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Toxic and nontoxic volatile organic compound (VOC) gases are emitted into the atmosphere from certain solids and liquids as a consequence of wastage and some common daily activities. Inhalation of toxic VOCs has an adverse effect on human health, so it is necessary to monitor their concentration in the atmosphere. In this work, we report on the fabrication of inorganic nanotube (INT)-tungsten disulfide, paper-based graphene–PEDOT:PSS sheet and WS2 nanotube-modified conductive paper-based chemiresistors for VOC gas sensing. The WS2 nanotubes were fabricated by a two-step reaction, that is oxide reduction and sulfurization, carried out at 900 °C. The synthesized nanotubes were characterized by FE-SEM, EDS, XRD, Raman spectroscopy, and TEM. The synthesized nanotubes were 206–267 nm in diameter. The FE-SEM results show the length of the nanotubes to be 4.5–8 µm. The graphene–PEDOT:PSS hybrid conductive paper sheet was fabricated by a continuous coating process. Then, WS2 nanotubes were drop-cast onto conductive paper for fabrication of the chemiresistors. The feasibility and sensitivity of the WS2 nanotube-modified paper-based chemiresistor were tested in four VOC gases at different concentrations at room temperature (RT). Experimental results show the proposed sensor to be more sensitive to butanol gas when the concentration ranges from 50 to 1000 ppm. The limit of detection (LOD) of this chemiresistor for butanol gas was 44.92 ppm. The WS2 nanotube-modified paper-based chemiresistor exhibits good potential as a VOC sensor with the advantages of flexibility, easy fabrication, and low fabrication cost.

Paper-based sensors are a new alternative technology for fabricating simple, low-cost, portable and disposable analytical devices for many application areas including clinical diagnosis, food quality control and environmental monitoring. The unique properties of paper which allow passive liquid transport and compatibility with chemicals/biochemicals are the main advantages of using paper as a sensing platform. Depending on the main goal to be achieved in paper-based sensors, the fabrication methods and the analysis techniques can be tuned to fulfill the needs of the end-user. Current paper-based sensors are focused on microfluidic delivery of solution to the detection site whereas more advanced designs involve complex 3-D geometries based on the same microfluidic principles. Although paper-based sensors are very promising, they still suffer from certain limitations such as accuracy and sensitivity. However, it is anticipated that in the future, with advances in fabrication and analytical techniques, that there will be more new and innovative developments in paper-based sensors. These sensors could better meet the current objectives of a viable low-cost and portable device in addition to offering high sensitivity and selectivity, and multiple analyte discrimination. This paper is a review of recent advances in paper-based sensors and covers the following topics: existing fabrication techniques, analytical methods and application areas. Finally, the present challenges and future outlooks are discussed.

We demonstrate novel graphite-on-paper piezoresistive devices. The graphite was used as sensing component. The fabrication process can be finished in a short time with simple tools (e.g., a scissor and a pencil). A small array of six paper-based piezoresistive devices is made. The whole device is flexible. The test results showed that the change of resistance was proportional to the applied force. A paper-based weighing balance was also made as an example of applications. This novel array of paper-based piezoresistive devices will open wide applications in force and acceleration sensing areas.

Since 2011, an annual award system was instituted to recognize outstanding Sensors papers that are related to sensing technologies and applications and meet the aims, scope and high standards of this journal [1–4]. This year, the winners were chosen by the Section Editor-in-Chiefs of Sensors from among all the papers published in 2011 to track citations. Reviews and full research articles were considered separately. We gladly announce that the following eight papers were awarded the Sensors Best Paper Award in 2015.[...]

With the start of 2011, Sensors is instituting an annual award to recognize outstanding papers related to sensing technologies and applications that meet the aims, scope and high standards of this journal. We are pleased to announce the first “Sensors Best Paper Award” for 2011. Nominations were solicited from the Section Editor-in-Chiefs of Sensors, with all papers published in 2005 eligible for consideration. [...]

Simultaneous sensing of multiple gases by a single fluorescent-based gas sensor is of utmost importance for practical applications. Such sensing is strongly hindered by cross-sensitivity effects. In this study, we propose a novel analysis method to ameliorate such hindrance. The trial sensor used here was fabricated by coating platinum(II) meso-tetrakis(pentafluorophenyl)porphyrin (PtTFPP) and eosin-Y dye molecules on both sides of a filter paper for sensing O2 and NH3 gases simultaneously. The fluorescent peak intensities of the dyes can be quenched by the analytes and this phenomenon is used to identify the gas concentrations. Ideally, each dye is only sensitive to one gas species. However, the fluorescent peak related to O2 sensing is also quenched by NH3 and vice versa. Such cross-sensitivity strongly hinders gas concentration detection. Therefore, we have studied this cross-sensitivity effect systematically and thus proposed a new analysis method for accurate estimation of gas concentration. Comparing with a traditional method (neglecting cross-sensitivity), this analysis improves O2-detection error from −11.4% ± 34.3% to 2.0% ± 10.2% in a mixed background of NH3 and N2.

Falls are unusual actions that cause a significant health risk among older people. The growing percentage of people of old age requires urgent development of fall detection and prevention systems. The emerging technology focuses on developing such systems to improve quality of life, especially for the elderly. A fall prevention system tries to predict and reduce the risk of falls. In contrast, a fall detection system observes the fall and generates a help notification to minimize the consequences of falls. A plethora of technical and review papers exist in the literature with a primary focus on fall detection. Similarly, several studies are relatively old, with a focus on wearables only, and use statistical and threshold-based approaches with a high false alarm rate. Therefore, this paper presents the latest research trends in fall detection and prevention systems using Machine Learning (ML) algorithms. It uses recent studies and analyzes datasets, age groups, ML algorithms, sensors, and location. Additionally, it provides a detailed discussion of the current trends of fall detection and prevention systems with possible future directions. This overview can help researchers understand the current systems and propose new methodologies by improving the highlighted issues. ispartof: SENSORS vol:21 issue:15 ispartof: location:Switzerland status: published

This paper is a survey of existing and upcoming industrial applications of terahertz technologies, comprising sections on polymers, paint and coatings, pharmaceuticals, electronics, petrochemicals, gas sensing, and paper and wood industries. Finally, an estimate of the market size and growth rates is given, as obtained from a comparison of market reports.

In this paper, we propose a paper-based pattern switchable antenna system using inkjet-printing technology for bi-direction sensor applications. The proposed antenna system is composed of two directional bow-tie antennas and a switching network. The switching network consists of a single-pole-double-throw (SPDT) switch and a balun element. A double-sided parallel-strip line (DSPSL) is employed to convert the unbalanced microstrip mode to the balanced strip mode. Two directional bow-tie antennas have different radiation patterns because of the different orientation of the reflectors and antennas. It is demonstrated from electromagnetic (EM) simulation and measurement that the radiation patterns of the proposed antenna are successfully switched by the SPDT switch.

In this work, we report novel relative humidity sensors realized by functionalising fibre Bragg gratings with chitosan, a moisture-sensitive biopolymer never used before for this kind of fibre optic sensor. The swelling capacity of chitosan is fundamental to the sensing mechanism. Different samples were fabricated, testing the influence of coating design and deposition procedure on sensor performance. The sensitivity of the sensors was measured in an airtight humidity-controlled chamber using saturated chemical salt solutions. The best result in terms of sensitivity was obtained for a sensor produced on filter paper substrate. Tests for each design were performed in the environment, lasted several days, and all designs were independently re-tested at different seasons of the year. The produced sensors closely followed the ambient humidity variation common to the 24-h circadian cycle.

Traditional techniques of active thermography require an external source of energy used for excitation, usually in the form of high power lamps or ultrasonic devices. In this paper, the author presents an alternative approach based on the self-heating effect observable in polymer-based structures during cyclic loading. The presented approach is based on, firstly, determination of bending resonance frequencies of a tested structure, and then, on excitation of a structure with a multi-harmonic signal constructed from the harmonics with frequencies of determined resonances. Following this, heating-up of a tested structure occurs in the location of stress concentration and mechanical energy dissipation due to the viscoelastic response of a structure. By applying multi-harmonic signal, one ensures coverage of the structure by such heated regions. The concept is verified experimentally on artificially damaged composite specimens. The results demonstrate the presented approach and indicate its potential, especially when traditional methods of excitation with an external structure for thermographic inspection cannot be applied.

This paper presents a miniaturized Doppler radar that can be used as a motion sensor for low-cost Internet of things (IoT) applications. For the first time, a radar front-end and its antenna are integrated on a multilayer cellulose-based substrate, built-up by alternating paper, glue and metal layers. The circuit exploits a distributed microstrip structure that is realized using a copper adhesive laminate, so as to obtain a low-loss conductor. The radar operates at 24 GHz and transmits 5 mW of power. The antenna has a gain of 7.4 dBi and features a half power beam-width of 48 degrees. The sensor, that is just the size of a stamp, is able to detect the movement of a walking person up to 10 m in distance, while a minimum speed of 50 mm/s up to 3 m is clearly measured. Beyond this specific result, the present paper demonstrates that the attractive features of cellulose, including ultra-low cost and eco-friendliness (i.e., recyclability and biodegradability), can even be exploited for the realization of future high-frequency hardware. This opens opens the door to the implementation on cellulose of devices and systems which make up the “sensing layer” at the base of the IoT ecosystem.

This paper presents the integration of an inductor by complementary metal-oxide-semiconductor (CMOS) compatible processes for integrated smart microsensor systems that have been developed to monitor the motion and vital signs of humans in various environments. Integration of radio frequency transmitter (RF) technology with complementary metal-oxide-semiconductor/micro electro mechanical systems (CMOS/MEMS) microsensors is required to realize the wireless smart microsensors system. The essential RF components such as a voltage controlled RF-CMOS oscillator (VCO), spiral inductors for an LC resonator and an integrated antenna have been fabricated and evaluated experimentally. The fabricated RF transmitter and integrated antenna were packaged with subminiature series A (SMA) connectors, respectively. For the impedance (50 Ω) matching, a bonding wire type inductor was developed. In this paper, the design and fabrication of the bonding wire inductor for impedance matching is described. Integrated techniques for the RF transmitter by CMOS compatible processes have been successfully developed. After matching by inserting the bonding wire inductor between the on-chip integrated antenna and the VCO output, the measured emission power at distance of 5 m from RF transmitter was -37 dBm (0.2 μW).

Oxygen is an important parameter for organic-waste composting, and continuous control of the oxygen in a composting pile may be beneficial. The oxygen consumption rate can be used to measure the degree of biological oxidation and decomposition of organic matter. However, without having a real-time online device to monitor oxygen levels in the composting pile, the adjustment and optimization of the composting process cannot be directly implemented. In the present study, we researched and developed such a system, and then tested its stability, reliability, and characteristics. The test results showed that the equipment was accurate and stable, and produced good responses with good repeatability. The equilibrium time required to detect oxygen concentration in the composting pile was 50 s, and the response time for oxygen detection was less than 2 s. The equipment could monitor oxygen concentration online and in real time to optimize the aeration strategy for the compost depending on the concentration indicated by the oxygen-measuring equipment.

This paper discusses a novel dynamic resonant wall shear stress sensor concept based on an oscillating sensor operating near resonance. The interaction between the oscillating sensor surface and the fluid above it is modelled using the unsteady laminar boundary layer equations. The numerical experiment shows that the effect of the oscillating shear stress is well correlated by the Hummer number, the ratio of the steady shear force caused by the outside flow to the oscillating viscous force created by the sensor motion. The oscillating shear stress predicted by the fluid model is used in a mechanical model of the sensor to predict the sensor’s dynamic motion. Static calibration curves for amplitude and frequency influences are predicted. These results agree with experimental results on some extent, and shows some expectation for further development of the dynamic resonant sensor concept.

Due to the wide potential applications of wireless sensor networks, this topic has attracted great attention. The strict energy constraints of sensor nodes result in great challenges for energy efficiency. This paper proposes an energy-efficient organization method. The organization of wireless sensor networks is formulated for target tracking. Target localization is achieved by collaborative sensing with multi-sensor fusion. The historical localization results are utilized for adaptive target trajectory forecasting. Combining autoregressive moving average (ARMA) model and radial basis function networks (RBFNs), robust target position forecasting is performed. Moreover, an energy-efficient organization method is presented to enhance the energy efficiency of wireless sensor networks. The sensor nodes implement sensing tasks are awakened in a distributed manner. When the sensor nodes transfer their observations to achieve data fusion, the routing scheme is obtained by ant colony optimization. Thus, both the operation and communication energy consumption can be minimized. Experimental results verify that the combination of ARMA model and RBFN can estimate the target position efficiently and energy saving is achieved by the proposed organization method in wireless sensor networks.

This paper reports a micromachined capacitive pressure sensor intended for applications that require mechanical robustness. The device is constructed with two micromachined metal plates and an intermediate polymer layer that is soft enough to deform in a target pressure range. The plates are formed of micromachined stainless steel fabricated by batch-compatible micro-electro-discharge machining. A polyurethane roomtemperature- vulcanizing liquid rubber of 38-μm thickness is used as the deformable material. This structure eliminates both the vacuum cavity and the associated lead transfer challenges common to micromachined capacitive pressure sensors. For frequency-based interrogation of the capacitance, passive inductor-capacitor tanks are fabricated by combining the capacitive sensor with an inductive coil. The coil has 40 turns of a 127-μmdiameter copper wire. Wireless sensing is demonstrated in liquid by monitoring the variation in the resonant frequency of the tank via an external coil that is magnetically coupled with the tank. The sensitivity at room temperature is measured to be 23-33 ppm/KPa over a dynamic range of 340 KPa, which is shown to match a theoretical estimation. Temperature dependence of the tank is experimentally evaluated.

Steel corrosion resulting from the penetration of chloride ions or carbon dioxide is a major cause of degradation for reinforced concrete structures,. The objective of the present investigation was to develop a low-cost sensor for steel corrosion, which is based on a very simple physical principle. The flat end of a cut optical fiber is coated with an iron thin film using the ion sputtering technique. Light is then sent into a fiber embedded in concrete and the reflected signal is monitored. Initially, most of the light is reflected by the iron layer. When corrosion occurs to remove the iron layer, a significant portion of the light power will leave the fiber at its exposed end, and the reflected power is greatly reduced. Monitoring of the reflected signal is hence an effective way to assess if the concrete environment at the location of the fiber tip may induce steel corrosion or not. In this paper, first the principle of the corrosion sensor and its fabrication are described. The sensing principle is then verified by experimental results. Sensor packaging for practical installation will be presented and the performance of the packaged sensors is assessed by additional experiments.

The paper describes a new PC and LabVIEW software package based system for electrochemical research. An overview of well known electrochemical methods, such as potential measurements, galvanostatic and potentiostatic method, cyclic voltammetry and EIS is given. Electrochemical impedance spectroscopy has been adapted for systems containing large capacitances. For signal generation and recording of the response of investigated electrochemical cell, a measurement and control system was developed, based on a PC P4. The rest of the hardware consists of a commercially available AD-DA converter and an external interface for analog signal processing. The interface is a result of authors own research. The software platform for desired measurement methods is LabVIEW 8.2 package, which is regarded as a high standard in the area of modern virtual instruments. The developed system was adjusted, tested and compared with commercially available system and ORCAD simulation.

This paper describes artificial neural network ( ANN) based prediction of the response of a fiber optic sensor using evanescent field absorption (EFA). The sensing probe of the sensor is made up a bundle of five PCS fibers to maximize the interaction of evanescent field with the absorbing medium. Different backpropagation algorithms are used to train the multilayer perceptron ANN. The Levenberg-Marquardt algorithm, as well as the other algorithms used in this work successfully predicts the sensor responses.

Wireless multimedia sensor networks (WMSN) have recently emerged as one of the most important technologies, driven by the powerful multimedia signal acquisition and processing abilities. Target classification is an important research issue addressed in WMSN, which has strict requirement in robustness, quickness and accuracy. This paper proposes a collaborative semi-supervised classifier learning algorithm to achieve durative online learning for support vector machine (SVM) based robust target classification. The proposed algorithm incrementally carries out the semi-supervised classifier learning process in hierarchical WMSN, with the collaboration of multiple sensor nodes in a hybrid computing paradigm. For decreasing the energy consumption and improving the performance, some metrics are introduced to evaluate the effectiveness of the samples in specific sensor nodes, and a sensor node selection strategy is also proposed to reduce the impact of inevitable missing detection and false detection. With the ant optimization routing, the learning process is implemented with the selected sensor nodes, which can decrease the energy consumption. Experimental results demonstrate that the collaborative hybrid semi-supervised classifier learning algorithm can effectively implement target classification in hierarchical WMSN. It has outstanding performance in terms of energy efficiency and time cost, which verifies the effectiveness of the sensor nodes selection and ant optimization routing.

Quantitative Accelerated Life Testing (QALT) is a solution for assessing the reliability of Micro Electro Mechanical Systems (MEMS). A procedure for QALT is shown in this paper and an attempt to assess the reliability level for a batch of MEMS accelerometers is reported. The testing plan is application-driven and contains combined tests: thermal (high temperature) and mechanical stress. Two variants of mechanical stress are used: vibration (at a fixed frequency) and tilting. Original equipment for testing at tilting and high temperature is used. Tilting is appropriate as application-driven stress, because the tilt movement is a natural environment for devices used for automotive and aerospace applications. Also, tilting is used by MEMS accelerometers for anti-theft systems. The test results demonstrated the excellent reliability of the studied devices, the failure rate in the “worst case” being smaller than 10 -7 h -1 . Keywords: reliability, accelerometers, MEMS, tilting, vibration.

Hai Huang*, Guang Meng, and Jieyu Chen State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, 800 DongChuan Road, Shanghai, 200240, People Republic of China); E-mails: huanghai2003@gmail.com; gmeng@sjtu.edu.cn * Author to whom correspondence should be addressed: huanghai2003@gmail.com Received: 27 June 2007 / Accepted: 2 August 2007 / Published: 3 August 2007 Abstract: Incorporating the velocity slip effect of the gas flow at the solid boundary, the performance and dynamic response of a micro gas-bearing-rotor system are investigated in this paper. For the characteristic length scale of the micro gas bearing, the gas flow in the bearing resides in the slip regime rather than in the continuum regime. The modified Reynolds equations of different slip models are presented. Gas pressure distribution and load carrying capacity are obtained by solving the Reynolds equations with finite different method (FDM). Comparing results from different models, it is found that the second order slip model agrees reasonably well with the benchmarked solutions obtained from the linearized Boltzmann equation. Therefore, dynamic coefficients derived from the second order slip model are employed to evaluate the linear dynamic stability and vibration characteristics of the system. Compared with the continuum flow model, the slip effect reduces dynamic coefficients of the micro gas bearing, and the threshold speed for stable operation is consequently raised. Also, dynamic analysis shows that the system responses change with variation of the operating parameters including the eccentricity ratio, the rotational speed, and the unbalance ratio. Keywords: MEMS, Micro rotor, Micro gas bearing, Velocity slip, Mechanical performance, Stability, Dynamical response.

Target tracking is usually a challenging application for wireless sensor networks (WSNs) because it is always computation-intensive and requires real-time processing. This paper proposes a practical target tracking system based on the auto regressive moving average (ARMA) model in a distributed peer-to-peer (P2P) signal processing framework. In the proposed framework, wireless sensor nodes act as peers that perform target detection, feature extraction, classification and tracking, whereas target localization requires the collaboration between wireless sensor nodes for improving the accuracy and robustness. For carrying out target tracking under the constraints imposed by the limited capabilities of the wireless sensor nodes, some practically feasible algorithms, such as the ARMA model and the 2-D integer lifting wavelet transform, are adopted in single wireless sensor nodes due to their outstanding performance and light computational burden. Furthermore, a progressive multi-view localization algorithm is proposed in distributed P2P signal processing framework considering the tradeoff between the accuracy and energy consumption. Finally, a real world target tracking experiment is illustrated. Results from experimental implementations have demonstrated that the proposed target tracking system based on a distributed P2P signal processing framework can make efficient use of scarce energy and communication resources and achieve target tracking successfully.

Xue Wang *, Jun-Jie Ma , Sheng Wang and Dao-Wei Bi State Key Laboratory of Precision Measurement Technology and Instrument, Department of Precision Instruments, Tsinghua University, Beijing 100084, P. R. China; E-mails: {mjj, wang_sheng00, bdw02} @mails.tsinghua.edu.cn. * Author to whom correspondence should be addressed; E-mail: wangxue@mail.tsinghua.edu.cn. Received: 25 April 2007 / Accepted: 8 May 2007 / Published: 10 May 2007 Abstract: The limited energy supply of wireless sensor networks poses a great challenge for the deployment of wireless sensor nodes. In this paper, we focus on energy-efficient coverage with distributed particle swarm optimization and simulated annealing. First, the energy-efficient coverage problem is formulated with sensing coverage and energy consumption models. We consider the network composed of stationary and mobile nodes. Second, coverage and energy metrics are presented to evaluate the coverage rate and energy consumption of a wireless sensor network, where a grid exclusion algorithm extracts the coverage state and Dijkstra’s algorithm calculates the lowest cost path for communication. Then, a hybrid algorithm optimizes the energy consumption, in which particle swarm optimization and simulated annealing are combined to find the optimal deployment solution in a distributed manner. Simulated annealing is performed on multiple wireless sensor nodes, results of which are employed to correct the local and global best solution of particle swarm optimization. Simulations of wireless sensor node deployment verify that coverage performance can be guaranteed, energy consumption of communication is conserved after deployment optimization and the optimization performance is boosted by the distributed algorithm. Moreover, it is demonstrated that energy efficiency of wireless sensor networks is enhanced by the proposed optimization algorithm in target tracking applications. Keywords: Wireless sensor network, deployment optimization, energy efficiency, particle swarm optimization, simulated annealing.

The effectiveness of wireless sensor networks (WSNs) depends on the coverage and target detection probability provided by dynamic deployment, which is usually supported by the virtual force (VF) algorithm. However, in the VF algorithm, the virtual force exerted by stationary sensor nodes will hinder the movement of mobile sensor nodes. Particle swarm optimization (PSO) is introduced as another dynamic deployment algorithm, but in this case the computation time required is the big bottleneck. This paper proposes a dynamic deployment algorithm which is named “virtual force directed co-evolutionary particle swarm optimization†(VFCPSO), since this algorithm combines the co-evolutionary particle swarm optimization (CPSO) with the VF algorithm, whereby the CPSO uses multiple swarms to optimize different components of the solution vectors for dynamic deployment cooperatively and the velocity of each particle is updated according to not only the historical local and global optimal solutions, but also the virtual forces of sensor nodes. Simulation results demonstrate that the proposed VFCPSO is competent for dynamic deployment in WSNs and has better performance with respect to computation time and effectiveness than the VF, PSO and VFPSO algorithms.

Electromagnetic flowmeters are used to measure the speed of water flow in water distribution systems. Corrosion problem in metal pipelines can be solved by cathodic protection methods. This paper presents a research on corruptive effects of the cathodic protection system on electromagnetic flowmeter depending on its measuring principle. Experimental measurements are realized on the water distribution pipelines of the Izmir Municipality, Department of Water and Drainage Administration (IZSU) in Turkey and measurement results are given. Experimental results proved that the values measured by the electromagnetic flowmeter (EMF) are affected by cathodic protection system current. Comments on the measurement results are made and precautions to be taken are proposed.

Sensor systems are not always equipped with the ability to track targets. Sudden maneuvers of a target can have a great impact on the sensor system, which will increase the miss rate and rate of false target detection. The use of the generic particle filter (PF) algorithm is well known for target tracking, but it can not overcome the degeneracy of particles and cumulation of estimation errors. In this paper, we propose an improved PF algorithm called PF-RBF. This algorithm uses the radial-basis function network (RBFN) in the sampling step for dynamically constructing the process model from observations and updating the value of each particle. With the RBFN sampling step, PF-RBF can give an accurate proposal distribution and maintain the convergence of a sensor system. Simulation results verify that PF-RBF performs better than the Unscented Kalman Filter (UKF), PF and Unscented Particle Filter (UPF) in both robustness and accuracy whether the observation model used for the sensor system is linear or nonlinear. Moreover, the intrinsic property of PF-RBF determines that, when the particle number exceeds a certain amount, the execution time of PF-RBF is less than UPF. This makes PF-RBF a better candidate for the sensor systems which need many particles for target tracking.

Optical sensors have been investigated and widely deployed in industrial and scientific measurement and control processes, mainly due to their accuracy, high sensitivity and immunity to electromagnetic interference and other unique characteristics. They are especially suited for harsh environments applications, where no commercial electrical sensors are available for long-term stable operations. This paper reports a novel contact optical high temperature sensor targeting at harsh environments. Utilizing birefringent single crystal sapphire as the sensing element and white light interferometric signal processing techniques, an optical birefringence based temperature sensor was developed. With a simple mechanically structured sensing probe, and an optical spectrum-coded interferometric signal processor, it has been tested to measure temperature up to 1600 °C with high accuracy, high resolution, and long-term measurement stability.

In the oil industry, huge saving may be made if suitable multi-interface level measurement systems are employed for effectively monitoring crude oil separators and efficient control of their operation. A number of techniques, e.g. externally mounted displacers, differential pressure transmitters and capacitance rod devices, have been developed to measure the separation process with gas, oil, water and other components. Because of the unavailability of suitable multi-interface level measurement systems, oil separators are currently operated by the trial-and-error approach. In this paper some conventional techniques, which have been used for level measurement in industry, and new development are discussed.

In the paper a discussion on how to optimize LonWorks/EIA-709 sensor networking technology for wireless applications, in presented. Main solutions offered by Local Operating Networks (LON, LonWorks) platform attractive for wireless communication, that is, the send-on-delta concept and the sleep mode, are displayed. The predictive p-persistent CSMA MAC protocol constituting the heart of the communication capability of LON networks is analysed in detail. Next, the message services are described, and the analytical evaluation of delivery reliability is derived. Performance evaluation based on simulation results for unicast traffic is presented first. In order to highlight the robustness of the predictive CSMA to overload situations, the saturation performance for a general case load scenario including multicast transactions is reported. The methods of effective management of energy consumption in LonWorks networks are discussed. Finally, the LON design tradeoffs are summarized.

This study investigates how the use of a Hitman ST300 acoustic sensor can help identify the best forest stands to be used as supply sources for the production of Machine Stress-Rated (MSR) lumber. Using two piezoelectric sensors, the ST300 measures the velocity of a mechanical wave induced in a standing tree. Measurements were made on 333 black spruce (Picea mariana (Mill.) BSP) trees from the North Shore region, Quebec (Canada) selected across a range of locations and along a chronosequence of elapsed time since the last fire (TSF). Logs were cut from a subsample of 39 trees, and sawn into 77 pieces of 38 mm × 89 mm cross-section before undergoing mechanical testing according to ASTM standard D-4761. A linear regression model was developed to predict the static modulus of elasticity of lumber using tree acoustic velocity and stem diameter at 1.3 m above ground level (R2 = 0.41). Results suggest that, at a regional level, 92% of the black spruce trees meet the requirements of MSR grade 1650Fb-1.5E, whilst 64% and 34% meet the 2100Fb-1.8E and 2400Fb-2.0E, respectively. Mature stands with a TSF < 150 years had 11 and 18% more boards in the latter two categories, respectively, and therefore represented the best supply source for MSR lumber.

Inkjet printing is an advanced printing technology that has been used to develop conducting layers, interconnects and other features on a variety of substrates. It is an additive manufacturing process that offers cost-effective, lightweight designs and simplifies the fabrication process with little effort. There is hardly sufficient research on tactile sensors and inkjet printing. Advancements in materials science and inkjet printing greatly facilitate the realization of sophisticated tactile sensors. Starting from the concept of capacitive sensing, a brief comparison of printing techniques, the essential requirements of inkjet-printing and the attractive features of state-of-the art inkjet-printed tactile sensors developed on diverse substrates (paper, polymer, glass and textile) are presented in this comprehensive review. Recent trends in inkjet-printed wearable/flexible and foldable tactile sensors are evaluated, paving the way for future research.

In this paper we present an inexpensive electronic measurement instrumentation developed in our laboratory, to measure and plot the impedance of a loaded fuel cell or battery. Impedance measurements were taken by using the load modulation method. This instrumentation has been developed around a VXI system stand which controls electronic cards. Software under Hpvee® was developed for automatic measurements and the layout of the impedance of the fuel cell on load. The measurement environment, like the ambient temperature, the fuel cell temperature, the level of the hydrogen, etc…, were taken with several sensors that enable us to control the measurement. To filter the noise and the influence of the 50Hz, we have implemented a synchronous detection which filters in a very narrow way around the useful signal. The theoretical result obtained by a simulation under Pspice® of the method used consolidates the choice of this method and the possibility of obtaining correct and exploitable results. The experimental results are preliminary results on a 12V vehicle battery, having an inrush current of 330A and a capacity of 40Ah (impedance measurements on a fuel cell are in progress, and will be the subject of a forthcoming paper). The results were plotted at various nominal voltages of the battery (12.7V, 10V, 8V and 5V) and with two imposed currents (0.6A and 4A). The Nyquist diagram resulting from the experimental data enable us to show an influence of the load of the battery on its internal impedance. The similitude in the graph form and in order of magnitude of the values obtained (both theoretical and practical) enables us to validate our electronic measurement instrumentation. One of the future uses for this instrumentation is to integrate it with several control sensors, on a vehicle as an embedded system to monitor the degradation of fuel cell membranes.

In this article, we report on the new design of a miniaturized strain microsensor. The proposed sensor utilizes the piezoresistive properties of doped single crystal silicon. Employing the Micro Electro Mechanical Systems (MEMS) technology, high sensor sensitivities and resolutions have been achieved. The current sensor design employs different levels of signal amplifications. These amplifications include geometric, material and electronic levels. The sensor and the electronic circuits can be integrated on a single chip, and packaged as a small functional unit. The sensor converts input strain to resistance change, which can be transformed to bridge imbalance voltage. An analog output that demonstrates high sensitivity (0.03mV/me), high absolute resolution (1μe) and low power consumption (100μA) with a maximum range of ±4000μe has been reported. These performance characteristics have been achieved with high signal stability over a wide temperature range (±50oC), which introduces the proposed MEMS strain sensor as a strong candidate for wireless strain sensing applications under harsh environmental conditions. Moreover, this sensor has been designed, verified and can be easily modified to measure other values such as force, torque…etc. In this work, the sensor design is achieved using Finite Element Method (FEM) with the application of the piezoresistivity theory. This design process and the microfabrication process flow to prototype the design have been presented.

and SangYong Han School of Computer Science and Engineering, Chung-Ang University 221, Heukseok-dong, Dongjak-gu, Seoul 156-756, Korea; E-mails: okchoi20@gmail.com; hansy@cau.ac.kr * Author to whom correspondence should be addressed. Received: 5 February 2008 / Accepted: 1 April 2008 / Published: 4 April 2008 Abstract: Nowadays Web users have clearly expressed their wishes to receive personalized services directly. Personalization is the way to tailor services directly to the immediate requirements of the user. However, the current Web Services System does not provide any features supporting this such as consideration of personalization of services and intelligent matchmaking. In this research a flexible, personalized Rule-based Web Services System to address these problems and to enable efficient search, discovery and construction across general Web documents and Semantic Web documents in a Web Services System is proposed. This system utilizes matchmaking among service requesters’, service providers’ and users’ preferences using a Rule-based Search Method, and subsequently ranks search results. A prototype of efficient Web Services search and construction for the suggested system is developed based on the current work. Keywords: Personalization, Web Services, Rule-based Web Services, Semantic Web, Matchmaking Engine 1. Introduction Web Services technology is rapidly emerging as a critical solution for information and system integration among departmental systems within an enterprise or between different enterprises. Web Services allow liberal exchange of information among different platforms and applications using open and flexible standards such as SOAP (Simple Object Access Protocol), WSDL (Web Services Description Language) and UDDI (Universal Description, Discovery and Integration). Clustering

Spatial as well as spectral resolution has a very important role to play in water resource management. It was a challenge to explore the groundwater and rainwater harvesting sites in the Aravalli Quartzite-Granite-Pegmatite Precambrian terrain of Delhi, India. Use of only panchromatic sensor data of IRS-1D satellite with 5.8-meter spatial resolution has the potential to infer lineaments and faults in this hard rock area. It is essential to identify the location of interconnected lineaments below buried pediment plains in the hard rock area for targeting sub-surface water resources. Linear Image Self Scanning sensor data of the same satellite with 23.5-meter resolution when merged with the panchromatic data has produced very good results in delineation of interconnected lineaments over buried pediment plains as vegetation anomaly. These specific locations of vegetation anomaly were detected as dark red patches in various hard rock areas of Delhi. Field investigation was carried out on these patches by resistivity and magnetic survey in parts of Jawaharlal Nehru University (JNU), Indira Gandhi national Open University, Research and Referral Hospital and Humayuns Tomb areas. Drilling was carried out in four locations of JNU that proved to be the most potential site with ground water discharge ranging from 20,000 to 30,000 liters per hour with 2 to 4 meters draw down. Further the impact of urbanization on groundwater recharging in the terrain was studied by generating Normalized difference Vegetation Index (NDVI) map which was possible to generate by using the LISS-III sensor of IRS-1D satellite. Selection of suitable sensors has definitely a cutting edge on natural resource exploration and management including groundwater.

The development of impedance-based array devices is hindered by a lack of robust platforms and methods upon which to evaluate and interrogate sensors. One aspect to be addressed is the development of measurement-time efficient techniques for broadband impedance spectroscopy of large electrode arrays. The objective of this work was to substantially increase the low frequency impedance measurement throughput capability of a large channel count array analyzer by developing true parallel measurement methods. The goal was achieved by Fourier transform-based analysis of simultaneously-acquired multi-channel time-based current and voltage data. Efficacy and quantitative analysis of the parallel approach at frequencies less than ca. 10 Hz as well as a combined sequential + parallel approach for efficient broadband impedance spectroscopy over 5-orders of magnitude in frequency is demonstrated through complex impedance measurement of arrays consisting of up to 100 elements.

Sensors based on the giant magnetoimpedance (GMI) effect in silicon steels were constructed. Strips of silicon steels (0.500 mm-thick, 35.0 mm-long) with widths ranging from 0.122 to 1.064 mm were cut from recycled transformer cores. Since a maximum GMI ratio of 300% and a maximum field sensitivity of 1.5%/Oe were observed in a 1.064 mm-wide sample at 200 kHz, the 1.064 mm-wide strips were chosen as sensing elements in a slot key switch, angular velocity sensor, current sensor and force sensor. The sensing elements were integrated into electronic circuits and the changes in impedance were monitored. Variations in voltage due to these changes were typically small and must therefore be amplified by the electronic circuits. For the current sensor and force sensor, the variation in the voltage drop across the GMI sensing element had non-linear variations with either current or force and a conversion formula from a computer program was therefore needed. The performance of the systems was tested. These sensing systems were stable, highly sensitive, hysteresis-free and could be produced on a mass scale. Based on their GMI effect, the silicon steels are versatile alternative low-cost sensors.

A navigation method for a lunar rover based on large scale wireless sensor networks is proposed. To obtain high navigation accuracy and large exploration area, high node localization accuracy and large network scale are required. However, the computational and communication complexity and time consumption are greatly increased with the increase of the network scales. A localization algorithm based on a spring model (LASM) method is proposed to reduce the computational complexity, while maintaining the localization accuracy in large scale sensor networks. The algorithm simulates the dynamics of physical spring system to estimate the positions of nodes. The sensor nodes are set as particles with masses and connected with neighbor nodes by virtual springs. The virtual springs will force the particles move to the original positions, the node positions correspondingly, from the randomly set positions. Therefore, a blind node position can be determined from the LASM algorithm by calculating the related forces with the neighbor nodes. The computational and communication complexity are O(1) for each node, since the number of the neighbor nodes does not increase proportionally with the network scale size. Three patches are proposed to avoid local optimization, kick out bad nodes and deal with node variation. Simulation results show that the computational and communication complexity are almost constant despite of the increase of the network scale size. The time consumption has also been proven to remain almost constant since the calculation steps are almost unrelated with the network scale size.

A gas diffusion sequential injection system with amperometric detection using aboron-doped diamond electrode was developed for the determination of sulfite. A gasdiffusion unit (GDU) was used to prevent interference from sample matrices for theelectrochemical measurement. The sample was mixed with an acid solution to generategaseous sulfur dioxide prior to its passage through the donor channel of the GDU. Thesulfur dioxide diffused through the PTFE hydrophobic membrane into a carrier solution of 0.1 M phosphate buffer (pH 8)/0.1% sodium dodecyl sulfate in the acceptor channel of theGDU and turned to sulfite. Then the sulfite was carried to the electrochemical flow cell anddetected directly by amperometry using the boron-doped diamond electrode at 0.95 V(versus Ag/AgCl). Sodium dodecyl sulfate was added to the carrier solution to preventelectrode fouling. This method was applicable in the concentration range of 0.2-20 mgSO32−/L and a detection limit (S/N = 3) of 0.05 mg SO32−/L was achieved. This method wassuccessfully applied to the determination of sulfite in wines and the analytical resultsagreed well with those obtained by iodimetric titration. The relative standard deviations forthe analysis of sulfite in wines were in the range of 1.0-4.1 %. The sampling frequency was65 h−1.

For microfabrications of biochips with micro fluidic channels, a large number of microfabrication techniques based on silicon or glass-based Micro-Electro-Mechanical System (MEMS) technologies were proposed in the last decade. In recent years, for low cost and mass production, polymer-based microfabrication techniques by microinjection molding and micro hot embossing have been proposed. These techniques, which require a proper photoresist, mask, UV light exposure, developing, and electroplating as a pre-process, are considered to have some problems. In this study, we propose a new microfabrication technology which consists of micro end-milling and powder blasting. This technique could be directly applied to fabricate the metal mold without any preprocesses. The metal mold with micro-channels is machined by micro end-milling, and then, burrs generated in the end-milling process are removed by powder blasting. From the experimental results, micro end-milling combined with powder blasting could be applied effectively for fabrication of the injection mold of biochips with micro fluidic channels.

This study is to develop a micromachining technology for a light guide panel(LGP) mold, whereby micro dot patterns are formed on a LGP surface by a single injection process instead of existing screen printing processes. The micro powder blasting technique is applied to form micro dot patterns on the LGP mold surface. The optimal conditions for masking, laminating, exposure, and developing processes to form the micro dot patterns are first experimentally investigated. A LGP mold with masked micro patterns is then machined using the micro powder blasting method and the machinability of the micro dot patterns is verified. A prototype LGP is test- injected using the developed LGP mold and a shape analysis of the patterns and performance testing of the injected LGP are carried out. As an additional approach, matte finishing, a special surface treatment method, is applied to the mold surface to improve the light diffusion characteristics, uniformity and brightness of the LGP. The results of this study show that the applied powder blasting method can be successfully used to manufacture LGPs with micro patterns by just single injection using the developed mold and thereby replace existing screen printing methods.

Recently, the magnetorheological (MR) polishing process has been examined as a new ultra-precision polishing technology for micro parts in MEMS applications. In the MR polishing process, the magnetic force plays a dominant role. This method uses MR fluids which contains micro abrasives as a polishing media. The objective of the present research is to shed light onto the material removal mechanism under various slurry conditions for polishing and to investigate surface characteristics, including shape analysis and surface roughness measurement, of spots obtained from the MR polishing process using alumina abrasives. A series of basic experiments were first performed to determine the optimum polishing conditions for BK7 glass using prepared slurries by changing the process parameters, such as wheel rotating speed and electric current. Using the obtained results, groove polishing was then performed and the results are investigated. Outstanding surface roughness of Ra=3.8nm was obtained on the BK7 glass specimen. The present results highlight the possibility of applying this polishing method to ultra-precision micro parts production, especially in MEMS applications.

A system for remotely measuring the distribution of air space charge in real time is developed. The system consists of a loudspeaker and an electric field antenna. By propagating a burst of directional sound wave from the speaker, a modulation in the space charge and, therefore, an electric field change at ground is produced. The distribution of the space charge density is derived from the E-field change which can be measured by the E- field antenna. The developed system has been confirmed by both laboratory and field experiments.

By introducing a percentage of conductive material during the manufacture of sewing thread, it is possible to obtain a fabric which is able to detect variations in pressure in certain areas. In previous experiments the existence of resistance variations has been demonstrated, although some constrains of cause and effect were found in the fabric. The research has been concentrated in obtaining a fabric that allows electronic detection of its shape changes. Additionally, and because a causal behavior is needed, it is necessary that the fabric recovers its original shape when the external forces cease. The structure of the fabric varies with the type of deformation applied. Two kinds of deformation are described: those caused by stretching and those caused by pressure. This last type of deformation gives different responses depending on the conductivity of the object used to cause the pressure. This effect is related to the type of thread used to manufacture the fabric. So, if the pressure is caused by a finger the response is different compared to the response caused by a conductive object. Another fact that has to be mentioned is that a pressure in a specific point of the fabric can affect other detection points depending on the force applied. This effect is related to the fabric structure. The goals of this article are validating the structure of the fabric used, as well as the study of the two types of deformation mentioned before.

Virtual Force Algorithm (VFA) is becoming a main solution to area coverage for homogeneous wireless sensor networks with random distribution of mobile sensor nodes. Consider the factors of the convergence, the boundary in Region Of Interest (ROI), effective distance of acting force and useless moving, etc, VFA is improved to overcome the above problems. Furthermore, an expression of exponential function for the relationship of virtual force is proposed to converge rapidly. Extensive simulation results indicate that these improved VFA get better performance in coverage rate, moving energy consumption, convergence etc. than original VFA.

Recently, the polymeric micro-fluidic biochip, often called LOC (lab-on-a-chip), has been focused as a cheap, rapid and simplified method to replace the existing biochemical laboratory works. It becomes possible to form miniaturized lab functionalities on a chip with the development of MEMS technologies. The micro-fluidic chips contain many micro-channels for the flow of sample and reagents, mixing, and detection tasks. Typical substrate materials for the chip are glass and polymers. Typical techniques for micro-fluidic chip fabrication are utilizing various micro pattern forming methods, such as wet-etching, micro-contact printing, and hot-embossing, micro injection molding, LIGA, and micro powder blasting processes, etc. In this study, to establish the basis of the micro pattern fabrication and mass production of polymeric micro-fluidic chips using injection molding process, micro machining method was applied to form micro-channels on the LOC molds. In the research, a series of machining experiments using micro end-mills were performed to determine optimum machining conditions to improve surface roughness and shape accuracy of designed simplified micro-channels. Obtained conditions were used to machine required mold inserts for micro-channels using micro end-mills. Test injection processes using machined molds and COC polymer were performed, and then the results were investigated.

The increasing number of structural collapses, slope failures and other natural disasters has lead to a demand for new sensors, sensor integration techniques and data processing strategies for deformation monitoring systems. In order to meet extraordinary accuracy requirements for displacement detection in recent deformation monitoring projects, research has been devoted to integrating Global Positioning System (GPS) as a monitoring sensor. Although GPS has been used for monitoring purposes worldwide, certain environments pose challenges where conventional processing techniques cannot provide the required accuracy with sufficient update frequency. Described is the development of a fully automated, continuous, real-time monitoring system that employs GPS sensors and pseudolite technology to meet these requirements in such environments. Ethernet and/or serial port communication techniques are used to transfer data between GPS receivers at target points and a central processing computer. The data can be processed locally or remotely based upon client needs. A test was conducted that illustrated a 10 mm displacement was remotely detected at a target point using the designed system. This information could then be used to signal an alarm if conditions are deemed to be unsafe.

This study investigated the feasibility of the micro powder blasting technique for the micro fabrication of sensor structures using the Pyrex glass to replace the existing silicon-based acceleration sensor fabrication processes. As the preliminary experiments, the effects of the blasting pressure, the mass flow rate of abrasive and the number of nozzle scanning times on erosion depth of the Pyrex and the soda lime glasses were examined. From the experimental results, optimal blasting conditions were selected for the Pyrex glass machining. The dimensions of the designed glass sensor was 1.7×1.7×0.6mm for the vibrating mass, and 2.9×0.7×0.2mm for the cantilever beam. The machining results showed that the dimensional errors of the machined glass sensor ranged from 3 μm in minimum to 20 μm in maximum. These results imply that the micro powder blasting method can be applied for the micromachining of glass-based acceleration sensors to replace the exiting method.