pH Induced switching in hydrogel coated fiber bragg grating sensor

In this paper we report a novel hydrogel functionalized optical Fiber Bragg Grating (FBG) sensor based on chemo-mechanical-optical sensing, and demonstrate its specific application in pH activated process monitoring. The sensing mechanism is based on the stress due to ion diffusion and polymer phase transition which produce strain in the FBG. This results in shift in the Bragg wavelength which is detected by an interrogator system. A simple dip coating method to coat a thin layer of hydrogel on the FBG has been established. The gel consists of sodium alginate and calcium chloride. Gel formation is observed in real-time by continuously monitoring the Bragg wavelength shift. We have demonstrated pH sensing in the range of pH of 2 to 10. Another interesting phenomenon is observed by swelling and deswelling of FBG functionalized with hydrogel by a sequence of alternate dipping between acidic and base solutions. It is observed that the Bragg wavelength undergoes reversible and repeatable pH dependent switching.

Novel piezoelectric thin film impact sensor: application in non-destructive material discrimination

We report on the design, development, and performance study of a packaged piezoelectric thin film impact sensor, and its potential application in non-destructive material discrimination. The impact sensing element employed was a thin circular diaphragm of flexible Phynox alloy. Piezoelectric ZnO thin film as an impact sensing layer was deposited on to the Phynox alloy diaphragm by RF reactive magnetron sputtering. Deposited ZnO thin film was characterized by X-ray diffraction (XRD), Atomic Force Microscopy (AFM), and Scanning Electron Microscopy (SEM) techniques. The d(31) piezoelectric coefficient value of ZnO thin film was 4.7 pm V-1, as measured by 4-point bending method. ZnO film deposited diaphragm based sensing element was properly packaged in a suitable housing made of High Density Polyethylene (HDPE) material. Packaged impact sensor was used in an experimental set-up, which was designed and developed in-house for non-destructive material discrimination studies. Materials of different densities (iron, glass, wood, and plastic) were used as test specimens for material discrimination studies. The analysis of output voltage waveforms obtained reveals lots of valuable information about the impacted material. Impact sensor was able to discriminate the test materials on the basis of the difference in their densities. The output response of packaged impact sensor shows high linearity and repeatability. The packaged impact sensor discussed in this paper is highly sensitive, reliable, and cost-effective.

Narrowband signal detection techniques in shallow ocean by acoustic vector sensor array

This paper presents the formulation and performance analysis of four techniques for detection of a narrowband acoustic source in a shallow range-independent ocean using an acoustic vector sensor (AVS) array. The array signal vector is not known due to the unknown location of the source. Hence all detectors are based on a generalized likelihood ratio test (GLRT) which involves estimation of the array signal vector. One non-parametric and three parametric (model-based) signal estimators are presented. It is shown that there is a strong correlation between the detector performance and the mean-square signal estimation error. Theoretical expressions for probability of false alarm and probability of detection are derived for all the detectors, and the theoretical predictions are compared with simulation results. It is shown that the detection performance of an AVS array with a certain number of sensors is equal to or slightly better than that of a conventional acoustic pressure sensor array with thrice as many sensors.

Naphthalene Carbohydrazone Based Dizinc(II) Chemosensor for a Pyrophosphate Ion and Its DNA Assessment Application in Polymerase Chain Reaction Products

A new naphthalene carbohydrazone based dizinc(II) complex has been synthesized and investigated to act as a highly selective fluorescence and visual sensor for a pyrophosphate ion with a quite low detection limit of 155 ppb; this has also been used to detect the pyrophosphate ion released from polymerase-chain-reaction.

Guided Ultrasonic Wave Propagation through Inaccessible Damage in a Folded Plate using Sensor-Actuator Network

Rapid diagnostics and virtual imaging of damages in complex structures like folded plate can help reduce the inspection time for guided wave based NDE and integrated SHM. Folded plate or box structure is one of the major structural components for increasing the structural strength. Damage in the folded plate, mostly in the form of surface breaking cracks in the inaccessible zone is a usual problem in aerospace structures. One side of the folded plate is attached (either riveted or bonded) to adjacent structure which is not accessible for immediate inspection. The sensor-actuator network in the form of a circular array is placed on the accessible side of the folded plate. In the present work, a circular array is employed for scanning the entire folded plate type structure for damage diagnosis and wave field visualization of entire structural panel. The method employs guided wave with relatively low frequency bandwidth of 100-300 kHz. Change in the response signal with respect to a baseline signal is used to construct a quantitative relationship with damage size parameters. Detecting damage in the folded plate by using this technique has significant potential for off-line and on-line SHM technologies. By employing this technique, surface breaking cracks on inaccessible face of the folded plate are detected without disassembly of structure in a realistic environment.

Maximizing transported data in a wireless sensor network: how much can the network transport before partition?

We consider a scenario where the communication nodes in a sensor network have limited energy, and the objective is to maximize the aggregate bits transported from sources to respective destinations before network partition due to node deaths. This performance metric is novel, and captures the useful information that a network can provide over its lifetime. The optimization problem that results from our approach is nonlinear; however, we show that it can be converted to a Multicommodity Flow (MCF) problem that yields the optimal value of the metric. Subsequently, we compare the performance of a practical routing strategy, based on Node Disjoint Paths (NDPs), with the ideal corresponding to the MCF formulation. Our results indicate that the performance of NDP-based routing is within 7.5% of the optimal.

A power-scalable RF CMOS receiver for 2.4 GHz Wireless Sensor Network applications

A power scalable receiver architecture is presented for low data rate Wireless Sensor Network (WSN) applications in 130nm RF-CMOS technology. Power scalable receiver is motivated by the ability to leverage lower run-time performance requirement to save power. The proposed receiver is able to switch power settings based on available signal and interference levels while maintaining requisite BER. The Low-IF receiver consists of Variable Noise and Linearity LNA, IQ Mixers, VGA, Variable Order Complex Bandpass Filter and Variable Gain and Bandwidth Amplifier (VGBWA) capable of driving variable sampling rate ADC. Various blocks have independent power scaling controls depending on their noise, gain and interference rejection (IR) requirements. The receiver is designed for constant envelope QPSK-type modulation with 2.4GHz RF input, 3MHz IF and 2MHz bandwidth. The chip operates at 1V Vdd with current scalable from 4.5mA to 1.3mA and chip area of 0.65mm2.

6PANview: Application performance conscious network monitoring for 6LoWPAN based WSNs

6PANview[1] is a Wireless Sensor Network(WSN) monitoring system for 6LoWPAN/RPL networks which we developed as an overlay network for a WSN application. A monitoring system, while performing its operations for maintaining the health of the monitored network, must also be conscious of its impact on the application performance, and must strive to minimize this impact. To this end, we propose a centralized scheduling algorithm within 6PANview which non-intrusively analyzes application traffic arrival patterns at the base station, identifies network idle periods and schedules monitoring activities. The proposed algorithm finds those periodic sequences which are likely to have given rise to the pattern of arrivals seen at the base station. Parts of those sequences are then extended to coarsely predict future traffic and find epochs where low traffic is predicted, in order to schedule monitoring traffic or other activities at these times. We present simulation results for the proposed prediction and scheduling algorithm and its implementation as part of 6PANview. As an enhancement, we briefly talk about using 6PANview's overlay network architecture for distributed scheduling.

Lamb wave based detection of damage in a stiffener bonded to a plate

Stiffener is one of the major components of aircraft structures to increase the load carrying capacity. Damage in the stiffener, mostly in the form of crack is an unavoidable problem in aerospace structures. Stiffener is bonded to the inner side of the aircraft panel which is not accessible for immediate inspection. A sensor-actuator network can be placed on the outer side of the panel that is accessible. Ultrasonic lamb waves are transmitted through stiffener using the sensoractuator network for detecting the presence of damages. The sensor-actuator network is placed on both halves of the stiffened section on the accessible surface of the plate. Detecting damage in stiffener by using this technique has significant potential for SHM technology. One of the major objectives of the present work is to determine the smallest detectable crack on the stiffener using the proposed technique. Wavelet based damage parameter correlation studies are carried out. In the proposed scheme, with increase in the damage size along the stiffener, it is found that the amplitude of the received signal decreases monotonically. The advantage of this technique is that the stiffened panels need not be disassembled in a realistic deployment of SHM system.

A Diffusion-Based Processor Reallocation Strategy for Tracking Multiple Dynamically Varying Weather Phenomena

Many meteorological phenomena occur at different locations simultaneously. These phenomena vary temporally and spatially. It is essential to track these multiple phenomena for accurate weather prediction. Efficient analysis require high-resolution simulations which can be conducted by introducing finer resolution nested simulations, nests at the locations of these phenomena. Simultaneous tracking of these multiple weather phenomena requires simultaneous execution of the nests on different subsets of the maximum number of processors for the main weather simulation. Dynamic variation in the number of these nests require efficient processor reallocation strategies. In this paper, we have developed strategies for efficient partitioning and repartitioning of the nests among the processors. As a case study, we consider an application of tracking multiple organized cloud clusters in tropical weather systems. We first present a parallel data analysis algorithm to detect such clouds. We have developed a tree-based hierarchical diffusion method which reallocates processors for the nests such that the redistribution cost is less. We achieve this by a novel tree reorganization approach. We show that our approach exhibits up to 25% lower redistribution cost and 53% lesser hop-bytes than the processor reallocation strategy that does not consider the existing processor allocation.

Optical bio-sensing devices based on etched fiber Bragg gratings coated with carbon nanotubes and graphene oxide along with a specific dendrimer

We demonstrate that etched fiber Bragg gratings (eFBGs) coated with single walled carbon nanotubes (SWNTs) and graphene oxide (GO) are highly sensitive and accurate biochemical sensors. Here, for detecting protein concanavalin A (Con A), mannose-functionalized poly(propyl ether imine) (PETIM) dendrimers (DMs) have been attached to the SWNTs (or GO) coated on the surface modified eFBG. The dendrimers act as multivalent ligands, having specificity to detect lectin Con A. The specificity of the sensor is shown by a much weaker response (factor of similar to 2500 for the SWNT and similar to 2000 for the GO coated eFBG) to detect non specific lectin peanut agglutinin. DM molecules functionalized GO coated eFBG sensors showed excellent specificity to Con A even in the presence of excess amount of an interfering protein bovine serum albumin. The shift in the Bragg wavelength (Delta lambda(B)) with respect to the lambda(B) values of SWNT (or GO)-DM coated eFBG for various concentrations of lectin follows Langmuir type adsorption isotherm, giving an affinity constant of similar to 4 x 10(7) M-1 for SWNTs coated eFBG and similar to 3 x 10(8) M-1 for the GO coated eFBG. (C) 2014 Elsevier B.V. All rights reserved.

Conducting polymer-carbon black nanocomposite sensor for volatile organic compounds and correlating sensor response by molecular dynamics

Volatile organic compounds (VOCs) are present in our every day used products such as plastics, cosmetics, air fresheners, paint, etc. The determination of amount of VOC present in atmosphere can be carried out via various sensors. In this work a nanocomposite of a novel thiophene based conducting polymer and carbon black is used as a volatile organic compound sensor. The fabricated 2 lead chemiresistor sensor was tested for vapours of toluene, acetone, cylcohexane, and carbon tetrachloride. The sensor responds to all the vapours, however, exhibit maximum response to toluene vapours. The sensor was evaluated for various concentrations of toluene. The lower limit of detection of the sensor is 15 +/- 10 ppm. The study of the effect of humidity on senor response to toluene showed that the response decreases at higher humidity conditions. The surface morphology of the nanocomposite was characterized by scanning electron microscopy. Diffuse reflectance spectroscopy was used to investigate the absorption of vapours by the nanocomposite film. Contact angle measurements were used to present the effect of water vapour on the toluene response of nanocomposite film. Solubility parameter of the conducting polymer is predicted by molecular dynamics. The sensing behaviour of the conducting polymer is correlated with solubility parameter of the polymer. Dispersion interaction of conducting polymer with toluene is believed to be the reason for the selective response towards toluene. (C) 2014 Elsevier B.V. All rights reserved.

Carbon nanotubes and graphene-based chemical sensors

The chemical sensing behaviour of the carbon nano-tube and graphene-based sensors for detecting various chemical analytes is presented in this article. A focus on detection mechanisms has been provided to assess their relative potential under different environmental conditions. The performance of these two carbon allotropes is compared based on their sensitivity towards various types of electron donating and accepting molecules. Although these carbon materials still have to meet crucial challenges in fabrication and optimization, continued progress in this field may lead to a sensor with superior sensitivity for a wide range of applications.

Two timescale convergent Q-learning for sleep-scheduling in wireless sensor networks

In this paper, we consider an intrusion detection application for Wireless Sensor Networks. We study the problem of scheduling the sleep times of the individual sensors, where the objective is to maximize the network lifetime while keeping the tracking error to a minimum. We formulate this problem as a partially-observable Markov decision process (POMDP) with continuous stateaction spaces, in a manner similar to Fuemmeler and Veeravalli (IEEE Trans Signal Process 56(5), 2091-2101, 2008). However, unlike their formulation, we consider infinite horizon discounted and average cost objectives as performance criteria. For each criterion, we propose a convergent on-policy Q-learning algorithm that operates on two timescales, while employing function approximation. Feature-based representations and function approximation is necessary to handle the curse of dimensionality associated with the underlying POMDP. Our proposed algorithm incorporates a policy gradient update using a one-simulation simultaneous perturbation stochastic approximation estimate on the faster timescale, while the Q-value parameter (arising from a linear function approximation architecture for the Q-values) is updated in an on-policy temporal difference algorithm-like fashion on the slower timescale. The feature selection scheme employed in each of our algorithms manages the energy and tracking components in a manner that assists the search for the optimal sleep-scheduling policy. For the sake of comparison, in both discounted and average settings, we also develop a function approximation analogue of the Q-learning algorithm. This algorithm, unlike the two-timescale variant, does not possess theoretical convergence guarantees. Finally, we also adapt our algorithms to include a stochastic iterative estimation scheme for the intruder's mobility model and this is useful in settings where the latter is not known. Our simulation results on a synthetic 2-dimensional network setting suggest that our algorithms result in better tracking accuracy at the cost of only a few additional sensors, in comparison to a recent prior work.

Porous wide band gap BiNbO4 ceramic nanopowder synthesised by low temperature solution-based method for gas sensing applications

In this study, we report the gas sensing behavior of BiNbO4 nanopowder prepared by a low temperature simple solution-based method. Before the sensing behaviour study, the as-synthesized nanopowder was characterized by X-ray diffraction, scanning electron microscopy, transmission electron microscopy, UV-diffuse reflectance spectroscopy, impedance analysis, and surface area measurement. The NH3 sensing behavior of BiNbO4 was then studied by temperature modulation (50-350 degrees C) as well as concentration modulation (20-140 ppm). At the optimum operating temperature of 325 degrees C, the sensitivity was measured to be 90%. The cross-sensitivity of as-synthesized BiNbO4 sensor was also investigated by assessing the sensing behavior toward other gases such as hydrogen sulphide (H2S), ethanol (C2H5OH), and liquid petroleum gas (LPG). Finally, selectivity of the sensing material toward NH3 was characterized by observing the sensor response with gas concentrations in the range 20-140 ppm. The response and recovery time for NH3 sensing at 120 ppm were about 16 s and about 17 s, respectively.