycles/passes is the event this research work intends to classify and the algorithm used to compute PSD is Welch’s estimate method. A comparison between Welch’s estimate method and statistical methods is also discussed. A clear co-relation was observed using Welch’s estimate to classify the number of cycles/passes. The paper also succeeds in classifying vibration signal generated by the spindle from the vibration signal acquired during finishing process. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessCommunication A Low-Cost System Based on Image Analysis for Monitoring the Crystal Growth Process
Sensors 2017, 17(6), 1248; doi:10.3390/s17061248
Received: 8 April 2017 / Revised: 8 May 2017 / Accepted: 19 May 2017 / Published: 31 May 2017
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Abstract
Many techniques are used to monitor one or more of the phenomena involved in the crystallization process. One of the challenges in crystal growth monitoring is finding techniques that allow direct interpretation of the data. The present study used a low-cost system, composed
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Many techniques are used to monitor one or more of the phenomena involved in the crystallization process. One of the challenges in crystal growth monitoring is finding techniques that allow direct interpretation of the data. The present study used a low-cost system, composed of a commercial webcam and a simple white LED (Light Emitting Diode) illuminator, to follow the calcium carbonate crystal growth process. The experiments were followed with focused beam reflectance measurement (FBRM), a common technique for obtaining information about the formation and growth of crystals. The images obtained in real time were treated with the red, blue, and green (RGB) system. The results showed a qualitative response of the system to crystal formation and growth processes, as there was an observed decrease in the signal as the growth process occurred. Control of the crystal growth was managed by increasing the viscosity of the test solution with the addition of monoethylene glycol (MEG) at 30% and 70% in a mass to mass relationship, providing different profiles of the RGB average curves. The decrease in the average RGB value became slower as the concentration of MEG was increased; this reflected a lag in the growth process that was proven by the FBRM. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Enhanced Flexibility and Reusability through State Machine-Based Architectures for Multisensor Intelligent Robotics
Sensors 2017, 17(6), 1249; doi:10.3390/s17061249
Received: 1 March 2017 / Revised: 23 May 2017 / Accepted: 23 May 2017 / Published: 31 May 2017
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Abstract
This paper presents a state machine-based architecture, which enhances the flexibility and reusability of industrial robots, more concretely dual-arm multisensor robots. The proposed architecture, in addition to allowing absolute control of the execution, eases the programming of new applications by increasing the reusability
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This paper presents a state machine-based architecture, which enhances the flexibility and reusability of industrial robots, more concretely dual-arm multisensor robots. The proposed architecture, in addition to allowing absolute control of the execution, eases the programming of new applications by increasing the reusability of the developed modules. Through an easy-to-use graphical user interface, operators are able to create, modify, reuse and maintain industrial processes, increasing the flexibility of the cell. Moreover, the proposed approach is applied in a real use case in order to demonstrate its capabilities and feasibility in industrial environments. A comparative analysis is presented for evaluating the presented approach versus traditional robot programming techniques. Full article
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Spain 2017)
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Open AccessArticle Electromagnetic Field Assessment as a Smart City Service: The SmartSantander Use-Case
Sensors 2017, 17(6), 1250; doi:10.3390/s17061250
Received: 3 April 2017 / Revised: 17 May 2017 / Accepted: 24 May 2017 / Published: 31 May 2017
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Abstract
Despite the increasing presence of wireless communications in everyday life, there exist some voices raising concerns about their adverse effects. One particularly relevant example is the potential impact of the electromagnetic field they induce on the population’s health. Traditionally, very specialized methods and
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Despite the increasing presence of wireless communications in everyday life, there exist some voices raising concerns about their adverse effects. One particularly relevant example is the potential impact of the electromagnetic field they induce on the population’s health. Traditionally, very specialized methods and devices (dosimetry) have been used to assess the strength of the E-field, with the main objective of checking whether it respects the corresponding regulations. In this paper, we propose a complete novel approach, which exploits the functionality leveraged by a smart city platform. We deploy a number of measuring probes, integrated as sensing devices, to carry out a characterization embracing large areas, as well as long periods of time. This unique platform has been active for more than one year, generating a vast amount of information. We process such information, and the obtained results validate the whole methodology. In addition, we discuss the variation of the E-field caused by cellular networks, considering additional information, such as usage statistics. Finally, we establish the exposure that can be attributed to the base stations within the scenario under analysis. Full article
(This article belongs to the Special Issue Next Generation Wireless Technologies for Internet of Things)
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Open AccessArticle Distributed Piezoelectric Sensor System for Damage Identification in Structures Subjected to Temperature Changes
Sensors 2017, 17(6), 1252; doi:10.3390/s17061252
Received: 24 April 2017 / Revised: 25 May 2017 / Accepted: 26 May 2017 / Published: 31 May 2017
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Abstract
Structural health monitoring (SHM) is a very important area in a wide spectrum of fields and engineering applications. With an SHM system, it is possible to reduce the number of non-necessary inspection tasks, the associated risk and the maintenance cost in a wide
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Structural health monitoring (SHM) is a very important area in a wide spectrum of fields and engineering applications. With an SHM system, it is possible to reduce the number of non-necessary inspection tasks, the associated risk and the maintenance cost in a wide range of structures during their lifetime. One of the problems in the detection and classification of damage are the constant changes in the operational and environmental conditions. Small changes of these conditions can be considered by the SHM system as damage even though the structure is healthy. Several applications for monitoring of structures have been developed and reported in the literature, and some of them include temperature compensation techniques. In real applications, however, digital processing technologies have proven their value by: (i) offering a very interesting way to acquire information from the structures under test; (ii) applying methodologies to provide a robust analysis; and (iii) performing a damage identification with a practical useful accuracy. This work shows the implementation of an SHM system based on the use of piezoelectric (PZT) sensors for inspecting a structure subjected to temperature changes. The methodology includes the use of multivariate analysis, sensor data fusion and machine learning approaches. The methodology is tested and evaluated with aluminum and composite structures that are subjected to temperature variations. Results show that damage can be detected and classified in all of the cases in spite of the temperature changes. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle A Point Temperature Sensor Based on Upconversion Emission in Er3+/Yb3+ Codoped Tellurite-Zinc-Niobium Glass
Sensors 2017, 17(6), 1253; doi:10.3390/s17061253
Received: 9 April 2017 / Revised: 17 May 2017 / Accepted: 22 May 2017 / Published: 31 May 2017
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Abstract
Er3+/Yb3+ codoped tellurite-zinc-niobium (TZNb) glass was prepared by the melt-quenching method and used for the construction of a point all-fiber temperature sensor. The glass thermal stability and network structural properties were studied by differential thermal analysis and Raman spectrum, respectively.
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Er3+/Yb3+ codoped tellurite-zinc-niobium (TZNb) glass was prepared by the melt-quenching method and used for the construction of a point all-fiber temperature sensor. The glass thermal stability and network structural properties were studied by differential thermal analysis and Raman spectrum, respectively. High glass transition temperature is beneficial to widen the working temperature range. The dependence of fluorescence intensity ratio (FIR) of green upconversion emissions on the surrounding temperature from 276 to 363 K was experimentally investigated and the maximum temperature sensitivity is 95 × 10−4 K−1 at 363 K. Strong green upconversion emission, broad temperature measurement range and high sensitivity indicate this point temperature sensor is a promising optical device for application on optical temperature sensing. Full article
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Open AccessArticle Adaptive Estimation of Multiple Fading Factors for GPS/INS Integrated Navigation Systems
Sensors 2017, 17(6), 1254; doi:10.3390/s17061254
Received: 12 April 2017 / Revised: 25 May 2017 / Accepted: 27 May 2017 / Published: 1 June 2017
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Abstract
The Kalman filter has been widely applied in the field of dynamic navigation and positioning. However, its performance will be degraded in the presence of significant model errors and uncertain interferences. In the literature, the fading filter was proposed to control the influences
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The Kalman filter has been widely applied in the field of dynamic navigation and positioning. However, its performance will be degraded in the presence of significant model errors and uncertain interferences. In the literature, the fading filter was proposed to control the influences of the model errors, and the H-infinity filter can be adopted to address the uncertainties by minimizing the estimation error in the worst case. In this paper, a new multiple fading factor, suitable for the Global Positioning System (GPS) and the Inertial Navigation System (INS) integrated navigation system, is proposed based on the optimization of the filter, and a comprehensive filtering algorithm is constructed by integrating the advantages of the H-infinity filter and the proposed multiple fading filter. Measurement data of the GPS/INS integrated navigation system are collected under actual conditions. Stability and robustness of the proposed filtering algorithm are tested with various experiments and contrastive analysis are performed with the measurement data. Results demonstrate that both the filter divergence and the influences of outliers are restrained effectively with the proposed filtering algorithm, and precision of the filtering results are improved simultaneously. Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle Nanoporous Gold Films Prepared by a Combination of Sputtering and Dealloying for Trace Detection of Benzo[a]pyrene Based on Surface Plasmon Resonance Spectroscopy
Sensors 2017, 17(6), 1255; doi:10.3390/s17061255
Received: 8 April 2017 / Revised: 8 May 2017 / Accepted: 26 May 2017 / Published: 1 June 2017
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Abstract
A wavelength-interrogated surface plasmon resonance (SPR) sensor based on a nanoporous gold (NPG) film has been fabricated for the sensitive detection of trace quantities of benzo[a]pyrene (BaP) in water. The large-area uniform NPG film was prepared by a two-step process that includes sputtering
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A wavelength-interrogated surface plasmon resonance (SPR) sensor based on a nanoporous gold (NPG) film has been fabricated for the sensitive detection of trace quantities of benzo[a]pyrene (BaP) in water. The large-area uniform NPG film was prepared by a two-step process that includes sputtering deposition of a 60-nm-thick AuAg alloy film on a glass substrate and chemical dealloying of the alloy film in nitric acid. For SPR sensor applications, the NPG film plays the dual roles of analyte enrichment and supporting surface plasmon waves, which leads to sensitivity enhancement. In this work, the as-prepared NPG film was first modified with 1-dodecanethiol molecules to make the film hydrophobic so as to improve BaP enrichment from water via hydrophobic interactions. The SPR sensor with the hydrophobic NPG film enables one to detect BaP at concentrations as low as 1 nmol·L−1. In response to this concentration of BaP the sensor produced a resonance-wavelength shift of ΔλR = 2.22 nm. After the NPG film was functionalized with mouse monoclonal IgG1 that is the antibody against BaP, the sensor’s sensitivity was further improved and the BaP detection limit decreased further down to 5 pmol·L−1 (the corresponding ΔλR = 1.77 nm). In contrast, the conventional SPR sensor with an antibody-functionalized dense gold film can give a response of merely ΔλR = 0.9 nm for 100 pmol·L−1 BaP. Full article
(This article belongs to the Special Issue Surface Plasmon Resonance Sensing)
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