982 resultados para Sensor Platform


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A low-altitude platform utilising a 1.8-m diameter tethered helium balloon was used to position a multispectral sensor, consisting of two digital cameras, above a fertiliser trial plot where wheat (Triticum spp.) was being grown. Located in Cecil Plains, Queensland, Australia, the plot was a long-term fertiliser trial being conducted by a fertiliser company to monitor the response of crops to various levels of nutrition. The different levels of nutrition were achieved by varying nitrogen application rates between 0 and 120 units of N at 40 unit increments. Each plot had received the same application rate for 10 years. Colour and near-infrared images were acquired that captured the whole 2 ha plot. These images were examined and relationships sought between the captured digital information and the crop parameters imaged at anthesis and the at-harvest quality and quantity parameters. The statistical analysis techniques used were correlation analysis, discriminant analysis and partial least squares regression. A high correlation was found between the image and yield (R2 = 0.91) and a moderate correlation between the image and grain protein content (R2 = 0.66). The utility of the system could be extended by choosing a more mobile platform. This would increase the potential for the system to be used to diagnose the causes of the variability and allow remediation, and/or to segregate the crop at harvest to meet certain quality parameters.

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The design and analysis of an optical read-out scheme based on a grated waveguide (GWG) resonator for interrogating microcantilever sensor arrays is presented. The optical system consisting of a micro cantilever monolithically integrated in proximity to a grated waveguide (GWG), is realized in silicon optical bench platform. The mathematical analysis of the optical system is performed using a Fabry-Perot interferometer model with a lossy cavity formed between the cantilever and the GWG and an analytical expression is derived for the optical power transmission as a function of the cantilever deflection which corresponds to cavity width variation. The intensity transmission of the optical system for different cantilever deflections estimated using the analytical expression captures the essential features exhibited by a FDTD numerical model.

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Here we demonstrate that a free-standing carbon nanotube (CNT) array can be used as a large surface area and high porosity 3D platform for molecular imprinted polymer (MIP), especially for surface imprinting. The thickness of polymer grafted around each CNT can be fine-tuned to imprint different sizes of target molecules, and yet it can be thin enough to expose every imprint site to the target molecules in solution without sacrificing the capacity of binding sites. The performance of this new CNT-MIP architecture was first assessed with a caffeine-imprinted polypyrrole (PPy) coating on two types of CNT arrays: sparse and dense CNTs. Real-time pulsed amperometric detection was used to study the rebinding of the caffeine molecules onto these CNT-MIPPy sensors. The dense CNT-MIPPy sensor presented the highest sensitivity, about 15 times better when compared to the conventional thin film, whereas an improvement of 3.6 times was recorded on the sparse CNT. However, due to the small tube-to-tube spacing in the dense CNT array, electrode fouling was observed during the detection of concentrated caffeine in phosphate buffer solution. A new I-V characterization method using pulsed amperometry was introduced to investigate the electrical characterization of these new devices. The resistance value derived from the I-V plot provides insight into the electrical conductivity of the CNT transducer and also the effective surface area for caffeine imprinting.

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A novel technological platform for multiple gas detection based on the use of PCB-integrated polymer waveguides is presented. A proof-of-principle ammonia sensor is reported integrating onto low-cost FR4 substrates all essential photonic, electronic and chemical components. The device's potential to detect multiple gases is demonstrated. © 2011 IEEE.

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In this paper we present a robust SOI-CMOS ethanol sensor based on a tungsten-doped lanthanum iron oxide sensing material. The device shows response to gas, has low power consumption, good uniformity, high temperature stability and can be manufactured at low cost and with integrated circuitry. The platform is a tungsten-based CMOS micro-hotplate that has been shown to be stable for over two thousand hours at a high temperature (600°C) in a form of accelerated life test. The tungsten-doped lanthanum iron oxide was deposited on the micro-hotplate as a slurry with terpineol using a syringe, dried and annealed. Preliminary gas testing was done and the material shows response to ethanol vapour. These results are promising and we believe that this combination of a robust CMOS micro-hotplate and a good sensing material can form the basis for a commercial CMOS gas sensor. © 2011 Published by Elsevier Ltd.

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This paper presents a novel platform for the formation of cost-effective PCB-integrated optical waveguide sensors. The sensor design relies on the use of multimode polymer waveguides that can be formed directly on standard PCBs and commercially-available chemical dyes, enabling the integration of all essential sensor components (electronic, photonic, chemical) on low-cost substrates. Moreover, it enables the detection of multiple analytes from a single device by employing waveguide arrays functionalised with different chemical dyes. The devices can be manufactured with conventional methods of the PCB industry, such as solder-reflow processes and pick-and-place assembly techniques. As a proof of principle, a PCB-integrated ammonia gas sensor is fabricated on a FR4 substrate. The sensor operation relies on the change of the optical transmission characteristics of chemically functionalised optical waveguides in the presence of ammonia molecules. The fabrication and assembly of the sensor unit, as well as fundamental simulation and characterisation studies, are presented. The device achieves a sensitivity of approximately 30 ppm and a linear response up to 600 ppm at room temperature. Finally, the potential to detect multiple analytes from a single device is demonstrated using principal-component analysis. © 1983-2012 IEEE.

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Morphological control of nanomaterials is of great interest due to their size and shape-dependent chemical and physical properties and very important applications in many fields such as biomedicine, sensors, electronics and others. In this paper, we reported a simple strategy for synthesizing gold nanowire assembling architecture at room temperature. It is found that two important factors, the proper volume ratio of ethanol to water and poly(vinyl pyrrolidone) (PVP), will play important roles in synthesizing flower-like short gold nanowire assembling spheres. Furthermore, the obtained flower-like gold assembling spheres with high surface-to-volume ratio have been employed as enhancing materials for electrochemical sensing H2O2. The present electrochemical sensing platform exhibited good electrocatalytic activity towards the reduction of H2O2. The detection limit for H2O2 was found to be 1.2 mu M, which was lower than certain enzyme-based biosensors.

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We initially report an electrochemical sensing platform based on molecularly imprinted polymers (MIPs) at functionalized Indium Tin Oxide Electrodes (ITO). In this research, aminopropyl-derivatized organosilane aminopropyltriethoxysilane (APTES), which plays the role of functional monomers for template recognition, was firstly self-assembled on an ITO electrode and then dopamine-imprinted sol was spin-coated on the modified surface. APTES which can interact with template dopamine (DA) through hydrogen bonds brought more binding sites located closely to the surface of the ITO electrode, thus made the prepared sensor more sensitive for DA detection. Potential scanning is presented to extract DA from the modified film, thus DA can rapidly and completely leach out. The affinity and selectivity of the resulting biomimetic sensor were characterized using cyclic voltammetry (CV). It exhibited an increased affinity for DA over that of structurally related molecules, the anodic current for DA oxidation depended on the concentration of DA in the linear range from 2 x 10(-6) M to 0.8 x 10(-3) M with a correlation coefficient of 0.9927.In contrast, DA-templated film prepared under identical conditions on a bare ITO showed obviously lower response toward dopamine in solution.

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An effective electrogenerated chemiluminescence (ECL) sensor was developed by coimmobilization of the Ru(bpy)(2)(3+)-doped silica (RuDS) nanoparticles and carbon nanotubes (CNTs) on glassy carbon electrode through hydrophobic interaction. The uniform RuDS nanoparticles were prepared by a water-in-oil (W/O) microemulsion method and Ru(bpy)(3)(2+) doped inside could still maintain its high ECL efficiency. With such unique immobilization method, a great deal of Ru(bpy)(3)(2+) was immobilized three-dimensionally on the electrode , which could greatly enhance the ECL response and result in the increased sensitivity. On the other hand, CNTs played dual roles as matrix to immobilize RuDS nanoparticles and promoter to accelerate the electron transfer between Ru(bpy)(3)(2+) and the electrode. The as-prepared ECL sensor displayed good sensitivity and stability.

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As the commoditization of sensing, actuation and communication hardware increases, so does the potential for dynamically tasked sense and respond networked systems (i.e., Sensor Networks or SNs) to replace existing disjoint and inflexible special-purpose deployments (closed-circuit security video, anti-theft sensors, etc.). While various solutions have emerged to many individual SN-centric challenges (e.g., power management, communication protocols, role assignment), perhaps the largest remaining obstacle to widespread SN deployment is that those who wish to deploy, utilize, and maintain a programmable Sensor Network lack the programming and systems expertise to do so. The contributions of this thesis centers on the design, development and deployment of the SN Workbench (snBench). snBench embodies an accessible, modular programming platform coupled with a flexible and extensible run-time system that, together, support the entire life-cycle of distributed sensory services. As it is impossible to find a one-size-fits-all programming interface, this work advocates the use of tiered layers of abstraction that enable a variety of high-level, domain specific languages to be compiled to a common (thin-waist) tasking language; this common tasking language is statically verified and can be subsequently re-translated, if needed, for execution on a wide variety of hardware platforms. snBench provides: (1) a common sensory tasking language (Instruction Set Architecture) powerful enough to express complex SN services, yet simple enough to be executed by highly constrained resources with soft, real-time constraints, (2) a prototype high-level language (and corresponding compiler) to illustrate the utility of the common tasking language and the tiered programming approach in this domain, (3) an execution environment and a run-time support infrastructure that abstract a collection of heterogeneous resources into a single virtual Sensor Network, tasked via this common tasking language, and (4) novel formal methods (i.e., static analysis techniques) that verify safety properties and infer implicit resource constraints to facilitate resource allocation for new services. This thesis presents these components in detail, as well as two specific case-studies: the use of snBench to integrate physical and wireless network security, and the use of snBench as the foundation for semester-long student projects in a graduate-level Software Engineering course.

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Rachit Agarwal, Rafael V. Martinez-Catala, Sean Harte, Cedric Segard, Brendan O'Flynn, "Modeling Power in Multi-functionality Sensor Network Applications," sensorcomm, pp.507-512, 2008 Proceedings of the Second International Conference on Sensor Technologies and Applications, August 25-August 31 2008, Cap Esterel, France

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Complex systems, from environmental behaviour to electronics reliability, can now be monitored with Wireless Sensor Networks (WSN), where multiple environmental sensors are deployed in remote locations. This ensures aggregation and reading of data, at lower cost and lower power consumption. Because miniaturisation of the sensing system is hampered by the fact that discrete sensors and electronics consume board area, the development of MEMS sensors offers a promising solution. At Tyndall, the fabrication flow of multiple sensors has been made compatible with CMOS circuitry to further reduce size and cost. An ideal platform on which to host these MEMS environmental sensors is the Tyndall modular wireless mote. This paper describes the development and test of the latest sensors incorporating temperature, humidity, corrosion, and gas. It demonstrates their deployment on the Tyndall platform, allowing real-time readings, data aggregation and cross-correlation capabilities. It also presents the design of the next generation sensing platform using the novel 10mm wireless cube developed by Tyndall.

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Emerging healthcare applications can benefit enormously from recent advances in pervasive technology and computing. This paper introduces the CLARITY Modular Ambient Health and Wellness Measurement Platform:, which is a heterogeneous and robust pervasive healthcare solution currently under development at the CLARITY Center for Sensor Web Technologies. This intelligent and context-aware platform comprises the Tyndall Wireless Sensor Network prototyping system, augmented with an agent-based middleware and frontend computing architecture. The key contribution of this work is to highlight how interoperability, expandability, reusability and robustness can be manifested in the modular design of the constituent nodes and the inherently distributed nature of the controlling software architecture.Emerging healthcare applications can benefit enormously from recent advances in pervasive technology and computing. This paper introduces the CLARITY Modular Ambient Health and Wellness Measurement Platform:, which is a heterogeneous and robust pervasive healthcare solution currently under development at the CLARITY Center for Sensor Web Technologies. This intelligent and context-aware platform comprises the Tyndall Wireless Sensor Network prototyping system, augmented with an agent-based middleware and frontend computing architecture. The key contribution of this work is to highlight how interoperability, expandability, reusability and robustness can be manifested in the modular design of the constituent nodes and the inherently distributed nature of the controlling software architecture.

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This paper documents the design, implementation and characterisation of a wireless sensor node (GENESI Node v1.0), applicable to long-term structural health monitoring. Presented is a three layer abstraction of the hardware platform; consisting of a Sensor Layer, a Main Layer and a Power Layer. Extended operational lifetime is one of the primary design goals, necessitating the inclusion of supplemental energy sources, energy awareness, and the implementation of optimal components (microcontroller(s), RF transceiver, etc.) to achieve lowest-possible power consumption, whilst ensuring that the functional requirements of the intended application area are satisfied. A novel Smart Power Unit has been developed; including intelligence, ambient available energy harvesting (EH), storage, electrochemical fuel cell integration, and recharging capability, which acts as the Power Layer for the node. The functional node has been prototyped, demonstrated and characterised in a variety of operational modes. It is demonstrable via simulation that, under normal operating conditions within a structural health monitoring application, the node may operate perpetually.

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Wireless sensor node platforms are very diversified and very constrained, particularly in power consumption. When choosing or sizing a platform for a given application, it is necessary to be able to evaluate in an early design stage the impact of those choices. Applied to the computing platform implemented on the sensor node, it requires a good understanding of the workload it must perform. Nevertheless, this workload is highly application-dependent. It depends on the data sampling frequency together with application-specific data processing and management. It is thus necessary to have a model that can represent the workload of applications with various needs and characteristics. In this paper, we propose a workload model for wireless sensor node computing platforms. This model is based on a synthetic application that models the different computational tasks that the computing platform will perform to process sensor data. It allows to model the workload of various different applications by tuning data sampling rate and processing. A case study is performed by modeling different applications and by showing how it can be used for workload characterization. © 2011 IEEE.