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Sensors, Volume 11, Issue 3 (March 2011), Pages 2282-3400

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Open AccessArticle A Reliable Energy-Efficient Multi-Level Routing Algorithm for Wireless Sensor Networks Using Fuzzy Petri Nets
Sensors 2011, 11(3), 3381-3400; https://doi.org/10.3390/s110303381
Received: 25 January 2011 / Revised: 16 February 2011 / Accepted: 4 March 2011 / Published: 22 March 2011
Cited by 28 | PDF Full-text (311 KB) | HTML Full-text | XML Full-text
Abstract
A reliable energy-efficient multi-level routing algorithm in wireless sensor networks is proposed. The proposed algorithm considers the residual energy, number of the neighbors and centrality of each node for cluster formation, which is critical for well-balanced energy dissipation of the network. In the
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A reliable energy-efficient multi-level routing algorithm in wireless sensor networks is proposed. The proposed algorithm considers the residual energy, number of the neighbors and centrality of each node for cluster formation, which is critical for well-balanced energy dissipation of the network. In the algorithm, a knowledge-based inference approach using fuzzy Petri nets is employed to select cluster heads, and then the fuzzy reasoning mechanism is used to compute the degree of reliability in the route sprouting tree from cluster heads to the base station. Finally, the most reliable route among the cluster heads can be constructed. The algorithm not only balances the energy load of each node but also provides global reliability for the whole network. Simulation results demonstrate that the proposed algorithm effectively prolongs the network lifetime and reduces the energy consumption. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Signal Injection as a Fault Detection Technique
Sensors 2011, 11(3), 3356-3380; https://doi.org/10.3390/s110303356
Received: 25 January 2011 / Revised: 28 February 2011 / Accepted: 10 March 2011 / Published: 21 March 2011
Cited by 12 | PDF Full-text (2188 KB) | HTML Full-text | XML Full-text
Abstract
Double frequency tests are used for evaluating stator windings and analyzing the temperature. Likewise, signal injection on induction machines is used on sensorless motor control fields to find out the rotor position. Motor Current Signature Analysis (MCSA), which focuses on the spectral analysis
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Double frequency tests are used for evaluating stator windings and analyzing the temperature. Likewise, signal injection on induction machines is used on sensorless motor control fields to find out the rotor position. Motor Current Signature Analysis (MCSA), which focuses on the spectral analysis of stator current, is the most widely used method for identifying faults in induction motors. Motor faults such as broken rotor bars, bearing damage and eccentricity of the rotor axis can be detected. However, the method presents some problems at low speed and low torque, mainly due to the proximity between the frequencies to be detected and the small amplitude of the resulting harmonics. This paper proposes the injection of an additional voltage into the machine being tested at a frequency different from the fundamental one, and then studying the resulting harmonics around the new frequencies appearing due to the composition between injected and main frequencies. Full article
(This article belongs to the Section Physical Sensors)
Open AccessReview Functional Polymers in Protein Detection Platforms: Optical, Electrochemical, Electrical, Mass-Sensitive, and Magnetic Biosensors
Sensors 2011, 11(3), 3327-3355; https://doi.org/10.3390/s110303327
Received: 26 January 2011 / Revised: 26 February 2011 / Accepted: 15 March 2011 / Published: 21 March 2011
Cited by 24 | PDF Full-text (1399 KB) | HTML Full-text | XML Full-text
Abstract
The rapidly growing field of proteomics and related applied sectors in the life sciences demands convenient methodologies for detecting and measuring the levels of specific proteins as well as for screening and analyzing for interacting protein systems. Materials utilized for such protein detection
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The rapidly growing field of proteomics and related applied sectors in the life sciences demands convenient methodologies for detecting and measuring the levels of specific proteins as well as for screening and analyzing for interacting protein systems. Materials utilized for such protein detection and measurement platforms should meet particular specifications which include ease-of-mass manufacture, biological stability, chemical functionality, cost effectiveness, and portability. Polymers can satisfy many of these requirements and are often considered as choice materials in various biological detection platforms. Therefore, tremendous research efforts have been made for developing new polymers both in macroscopic and nanoscopic length scales as well as applying existing polymeric materials for protein measurements. In this review article, both conventional and alternative techniques for protein detection are overviewed while focusing on the use of various polymeric materials in different protein sensing technologies. Among many available detection mechanisms, most common approaches such as optical, electrochemical, electrical, mass-sensitive, and magnetic methods are comprehensively discussed in this article. Desired properties of polymers exploited for each type of protein detection approach are summarized. Current challenges associated with the application of polymeric materials are examined in each protein detection category. Difficulties facing both quantitative and qualitative protein measurements are also identified. The latest efforts on the development and evaluation of nanoscale polymeric systems for improved protein detection are also discussed from the standpoint of quantitative and qualitative measurements. Finally, future research directions towards further advancements in the field are considered. Full article
(This article belongs to the Section Biosensors)
Open AccessArticle Contrast-Independent Biologically Inspired Motion Detection
Sensors 2011, 11(3), 3303-3326; https://doi.org/10.3390/s110303303
Received: 28 January 2011 / Revised: 15 March 2011 / Accepted: 17 March 2011 / Published: 18 March 2011
Cited by 7 | PDF Full-text (5324 KB) | HTML Full-text | XML Full-text
Abstract
Optic flow, i.e., retinal image movement resulting from ego-motion, is a crucial source of information used for obstacle avoidance and course control in flying insects. Optic flow analysis may prove promising for mobile robotics although it is currently not among the standard
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Optic flow, i.e., retinal image movement resulting from ego-motion, is a crucial source of information used for obstacle avoidance and course control in flying insects. Optic flow analysis may prove promising for mobile robotics although it is currently not among the standard techniques. Insects have developed a computationally cheap analysis mechanism for image motion. Detailed computational models, the so-called elementary motion detectors (EMDs), describe motion detection in insects. However, the technical application of EMDs is complicated by the strong effect of local pattern contrast on their motion response. Here we present augmented versions of an EMD, the (s)cc-EMDs, which normalise their responses for contrast and thereby reduce the sensitivity to contrast changes. Thus, velocity changes of moving natural images are reflected more reliably in the detector response. The (s)cc-EMDs can easily be implemented in hardware and software and can be a valuable novel visual motion sensor for mobile robots. Full article
Open AccessArticle A Compatible Control Algorithm for Greenhouse Environment Control Based on MOCC Strategy
Sensors 2011, 11(3), 3281-3302; https://doi.org/10.3390/s110303281
Received: 21 February 2011 / Accepted: 10 March 2011 / Published: 18 March 2011
Cited by 14 | PDF Full-text (596 KB) | HTML Full-text | XML Full-text
Abstract
Conventional methods used for solving greenhouse environment multi-objective conflict control problems lay excessive emphasis on control performance and have inadequate consideration for both energy consumption and special requirements for plant growth. The resulting solution will cause higher energy cost. However, during the long
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Conventional methods used for solving greenhouse environment multi-objective conflict control problems lay excessive emphasis on control performance and have inadequate consideration for both energy consumption and special requirements for plant growth. The resulting solution will cause higher energy cost. However, during the long period of work and practice, we find that it may be more reasonable to adopt interval or region control objectives instead of point control objectives. In this paper, we propose a modified compatible control algorithm, and employ Multi-Objective Compatible Control (MOCC) strategy and an extant greenhouse model to achieve greenhouse climate control based on feedback control architecture. A series of simulation experiments through various comparative studies are presented to validate the feasibility of the proposed algorithm. The results are encouraging and suggest the energy-saving application to real-world engineering problems in greenhouse production. It may be valuable and helpful to formulate environmental control strategies, and to achieve high control precision and low energy cost for real-world engineering application in greenhouse production. Moreover, the proposed approach has also potential to be useful for other practical control optimization problems with the features like the greenhouse environment control system. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle Optical Sensor for Diverse Organic Vapors at ppm Concentration Ranges
Sensors 2011, 11(3), 3267-3280; https://doi.org/10.3390/s110303267
Received: 17 February 2011 / Revised: 12 March 2011 / Accepted: 15 March 2011 / Published: 17 March 2011
Cited by 15 | PDF Full-text (291 KB) | HTML Full-text | XML Full-text
Abstract
A broadly responsive optical organic vapor sensor is described that responds to low concentrations of organic vapors without significant interference from water vapor. Responses to several classes of organic vapors are highlighted, and trends within classes are presented. The relationship between molecular properties
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A broadly responsive optical organic vapor sensor is described that responds to low concentrations of organic vapors without significant interference from water vapor. Responses to several classes of organic vapors are highlighted, and trends within classes are presented. The relationship between molecular properties (vapor pressure, boiling point, polarizability, and refractive index) and sensor response are discussed. Full article
(This article belongs to the Special Issue Direct and Indirect Sensing of Odor and VOCs and Their Control)
Open AccessArticle Three Realizations and Comparison of Hardware for Piezoresistive Tactile Sensors
Sensors 2011, 11(3), 3249-3266; https://doi.org/10.3390/s110303249
Received: 17 January 2011 / Revised: 10 March 2011 / Accepted: 14 March 2011 / Published: 17 March 2011
Cited by 33 | PDF Full-text (862 KB) | HTML Full-text | XML Full-text
Abstract
Tactile sensors are basically arrays of force sensors that are intended to emulate the skin in applications such as assistive robotics. Local electronics are usually implemented to reduce errors and interference caused by long wires. Realizations based on standard microcontrollers, Programmable Systems on
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Tactile sensors are basically arrays of force sensors that are intended to emulate the skin in applications such as assistive robotics. Local electronics are usually implemented to reduce errors and interference caused by long wires. Realizations based on standard microcontrollers, Programmable Systems on Chip (PSoCs) and Field Programmable Gate Arrays (FPGAs) have been proposed by the authors for the case of piezoresistive tactile sensors. The solution employing FPGAs is especially relevant since their performance is closer to that of Application Specific Integrated Circuits (ASICs) than that of the other devices. This paper presents an implementation of such an idea for a specific sensor. For the purpose of comparison, the circuitry based on the other devices is also made for the same sensor. This paper discusses the implementation issues, provides details regarding the design of the hardware based on the three devices and compares them. Full article
(This article belongs to the Special Issue Bioinspired Sensor Systems)
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Open AccessArticle Gyroscope Pivot Bearing Dimension and Surface Defect Detection
Sensors 2011, 11(3), 3227-3248; https://doi.org/10.3390/s110303227
Received: 31 January 2011 / Revised: 1 March 2011 / Accepted: 4 March 2011 / Published: 16 March 2011
Cited by 2 | PDF Full-text (725 KB) | HTML Full-text | XML Full-text
Abstract
Because of the perceived lack of systematic analysis in illumination system design processes and a lack of criteria for design methods in vision detection a method for the design of a task-oriented illumination system is proposed. After detecting the micro-defects of a gyroscope
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Because of the perceived lack of systematic analysis in illumination system design processes and a lack of criteria for design methods in vision detection a method for the design of a task-oriented illumination system is proposed. After detecting the micro-defects of a gyroscope pivot bearing with a high curvature glabrous surface and analyzing the characteristics of the surface detection and reflection model, a complex illumination system with coaxial and ring lights is proposed. The illumination system is then optimized based on the analysis of illuminance uniformity of target regions by simulation and grey scale uniformity and articulation that are calculated from grey imagery. Currently, in order to apply the Pulse Coupled Neural Network (PCNN) method, structural parameters must be tested and adjusted repeatedly. Therefore, this paper proposes the use of a particle swarm optimization (PSO) algorithm, in which the maximum between cluster variance rules is used as fitness function with a linearily reduced inertia factor. This algorithm is used to adaptively set PCNN connection coefficients and dynamic threshold, which avoids algorithmic precocity and local oscillations. The proposed method is used for pivot bearing defect image processing. The segmentation results of the maximum entropy and minimum error method and the one described in this paper are compared using buffer region matching, and the experimental results show that the method of this paper is effective. Full article
(This article belongs to the Special Issue 10 Years Sensors - A Decade of Publishing)
Open AccessArticle Potentiometric Electronic Tongue to Resolve Mixtures of Sulfide and Perchlorate Anions
Sensors 2011, 11(3), 3214-3226; https://doi.org/10.3390/s110303214
Received: 11 January 2011 / Revised: 24 February 2011 / Accepted: 10 March 2011 / Published: 16 March 2011
Cited by 13 | PDF Full-text (449 KB) | HTML Full-text | XML Full-text
Abstract
This work describes the use of an array of potentiometric sensors and an artificial neural network response model to determine perchlorate and sulfide ions in polluted waters, by what is known as an electronic tongue. Sensors used have been all-solid-state PVC membrane selective
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This work describes the use of an array of potentiometric sensors and an artificial neural network response model to determine perchlorate and sulfide ions in polluted waters, by what is known as an electronic tongue. Sensors used have been all-solid-state PVC membrane selective electrodes, where their ionophores were different metal-phtalocyanine complexes with specific and anion generic responses. The study case illustrates the potential use of electronic tongues in the quantification of mixtures when interfering effects need to be counterbalanced: relative errors in determination of individual ions can be decreased typically from 25% to less than 5%, if compared to the use of a single proposed ion-selective electrode. Full article
(This article belongs to the Special Issue Bioinspired Sensor Systems)
Open AccessArticle Adaptive Marginal Median Filter for Colour Images
Sensors 2011, 11(3), 3205-3213; https://doi.org/10.3390/s110303205
Received: 5 January 2011 / Revised: 3 February 2011 / Accepted: 10 March 2011 / Published: 15 March 2011
Cited by 20 | PDF Full-text (1421 KB) | HTML Full-text | XML Full-text
Abstract
This paper describes a new filter for impulse noise reduction in colour images which is aimed at improving the noise reduction capability of the classical vector median filter. The filter is inspired by the application of a vector marginal median filtering process over
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This paper describes a new filter for impulse noise reduction in colour images which is aimed at improving the noise reduction capability of the classical vector median filter. The filter is inspired by the application of a vector marginal median filtering process over a selected group of pixels in each filtering window. This selection, which is based on the vector median, along with the application of the marginal median operation constitutes an adaptive process that leads to a more robust filter design. Also, the proposed method is able to process colour images without introducing colour artifacts. Experimental results show that the images filtered with the proposed method contain less noisy pixels than those obtained through the vector median filter. Full article
(This article belongs to the Special Issue Adaptive Sensing)
Open AccessArticle Ontological Problem-Solving Framework for Dynamically Configuring Sensor Systems and Algorithms
Sensors 2011, 11(3), 3177-3204; https://doi.org/10.3390/s110303177
Received: 7 January 2011 / Revised: 4 February 2011 / Accepted: 11 March 2011 / Published: 15 March 2011
Cited by 3 | PDF Full-text (297 KB) | HTML Full-text | XML Full-text
Abstract
The deployment of ubiquitous sensor systems and algorithms has led to many challenges, such as matching sensor systems to compatible algorithms which are capable of satisfying a task. Compounding the challenges is the lack of the requisite knowledge models needed to discover sensors
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The deployment of ubiquitous sensor systems and algorithms has led to many challenges, such as matching sensor systems to compatible algorithms which are capable of satisfying a task. Compounding the challenges is the lack of the requisite knowledge models needed to discover sensors and algorithms and to subsequently integrate their capabilities to satisfy a specific task. A novel ontological problem-solving framework has been designed to match sensors to compatible algorithms to form synthesized systems, which are capable of satisfying a task and then assigning the synthesized systems to high-level missions. The approach designed for the ontological problem-solving framework has been instantiated in the context of a persistence surveillance prototype environment, which includes profiling sensor systems and algorithms to demonstrate proof-of-concept principles. Even though the problem-solving approach was instantiated with profiling sensor systems and algorithms, the ontological framework may be useful with other heterogeneous sensing-system environments. Full article
(This article belongs to the Special Issue Semantic Sensor Network Technologies and Applications)
Open AccessArticle Delaunay Triangulation as a New Coverage Measurement Method in Wireless Sensor Network
Sensors 2011, 11(3), 3163-3176; https://doi.org/10.3390/s110303163
Received: 15 January 2011 / Revised: 25 February 2011 / Accepted: 28 February 2011 / Published: 15 March 2011
Cited by 18 | PDF Full-text (985 KB) | HTML Full-text | XML Full-text
Abstract
Sensing and communication coverage are among the most important trade-offs in Wireless Sensor Network (WSN) design. A minimum bound of sensing coverage is vital in scheduling, target tracking and redeployment phases, as well as providing communication coverage. Some methods measure the coverage as
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Sensing and communication coverage are among the most important trade-offs in Wireless Sensor Network (WSN) design. A minimum bound of sensing coverage is vital in scheduling, target tracking and redeployment phases, as well as providing communication coverage. Some methods measure the coverage as a percentage value, but detailed information has been missing. Two scenarios with equal coverage percentage may not have the same Quality of Coverage (QoC). In this paper, we propose a new coverage measurement method using Delaunay Triangulation (DT). This can provide the value for all coverage measurement tools. Moreover, it categorizes sensors as ‘fat’, ‘healthy’ or ‘thin’ to show the dense, optimal and scattered areas. It can also yield the largest empty area of sensors in the field. Simulation results show that the proposed DT method can achieve accurate coverage information, and provides many tools to compare QoC between different scenarios. Full article
(This article belongs to the Special Issue Advanced Sensing Technology for Nondestructive Evaluation)
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Open AccessArticle State Derivation of a 12-Axis Gyroscope-Free Inertial Measurement Unit
Sensors 2011, 11(3), 3145-3162; https://doi.org/10.3390/s110303145
Received: 28 December 2010 / Revised: 6 February 2011 / Accepted: 22 February 2011 / Published: 14 March 2011
Cited by 8 | PDF Full-text (445 KB) | HTML Full-text | XML Full-text
Abstract
The derivation of linear acceleration, angular acceleration, and angular velocity states from a 12-axis gyroscope-free inertial measurement unit that utilizes four 3-axis accelerometer measurements at four distinct locations is reported. Particularly, a new algorithm which derives the angular velocity from its quadratic form
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The derivation of linear acceleration, angular acceleration, and angular velocity states from a 12-axis gyroscope-free inertial measurement unit that utilizes four 3-axis accelerometer measurements at four distinct locations is reported. Particularly, a new algorithm which derives the angular velocity from its quadratic form and derivative form based on the context-based interacting multiple model is demonstrated. The performance of the system was evaluated under arbitrary 3-dimensional motion. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle A High Temperature Capacitive Humidity Sensor Based on Mesoporous Silica
Sensors 2011, 11(3), 3135-3144; https://doi.org/10.3390/s110303135
Received: 30 January 2011 / Revised: 20 February 2011 / Accepted: 25 February 2011 / Published: 14 March 2011
Cited by 24 | PDF Full-text (604 KB) | HTML Full-text | XML Full-text
Abstract
Capacitive sensors are the most commonly used devices for the detection of humidity because they are inexpensive and the detection mechanism is very specific for humidity. However, especially for industrial processes, there is a lack of dielectrics that are stable at high temperature
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Capacitive sensors are the most commonly used devices for the detection of humidity because they are inexpensive and the detection mechanism is very specific for humidity. However, especially for industrial processes, there is a lack of dielectrics that are stable at high temperature (>200 °C) and under harsh conditions. We present a capacitive sensor based on mesoporous silica as the dielectric in a simple sensor design based on pressed silica pellets. Investigation of the structural stability of the porous silica under simulated operating conditions as well as the influence of the pellet production will be shown. Impedance measurements demonstrate the utility of the sensor at both low (90 °C) and high (up to 210 °C) operating temperatures. Full article
(This article belongs to the Special Issue Gas Sensors - 2010)
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Open AccessArticle Simple Random Sampling-Based Probe Station Selection for Fault Detection in Wireless Sensor Networks
Sensors 2011, 11(3), 3117-3134; https://doi.org/10.3390/s110303117
Received: 10 January 2011 / Revised: 28 February 2011 / Accepted: 1 March 2011 / Published: 14 March 2011
Cited by 3 | PDF Full-text (1205 KB) | HTML Full-text | XML Full-text
Abstract
Fault detection for wireless sensor networks (WSNs) has been studied intensively in recent years. Most existing works statically choose the manager nodes as probe stations and probe the network at a fixed frequency. This straightforward solution leads however to several deficiencies. Firstly, by
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Fault detection for wireless sensor networks (WSNs) has been studied intensively in recent years. Most existing works statically choose the manager nodes as probe stations and probe the network at a fixed frequency. This straightforward solution leads however to several deficiencies. Firstly, by only assigning the fault detection task to the manager node the whole network is out of balance, and this quickly overloads the already heavily burdened manager node, which in turn ultimately shortens the lifetime of the whole network. Secondly, probing with a fixed frequency often generates too much useless network traffic, which results in a waste of the limited network energy. Thirdly, the traditional algorithm for choosing a probing node is too complicated to be used in energy-critical wireless sensor networks. In this paper, we study the distribution characters of the fault nodes in wireless sensor networks, validate the Pareto principle that a small number of clusters contain most of the faults. We then present a Simple Random Sampling-based algorithm to dynamic choose sensor nodes as probe stations. A dynamic adjusting rule for probing frequency is also proposed to reduce the number of useless probing packets. The simulation experiments demonstrate that the algorithm and adjusting rule we present can effectively prolong the lifetime of a wireless sensor network without decreasing the fault detected rate. Full article
(This article belongs to the Section Physical Sensors)
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