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Sensors, Volume 18, Issue 7 (July 2018)

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Cover Story (view full-size image) Radon is a noble gas originated from the radioactive decay chain of uranium or thorium. It emanates [...] Read more.
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Open AccessArticle Cellular Simulation for Distributed Sensing over Complex Terrains
Sensors 2018, 18(7), 2323; https://doi.org/10.3390/s18072323 (registering DOI)
Received: 15 June 2018 / Revised: 11 July 2018 / Accepted: 13 July 2018 / Published: 17 July 2018
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Abstract
Long-range radio transmissions open new sensor application fields, in particular for environment monitoring. For example, the LoRa radio protocol enables connecting remote sensors at a distance as long as ten kilometers in a line-of-sight. However, the large area covered also brings several difficulties,
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Long-range radio transmissions open new sensor application fields, in particular for environment monitoring. For example, the LoRa radio protocol enables connecting remote sensors at a distance as long as ten kilometers in a line-of-sight. However, the large area covered also brings several difficulties, such as the placement of sensing devices in regards to topology in geography, or the variability of communication latency. Sensing the environment also carries constraints related to the interest of sensing points in relation to a physical phenomenon. Thus, criteria for designs are evolving a lot from the existing methods, especially in complex terrains. This article describes simulation techniques based on geography analysis to compute long-range radio coverages and radio characteristics in these situations. As radio propagation is just a particular case of physical phenomena, it is shown how a unified approach also allows for characterizing the behavior of potential physical risks. The case of heavy rainfall and flooding is investigated. Geography analysis is achieved using segmentation tools to produce cellular systems which are in turn translated into code for high-performance computations. The paper provides results from practical complex terrain experiments using LoRa, which confirm the accuracy of the simulation, and scheduling characteristics for sample networks. Performance tables are produced for these simulations on current Graphics Processing Units (GPUs). Full article
(This article belongs to the Special Issue Dependable Monitoring in Wireless Sensor Networks)
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Open AccessArticle Levenberg-Marquardt Neural Network Algorithm for Degree of Arteriovenous Fistula Stenosis Classification Using a Dual Optical Photoplethysmography Sensor
Sensors 2018, 18(7), 2322; https://doi.org/10.3390/s18072322 (registering DOI)
Received: 5 June 2018 / Revised: 10 July 2018 / Accepted: 12 July 2018 / Published: 17 July 2018
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Abstract
This paper proposes a noninvasive dual optical photoplethysmography (PPG) sensor to classify the degree of arteriovenous fistula (AVF) stenosis in hemodialysis (HD) patients. Dual PPG measurement node (DPMN) becomes the primary tool in this work for detecting abnormal narrowing vessel simultaneously in multi-beds
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This paper proposes a noninvasive dual optical photoplethysmography (PPG) sensor to classify the degree of arteriovenous fistula (AVF) stenosis in hemodialysis (HD) patients. Dual PPG measurement node (DPMN) becomes the primary tool in this work for detecting abnormal narrowing vessel simultaneously in multi-beds monitoring patients. The mean and variance of Rising Slope (RS) and Falling Slope (FS) values between before and after HD treatment was used as the major features to classify AVF stenosis. Multilayer perceptron neural networks (MLPN) training algorithms are implemented for this analysis, which are the Levenberg-Marquardt, Scaled Conjugate Gradient, and Resilient Back-propagation, to identify the degree of HD patient stenosis. Eleven patients were recruited with mean age of 77 ± 10.8 years for analysis. The experimental results indicated that the variance of RS in the HD hand between before and after treatment was significant difference statistically to stenosis (p < 0.05). Levenberg-Marquardt algorithm (LMA) was significantly outperforms the other training algorithm. The classification accuracy and precision reached 94.82% and 92.22% respectively, thus this technique has a potential contribution to the early identification of stenosis for a medical diagnostic support system. Full article
(This article belongs to the Special Issue Selected Papers from IEEE ICASI 2018)
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Open AccessArticle Experimental Evaluation on Depth Control Using Improved Model Predictive Control for Autonomous Underwater Vehicle (AUVs)
Sensors 2018, 18(7), 2321; https://doi.org/10.3390/s18072321 (registering DOI)
Received: 3 May 2018 / Revised: 11 July 2018 / Accepted: 16 July 2018 / Published: 17 July 2018
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Abstract
Due to the growing interest using model predictive control (MPC), there are more and more researches about the applications of MPC on autonomous underwater vehicle (AUV), and these researches are mainly focused on simulation and simple application of MPC on AUV. This paper
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Due to the growing interest using model predictive control (MPC), there are more and more researches about the applications of MPC on autonomous underwater vehicle (AUV), and these researches are mainly focused on simulation and simple application of MPC on AUV. This paper focuses on the improvement of MPC based on the state space model of an AUV. Unlike the previous approaches using a fixed weighting matrix, in this paper, a coefficient, varied with the error, is introduced to adjust the control increment vector weighting matrix to reduce the settling time. Then, an analysis on the effect of the adjustment to the stability is given. In addition, there is always a lag between the AUV real trajectory and the desired trajectory when the AUV tracks a continuous trajectory. To solve this problem, a simple re-planning of the desired trajectory is developed. Specifically, the point certain steps ahead from current time on the desired trajectory is treated as the current desired point and input to the controller. Finally, experimental results for depth control are given to demonstrate the feasibility and effectiveness of the improved MPC. Experimental results show that the method of real-time adjusting control increment weighting matrix can reduce settling time by about 2 s when tracking step trajectory of 1 m, and the simple re-planning of the desired trajectory method can reduce the average of absolute error by about 15% and standard deviation of error by about 17%. Full article
(This article belongs to the Section Remote Sensors)
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Open AccessArticle Dissimilarity Metric Based on Local Neighboring Information and Genetic Programming for Data Dissemination in Vehicular Ad Hoc Networks (VANETs)
Sensors 2018, 18(7), 2320; https://doi.org/10.3390/s18072320 (registering DOI)
Received: 6 June 2018 / Revised: 10 July 2018 / Accepted: 12 July 2018 / Published: 17 July 2018
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Abstract
This paper presents a novel dissimilarity metric based on local neighboring information and a genetic programming approach for efficient data dissemination in Vehicular Ad Hoc Networks (VANETs). The primary aim of the dissimilarity metric is to replace the Euclidean distance in probabilistic data
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This paper presents a novel dissimilarity metric based on local neighboring information and a genetic programming approach for efficient data dissemination in Vehicular Ad Hoc Networks (VANETs). The primary aim of the dissimilarity metric is to replace the Euclidean distance in probabilistic data dissemination schemes, which use the relative Euclidean distance among vehicles to determine the retransmission probability. The novel dissimilarity metric is obtained by applying a metaheuristic genetic programming approach, which provides a formula that maximizes the Pearson Correlation Coefficient between the novel dissimilarity metric and the Euclidean metric in several representative VANET scenarios. Findings show that the obtained dissimilarity metric correlates with the Euclidean distance up to 8.9% better than classical dissimilarity metrics. Moreover, the obtained dissimilarity metric is evaluated when used in well-known data dissemination schemes, such as p-persistence, polynomial and irresponsible algorithm. The obtained dissimilarity metric achieves significant improvements in terms of reachability in comparison with the classical dissimilarity metrics and the Euclidean metric-based schemes in the studied VANET urban scenarios. Full article
(This article belongs to the Section Sensor Networks)
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Open AccessArticle Optical Strain Measurement with Step-Index Polymer Optical Fiber Based on the Phase Measurement of an Intensity-Modulated Signal
Sensors 2018, 18(7), 2319; https://doi.org/10.3390/s18072319 (registering DOI)
Received: 20 June 2018 / Revised: 11 July 2018 / Accepted: 13 July 2018 / Published: 17 July 2018
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Abstract
Polymer optical fibers (POFs) have been proposed for optical strain sensors due to their large elastic strain range compared to glass optical fibers (GOFs). The phase response of a single-mode polymer optical fiber (SM-POF) is well-known in the literature, and depends on the
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Polymer optical fibers (POFs) have been proposed for optical strain sensors due to their large elastic strain range compared to glass optical fibers (GOFs). The phase response of a single-mode polymer optical fiber (SM-POF) is well-known in the literature, and depends on the physical deformation of the fiber as well as the impact on the refractive index of the core. In this paper, we investigate the impact of strain on a step-index polymer optical fiber (SI-POF). In particular, we discuss the responsivity of an optical strain sensor which is based on the phase measurement of an intensity-modulated signal. In comparison to the phase response of an SM-POF, we must take additional influences into account. Firstly, the SI-POF is a multi-mode fiber (MMF). Consequently, we not only consider the strain dependence of the refractive index, but also its dependency on the propagation angle θz. Second, we investigate the phase of an intensity-modulated signal. The development of this modulation phase along the fiber is influenced by modal dispersion, scattering, and attenuation. The modulation phase therefore has no linear dependency on the length of the fiber, even in the unstrained state. For the proper consideration of these effects, we rely on a novel model for step-index multi-mode fibers (SI-MMFs). We expand the model to consider the strain-induced effects, simulate the strain responsivity of the sensor, and compare it to experimental results. This led to the conclusion that the scattering behavior of a SI-POF is strain-dependent, which was further proven by measuring the far field at the end of a SI-POF under different strain conditions. Full article
(This article belongs to the Special Issue Optical Waveguide Based Sensors)
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Open AccessArticle An Ultrahigh Sensitivity Acetone Sensor Enhanced by Light Illumination
Sensors 2018, 18(7), 2318; https://doi.org/10.3390/s18072318 (registering DOI)
Received: 22 June 2018 / Revised: 13 July 2018 / Accepted: 15 July 2018 / Published: 17 July 2018
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Abstract
Au:SmFe0.9Zn0.1O3 is synthesized by a sol-gel method and annealed at 750 °C. Through XRD, SEM and XPS analysis methods, the microstructure of the material has been observed. The average particle size is about 50 nm. The sensor shows
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Au:SmFe0.9Zn0.1O3 is synthesized by a sol-gel method and annealed at 750 °C. Through XRD, SEM and XPS analysis methods, the microstructure of the material has been observed. The average particle size is about 50 nm. The sensor shows a high sensitivity toward acetone vapor. As the relative humidity increases, the resistance and sensitivity of the sensor decline. To obtain a low optimum operating temperature, light illumination with different wavelengths has been introduced. The sensitivity toward acetone is improved at lower operating temperature when the sensor is irradiated by light. The smaller the wavelengths, the better the sensitivity of the sensor. Compared with other gases, the sensor shows excellent selectivity to acetone vapor, with better sensitivity, selectivity and stability when under light illumination. Full article
(This article belongs to the Section Chemical Sensors)
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Open AccessArticle Development of Wheel Pressure Control Algorithm for Electronic Stability Control (ESC) System of Commercial Trucks
Sensors 2018, 18(7), 2317; https://doi.org/10.3390/s18072317 (registering DOI)
Received: 14 May 2018 / Revised: 27 June 2018 / Accepted: 12 July 2018 / Published: 17 July 2018
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Abstract
This paper presents a wheel cylinder pressure control algorithm for application to the vehicle electronic stability control (ESC) systems for commercial trucks. An ESC system is an active system that improves the driving stability by distributing the appropriate braking pressure to each wheel,
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This paper presents a wheel cylinder pressure control algorithm for application to the vehicle electronic stability control (ESC) systems for commercial trucks. An ESC system is an active system that improves the driving stability by distributing the appropriate braking pressure to each wheel, which is an essential system for safe driving. It is important that the ESC system, through proper braking pressure supply, delivers the correct pressure under control. However, to reduce the cost involved, commercial trucks use a solenoid valve of the on/off-type, rather than a proportional valve that has good pressure control capability. The performance of a proposed wheel pressure control system based on an on/off solenoid valve control was verified by means of experiments conducted using the wheel pressure control algorithm presented in this paper. Full article
(This article belongs to the Special Issue Mechatronic Systems for Automatic Vehicles)
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Open AccessArticle Health Management Decision of Sensor System Based on Health Reliability Degree and Grey Group Decision-Making
Sensors 2018, 18(7), 2316; https://doi.org/10.3390/s18072316 (registering DOI)
Received: 10 June 2018 / Revised: 6 July 2018 / Accepted: 10 July 2018 / Published: 17 July 2018
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Abstract
Metal Oxide Semiconductor (MOS) gas sensor has been widely used in sensor systems for the advantages of fast response, high sensitivity, low cost, and so on. But, limited to the properties of materials, the phenomenon, such as aging, poisoning, and damage of the
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Metal Oxide Semiconductor (MOS) gas sensor has been widely used in sensor systems for the advantages of fast response, high sensitivity, low cost, and so on. But, limited to the properties of materials, the phenomenon, such as aging, poisoning, and damage of the gas sensitive material will affect the measurement quality of MOS gas sensor array. To ensure the stability of the system, a health management decision strategy for the prognostics and health management (PHM) of a sensor system that is based on health reliability degree (HRD) and grey group decision-making (GGD) is proposed in this paper. The health management decision-making model is presented to choose the best health management strategy. Specially, GGD is utilized to provide health management suggestions for the sensor system. To evaluate the status of the sensor system, a joint HRD-GGD framework is declared as the health management decision-making. In this method, HRD of sensor system is obtained by fusing the output data of each sensor. The optimal decision-making recommendations for health management of the system is proposed by combining historical health reliability degree, maintenance probability, and overhaul rate. Experimental results on four different kinds of health levels demonstrate that the HRD-GGD method outperforms other methods in decision-making accuracy of sensor system. Particularly, the proposed HRD-GGD decision-making method achieves the best decision accuracy of 98.25%. Full article
(This article belongs to the collection Multi-Sensor Information Fusion)
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Open AccessArticle Sensitivity-Improved Ultrasonic Sensor for 3D Imaging of Seismic Physical Model Using a Compact Microcavity
Sensors 2018, 18(7), 2315; https://doi.org/10.3390/s18072315 (registering DOI)
Received: 12 May 2018 / Revised: 19 June 2018 / Accepted: 13 July 2018 / Published: 17 July 2018
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Abstract
A sensitivity-improved ultrasonic sensor is proposed and demonstrated experimentally in this present study. The device is comprised only a fiber-optic microcavity that is formed by discharging a short section of hollow core fiber (HCF). The key to ensuring the success of the sensor
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A sensitivity-improved ultrasonic sensor is proposed and demonstrated experimentally in this present study. The device is comprised only a fiber-optic microcavity that is formed by discharging a short section of hollow core fiber (HCF). The key to ensuring the success of the sensor relies on the preprocessing of hydrogen loading for HCF. When discharging the HCF, the hydrogen is heated up during the formation of the air bubble, which enlarges the bubble diameter, smoothens its surfaces simultaneously and decreases Young’s modulus of the material of the bubble. Ultimately, this results in the probe being highly sensitive to ultrasound with a SNR of 69.28 dB. Once the compact air cavity is formed between the end face of the leading-in fiber and the top wall of the bubble, a well-defined interference spectrum is achieved based on the Fabry–Perot interference. By using spectral side-band filtering technology, we detect the ultrasonic waves reflected by the seismic physical model (SMF) and then reconstruct its three-dimensional image. Full article
(This article belongs to the Special Issue Ultrasonic Sensors 2018)
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Open AccessArticle Accelerating the K-Nearest Neighbors Filtering Algorithm to Optimize the Real-Time Classification of Human Brain Tumor in Hyperspectral Images
Sensors 2018, 18(7), 2314; https://doi.org/10.3390/s18072314 (registering DOI)
Received: 18 June 2018 / Revised: 12 July 2018 / Accepted: 15 July 2018 / Published: 17 July 2018
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Abstract
The use of hyperspectral imaging (HSI) in the medical field is an emerging approach to assist physicians in diagnostic or surgical guidance tasks. However, HSI data processing involves very high computational requirements due to the huge amount of information captured by the sensors.
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The use of hyperspectral imaging (HSI) in the medical field is an emerging approach to assist physicians in diagnostic or surgical guidance tasks. However, HSI data processing involves very high computational requirements due to the huge amount of information captured by the sensors. One of the stages with higher computational load is the K-Nearest Neighbors (KNN) filtering algorithm. The main goal of this study is to optimize and parallelize the KNN algorithm by exploiting the GPU technology to obtain real-time processing during brain cancer surgical procedures. This parallel version of the KNN performs the neighbor filtering of a classification map (obtained from a supervised classifier), evaluating the different classes simultaneously. The undertaken optimizations and the computational capabilities of the GPU device throw a speedup up to 66.18× when compared to a sequential implementation. Full article
(This article belongs to the Special Issue Sensors Signal Processing and Visual Computing)
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Open AccessArticle Fast Visual Odometry for a Low-Cost Underwater Embedded Stereo System
Sensors 2018, 18(7), 2313; https://doi.org/10.3390/s18072313 (registering DOI)
Received: 21 June 2018 / Revised: 10 July 2018 / Accepted: 14 July 2018 / Published: 17 July 2018
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Abstract
This paper provides details of hardware and software conception and realization of a stereo embedded system for underwater imaging. The system provides several functions that facilitate underwater surveys and run smoothly in real-time. A first post-image acquisition module provides direct visual feedback on
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This paper provides details of hardware and software conception and realization of a stereo embedded system for underwater imaging. The system provides several functions that facilitate underwater surveys and run smoothly in real-time. A first post-image acquisition module provides direct visual feedback on the quality of the taken images which helps appropriate actions to be taken regarding movement speed and lighting conditions. Our main contribution is a light visual odometry method adapted to the underwater context. The proposed method uses the captured stereo image stream to provide real-time navigation and a site coverage map which is necessary to conduct a complete underwater survey. The visual odometry uses a stochastic pose representation and semi-global optimization approach to handle large sites and provides long-term autonomy, whereas a novel stereo matching approach adapted to underwater imaging and system attached lighting allows fast processing and suitability to low computational resource systems. The system is tested in a real context and shows its robustness and promising future potential. Full article
(This article belongs to the Special Issue Visual Sensors)
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Open AccessArticle Amplitude-Based Filtering for Video Magnification in Presence of Large Motion
Sensors 2018, 18(7), 2312; https://doi.org/10.3390/s18072312 (registering DOI)
Received: 7 June 2018 / Revised: 5 July 2018 / Accepted: 11 July 2018 / Published: 17 July 2018
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Abstract
Video magnification reveals important and informative subtle variations in the world. These signals are often combined with large motions which result in significant blurring artifacts and haloes when conventional video magnification approaches are used. To counter these issues, this paper presents an amplitude-based
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Video magnification reveals important and informative subtle variations in the world. These signals are often combined with large motions which result in significant blurring artifacts and haloes when conventional video magnification approaches are used. To counter these issues, this paper presents an amplitude-based filtering algorithm that can magnify small changes in video in presence of large motions. We seek to understand the amplitude characteristic of small changes and large motions with the goal of extracting accurate signals for visualization. Based on spectrum amplitude filtering, the large motions can be removed while small changes can still be magnified by Eulerian approach. An advantage of this algorithm is that it can handle large motions, whether they are linear or nonlinear. Our experimental results show that the proposed method can amplify subtle variations in the presence of large motion, as well as significantly reduce artifacts. We demonstrate the presented algorithm by comparing to the state-of-the-art and provide subjective and objective evidence for the proposed method. Full article
(This article belongs to the Special Issue Sensors Signal Processing and Visual Computing)
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Open AccessArticle Experimental Verification of the Pumping Effect Caused by the Micro-Tapered Hole in a Piezoelectric Atomizer
Sensors 2018, 18(7), 2311; https://doi.org/10.3390/s18072311 (registering DOI)
Received: 20 June 2018 / Revised: 11 July 2018 / Accepted: 15 July 2018 / Published: 17 July 2018
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Abstract
In this study, we examined the use of a dynamic micro-tapered hole as a micro-scale tapered flow tube valveless piezoelectric pump. Firstly, we obtained photographs of a micro-tapered hole by using an environmental scanning electron microscope (ESEM). Then, we explained the pump effect
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In this study, we examined the use of a dynamic micro-tapered hole as a micro-scale tapered flow tube valveless piezoelectric pump. Firstly, we obtained photographs of a micro-tapered hole by using an environmental scanning electron microscope (ESEM). Then, we explained the pump effect of the micro-tapered hole, and derived the atomization rate equation. Furthermore, we reported an atomization rate measurement experiment that eliminated the atomization caused by a pressure increase, and demonstrated that a change in the volume of a micro-tapered hole could produce atomization. The experimental results indicate that, under the same voltage, the forward atomization rate is much higher than the reverse atomization rate and that the atomization rate increases with the micro-tapered hole volume. The experimental results show that the atomization of the micro-tapered aperture atomizer is caused by its pumping effect. Moreover, the flow resistance and volume of the micro-tapered hole can affect the atomization rate. Full article
(This article belongs to the Special Issue Recent Advances of Piezoelectric Transducers and Applications)
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Open AccessArticle A Smart Sensing Architecture for Domestic Monitoring: Methodological Approach and Experimental Validation
Sensors 2018, 18(7), 2310; https://doi.org/10.3390/s18072310 (registering DOI)
Received: 5 June 2018 / Revised: 13 July 2018 / Accepted: 14 July 2018 / Published: 17 July 2018
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Abstract
Smart homes play a strategic role for improving life quality of people, enabling to monitor people at home with numerous intelligent devices. Sensors can be installed to provide a continuous assistance without limiting the resident’s daily routine, giving her/him greater comfort, well-being and
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Smart homes play a strategic role for improving life quality of people, enabling to monitor people at home with numerous intelligent devices. Sensors can be installed to provide a continuous assistance without limiting the resident’s daily routine, giving her/him greater comfort, well-being and safety. This paper is based on the development of domestic technological solutions to improve the life quality of citizens and monitor the users and the domestic environment, based on features extracted from the collected data. The proposed smart sensing architecture is based on an integrated sensor network to monitor the user and the environment to derive information about the user’s behavior and her/his health status. The proposed platform includes biomedical, wearable, and unobtrusive sensors for monitoring user’s physiological parameters and home automation sensors to obtain information about her/his environment. The sensor network stores the heterogeneous data both locally and remotely in Cloud, where machine learning algorithms and data mining strategies are used for user behavior identification, classification of user health conditions, classification of the smart home profile, and data analytics to implement services for the community. The proposed solution has been experimentally tested in a pilot study based on the development of both sensors and services for elderly users at home. Full article
(This article belongs to the Special Issue Smart Homes)
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Open AccessArticle Gold Nanocage-Based Electrochemical Sensing Platform for Sensitive Detection of Luteolin
Sensors 2018, 18(7), 2309; https://doi.org/10.3390/s18072309 (registering DOI)
Received: 2 June 2018 / Revised: 7 July 2018 / Accepted: 7 July 2018 / Published: 17 July 2018
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Abstract
A simple and sensitive electrochemical sensor was developed for the detection of tracelevels of luteolin. The sensoris based on a novel type of chemically modified electrode: gold nanocage (AuNCs)-modified carbon ionic liquid electrode (CILE). To construct this electrochemical sensing platform for luteolin, CILE
[...] Read more.
A simple and sensitive electrochemical sensor was developed for the detection of tracelevels of luteolin. The sensoris based on a novel type of chemically modified electrode: gold nanocage (AuNCs)-modified carbon ionic liquid electrode (CILE). To construct this electrochemical sensing platform for luteolin, CILE is initially prepared by using 1-hexylpyridinium hexafluorophosphate as the binder and then AuNCs are coated on the surface of CILE to fabricate AuNCs-modified CILE (AuNCs/CILE). Electrochemical studies have shown that AuNCs/CILE can exhibit enhanced electrocatalytic activity toward the redox reaction of luteolin, therefore, the redox peak current of luteolin can be greatly improved, resulting in the high sensitivity of the developed sensor. Under the optimal conditions, the oxidation peak currents of the sensor increase linearly with an increase in the luteolin concentration in a range from 1 to 1000 nM with a detection limit of 0.4 nM, which is lower than those of most reported electrochemical luteolin sensors. Moreover, the reproducibility, precision, selectivity, and stability of this sensor are excellent. Finally, the sensing system was applied to the analysis of luteolin-spiked drug samples and the recovery in all cases was 95.0–96.7%, indicating the potential application of this simple, facile, and sensitive sensing system in pharmaceutical analysis. Full article
(This article belongs to the Section Chemical Sensors)
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