A low-cost wireless temperature sensor: evaluation for use in environmental applications

With a wide range of applications benefiting from dense network air temperature observations but with limitations of costs, existing siting guidelines and risk of damage to sensors, new methods are required to gain a high resolution understanding of the spatio-temporal patterns of urban meteorological phenomena such as the urban heat island or precision farming needs. With the launch of a new generation of low cost sensors it is possible to deploy a network to monitor air temperature at finer spatial resolutions. Here we investigate the Aginova Sentinel Micro (ASM) sensor with a bespoke radiation shield (together < US$150) which can provide secure near-real-time air temperature data to a server utilising existing (or user deployed) Wireless Fidelity (Wi-Fi) networks. This makes it ideally suited for deployment where wireless communications readily exist, notably urban areas. Assessment of the performance of the ASM relative to traceable standards in a water bath and atmospheric chamber show it to have good measurement accuracy with mean errors < ± 0.22 °C between -25 and 30 °C, with a time constant in ambient air of 110 ± 15 s. Subsequent field tests of it within the bespoke shield also had excellent performance (root-mean-square error = 0.13 °C) over a range of meteorological conditions relative to a traceable operational UK Met Office platinum resistance thermometer. These results indicate that the ASM and bespoke shield are more than fit-for-purpose for dense network deployment in urban areas at relatively low cost compared to existing observation techniques.

BodyCloud: a SaaS approach for community body sensor networks

Body Sensor Networks (BSNs) have been recently introduced for the remote monitoring of human activities in a broad range of application domains, such as health care, emergency management, fitness and behaviour surveillance. BSNs can be deployed in a community of people and can generate large amounts of contextual data that require a scalable approach for storage, processing and analysis. Cloud computing can provide a flexible storage and processing infrastructure to perform both online and offline analysis of data streams generated in BSNs. This paper proposes BodyCloud, a SaaS approach for community BSNs that supports the development and deployment of Cloud-assisted BSN applications. BodyCloud is a multi-tier application-level architecture that integrates a Cloud computing platform and BSN data streams middleware. BodyCloud provides programming abstractions that allow the rapid development of community BSN applications. This work describes the general architecture of the proposed approach and presents a case study for the real-time monitoring and analysis of cardiac data streams of many individuals.

A real-time measurement system for long-life flood monitoring and warning applications

A flood warning system incorporates telemetered rainfall and flow/water level data measured at various locations in the catchment area. Real-time accurate data collection is required for this use, and sensor networks improve the system capabilities. However, existing sensor nodes struggle to satisfy the hydrological requirements in terms of autonomy, sensor hardware compatibility, reliability and long-range communication. We describe the design and development of a real-time measurement system for flood monitoring, and its deployment in a flash-flood prone 650 km2 semiarid watershed in Southern Spain. A developed low-power and long-range communication device, so-called DatalogV1, provides automatic data gathering and reliable transmission. DatalogV1 incorporates self-monitoring for adapting measurement schedules for consumption management and to capture events of interest. Two tests are used to assess the success of the development. The results show an autonomous and robust monitoring system for long-term collection of water level data in many sparse locations during flood events.

Structure effects of self-assembled Prussian blue confined in highly organized mesoporous TiO(2) on the electrocatalytic properties towards H(2)O(2) detection

Here we report the derivatization of mesoporous TiO(2) thin films for the preparation of H(2)O(2) amperometric sensors. The coordination of the bifunctional ligand 1,10 phenantroline, 5,6 dione on the surface Ti(IV) ions provides open coordination sites for Fe(II) cations which are the starting point for the growth of a layer of Prussian blue polymer. The porous structure of the mesoporous TiO(2) allows the growth, ion by ion of the coordination polymer. Up to four layer of Prussian blue can be deposit without losing the porous structure of the film, which results in an enhanced response of these materials as H(2)O(2) sensors. These porous confined PB modified electrodes are robust sensors that exhibit good reproducibility, environmental stability and high sensitivity towards H(2)O(2) detection. (C) 2010 Elsevier B.V. All rights reserved.

Adaptive, Decentralized, And Real-Time Sampling Strategies For Resource Constrained Hydraulic And Hydrologic Sensor Networks

We discuss the development and performance of a low-power sensor node (hardware, software and algorithms) that autonomously controls the sampling interval of a suite of sensors based on local state estimates and future predictions of water flow. The problem is motivated by the need to accurately reconstruct abrupt state changes in urban watersheds and stormwater systems. Presently, the detection of these events is limited by the temporal resolution of sensor data. It is often infeasible, however, to increase measurement frequency due to energy and sampling constraints. This is particularly true for real-time water quality measurements, where sampling frequency is limited by reagent availability, sensor power consumption, and, in the case of automated samplers, the number of available sample containers. These constraints pose a significant barrier to the ubiquitous and cost effective instrumentation of large hydraulic and hydrologic systems. Each of our sensor nodes is equipped with a low-power microcontroller and a wireless module to take advantage of urban cellular coverage. The node persistently updates a local, embedded model of flow conditions while IP-connectivity permits each node to continually query public weather servers for hourly precipitation forecasts. The sampling frequency is then adjusted to increase the likelihood of capturing abrupt changes in a sensor signal, such as the rise in the hydrograph – an event that is often difficult to capture through traditional sampling techniques. Our architecture forms an embedded processing chain, leveraging local computational resources to assess uncertainty by analyzing data as it is collected. A network is presently being deployed in an urban watershed in Michigan and initial results indicate that the system accurately reconstructs signals of interest while significantly reducing energy consumption and the use of sampling resources. We also expand our analysis by discussing the role of this approach for the efficient real-time measurement of stormwater systems.

Studies on the interaction between humic substances and conducting polymers for sensor application

The interaction between humic substances and poly(o-ethoxyaniline) (POEA), a conducting polymer, was investigated for both solution and self-assembled films. The results have shown that the humic substances induce a doping of POEA by protonation, as indicated by UV-Vis and Raman spectroscopies. The atomic force microscopy (AFM) studies on the self-assembled films have shown that the average roughness of the polymer film has increased after exposing it to humic substances (fulvic and humic acids), consistent with the interaction between POEA and humic substances. However, this change in morphology is reversible by washing the films with water in agreement with the electrical data allowing using this system in sensor applications. Here, the sensor formed by an array of different sensing units was able to detect and distinguish humic substances in aqueous solution, as shown by multivariate analysis (principal component analysis). The motivation to detect humic substance comes due to its importance in terms of quality control of water or soil. ©2005 Sociedade Brasileira de Química.

Tethered DNA scaffolds on optical sensor platforms for detection of hipO gene from Campylobacter jejuni

DNA biosensors have gained increased attention over traditional diagnostic methods due to their fast and responsive operation and cost-effective design. The specificity of DNA biosensors relies on single-stranded oligonucleotide probes immobilized to a transduction platform. Here, we report the development of biosensors to detect the hippuricase gene (hipO) from Campylobacter jejuni using direct covalent coupling of thiol- and biotin-labeled single-stranded DNA (ssDNA) on both surface plasmon resonance (SPR) and diffraction optics technology (DOT, dotLab) transduction platforms. This is the first known report of the dotLab to detect targeted DNA. Application of 6-mercapto-1-hexanol as a spacer thiol for SPR gold surface created a self-assembled monolayer that removed unbound ssDNA and minimized non-specific detection. The detection limit of SPR sensors was shown to be 2.5 nM DNA while dotLab sensors demonstrated a slightly decreased detection limit of 5.0 nM (0.005 μM). It was possible to reuse the SPR sensor due to the negligible changes in sensor sensitivity (∼9.7 × 10 -7 ΔRU) and minimal damage to immobilized probes following use, whereas dotLab sensors could not be reused. Results indicated feasibility of optical biosensors for rapid and sensitive detection of the hipO gene of Campylobacter jejuni using specific ssDNA as a probe. © 2011 Elsevier B.V.

QK-Means: A clustering technique based on community detection and K-Means for deployment of cluster head nodes

Wireless Sensor Networks (WSN) are a special kind of ad-hoc networks that is usually deployed in a monitoring field in order to detect some physical phenomenon. Due to the low dependability of individual nodes, small radio coverage and large areas to be monitored, the organization of nodes in small clusters is generally used. Moreover, a large number of WSN nodes is usually deployed in the monitoring area to increase WSN dependability. Therefore, the best cluster head positioning is a desirable characteristic in a WSN. In this paper, we propose a hybrid clustering algorithm based on community detection in complex networks and traditional K-means clustering technique: the QK-Means algorithm. Simulation results show that QK-Means detect communities and sub-communities thus lost message rate is decreased and WSN coverage is increased. © 2012 IEEE.

Desenvolvimento de sensor biomimético para detecção de resíduos de pesticidas organofosforados e carbamatos em alimentos

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Desenvolvimento de biossensor baseado em extrato de açaí e sensor biomimético para detecção de hexazinona

Pós-graduação em Química - IQ

Nanostructured screen-printed electrodes modified with self-assembled monolayers for determination of metronidazole in different matrices

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Aplicação do desdobramento da função qualidade (QFD) para melhoria da qualidade em um restaurante self-service

Currently, with the competitiveness that is seen in the market, it is crucial to the success of the business, develop new strategies to keep and win new customer preference. To ensure the success of a particular service or product, the secret is to continually meet the wishes and demands of the customers, which are the key parts of the business, through innovation, variety and quality assurance. To achieve this goal managers should be aware of all types of process that exist in the company, as they are primarily responsible and interested by quality service, customer satisfaction and consequently, generating favorable financial results. A tool used to ensure good results to business is the Quality Function Deployment (QFD) that seeks to hear and interpret customers requirements and turn them into essential features for a project

Organization model for mobile wireless sensor networks inspired in artificial bee colony

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Surface coverage in wireless sensor networks based on delaunay tetrahedralization

In this work is presented a new method for sensor deployment on 3D surfaces. The method was structured on different steps. The first one aimed discretizes the relief of interest with Delaunay algorithm. The tetrahedra and relative values (spatial coordinates of each vertex and faces) were input to construction of 3D Voronoi diagram. Each circumcenter was calculated as a candidate position for a sensor node: the corresponding circular coverage area was calculated based on a radius r. The r value can be adjusted to simulate different kinds of sensors. The Dijkstra algorithm and a selection method were applied to eliminate candidate positions with overlapped coverage areas or beyond of surface of interest. Performance evaluations measures were defined using coverage area and communication as criteria. The results were relevant, once the mean coverage rate achieved on three different surfaces were among 91% and 100%.

Development of an Electrochemical Insulin Sensor Based on a High Affinity DNA Sequence Found in the Insulin-linked Polymorphic Region

The detection of pertinent biomarkers has the potential provide an early indication of disease progression before considerable damage has been incurred. A decrease in an individual’s sensitivity to insulin, which may be quantified as the ratio of insulin to glucose in the blood after a glucose pulse, has recently been reported as an early predictor of insulin-dependent diabetes mellitus. Routine measurement of insulin levels is therefore desirable in the care of diabetes-prone individuals. A rapid, simple, and reagentless method for insulin detection would allow for wide-spread screenings that provide earlier signs of diabetes onset. The aim of this thesis is to develop a folding-base electrochemical sensor for the detection of insulin. The sensor described herein consists of a DNA probe immobilized on a gold disc electrode via an alkanethiol linker and embedded in an alkanethiol self-assembled monolayer. The probe is labeled with a redox reporter, which readily transfers electrons to the gold electrode in the absence of insulin. In the presence of insulin, electron transfer is inhibited, presumably due to a binding-induced conformational or dynamic change in the DNA probe that significantly alters the electron-tunneling pathway. A 28-base segment of the insulin-linked polymorphic region that has been reported to bind insulin with high affinity serves as the capture element of the DNA probe. Three probe constructs that vary in their secondary structure and position of the redox label are evaluated for their utility as insulin-sensing elements on the electrochemical platform. The effects of probe modification on secondary structure are also evaluated using circular dichroism spectroscopy.