Low power consumption and high sensitivity carbon monoxide gas sensor using indium oxide nanowire.

In this paper, micro gas sensor was fabricated using indium oxide nanowire for effective gas detection and monitoring system. Indium oxide nanowire was grown using thermal CVD, and their structural properties were examined by the SEM, XRD and TEM. The electric properties for microdropped indium oxide nanowire device were measured, and gas response characteristics were examined for CO gas. Sensors showed high sensitivity and stability for CO gas. And with below 20 mw power consumption, 5 ppm CO could be detected.

A novel, sensitive potentiometric hydrocarbon sensor for high-vacuum applications.

A potentiometric device based on interfacing a solid electrolyte oxygen ion conductor with a thin platinum film acts as a robust, reproducible sensor for the detection of hydrocarbons in high- or ultrahigh-vacuum environments. Sensitivities in the order of approximately 5 x 10(-10) mbar are achievable under open circuit conditions, with good selectivity for discrimination between n-butane on one hand and toluene, n-octane, n-hexane, and 1-butene on the other hand. The sensor's sensitivity may be tuned by operating under constant current (closed circuit) conditions; injection of anodic current is also a very effective means of restoring a clean sensing surface at any desired point. XPS data and potentiometric measurements confirm the proposed mode of sensing action: the steady-state coverage of Oa, which sets the potential of the Pt sensing electrode, is determined by the partial pressure and dissociative sticking probability of the impinging hydrocarbon. The principles established here provide the basis for a viable, inherently flexible, and promising means for the sensitive and selective detection of hydrocarbons under demanding conditions.

Frequency diversity measurements at 2.4 GHz for wireless sensor networks deployed in tunnels

Wireless Sensor Networks (WSNs) which utilise IEEE 802.15.4 technology operate primarily in the 2.4 GHz globally compatible ISM band. However, the wireless propagation channel in this crowded band is notoriously variable and unpredictable, and it has a significant impact on the coverage range and quality of the radio links between the wireless nodes. Therefore, the use of Frequency Diversity (FD) has potential to ameliorate this situation. In this paper, the possible benefits of using FD in a tunnel environment have been quantified by performing accurate propagation measurements using modified and calibrated off-the-shelf 802.15.4 based sensor motes in the disused Aldwych underground railway tunnel. The objective of this investigation is to characterise the performance of FD in this confined environment. Cross correlation coefficients are calculated from samples of the received power on a number of frequency channels gathered during the field measurements. The low measured values of the cross correlation coefficients indicate that applying FD at 2.4 GHz will improve link performance in a WSN deployed in a tunnel. This finding closely matches results obtained by running a computational simulation of the tunnel radio propagation using a 2D Finite-Difference Time-Domain (FDTD) method. ©2009 IEEE.

Streaming covariance selection with applications to adaptive querying in sensor networks

Sensor networks can be naturally represented as graphical models, where the edge set encodes the presence of sparsity in the correlation structure between sensors. Such graphical representations can be valuable for information mining purposes as well as for optimizing bandwidth and battery usage with minimal loss of estimation accuracy. We use a computationally efficient technique for estimating sparse graphical models which fits a sparse linear regression locally at each node of the graph via the Lasso estimator. Using a recently suggested online, temporally adaptive implementation of the Lasso, we propose an algorithm for streaming graphical model selection over sensor networks. With battery consumption minimization applications in mind, we use this algorithm as the basis of an adaptive querying scheme. We discuss implementation issues in the context of environmental monitoring using sensor networks, where the objective is short-term forecasting of local wind direction. The algorithm is tested against real UK weather data and conclusions are drawn about certain tradeoffs inherent in decentralized sensor networks data analysis. © 2010 The Author. Published by Oxford University Press on behalf of The British Computer Society. All rights reserved.

An electrokinetic sensor for studying immersed surfaces, using focused ultrasound

A novel method for obtaining information on the charge density of an immersed surface is presented. The technique uses focused ultrasound to excite oscillatory fluid motion in the plane of the solid-liquid interface, over a localised area. The displacement current (resulting from the motion of fluid-borne ions in the outer double-layer) is detected by electrodes in the liquid. The method is demonstrated as a means for monitoring protein adsorption, and for monitoring interactions between two different proteins. A second electrokinetic effect at the interface is identified, isolated from the first, and shown to provide additional information on the compressibility and charge density of the double-layer. © 2001 Elsevier Science B.V. All rights reserved.