Pt/SnO2 nanowires/SiC based hydrogen gas sensor

Pt/SnO2 nanowires/SiC based metal-oxidesemiconductor (MOS) devices were fabricated and tested for their gas sensitivity towards hydrogen. Tin oxide (SnO2) nanowires were grown on SiC substrates by the vapour liquid solid growth process. The material properties of the SnO2 nanowires such as its formation and dimensions were analyzed using scanning electron microscopy (SEM). The currentvoltage (I-V) characteristics at different hydrogen concentrations are presented. The effective change in the barrier height for 0.06 and 1% hydrogen were found to be 20.78 and 131.59 meV, respectively. A voltage shift of 310 mV at 530°C for 1% hydrogen was measured.

Hydrogen gas sensing properties of Pt/Ta2O5 Schottky diodes based on Si and SiC substrates

We developed Pt/tantalum oxide (Ta2O5) Schottky diodes for hydrogen sensing applications. Thin layer (4 nm) of Ta2O5 was deposited on silicon (Si) and silicon carbide (SiC) substrates using the radio frequency sputtering technique. We compared the performance of these sensors at different temperatures of 100 °C and 150 °C. At these operating temperatures, the sensor based on SiC exhibited a larger sensitivity, whilst the sensor based on Si exhibited a faster response toward hydrogen gas. We discussed herein, the experimental results obtained for these Pt/Ta2O5 based Schottky diodes exhibited that they are promising candidates for hydrogen sensing applications.

Sensors for missions

An onboard payload may be seen in most instances as the “Raison d’Etre” for a UAV. It will define its capabilities, usability and hence market value. Large and medium UAV payloads exhibit significant differences in size and computing capability when compared with small UAVs. The latter have stringent size, weight, and power requirements, typically referred as SWaP, while the former still exhibit endless appetite for compute capability. The tendency for this type of UAVs (Global Hawk, Hunter, Fire Scout, etc.) is to increase payload density and hence processing capability. An example of this approach is the Northrop Grumman MQ-8 Fire Scout helicopter, which has a modular payload architecture that incorporates off-the-shelf components. Regardless of the UAV size and capabilities, advances in miniaturization of electronics are enabling the replacement of multiprocessing, power-hungry general-purpose processors for more integrated and compact electronics (e.g., FPGAs). Payloads play a significant role in the quality of ISR (intelligent, surveillance, and reconnaissance) data, and also in how quick that information can be delivered to the end user. At a high level, payloads are important enablers of greater mission autonomy, which is the ultimate aim in every UAV. This section describes common payload sensors and introduces two examples cases in which onboard payloads were used to solve real-world problems. A collision avoidance payload based on electro optical (EO) sensors is first introduced, followed by a remote sensing application for power line inspection and vegetation management.

Process monitoring using sensors in YAWL

This article describes the architecture of a monitoring component for the YAWL system. The architecture proposed is based on sensors and it is realized as a YAWL service to have perfect integration with the YAWL systems. The architecture proposed is generic and applicable in different contexts of business process monitoring. Finally, it was tested and evaluated in the context of risk monitoring for business processes.

Blocking layer optimisation of poly(3-hexylthiopene)based solid state dye sensitized solar cells

The optimisation study of the fabrication of a compact TiO2 blocking layer (via Spray Pyrolysis Deposition) for poly (3-hexylthiopene) (P3HT) for Solid State Dye Sensitized Solar Cells (SDSCs) is reported. We used a novel spray TiO2 precursor solution composition obtained by adding acetylacetone to a conventional formulation (Diisopropoxytitanium bis (acetylacetonate) in ethanol). By Scanning Electron Microscopy a TiO2 layer with compact morphology and thickness of around 100 nmis shown. Through a Tafel plot analysis an enhancement of the device diode-like behaviour induced by the acetylacetone blocking layer respect to the conventional one is observed. Significantly, the device fabricatedwith the acetylacetone blocking layer shows an overall increment of the cell performance with respect to the cellwith the conventional one (DJsc/Jsc = +13.8%, DFF/FF = +39.7%, DPCE/PCE = +55.6%). A conversion efficiency optimumis found for 15 successive spray cycles where the diode-like behaviour of the acetylacetone blocking layer is more effective. Over three batches of cells (fabricated with P3HT and dye D35) an average conversion efficiency value of 3.9% (under a class A sun simulator with 1 sun A.M. 1.5 illumination conditions) was measured. From the best cell we fabricated a conversion efficiency value of 4.5% was extracted. This represents a significant increment with respect to previously reported values for P3HT/dye D35 based SDSCs.

Vision-based place recognition : how low can you go?

In this paper we use the algorithm SeqSLAM to address the question, how little and what quality of visual information is needed to localize along a familiar route? We conduct a comprehensive investigation of place recognition performance on seven datasets while varying image resolution (primarily 1 to 512 pixel images), pixel bit depth, field of view, motion blur, image compression and matching sequence length. Results confirm that place recognition using single images or short image sequences is poor, but improves to match or exceed current benchmarks as the matching sequence length increases. We then present place recognition results from two experiments where low-quality imagery is directly caused by sensor limitations; in one, place recognition is achieved along an unlit mountain road by using noisy, long-exposure blurred images, and in the other, two single pixel light sensors are used to localize in an indoor environment. We also show failure modes caused by pose variance and sequence aliasing, and discuss ways in which they may be overcome. By showing how place recognition along a route is feasible even with severely degraded image sequences, we hope to provoke a re-examination of how we develop and test future localization and mapping systems.

Matrix metalloproteinase biosensor based on a porous silicon reflector

Matrix metalloproteinases (MMPs) are proteolytic enzymes important to wound healing. In non-healing wounds, it has been suggested that MMP levels become dysfunctional, hence it is of great interest to develop sensors to detect MMP biomarkers. This study presents the development of a label-free optical MMP biosensor based on a functionalised porous silicon (pSi) thin film. The biosensor is fabricated by immobilising a peptidomimetic MMP inhibitor in the porous layer using hydrosilylation followed by amide coupling. The binding of MMP to the immobilised inhibitor translates into a change of effective optical thickness (EOT) over the time. We investigate the effect of surface functionalisation on the stability of pSi surface and evaluate the sensing performance. We successfully demonstrate MMP detection in buffer solution and human wound fluid at physiologically relevant concentrations. This biosensor may find application as a point-of-care device that is prognostic of the healing trajectory of chronic wounds.

Exercise-based cardiac rehabilitation for the 21st century

Exercise-based cardiac rehabilitation (CR) is efficacious in reducing mortality and hospital admissions; however it remains inaccessible to large proportions of the patient population. Removal of attendance barriers for hospital or centre-based CR has seen the promotion of home-based CR. Delivery of safe and appropriately prescribed exercise in the home was first documented 25 years ago, with the utilisation of fixed land-line telecommunications to monitor ECG. The advent of miniature ECG sensors, in conjunction with smartphones, now enables CR to be delivered with greater flexibility with regard to location, time and format, while retaining the capacity for real-time patient monitoring. A range of new systems allow other signals including speed, location, pulse oximetry, and respiration to be monitored and these may have application in CR. There is compelling evidence that telemonitored-based CR is an effective alternative to traditional CR practice. The long-standing barrier of access to centre-based CR, combined with new delivery platforms, raises the question of when telemonitored-based CR could replace conventional approaches as the standard practice.

Monocular vision based autonomous navigation for a cost-effective MAV in GPS-denied environments

In this paper, we present a monocular vision based autonomous navigation system for Micro Aerial Vehicles (MAVs) in GPS-denied environments. The major drawback of monocular systems is that the depth scale of the scene can not be determined without prior knowledge or other sensors. To address this problem, we minimize a cost function consisting of a drift-free altitude measurement and up-to-scale position estimate obtained using the visual sensor. We evaluate the scale estimator, state estimator and controller performance by comparing with ground truth data acquired using a motion capture system. All resources including source code, tutorial documentation and system models are available online.

Methodology for measuring the vertical displacements of bridges using fibre bragg grating sensors

In many bridges, vertical displacements are one of the most relevant parameters for structural health monitoring in both the short- and long-terms. Bridge managers around the globe are always looking for a simple way to measure vertical displacements of bridges. However, it is difficult to carry out such measurements. On the other hand, in recent years, with the advancement of fibre-optic technologies, fibre Bragg grating (FBG) sensors are more commonly used in structural health monitoring due to their outstanding advantages including multiplexing capability, immunity of electromagnetic interference as well as high resolution and accuracy. For these reasons, a methodology for measuring the vertical displacements of bridges using FBG sensors is proposed. The methodology includes two approaches. One of which is based on curvature measurements while the other utilises inclination measurements from successfully developed FBG tilt sensors. A series of simulation tests of a full-scale bridge was conducted. It shows that both approaches can be implemented to measure the vertical displacements for bridges with various support conditions, varying stiffness along the spans and without any prior known loading. A static loading beam test with increasing loads at the mid-span and a beam test with different loading locations were conducted to measure vertical displacements using FBG strain sensors and tilt sensors. The results show that the approaches can successfully measure vertical displacements.

Bayesian inference of traffic volumes based on Bluetooth data

The study of the relationship between macroscopic traffic parameters, such as flow, speed and travel time, is essential to the understanding of the behaviour of freeway and arterial roads. However, the temporal dynamics of these parameters are difficult to model, especially for arterial roads, where the process of traffic change is driven by a variety of variables. The introduction of the Bluetooth technology into the transportation area has proven exceptionally useful for monitoring vehicular traffic, as it allows reliable estimation of travel times and traffic demands. In this work, we propose an approach based on Bayesian networks for analyzing and predicting the complex dynamics of flow or volume, based on travel time observations from Bluetooth sensors. The spatio-temporal relationship between volume and travel time is captured through a first-order transition model, and a univariate Gaussian sensor model. The two models are trained and tested on travel time and volume data, from an arterial link, collected over a period of six days. To reduce the computational costs of the inference tasks, volume is converted into a discrete variable. The discretization process is carried out through a Self-Organizing Map. Preliminary results show that a simple Bayesian network can effectively estimate and predict the complex temporal dynamics of arterial volumes from the travel time data. Not only is the model well suited to produce posterior distributions over single past, current and future states; but it also allows computing the estimations of joint distributions, over sequences of states. Furthermore, the Bayesian network can achieve excellent prediction, even when the stream of travel time observation is partially incomplete.

Towards discrimination of challenging conditions for UGVs with visual and infrared sensors

This work aims to contribute to reliability and integrity in perceptual systems of autonomous ground vehicles. Information theoretic based metrics to evaluate the quality of sensor data are proposed and applied to visual and infrared camera images. The contribution of the proposed metrics to the discrimination of challenging conditions is discussed and illustrated with the presence of airborne dust and smoke.

A sensor fault detection and isolation method in interior permanent-magnet synchronous motor drives based on an extended Kalman filter

Interior permanent-magnet synchronous motors (IPMSMs) become attractive candidates in modern hybrid electric vehicles and industrial applications. Usually, to obtain good control performance, the electric drives of this kind of motor require one position, one dc link, and at least two current sensors. Failure of any of these sensors might lead to degraded system performance or even instability. As such, sensor fault resilient control becomes a very important issue in modern drive systems. This paper proposes a novel sensor fault detection and isolation algorithm based on an extended Kalman filter. It is robust to system random noise and efficient in real-time implementation. Moreover, the proposed algorithm is compact and can detect and isolate all the sensor faults for IPMSM drives. Thorough theoretical analysis is provided, and the effectiveness of the proposed approach is proven by extensive experimental results.

Vertical displacement measurement using fibre Bragg grating (FBG) sensors for structural health monitoring of bridges

This thesis developed a practical, cost effective, easy-to-use method for measuring the vertical displacements of bridges using fiber Bragg grating (FBG) sensors, which includes the curvature and inclination approaches. These approaches were validated by the numerical simulation tests on a full scale bridge and the laboratory-based tests. In doing so, a novel frictionless FBG inclination sensor with extremely high sensitivity and resolution has also been developed and validated.

Accelerometer based performance assessment of basic routines in classical ballet

Classical ballet requires dancers to exercise significant muscle control and strength both while stationary and when moving. Following the Royal Academy of Dance (RAD) syllabus, 8 male and 27 female dancers (aged 20.2 + 1.9 yr) in a fulltime university undergraduate dance training program were asked to stand in first position for 10 seconds and then perform 10 repeats of a demi-plié exercise to a counted rhythm. Accelerometer records from the wrist, sacrum, knee and ankle were compared with the numerical scores from a professional dance instructor. The sacrum mounted sensor detected lateral tilts of the torso in dances with lower scores (Spearman’s rank correlation coefficient r = -0.64, p < 0.005). The RMS acceleration amplitude of wrist mounted sensor was linearly correlated to the movement scores (Spearman’s rank correlation coefficient r = 0.63, p < 0.005). The application of sacrum and wrist mounted sensors for biofeedback during dance training is a realistic, low cost option.