A traffic differentiation add-on to the IEEE 802.15.4 protocol: implementation and experimental validation over a real-time operating system

The IEEE 802.15.4 is the most widespread used protocol for Wireless Sensor Networks (WSNs) and it is being used as a baseline for several higher layer protocols such as ZigBee, 6LoWPAN or WirelessHART. Its MAC (Medium Access Control) supports both contention-free (CFP, based on the reservation of guaranteed time-slots GTS) and contention based (CAP, ruled by CSMA/CA) access, when operating in beacon-enabled mode. Thus, it enables the differentiation between real-time and best-effort traffic. However, some WSN applications and higher layer protocols may strongly benefit from the possibility of supporting more traffic classes. This happens, for instance, for dense WSNs used in time-sensitive industrial applications. In this context, we propose to differentiate traffic classes within the CAP, enabling lower transmission delays and higher success probability to timecritical messages, such as for event detection, GTS reservation and network management. Building upon a previously proposed methodology (TRADIF), in this paper we outline its implementation and experimental validation over a real-time operating system. Importantly, TRADIF is fully backward compatible with the IEEE 802.15.4 standard, enabling to create different traffic classes just by tuning some MAC parameters.

AUV Control and Communication using Underwater Acoustic Networks

Underwater acoustic networks can be quite effective to establish communication links between autonomous underwater vehicles (AUVs) and other vehicles or control units, enabling complex vehicle applications and control scenarios. A communications and control framework to support the use of underwater acoustic networks and sample application scenarios are described for single and multi-AUV operation.

3D-nanostructured Au electrodes for the event-specific detection of MON810 transgenic maize

In the present work, the development of a genosensor for the event-specific detection of MON810 transgenic maize is proposed. Taking advantage of nanostructuration, a cost-effective three dimensional electrode was fabricated and a ternary monolayer containing a dithiol, a monothiol and the thiolated capture probe was optimized to minimize the unspecific signals. A sandwich format assay was selected as a way of precluding inefficient hybridization associated with stable secondary target structures. A comparison between the analytical performance of the Au nanostructured electrodes and commercially available screen-printed electrodes highlighted the superior performance of the nanostructured ones. Finally, the genosensor was effectively applied to detect the transgenic sequence in real samples, showing its potential for future quantitative analysis.

Towards a reliable technology for antioxidant capacity and oxidative damage evaluation: Electrochemical (bio)sensors

To counteract and prevent the deleterious effect of free radicals the living organisms have developed complex endogenous and exogenous antioxidant systems. Several analytical methodologies have been proposed in order to quantify antioxidants in food, beverages and biological fluids. This paper revises the electroanalytical approaches developed for the assessment of the total or individual antioxidant capacity. Four electrochemical sensing approaches have been identified, based on the direct electrochemical detection of antioxidant at bare or chemically modified electrodes, and using enzymatic and DNA-based biosensors.

Geostatistical Prediction of Ocean Outfall Plume Characteristics Based on an Autonomous Underwater Vehicle

Geostatistics has been successfully used to analyze and characterize the spatial variability of environmental properties. Besides giving estimated values at unsampled locations, it provides a measure of the accuracy of the estimate, which is a significant advantage over traditional methods used to assess pollution. In this work universal block kriging is novelty used to model and map the spatial distribution of salinity measurements gathered by an Autonomous Underwater Vehicle in a sea outfall monitoring campaign, with the aim of distinguishing the effluent plume from the receiving waters, characterizing its spatial variability in the vicinity of the discharge and estimating dilution. The results demonstrate that geostatistical methodology can provide good estimates of the dispersion of effluents that are very valuable in assessing the environmental impact and managing sea outfalls. Moreover, since accurate measurements of the plume’s dilution are rare, these studies might be very helpful in the future to validate dispersion models.

Detection of quasi-periodic processes in complex systems: how do we quantitatively describe their properties?

It has been shown that in reality at least two general scenarios of data structuring are possible: (a) a self-similar (SS) scenario when the measured data form an SS structure and (b) a quasi-periodic (QP) scenario when the repeated (strongly correlated) data form random sequences that are almost periodic with respect to each other. In the second case it becomes possible to describe their behavior and express a part of their randomness quantitatively in terms of the deterministic amplitude–frequency response belonging to the generalized Prony spectrum. This possibility allows us to re-examine the conventional concept of measurements and opens a new way for the description of a wide set of different data. In particular, it concerns different complex systems when the ‘best-fit’ model pretending to be the description of the data measured is absent but the barest necessity of description of these data in terms of the reduced number of quantitative parameters exists. The possibilities of the proposed approach and detection algorithm of the QP processes were demonstrated on actual data: spectroscopic data recorded for pure water and acoustic data for a test hole. The suggested methodology allows revising the accepted classification of different incommensurable and self-affine spatial structures and finding accurate interpretation of the generalized Prony spectroscopy that includes the Fourier spectroscopy as a partial case.

Sistema de detecção e localização de veículos subaquáticos

Mestrado em Engenharia Electrotécnica e de Computadores.Área de Especialização de Sistemas Autónomos

Coordinated Maneuver for Gradient Search Using Multiple AUV's

OCEANS 2003. Proceedings (Volume:1 )

Field experiments for marine casualty detection with autonomous surface vehicles

In this paper we present a set of field tests for detection of human in the water with an unmanned surface vehicle using infrared and color cameras. These experiments aimed to contribute in the development of victim target tracking and obstacle avoidance for unmanned surface vehicles operating in marine search and rescue missions. This research is integrated in the work conducted in the European FP7 research project Icarus aiming to develop robotic tools for large scale rescue operations. The tests consisted in the use of the ROAZ unmanned surface vehicle equipped with a precision GPS system for localization and both visible spectrum and IR cameras to detect the target. In the experimental setup, the test human target was deployed in the water wearing a life vest and a diver suit (thus having lower temperature signature in the body except hands and head) and was equipped with a GPS logger. Multiple target approaches were performed in order to test the system with different sun incidence relative angles. The experimental setup, detection method and preliminary results from the field trials performed in the summer of 2013 in Sesimbra, Portugal and in La Spezia, Italy are also presented in this work.

Groundtruth system for underwater benchmarking

Oceans - San Diego, 2013

Calibration Method for Underwater Visual Ground-Truth System

This work presents an automatic calibration method for a vision based external underwater ground-truth positioning system. These systems are a relevant tool in benchmarking and assessing the quality of research in underwater robotics applications. A stereo vision system can in suitable environments such as test tanks or in clear water conditions provide accurate position with low cost and flexible operation. In this work we present a two step extrinsic camera parameter calibration procedure in order to reduce the setup time and provide accurate results. The proposed method uses a planar homography decomposition in order to determine the relative camera poses and the determination of vanishing points of detected lines in the image to obtain the global pose of the stereo rig in the reference frame. This method was applied to our external vision based ground-truth at the INESC TEC/Robotics test tank. Results are presented in comparison with an precise calibration performed using points obtained from an accurate 3D LIDAR modelling of the environment.

Geostatistical Mapping of Outfall Plume Dispersion Data gathered with an autonomous underwater vehicle

The main purpose of this study was to examine the applicability of geostatistical modeling to obtain valuable information for assessing the environmental impact of sewage outfall discharges. The data set used was obtained in a monitoring campaign to S. Jacinto outfall, located off the Portuguese west coast near Aveiro region, using an AUV. The Matheron’s classical estimator was used the compute the experimental semivariogram which was fitted to three theoretical models: spherical, exponential and gaussian. The cross-validation procedure suggested the best semivariogram model and ordinary kriging was used to obtain the predictions of salinity at unknown locations. The generated map shows clearly the plume dispersion in the studied area, indicating that the effluent does not reach the near by beaches. Our study suggests that an optimal design for the AUV sampling trajectory from a geostatistical prediction point of view, can help to compute more precise predictions and hence to quantify more accurately dilution. Moreover, since accurate measurements of plume’s dilution are rare, these studies might be very helpful in the future for validation of dispersion models.

Intelligent Bio-Inspired system for manufacturing scheduling under uncertainties

A novel approach to scheduling resolution by combining Autonomic Computing (AC), Multi-Agent Systems (MAS), Case-based Reasoning (CBR), and Bio-Inspired Optimization Techniques (BIT) will be described. AC has emerged as a paradigm aiming at incorporating applications with a management structure similar to the central nervous system. The main intentions are to improve resource utilization and service quality. In this paper we envisage the use of MAS paradigm for supporting dynamic and distributed scheduling in Manufacturing Systems with AC properties, in order to reduce the complexity of managing manufacturing systems and human interference. The proposed CBR based Intelligent Scheduling System was evaluated under different dynamic manufacturing scenarios.

Celiac disease detection using a transglutaminase electrochemical immunosensor fabricated on nanohybrid screen-printed carbon electrodes

Celiac disease is a gluten-induced autoimmune enteropathy characterized by the presence of tissue tranglutaminase (tTG) autoantibodies. A disposable electrochemical immunosensor (EI) for the detection of IgA and IgG type anti-tTG autoantibodies in real patient’s samples is presented. Screen-printed carbon electrodes (SPCE) nanostructurized with carbon nanotubes and gold nanoparticles were used as the transducer surface. This transducer exhibits the excellent characteristics of carbon–metal nanoparticle hybrid conjugation and led to the amplification of the immunological interaction. The immunosensing strategy consisted of the immobilization of tTG on the nanostructured electrode surface followed by the electrochemical detection of the autoantibodies present in the samples using an alkaline phosphatase (AP) labelled anti-human IgA or IgG antibody. The analytical signal was based on the anodic redissolution of enzymatically generated silver by cyclic voltammetry. The results obtained were corroborated with a commercial ELISA kit indicating that the electrochemical immunosensor is a trustful analytical screening tool.

Molecular imprinted nanoelectrodes for ultra sensitive detection of ovarian cancer marker

The relentless discovery of cancer biomarkers demands improved methods for their detection. In this work, we developed protein imprinted polymer on three-dimensional gold nanoelectrode ensemble (GNEE) to detect epithelial ovarian cancer antigen-125 (CA 125), a protein biomarker associated with ovarian cancer. CA 125 is the standard tumor marker used to follow women during or after treatment for epithelial ovarian cancer. The template protein CA 125 was initially incorporated into the thin-film coating and, upon extraction of protein from the accessible surfaces on the thin film, imprints for CA 125 were formed. The fabrication and analysis of the CA 125 imprinted GNEE was done by using cyclic voltammetry (CV), differential pulse voltammetry (DPV) and electrochemical impedance spectroscopy (EIS) techniques. The surfaces of the very thin, protein imprinted sites on GNEE are utilized for immunospecific capture of CA 125 molecules, and the mass of bound on the electrode surface can be detected as a reduction in the faradic current from the redox marker. Under optimal conditions, the developed sensor showed good increments at the studied concentration range of 0.5–400 U mL−1. The lowest detection limit was found to be 0.5 U mL−1. Spiked human blood serum and unknown real serum samples were analyzed. The presence of non-specific proteins in the serum did not significantly affect the sensitivity of our assay. Molecular imprinting using synthetic polymers and nanomaterials provides an alternative approach to the trace detection of biomarker proteins.