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Sensors, Volume 16, Issue 1 (January 2016)

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Open AccessArticle
A Novel Pedestrian Navigation Algorithm for a Foot-Mounted Inertial-Sensor-Based System
Sensors 2016, 16(1), 139; https://doi.org/10.3390/s16010139
Received: 8 October 2015 / Revised: 7 January 2016 / Accepted: 18 January 2016 / Published: 21 January 2016
Cited by 30 | Viewed by 2256 | PDF Full-text (3718 KB) | HTML Full-text | XML Full-text
Abstract
This paper proposes a novel zero velocity update (ZUPT) method for a foot-mounted pedestrian navigation system (PNS). First, the error model of the PNS is developed and a Kalman filter is built based on the error model. Second, a novel zero velocity detection [...] Read more.
This paper proposes a novel zero velocity update (ZUPT) method for a foot-mounted pedestrian navigation system (PNS). First, the error model of the PNS is developed and a Kalman filter is built based on the error model. Second, a novel zero velocity detection algorithm based on the variations in speed over a gait cycle is proposed. A finite state machine including three states is employed to model a gait cycle. The state transition conditions are determined based on speed using a sliding window. Third, the ZUPT software flow is illustrated and described. Finally, the performances of the proposed method and other methods are examined and compared experimentally. The experimental results show that the mean relative accuracy of the proposed method is 0.89% under various motion modes. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
A Two Fiber Bragg Gratings Sensing System to Monitor the Torque of Rotating Shaft
Sensors 2016, 16(1), 138; https://doi.org/10.3390/s16010138
Received: 19 December 2015 / Revised: 18 January 2016 / Accepted: 18 January 2016 / Published: 21 January 2016
Cited by 7 | Viewed by 1768 | PDF Full-text (2593 KB) | HTML Full-text | XML Full-text
Abstract
By fixing two FBGs on the surface of a rotating shaft along the direction of ±45° and using dynamic wavelength demodulation technology, we propose an optical fiber sensing system to monitor the driving torque and torsion angle of the rotating shaft. In theory, [...] Read more.
By fixing two FBGs on the surface of a rotating shaft along the direction of ±45° and using dynamic wavelength demodulation technology, we propose an optical fiber sensing system to monitor the driving torque and torsion angle of the rotating shaft. In theory, the dependence relation of the dynamic difference of central wavelengths on the torque and torsion angle of the rotating shaft has been deduced. To verify an optical fiber sensing system, a series of sensing experiments have been completed and the measured data are approximately consistent with the theoretical analysis. The difference of two central wavelengths can be expressed as the sum of two parts: a “DC” part and a harmonic “AC” part. The driving torque or torsion angle is linear with the “DC” part of the difference of two central wavelengths, the harmonic “AC” part, meaning the torsion angle vibration, illustrates that periodic vibration torque may be caused by inhomogeneous centrifugal forces or inhomogeneous additional torques produced by the driving system and the load. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessReview
Graphene: The Missing Piece for Cancer Diagnosis?
Sensors 2016, 16(1), 137; https://doi.org/10.3390/s16010137
Received: 30 November 2015 / Revised: 15 January 2016 / Accepted: 19 January 2016 / Published: 21 January 2016
Cited by 19 | Viewed by 2970 | PDF Full-text (2641 KB) | HTML Full-text | XML Full-text
Abstract
This paper reviews recent advances in graphene-based biosensors development in order to obtain smaller and more portable devices with better performance for earlier cancer detection. In fact, the potential of Graphene for sensitive detection and chemical/biological free-label applications results from its exceptional physicochemical [...] Read more.
This paper reviews recent advances in graphene-based biosensors development in order to obtain smaller and more portable devices with better performance for earlier cancer detection. In fact, the potential of Graphene for sensitive detection and chemical/biological free-label applications results from its exceptional physicochemical properties such as high electrical and thermal conductivity, aspect-ratio, optical transparency and remarkable mechanical and chemical stability. Herein we start by providing a general overview of the types of graphene and its derivatives, briefly describing the synthesis procedure and main properties. It follows the reference to different routes to engineer the graphene surface for sensing applications with organic biomolecules and nanoparticles for the development of advanced biosensing platforms able to detect/quantify the characteristic cancer biomolecules in biological fluids or overexpressed on cancerous cells surface with elevated sensitivity, selectivity and stability. We then describe the application of graphene in optical imaging methods such as photoluminescence and Raman imaging, electrochemical sensors for enzymatic biosensing, DNA sensing, and immunosensing. The bioquantification of cancer biomarkers and cells is finally discussed, particularly electrochemical methods such as voltammetry and amperometry which are generally adopted transducing techniques for the development of graphene based sensors for biosensing due to their simplicity, high sensitivity and low-cost. To close, we discuss the major challenges that graphene based biosensors must overcome in order to reach the necessary standards for the early detection of cancer biomarkers by providing reliable information about the patient disease stage. Full article
(This article belongs to the Special Issue Graphene and 2D Material Bionanosensors: Chemistry Matters)
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Open AccessEditorial
Acknowledgement to Reviewers of Sensors in 2015
Sensors 2016, 16(1), 136; https://doi.org/10.3390/s16010136
Received: 15 January 2016 / Accepted: 21 January 2016 / Published: 21 January 2016
Viewed by 3437 | PDF Full-text (925 KB) | HTML Full-text | XML Full-text
Abstract
The editors of Sensors would like to express their sincere gratitude to the following reviewers for assessing manuscripts in 2015. [...] Full article
Open AccessArticle
A Novel Photoelectrochemical Biosensor for Tyrosinase and Thrombin Detection
Sensors 2016, 16(1), 135; https://doi.org/10.3390/s16010135
Received: 16 December 2015 / Revised: 14 January 2016 / Accepted: 16 January 2016 / Published: 21 January 2016
Cited by 13 | Viewed by 2587 | PDF Full-text (903 KB) | HTML Full-text | XML Full-text
Abstract
A novel photoelectrochemical biosensor for step-by-step assay of tyrosinase and thrombin was fabricated based on the specific interactions between the designed peptide and the target enzymes. A peptide chain with a special sequence which contains a positively charged lysine-labeled terminal, tyrosine at the [...] Read more.
A novel photoelectrochemical biosensor for step-by-step assay of tyrosinase and thrombin was fabricated based on the specific interactions between the designed peptide and the target enzymes. A peptide chain with a special sequence which contains a positively charged lysine-labeled terminal, tyrosine at the other end and a cleavage site recognized by thrombin between them was designed. The designed peptide can be fixed on surface of the CdTe quantum dots (QDs)-modified indium-tin oxide (ITO) electrode through electrostatic attraction to construct the photoelectrochemical biosensor. The tyrosinase target can catalyze the oxidization of tyrosine by oxygen into ortho-benzoquinone residues, which results in a decrease in the sensor photocurrent. Subsequently, the cleavage site could be recognized and cut off by another thrombin target, restoring the sensor photocurrent. The decrease or increase of photocurrent in the sensor enables us to assay tyrosinase and thrombin. Thus, the detection of tyrosinase and thrombin can be achieved in the linear range from 2.6 to 32 μg/mL and from 4.5 to 100 μg/mL with detection limits of 1.5 μg/mL and 1.9 μg/mL, respectively. Most importantly, this strategy shall allow us to detect different classes of enzymes simultaneously by designing various enzyme-specific peptide substrates. Full article
(This article belongs to the Special Issue Microbial and Enzymatic Biosensors)
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Open AccessArticle
A Machine Learning Framework for Gait Classification Using Inertial Sensors: Application to Elderly, Post-Stroke and Huntington’s Disease Patients
Sensors 2016, 16(1), 134; https://doi.org/10.3390/s16010134
Received: 7 December 2015 / Revised: 16 January 2016 / Accepted: 18 January 2016 / Published: 21 January 2016
Cited by 41 | Viewed by 4137 | PDF Full-text (948 KB) | HTML Full-text | XML Full-text
Abstract
Machine learning methods have been widely used for gait assessment through the estimation of spatio-temporal parameters. As a further step, the objective of this work is to propose and validate a general probabilistic modeling approach for the classification of different pathological gaits. Specifically, [...] Read more.
Machine learning methods have been widely used for gait assessment through the estimation of spatio-temporal parameters. As a further step, the objective of this work is to propose and validate a general probabilistic modeling approach for the classification of different pathological gaits. Specifically, the presented methodology was tested on gait data recorded on two pathological populations (Huntington’s disease and post-stroke subjects) and healthy elderly controls using data from inertial measurement units placed at shank and waist. By extracting features from group-specific Hidden Markov Models (HMMs) and signal information in time and frequency domain, a Support Vector Machines classifier (SVM) was designed and validated. The 90.5% of subjects was assigned to the right group after leave-one-subject–out cross validation and majority voting. The long-term goal we point to is the gait assessment in everyday life to early detect gait alterations. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
Analysis of a Segmented Annular Coplanar Capacitive Tilt Sensor with Increased Sensitivity
Sensors 2016, 16(1), 133; https://doi.org/10.3390/s16010133
Received: 11 December 2015 / Revised: 14 January 2016 / Accepted: 19 January 2016 / Published: 21 January 2016
Cited by 6 | Viewed by 2006 | PDF Full-text (2725 KB) | HTML Full-text | XML Full-text
Abstract
An investigation of a segmented annular coplanar capacitor is presented. We focus on its theoretical model, and a mathematical expression of the capacitance value is derived by solving a Laplace equation with Hankel transform. The finite element method is employed to verify the [...] Read more.
An investigation of a segmented annular coplanar capacitor is presented. We focus on its theoretical model, and a mathematical expression of the capacitance value is derived by solving a Laplace equation with Hankel transform. The finite element method is employed to verify the analytical result. Different control parameters are discussed, and each contribution to the capacitance value of the capacitor is obtained. On this basis, we analyze and optimize the structure parameters of a segmented coplanar capacitive tilt sensor, and three models with different positions of the electrode gap are fabricated and tested. The experimental result shows that the model (whose electrode-gap position is 10 mm from the electrode center) realizes a high sensitivity: 0.129 pF/° with a non-linearity of <0.4% FS (full scale of ±40°). This finding offers plenty of opportunities for various measurement requirements in addition to achieving an optimized structure in practical design. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
Vision-Based Georeferencing of GPR in Urban Areas
Sensors 2016, 16(1), 132; https://doi.org/10.3390/s16010132
Received: 4 September 2015 / Revised: 21 December 2015 / Accepted: 18 January 2016 / Published: 21 January 2016
Cited by 5 | Viewed by 1996 | PDF Full-text (2301 KB) | HTML Full-text | XML Full-text
Abstract
Ground Penetrating Radar (GPR) surveying is widely used to gather accurate knowledge about the geometry and position of underground utilities. The sensor arrays need to be coupled to an accurate positioning system, like a geodetic-grade Global Navigation Satellite System (GNSS) device. However, in [...] Read more.
Ground Penetrating Radar (GPR) surveying is widely used to gather accurate knowledge about the geometry and position of underground utilities. The sensor arrays need to be coupled to an accurate positioning system, like a geodetic-grade Global Navigation Satellite System (GNSS) device. However, in urban areas this approach is not always feasible because GNSS accuracy can be substantially degraded due to the presence of buildings, trees, tunnels, etc. In this work, a photogrammetric (vision-based) method for GPR georeferencing is presented. The method can be summarized in three main steps: tie point extraction from the images acquired during the survey, computation of approximate camera extrinsic parameters and finally a refinement of the parameter estimation using a rigorous implementation of the collinearity equations. A test under operational conditions is described, where accuracy of a few centimeters has been achieved. The results demonstrate that the solution was robust enough for recovering vehicle trajectories even in critical situations, such as poorly textured framed surfaces, short baselines, and low intersection angles. Full article
(This article belongs to the Section Remote Sensors, Control, and Telemetry)
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Open AccessArticle
Intravehicular, Short- and Long-Range Communication Information Fusion for Providing Safe Speed Warnings
Sensors 2016, 16(1), 131; https://doi.org/10.3390/s16010131
Received: 13 November 2015 / Revised: 15 January 2016 / Accepted: 18 January 2016 / Published: 21 January 2016
Cited by 4 | Viewed by 2280 | PDF Full-text (2839 KB) | HTML Full-text | XML Full-text
Abstract
Inappropriate speed is a relevant concurrent factor in many traffic accidents. Moreover, in recent years, traffic accidents numbers in Spain have fallen sharply, but this reduction has not been so significant on single carriageway roads. These infrastructures have less equipment than high-capacity roads, [...] Read more.
Inappropriate speed is a relevant concurrent factor in many traffic accidents. Moreover, in recent years, traffic accidents numbers in Spain have fallen sharply, but this reduction has not been so significant on single carriageway roads. These infrastructures have less equipment than high-capacity roads, therefore measures to reduce accidents on them should be implemented in vehicles. This article describes the development and analysis of the impact on the driver of a warning system for the safe speed on each road section in terms of geometry, the presence of traffic jams, weather conditions, type of vehicle and actual driving conditions. This system is based on an application for smartphones and includes knowledge of the vehicle position via Ground Positioning System (GPS), access to intravehicular information from onboard sensors through the Controller Area Network (CAN) bus, vehicle data entry by the driver, access to roadside information (short-range communications) and access to a centralized server with information about the road in the current and following sections of the route (long-range communications). Using this information, the system calculates the safe speed, recommends the appropriate speed in advance in the following sections and provides warnings to the driver. Finally, data are sent from vehicles to a server to generate new information to disseminate to other users or to supervise drivers’ behaviour. Tests in a driving simulator have been used to define the system warnings and Human Machine Interface (HMI) and final tests have been performed on real roads in order to analyze the effect of the system on driver behavior. Full article
(This article belongs to the Special Issue Sensors in New Road Vehicles)
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Open AccessArticle
Interferometric Laser Scanner for Direction Determination
Sensors 2016, 16(1), 130; https://doi.org/10.3390/s16010130
Received: 30 November 2015 / Revised: 24 December 2015 / Accepted: 19 January 2016 / Published: 21 January 2016
Cited by 2 | Viewed by 1601 | PDF Full-text (1988 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, we explore the potential capabilities of new laser scanning-based method for direction determination. The method for fully coherent beams is extended to the case when interference pattern is produced in the turbulent atmosphere by two partially coherent sources. The performed [...] Read more.
In this paper, we explore the potential capabilities of new laser scanning-based method for direction determination. The method for fully coherent beams is extended to the case when interference pattern is produced in the turbulent atmosphere by two partially coherent sources. The performed theoretical analysis identified the conditions under which stable pattern may form on extended paths of 0.5–10 km in length. We describe a method for selecting laser scanner parameters, ensuring the necessary operability range in the atmosphere for any possible turbulence characteristics. The method is based on analysis of the mean intensity of interference pattern, formed by two partially coherent sources of optical radiation. Visibility of interference pattern is estimated as a function of propagation pathlength, structure parameter of atmospheric turbulence, and spacing of radiation sources, producing the interference pattern. It is shown that, when atmospheric turbulences are moderately strong, the contrast of interference pattern of laser scanner may ensure its applicability at ranges up to 10 km. Full article
(This article belongs to the Section Remote Sensors, Control, and Telemetry)
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Open AccessArticle
Parallel Imaging of 3D Surface Profile with Space-Division Multiplexing
Sensors 2016, 16(1), 129; https://doi.org/10.3390/s16010129
Received: 16 November 2015 / Revised: 22 December 2015 / Accepted: 18 January 2016 / Published: 21 January 2016
Cited by 3 | Viewed by 1897 | PDF Full-text (1552 KB) | HTML Full-text | XML Full-text
Abstract
We have developed a modified optical frequency domain imaging (OFDI) system that performs parallel imaging of three-dimensional (3D) surface profiles by using the space division multiplexing (SDM) method with dual-area swept sourced beams. We have also demonstrated that 3D surface information for two [...] Read more.
We have developed a modified optical frequency domain imaging (OFDI) system that performs parallel imaging of three-dimensional (3D) surface profiles by using the space division multiplexing (SDM) method with dual-area swept sourced beams. We have also demonstrated that 3D surface information for two different areas could be well obtained in a same time with only one camera by our method. In this study, double field of views (FOVs) of 11.16 mm × 5.92 mm were achieved within 0.5 s. Height range for each FOV was 460 µm and axial and transverse resolutions were 3.6 and 5.52 µm, respectively. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
Use of Piezoelectric Immunosensors for Detection of Interferon-Gamma Interaction with Specific Antibodies in the Presence of Released-Active Forms of Antibodies to Interferon-Gamma
Sensors 2016, 16(1), 96; https://doi.org/10.3390/s16010096
Received: 18 December 2015 / Accepted: 6 January 2016 / Published: 20 January 2016
Cited by 6 | Viewed by 2121 | PDF Full-text (542 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
In preliminary ELISA studies where released-active forms (RAF) of antibodies (Abs) to interferon-gamma (IFNg) were added to the antigen-antibody system, a statistically significant difference in absorbance signals obtained in their presence in comparison to placebo was observed. A piezoelectric immunosensor assay was developed [...] Read more.
In preliminary ELISA studies where released-active forms (RAF) of antibodies (Abs) to interferon-gamma (IFNg) were added to the antigen-antibody system, a statistically significant difference in absorbance signals obtained in their presence in comparison to placebo was observed. A piezoelectric immunosensor assay was developed to support these data and investigate the effects of RAF Abs to IFNg on the specific interaction between Abs to IFNg and IFNg. The experimental conditions were designed and optimal electrode coating, detection circumstances and suitable chaotropic agents for electrode regeneration were selected. The developed technique was found to provide high repeatability, intermediate precision and specificity. The difference between the analytical signals of RAF Ab samples and those of the placebo was up to 50.8%, whereas the difference between non-specific controls and the placebo was within 5%–6%. Thus, the piezoelectric immunosensor as well as ELISA has the potential to be used for detecting the effects of RAF Abs to IFNg on the antigen-antibody interaction, which might be the result of RAF’s ability to modify the affinity of IFNg to specific/related Abs. Full article
(This article belongs to the Section Biosensors)
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Open AccessArticle
Construction of an Electrochemical Sensor Based on Carbon Nanotubes/Gold Nanoparticles for Trace Determination of Amoxicillin in Bovine Milk
Sensors 2016, 16(1), 56; https://doi.org/10.3390/s16010056
Received: 20 November 2015 / Revised: 22 December 2015 / Accepted: 26 December 2015 / Published: 20 January 2016
Cited by 13 | Viewed by 2510 | PDF Full-text (1873 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
In this work, a novel electrochemical sensor was fabricated for determination of amoxicillin in bovine milk samples by decoration of carboxylated multi-walled carbon nanotubes (MWCNTs) with gold nanoparticles (AuNPs) using ethylenediamine (en) as a cross linker (AuNPs/en-MWCNTs). The constructed nanocomposite was homogenized in [...] Read more.
In this work, a novel electrochemical sensor was fabricated for determination of amoxicillin in bovine milk samples by decoration of carboxylated multi-walled carbon nanotubes (MWCNTs) with gold nanoparticles (AuNPs) using ethylenediamine (en) as a cross linker (AuNPs/en-MWCNTs). The constructed nanocomposite was homogenized in dimethylformamide and drop casted on screen printed electrode. Field emission scanning electron microscopy (FESEM), energy dispersive X-Ray (EDX), X-Ray diffraction (XRD) and cyclic voltammetry were used to characterize the synthesized nanocomposites. The results show that the synthesized nanocomposites induced a remarkable synergetic effect for the oxidation of amoxicillin. Effect of some parameters, including pH, buffer, scan rate, accumulation potential, accumulation time and amount of casted nanocomposites, on the sensitivity of fabricated sensor were optimized. Under the optimum conditions, there was two linear calibration ranges from 0.2–10 µM and 10–30 µM with equations of Ipa (µA) = 2.88C (µM) + 1.2017; r = 0.9939 and Ipa (µA) = 0.88C (µM) + 22.97; r = 0.9973, respectively. The limit of detection (LOD) and limit of quantitation (LOQ) were calculated as 0.015 µM and 0.149 µM, respectively. The fabricated electrochemical sensor was successfully applied for determination of Amoxicillin in bovine milk samples and all results compared with high performance liquid chromatography (HPLC) standard method. Full article
(This article belongs to the Section Chemical Sensors)
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Open AccessArticle
A Microwave Ring-Resonator Sensor for Non-Invasive Assessment of Meat Aging
Sensors 2016, 16(1), 52; https://doi.org/10.3390/s16010052
Received: 15 September 2015 / Revised: 23 December 2015 / Accepted: 23 December 2015 / Published: 20 January 2016
Cited by 12 | Viewed by 2818 | PDF Full-text (2703 KB) | HTML Full-text | XML Full-text
Abstract
The assessment of moisture loss from meat during the aging period is a critical issue for the meat industry. In this article, a non-invasive microwave ring-resonator sensor is presented to evaluate the moisture content, or more precisely water holding capacity (WHC) of broiler [...] Read more.
The assessment of moisture loss from meat during the aging period is a critical issue for the meat industry. In this article, a non-invasive microwave ring-resonator sensor is presented to evaluate the moisture content, or more precisely water holding capacity (WHC) of broiler meat over a four-week period. The developed sensor has shown significant changes in its resonance frequency and return loss due to reduction in WHC in the studied duration. The obtained results are also confirmed by physical measurements. Further, these results are evaluated using the Fricke model, which provides a good fit for electric circuit components in biological tissue. Significant changes were observed in membrane integrity, where the corresponding capacitance decreases 30% in the early aging (0D-7D) period. Similarly, the losses associated with intracellular and extracellular fluids exhibit changed up to 42% and 53%, respectively. Ultimately, empirical polynomial models are developed to predict the electrical component values for a better understanding of aging effects. The measured and calculated values are found to be in good agreement. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
Vision-Based People Detection System for Heavy Machine Applications
Sensors 2016, 16(1), 128; https://doi.org/10.3390/s16010128
Received: 12 October 2015 / Revised: 10 January 2016 / Accepted: 13 January 2016 / Published: 20 January 2016
Cited by 4 | Viewed by 2117 | PDF Full-text (13314 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents a vision-based people detection system for improving safety in heavy machines. We propose a perception system composed of a monocular fisheye camera and a LiDAR. Fisheye cameras have the advantage of a wide field-of-view, but the strong distortions that they [...] Read more.
This paper presents a vision-based people detection system for improving safety in heavy machines. We propose a perception system composed of a monocular fisheye camera and a LiDAR. Fisheye cameras have the advantage of a wide field-of-view, but the strong distortions that they create must be handled at the detection stage. Since people detection in fisheye images has not been well studied, we focus on investigating and quantifying the impact that strong radial distortions have on the appearance of people, and we propose approaches for handling this specificity, adapted from state-of-the-art people detection approaches. These adaptive approaches nevertheless have the drawback of high computational cost and complexity. Consequently, we also present a framework for harnessing the LiDAR modality in order to enhance the detection algorithm for different camera positions. A sequential LiDAR-based fusion architecture is used, which addresses directly the problem of reducing false detections and computational cost in an exclusively vision-based system. A heavy machine dataset was built, and different experiments were carried out to evaluate the performance of the system. The results are promising, in terms of both processing speed and performance. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
Closed-Loop Control of Chemical Injection Rate for a Direct Nozzle Injection System
Sensors 2016, 16(1), 127; https://doi.org/10.3390/s16010127
Received: 19 October 2015 / Revised: 2 January 2016 / Accepted: 14 January 2016 / Published: 20 January 2016
Cited by 2 | Viewed by 2664 | PDF Full-text (2671 KB) | HTML Full-text | XML Full-text
Abstract
To realize site-specific and variable-rate application of agricultural pesticides, accurately metering and controlling the chemical injection rate is necessary. This study presents a prototype of a direct nozzle injection system (DNIS) by which chemical concentration transport lag was greatly reduced. In this system, [...] Read more.
To realize site-specific and variable-rate application of agricultural pesticides, accurately metering and controlling the chemical injection rate is necessary. This study presents a prototype of a direct nozzle injection system (DNIS) by which chemical concentration transport lag was greatly reduced. In this system, a rapid-reacting solenoid valve (RRV) was utilized for injecting chemicals, driven by a pulse-width modulation (PWM) signal at 100 Hz, so with varying pulse width the chemical injection rate could be adjusted. Meanwhile, a closed-loop control strategy, proportional-integral-derivative (PID) method, was applied for metering and stabilizing the chemical injection rate. In order to measure chemical flow rates and input them into the controller as a feedback in real-time, a thermodynamic flowmeter that was independent of chemical viscosity was used. Laboratory tests were conducted to assess the performance of DNIS and PID control strategy. Due to the nonlinear input–output characteristics of the RRV, a two-phase PID control process obtained better effects as compared with single PID control strategy. Test results also indicated that the set-point chemical flow rate could be achieved within less than 4 s, and the output stability was improved compared to the case without control strategy. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
EMD-Based Symbolic Dynamic Analysis for the Recognition of Human and Nonhuman Pyroelectric Infrared Signals
Sensors 2016, 16(1), 126; https://doi.org/10.3390/s16010126
Received: 10 November 2015 / Revised: 14 January 2016 / Accepted: 14 January 2016 / Published: 20 January 2016
Cited by 7 | Viewed by 1939 | PDF Full-text (4298 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, we propose an effective human and nonhuman pyroelectric infrared (PIR) signal recognition method to reduce PIR detector false alarms. First, using the mathematical model of the PIR detector, we analyze the physical characteristics of the human and nonhuman PIR signals; [...] Read more.
In this paper, we propose an effective human and nonhuman pyroelectric infrared (PIR) signal recognition method to reduce PIR detector false alarms. First, using the mathematical model of the PIR detector, we analyze the physical characteristics of the human and nonhuman PIR signals; second, based on the analysis results, we propose an empirical mode decomposition (EMD)-based symbolic dynamic analysis method for the recognition of human and nonhuman PIR signals. In the proposed method, first, we extract the detailed features of a PIR signal into five symbol sequences using an EMD-based symbolization method, then, we generate five feature descriptors for each PIR signal through constructing five probabilistic finite state automata with the symbol sequences. Finally, we use a weighted voting classification strategy to classify the PIR signals with their feature descriptors. Comparative experiments show that the proposed method can effectively classify the human and nonhuman PIR signals and reduce PIR detector’s false alarms. Full article
(This article belongs to the Special Issue Infrared and THz Sensing and Imaging)
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Open AccessArticle
Non-Cooperative Target Imaging and Parameter Estimation with Narrowband Radar Echoes
Sensors 2016, 16(1), 125; https://doi.org/10.3390/s16010125
Received: 19 October 2015 / Revised: 8 January 2016 / Accepted: 15 January 2016 / Published: 20 January 2016
Cited by 1 | Viewed by 1794 | PDF Full-text (1030 KB) | HTML Full-text | XML Full-text
Abstract
This study focuses on the rotating target imaging and parameter estimation with narrowband radar echoes, which is essential for radar target recognition. First, a two-dimensional (2D) imaging model with narrowband echoes is established in this paper, and two images of the target are [...] Read more.
This study focuses on the rotating target imaging and parameter estimation with narrowband radar echoes, which is essential for radar target recognition. First, a two-dimensional (2D) imaging model with narrowband echoes is established in this paper, and two images of the target are formed on the velocity-acceleration plane at two neighboring coherent processing intervals (CPIs). Then, the rotating velocity (RV) is proposed to be estimated by utilizing the relationship between the positions of the scattering centers among two images. Finally, the target image is rescaled to the range-cross-range plane with the estimated rotational parameter. The validity of the proposed approach is confirmed using numerical simulations. Full article
(This article belongs to the Section Remote Sensors, Control, and Telemetry)
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Open AccessArticle
A Pedestrian Detection Scheme Using a Coherent Phase Difference Method Based on 2D Range-Doppler FMCW Radar
Sensors 2016, 16(1), 124; https://doi.org/10.3390/s16010124
Received: 19 October 2015 / Revised: 14 January 2016 / Accepted: 14 January 2016 / Published: 20 January 2016
Cited by 22 | Viewed by 4489 | PDF Full-text (9421 KB) | HTML Full-text | XML Full-text
Abstract
For an automotive pedestrian detection radar system, fast-ramp based 2D range-Doppler Frequency Modulated Continuous Wave (FMCW) radar is effective for distinguishing between moving targets and unwanted clutter. However, when a weak moving target such as a pedestrian exists together with strong clutter, the [...] Read more.
For an automotive pedestrian detection radar system, fast-ramp based 2D range-Doppler Frequency Modulated Continuous Wave (FMCW) radar is effective for distinguishing between moving targets and unwanted clutter. However, when a weak moving target such as a pedestrian exists together with strong clutter, the pedestrian may be masked by the side-lobe of the clutter even though they are notably separated in the Doppler dimension. To prevent this problem, one popular solution is the use of a windowing scheme with a weighting function. However, this method leads to a spread spectrum, so the pedestrian with weak signal power and slow Doppler may also be masked by the main-lobe of clutter. With a fast-ramp based FMCW radar, if the target is moving, the complex spectrum of the range- Fast Fourier Transform (FFT) is changed with a constant phase difference over ramps. In contrast, the clutter exhibits constant phase irrespective of the ramps. Based on this fact, in this paper we propose a pedestrian detection for highly cluttered environments using a coherent phase difference method. By detecting the coherent phase difference from the complex spectrum of the range-FFT, we first extract the range profile of the moving pedestrians. Then, through the Doppler FFT, we obtain the 2D range-Doppler map for only the pedestrian. To test the proposed detection scheme, we have developed a real-time data logging system with a 24 GHz FMCW transceiver. In laboratory tests, we verified that the signal processing results from the proposed method were much better than those expected from the conventional 2D FFT-based detection method. Full article
(This article belongs to the Section Remote Sensors, Control, and Telemetry)
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Open AccessArticle
Analysis of BeiDou Satellite Measurements with Code Multipath and Geometry-Free Ionosphere-Free Combinations
Sensors 2016, 16(1), 123; https://doi.org/10.3390/s16010123
Received: 20 November 2015 / Revised: 11 January 2016 / Accepted: 15 January 2016 / Published: 20 January 2016
Cited by 25 | Viewed by 2514 | PDF Full-text (8221 KB) | HTML Full-text | XML Full-text
Abstract
Using GNSS observable from some stations in the Asia-Pacific area, the carrier-to-noise ratio (CNR) and multipath combinations of BeiDou Navigation Satellite System (BDS), as well as their variations with time and/or elevation were investigated and compared with those of GPS and Galileo. Provided [...] Read more.
Using GNSS observable from some stations in the Asia-Pacific area, the carrier-to-noise ratio (CNR) and multipath combinations of BeiDou Navigation Satellite System (BDS), as well as their variations with time and/or elevation were investigated and compared with those of GPS and Galileo. Provided the same elevation, the CNR of B1 observables is the lowest among the three BDS frequencies, while B3 is the highest. The code multipath combinations of BDS inclined geosynchronous orbit (IGSO) and medium Earth orbit (MEO) satellites are remarkably correlated with elevation, and the systematic “V” shape trends could be eliminated through between-station-differencing or modeling correction. Daily periodicity was found in the geometry-free ionosphere-free (GFIF) combinations of both BDS geostationary Earth orbit (GEO) and IGSO satellites. The variation range of carrier phase GFIF combinations of GEO satellites is −2.0 to 2.0 cm. The periodicity of carrier phase GFIF combination could be significantly mitigated through between-station differencing. Carrier phase GFIF combinations of BDS GEO and IGSO satellites might also contain delays related to satellites. Cross-correlation suggests that the GFIF combinations’ time series of some GEO satellites might vary according to their relative geometries with the sun. Full article
(This article belongs to the Section Remote Sensors, Control, and Telemetry)
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Open AccessArticle
Assessment of Three Tropospheric Delay Models (IGGtrop, EGNOS and UNB3m) Based on Precise Point Positioning in the Chinese Region
Sensors 2016, 16(1), 122; https://doi.org/10.3390/s16010122
Received: 2 November 2015 / Revised: 12 January 2016 / Accepted: 15 January 2016 / Published: 20 January 2016
Cited by 10 | Viewed by 1846 | PDF Full-text (4066 KB) | HTML Full-text | XML Full-text
Abstract
Tropospheric delays are one of the main sources of errors in the Global Navigation Satellite System (GNSS). They are usually corrected by using tropospheric delay models, which makes the accuracy of the models rather critical for accurate positioning. To provide references for suitable [...] Read more.
Tropospheric delays are one of the main sources of errors in the Global Navigation Satellite System (GNSS). They are usually corrected by using tropospheric delay models, which makes the accuracy of the models rather critical for accurate positioning. To provide references for suitable models to be chosen for GNSS users in China, we conduct herein a comprehensive study of the performances of the IGGtrop, EGNOS and UNB3m models in China. Firstly, we assess the models using 5 years’ Global Positioning System (GPS) derived Zenith Tropospheric Delay (ZTD) series from 25 stations of the Crustal Movement Observation Network of China (CMONOC). Then we study the effects of the models on satellite positioning by using various Precise Point Positioning (PPP) cases with different tropospheric delay resolutions, the observation data processed in PPP is from 21 base stations of CMONOC for a whole year of 2012. The results show that: (1) the Root Mean Square (RMS) of the IGGtrop model is about 4.4 cm, which improves the accuracy of ZTD estimations by about 24% for EGNOS and 19% for UNB3m; (2) The positioning error in the vertical component of the PPP solution obtained by using the IGGtrop model is about 15.0 cm, which is about 30% and 21% smaller than those of the EGNOS and UNB3m models, respectively. In summary, the IGGtrop model achieves the best performance among the three models in the Chinese region. Full article
(This article belongs to the Section Remote Sensors, Control, and Telemetry)
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Open AccessArticle
Realtime Gas Emission Monitoring at Hazardous Sites Using a Distributed Point-Source Sensing Infrastructure
Sensors 2016, 16(1), 121; https://doi.org/10.3390/s16010121
Received: 14 September 2015 / Revised: 14 January 2016 / Accepted: 14 January 2016 / Published: 20 January 2016
Cited by 7 | Viewed by 1733 | PDF Full-text (7127 KB) | HTML Full-text | XML Full-text
Abstract
This paper describes a distributed point-source monitoring platform for gas level and leakage detection in hazardous environments. The platform, based on a wireless sensor network (WSN) architecture, is organised into sub-networks to be positioned in the plant’s critical areas; each sub-net includes a [...] Read more.
This paper describes a distributed point-source monitoring platform for gas level and leakage detection in hazardous environments. The platform, based on a wireless sensor network (WSN) architecture, is organised into sub-networks to be positioned in the plant’s critical areas; each sub-net includes a gateway unit wirelessly connected to the WSN nodes, hence providing an easily deployable, stand-alone infrastructure featuring a high degree of scalability and reconfigurability. Furthermore, the system provides automated calibration routines which can be accomplished by non-specialized maintenance operators without system reliability reduction issues. Internet connectivity is provided via TCP/IP over GPRS (Internet standard protocols over mobile networks) gateways at a one-minute sampling rate. Environmental and process data are forwarded to a remote server and made available to authenticated users through a user interface that provides data rendering in various formats and multi-sensor data fusion. The platform is able to provide real-time plant management with an effective; accurate tool for immediate warning in case of critical events. Full article
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Open AccessArticle
DC-Compensated Current Transformer
Sensors 2016, 16(1), 114; https://doi.org/10.3390/s16010114
Received: 15 November 2015 / Revised: 31 December 2015 / Accepted: 12 January 2016 / Published: 20 January 2016
Cited by 6 | Viewed by 2311 | PDF Full-text (2864 KB) | HTML Full-text | XML Full-text
Abstract
Instrument current transformers (CTs) measure AC currents. The DC component in the measured current can saturate the transformer and cause gross error. We use fluxgate detection and digital feedback compensation of the DC flux to suppress the overall error to 0.15%. This concept [...] Read more.
Instrument current transformers (CTs) measure AC currents. The DC component in the measured current can saturate the transformer and cause gross error. We use fluxgate detection and digital feedback compensation of the DC flux to suppress the overall error to 0.15%. This concept can be used not only for high-end CTs with a nanocrystalline core, but it also works for low-cost CTs with FeSi cores. The method described here allows simultaneous measurements of the DC current component. Full article
(This article belongs to the Special Issue Magnetic Sensor Device-Part 2)
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Open AccessArticle
Dynamic Vehicle Detection via the Use of Magnetic Field Sensors
Sensors 2016, 16(1), 78; https://doi.org/10.3390/s16010078
Received: 12 November 2015 / Revised: 23 December 2015 / Accepted: 4 January 2016 / Published: 19 January 2016
Cited by 23 | Viewed by 3323 | PDF Full-text (5200 KB) | HTML Full-text | XML Full-text
Abstract
The vehicle detection process plays the key role in determining the success of intelligent transport management system solutions. The measurement of distortions of the Earth’s magnetic field using magnetic field sensors served as the basis for designing a solution aimed at vehicle detection. [...] Read more.
The vehicle detection process plays the key role in determining the success of intelligent transport management system solutions. The measurement of distortions of the Earth’s magnetic field using magnetic field sensors served as the basis for designing a solution aimed at vehicle detection. In accordance with the results obtained from research into process modeling and experimentally testing all the relevant hypotheses an algorithm for vehicle detection using the state criteria was proposed. Aiming to evaluate all of the possibilities, as well as pros and cons of the use of anisotropic magnetoresistance (AMR) sensors in the transport flow control process, we have performed a series of experiments with various vehicles (or different series) from several car manufacturers. A comparison of 12 selected methods, based on either the process of determining the peak signal values and their concurrence in time whilst calculating the delay, or by measuring the cross-correlation of these signals, was carried out. It was established that the relative error can be minimized via the Z component cross-correlation and Kz criterion cross-correlation methods. The average relative error of vehicle speed determination in the best case did not exceed 1.5% when the distance between sensors was set to 2 m. Full article
(This article belongs to the Special Issue Magnetic Sensor Device-Part 2)
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Open AccessArticle
Multi-Stage Feature Selection Based Intelligent Classifier for Classification of Incipient Stage Fire in Building
Sensors 2016, 16(1), 31; https://doi.org/10.3390/s16010031
Received: 23 October 2015 / Revised: 11 December 2015 / Accepted: 18 December 2015 / Published: 19 January 2016
Cited by 5 | Viewed by 2695 | PDF Full-text (1228 KB) | HTML Full-text | XML Full-text
Abstract
In this study, an early fire detection algorithm has been proposed based on low cost array sensing system, utilising off- the shelf gas sensors, dust particles and ambient sensors such as temperature and humidity sensor. The odour or “smellprint” emanated from various fire [...] Read more.
In this study, an early fire detection algorithm has been proposed based on low cost array sensing system, utilising off- the shelf gas sensors, dust particles and ambient sensors such as temperature and humidity sensor. The odour or “smellprint” emanated from various fire sources and building construction materials at early stage are measured. For this purpose, odour profile data from five common fire sources and three common building construction materials were used to develop the classification model. Normalised feature extractions of the smell print data were performed before subjected to prediction classifier. These features represent the odour signals in the time domain. The obtained features undergo the proposed multi-stage feature selection technique and lastly, further reduced by Principal Component Analysis (PCA), a dimension reduction technique. The hybrid PCA-PNN based approach has been applied on different datasets from in-house developed system and the portable electronic nose unit. Experimental classification results show that the dimension reduction process performed by PCA has improved the classification accuracy and provided high reliability, regardless of ambient temperature and humidity variation, baseline sensor drift, the different gas concentration level and exposure towards different heating temperature range. Full article
(This article belongs to the Special Issue Sensors for Fire Detection)
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Open AccessArticle
Pedestrian Navigation Using Foot-Mounted Inertial Sensor and LIDAR
Sensors 2016, 16(1), 120; https://doi.org/10.3390/s16010120
Received: 21 November 2015 / Revised: 14 January 2016 / Accepted: 15 January 2016 / Published: 19 January 2016
Cited by 19 | Viewed by 2244 | PDF Full-text (4350 KB) | HTML Full-text | XML Full-text
Abstract
Foot-mounted inertial sensors can be used for indoor pedestrian navigation. In this paper, to improve the accuracy of pedestrian location, we propose a method using a distance sensor (LIDAR) in addition to an inertial measurement unit (IMU). The distance sensor is a time [...] Read more.
Foot-mounted inertial sensors can be used for indoor pedestrian navigation. In this paper, to improve the accuracy of pedestrian location, we propose a method using a distance sensor (LIDAR) in addition to an inertial measurement unit (IMU). The distance sensor is a time of flight range finder with 30 m measurement range (at 33.33 Hz). Using a distance sensor, walls on corridors are automatically detected. The detected walls are used to correct the heading of the pedestrian path. Through experiments, it is shown that the accuracy of the heading is significantly improved using the proposed algorithm. Furthermore, the system is shown to work robustly in indoor environments with many doors and passing people. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle
Mapping Vineyard Leaf Area Using Mobile Terrestrial Laser Scanners: Should Rows be Scanned On-the-Go or Discontinuously Sampled?
Sensors 2016, 16(1), 119; https://doi.org/10.3390/s16010119
Received: 7 December 2015 / Revised: 14 January 2016 / Accepted: 15 January 2016 / Published: 19 January 2016
Cited by 8 | Viewed by 2177 | PDF Full-text (5763 KB) | HTML Full-text | XML Full-text
Abstract
The leaf area index (LAI) is defined as the one-side leaf area per unit ground area, and is probably the most widely used index to characterize grapevine vigor. However, LAI varies spatially within vineyard plots. Mapping and quantifying this variability is very important [...] Read more.
The leaf area index (LAI) is defined as the one-side leaf area per unit ground area, and is probably the most widely used index to characterize grapevine vigor. However, LAI varies spatially within vineyard plots. Mapping and quantifying this variability is very important for improving management decisions and agricultural practices. In this study, a mobile terrestrial laser scanner (MTLS) was used to map the LAI of a vineyard, and then to examine how different scanning methods (on-the-go or discontinuous systematic sampling) may affect the reliability of the resulting raster maps. The use of the MTLS allows calculating the enveloping vegetative area of the canopy, which is the sum of the leaf wall areas for both sides of the row (excluding gaps) and the projected upper area. Obtaining the enveloping areas requires scanning from both sides one meter length section along the row at each systematic sampling point. By converting the enveloping areas into LAI values, a raster map of the latter can be obtained by spatial interpolation (kriging). However, the user can opt for scanning on-the-go in a continuous way and compute 1-m LAI values along the rows, or instead, perform the scanning at discontinuous systematic sampling within the plot. An analysis of correlation between maps indicated that MTLS can be used discontinuously in specific sampling sections separated by up to 15 m along the rows. This capability significantly reduces the amount of data to be acquired at field level, the data storage capacity and the processing power of computers. Full article
(This article belongs to the Special Issue Sensors for Agriculture)
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Open AccessArticle
Defence against Black Hole and Selective Forwarding Attacks for Medical WSNs in the IoT
Sensors 2016, 16(1), 118; https://doi.org/10.3390/s16010118
Received: 17 December 2015 / Revised: 13 January 2016 / Accepted: 14 January 2016 / Published: 19 January 2016
Cited by 20 | Viewed by 2681 | PDF Full-text (6193 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Wireless sensor networks (WSNs) are being used to facilitate monitoring of patients in hospital and home environments. These systems consist of a variety of different components/sensors and many processes like clustering, routing, security, and self-organization. Routing is necessary for medical-based WSNs because it [...] Read more.
Wireless sensor networks (WSNs) are being used to facilitate monitoring of patients in hospital and home environments. These systems consist of a variety of different components/sensors and many processes like clustering, routing, security, and self-organization. Routing is necessary for medical-based WSNs because it allows remote data delivery and it facilitates network scalability in large hospitals. However, routing entails several problems, mainly due to the open nature of wireless networks, and these need to be addressed. This paper looks at two of the problems that arise due to wireless routing between the nodes and access points of a medical WSN (for IoT use): black hole and selective forwarding (SF) attacks. A solution to the former can readily be provided through the use of cryptographic hashes, while the latter makes use of a neighbourhood watch and threshold-based analysis to detect and correct SF attacks. The scheme proposed here is capable of detecting a selective forwarding attack with over 96% accuracy and successfully identifying the malicious node with 83% accuracy. Full article
(This article belongs to the Special Issue Security and Privacy in Sensor Networks)
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Open AccessArticle
Building SDN-Based Agricultural Vehicular Sensor Networks Based on Extended Open vSwitch
Sensors 2016, 16(1), 108; https://doi.org/10.3390/s16010108
Received: 26 November 2015 / Revised: 11 January 2016 / Accepted: 12 January 2016 / Published: 19 January 2016
Cited by 10 | Viewed by 2459 | PDF Full-text (1528 KB) | HTML Full-text | XML Full-text
Abstract
Software-defined vehicular sensor networks in agriculture, such as autonomous vehicle navigation based on wireless multi-sensor networks, can lead to more efficient precision agriculture. In SDN-based vehicle sensor networks, the data plane is simplified and becomes more efficient by introducing a centralized controller. However, [...] Read more.
Software-defined vehicular sensor networks in agriculture, such as autonomous vehicle navigation based on wireless multi-sensor networks, can lead to more efficient precision agriculture. In SDN-based vehicle sensor networks, the data plane is simplified and becomes more efficient by introducing a centralized controller. However, in a wireless environment, the main controller node may leave the sensor network due to the dynamic topology change or the unstable wireless signal, leaving the rest of network devices without control, e.g., a sensor node as a switch may forward packets according to stale rules until the controller updates the flow table entries. To solve this problem, this paper proposes a novel SDN-based vehicular sensor networks architecture which can minimize the performance penalty of controller connection loss. We achieve this by designing a connection state detection and self-learning mechanism. We build prototypes based on extended Open vSwitch and Ryu. The experimental results show that the recovery time from controller connection loss is under 100 ms and it keeps rule updating in real time with a stable throughput. This architecture enhances the survivability and stability of SDN-based vehicular sensor networks in precision agriculture. Full article
(This article belongs to the Special Issue Sensors for Agriculture)
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Open AccessArticle
Wireless Relay Selection in Pocket Switched Networks Based on Spatial Regularity of Human Mobility
Sensors 2016, 16(1), 94; https://doi.org/10.3390/s16010094
Received: 16 October 2015 / Revised: 20 December 2015 / Accepted: 28 December 2015 / Published: 18 January 2016
Cited by 5 | Viewed by 1689 | PDF Full-text (508 KB) | HTML Full-text | XML Full-text
Abstract
Pocket switched networks (PSNs) take advantage of human mobility to deliver data. Investigations on real-world trace data indicate that human mobility shows an obvious spatial regularity: a human being usually visits a few places at high frequencies. These most frequently visited places form [...] Read more.
Pocket switched networks (PSNs) take advantage of human mobility to deliver data. Investigations on real-world trace data indicate that human mobility shows an obvious spatial regularity: a human being usually visits a few places at high frequencies. These most frequently visited places form the home of a node, which is exploited in this paper to design two HomE based Relay selectiOn (HERO) algorithms. Both algorithms input single data copy into the network at any time. In the basic HERO, only the first node encountered by the source and whose home overlaps a destination’s home is selected as a relay while the enhanced HERO keeps finding more optimal relay that visits the destination’s home with higher probability. The two proposed algorithms only require the relays to exchange the information of their home and/or the visiting frequencies to their home when two nodes meet. As a result, the information update is reduced and there is no global status information that needs to be maintained. This causes light loads on relays because of the low communication cost and storage requirements. Additionally, only simple operations are needed in the two proposed algorithms, resulting in little computation overhead at relays. At last, a theoretical analysis is performed on some key metrics and then the real-world based simulations indicate that the two HERO algorithms are efficient and effective through employing only one or a few relays. Full article
(This article belongs to the Special Issue Identification, Information & Knowledge in the Internet of Things)
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