A review of sensor fusion techniques for underwater vehicle navigation

This work provides a general description of the multi sensor data fusion concept, along with a new classification of currently used sensor fusion techniques for unmanned underwater vehicles (UUV). Unlike previous proposals that focus the classification on the sensors involved in the fusion, we propose a synthetic approach that is focused on the techniques involved in the fusion and their applications in UUV navigation. We believe that our approach is better oriented towards the development of sensor fusion systems, since a sensor fusion architecture should be first of all focused on its goals and then on the fused sensors

Development of thermo-analytical prediction and classification models for food in thermal devices using a multi sensor system and artificial neural networks

Die thermische Verarbeitung von Lebensmitteln beeinflusst deren Qualität und ernährungsphysiologischen Eigenschaften. Im Haushalt ist die Überwachung der Temperatur innerhalb des Lebensmittels sehr schwierig. Zudem ist das Wissen über optimale Temperatur- und Zeitparameter für die verschiedenen Speisen oft unzureichend. Die optimale Steuerung der thermischen Zubereitung ist maßgeblich abhängig von der Art des Lebensmittels und der äußeren und inneren Temperatureinwirkung während des Garvorgangs. Das Ziel der Arbeiten war die Entwicklung eines automatischen Backofens, der in der Lage ist, die Art des Lebensmittels zu erkennen und die Temperatur im Inneren des Lebensmittels während des Backens zu errechnen. Die für die Temperaturberechnung benötigten Daten wurden mit mehreren Sensoren erfasst. Hierzu kam ein Infrarotthermometer, ein Infrarotabstandssensor, eine Kamera, ein Temperatursensor und ein Lambdasonde innerhalb des Ofens zum Einsatz. Ferner wurden eine Wägezelle, ein Strom- sowie Spannungs-Sensor und ein Temperatursensor außerhalb des Ofens genutzt. Die während der Aufheizphase aufgenommen Datensätze ermöglichten das Training mehrerer künstlicher neuronaler Netze, die die verschiedenen Lebensmittel in die entsprechenden Kategorien einordnen konnten, um so das optimale Backprogram auszuwählen. Zur Abschätzung der thermische Diffusivität der Nahrung, die von der Zusammensetzung (Kohlenhydrate, Fett, Protein, Wasser) abhängt, wurden mehrere künstliche neuronale Netze trainiert. Mit Ausnahme des Fettanteils der Lebensmittel konnten alle Komponenten durch verschiedene KNNs mit einem Maximum von 8 versteckten Neuronen ausreichend genau abgeschätzt werden um auf deren Grundlage die Temperatur im inneren des Lebensmittels zu berechnen. Die durchgeführte Arbeit zeigt, dass mit Hilfe verschiedenster Sensoren zur direkten beziehungsweise indirekten Messung der äußeren Eigenschaften der Lebensmittel sowie KNNs für die Kategorisierung und Abschätzung der Lebensmittelzusammensetzung die automatische Erkennung und Berechnung der inneren Temperatur von verschiedensten Lebensmitteln möglich ist.

A review of sensor fusion techniques for underwater vehicle navigation

This work provides a general description of the multi sensor data fusion concept, along with a new classification of currently used sensor fusion techniques for unmanned underwater vehicles (UUV). Unlike previous proposals that focus the classification on the sensors involved in the fusion, we propose a synthetic approach that is focused on the techniques involved in the fusion and their applications in UUV navigation. We believe that our approach is better oriented towards the development of sensor fusion systems, since a sensor fusion architecture should be first of all focused on its goals and then on the fused sensors

Ultra-thin films of alternating semi-interpenetrating layers of a conducting polymer with thermosetting phenolic resins for sensor application

In this work a new method for crosslinking ultra-thin films with potential applications in sensor systems is proposed. The films were produced by layer-by-layer (LbL) assembly using a conducting polymer, poly(o-ethoxyaniline) (POEA), alternated with a thermosetting resin, novolac-type phenolformaldehyde (PF), crosslinked by a simple thermal treatment. The PF resin served as both alternating and crosslinking agents. The films were characterized by Fourier transform infrared (FTIR) and ultraviolet-visible (UV-Vis) spectroscopy, thermogravimetry (TG), desorption, doping/dedoping cycling and electrical measurements. The results showed that film architecture and crosslinking degree can be controlled by the conditions used for film deposition (number of bilayers, polymer concentration, pH, and deposition time), and crosslinking time. Moreover, this approach offers several advantages such as fast curing time and low cost, indicating that these films can be used to produce sensors with improved stability.

Towards the design of efficient nonbeacon-enabled ZigBee networks

This paper presents experimental results of the communication performance evaluation of a prototype ZigBee-based patient monitoring system commissioned in an in-patient floor of a Portuguese hospital (HPG – Hospital Privado de Guimar~aes). Besides, it revisits relevant problems that affect the performance of nonbeacon-enabled ZigBee networks. Initially, the presence of hidden-nodes and the impact of sensor node mobility are discussed. It was observed, for instance, that the message delivery ratio in a star network consisting of six wireless electrocardiogram sensor devices may decrease from 100% when no hidden-nodes are present to 83.96% when half of the sensor devices are unable to detect the transmissions made by the other half. An additional aspect which affects the communication reliability is a deadlock condition that can occur if routers are unable to process incoming packets during the backoff part of the CSMA-CA mechanism. A simple approach to increase the message delivery ratio in this case is proposed and its effectiveness is verified. The discussion and results presented in this paper aim to contribute to the design of efficient networks,and are valid to other scenarios and environments rather than hospitals.

BANMAC: an opportunistic MAC protocol for reliable communications in body area networks

We consider reliable communications in Body Area Networks (BAN), where a set of nodes placed on human body are connected using wireless links. In order to keep the Specific Absorption Rate (SAR) as low as possible for health safety reasons, these networks operate in low transmit power regime, which however, is known to be error prone. It has been observed that the fluctuations of the Received Signal Strength (RSS) at the nodes of a BAN on a moving person show certain regularities and that the magnitude of these fluctuations are significant (5 - 20 dB). In this paper, we present BANMAC, a MAC protocol that monitors and predicts the channel fluctuations and schedules transmissions opportunistically when the RSS is likely to be higher. The MAC protocol is capable of providing differentiated service and resolves co-channel interference in the event of multiple co-located BANs in a vicinity. We report the design and implementation details of BANMAC integrated with the IEEE 802.15.4 protocol stack. We present experimental data which show that the packet loss rate (PLR) of BANMAC is significantly lower as compared to that of the IEEE 802.15.4 MAC. For comparable PLR, the power consumption of BANMAC is also significantly lower than that of the IEEE 802.15.4. For co-located networks, the convergence time to find a conflict-free channel allocation was approximately 1 s for the centralized coordination mechanism and was approximately 4 s for the distributed coordination mechanism.

Exploiting a prioritized MAC protocol to efficiently compute min and max in multihop networks

Consider a wireless sensor network (WSN) where a broadcast from a sensor node does not reach all sensor nodes in the network; such networks are often called multihop networks. Sensor nodes take sensor readings but individual sensor readings are not very important. It is important however to compute aggregated quantities of these sensor readings. The minimum and maximum of all sensor readings at an instant are often interesting because they indicate abnormal behavior, for example if the maximum temperature is very high then it may be that a fire has broken out. We propose an algorithm for computing the min or max of sensor reading in a multihop network. This algorithm has the particularly interesting property of having a time complexity that does not depend on the number of sensor nodes; only the network diameter and the range of the value domain of sensor readings matter.

Engineering a search and rescue application with a wireless sensor network - based localization mechanism

The advent of Wireless Sensor Network (WSN) technologies is paving the way for a panoply of new ubiquitous computing applications, some of them with critical requirements. In the ART-WiSe framework, we are designing a two-tiered communication architecture for supporting real-time and reliable communications in WSNs. Within this context, we have been developing a test-bed application, for testing, validating and demonstrating our theoretical findings - a search&rescue/pursuit-evasion application. Basically, a WSN deployment is used to detect, localize and track a target robot and a station controls a rescuer/pursuer robot until it gets close enough to the target robot. This paper describes how this application was engineered, particularly focusing on the implementation of the localization mechanism.

Cloud-assisted Wireless Body Area Networks

Wireless Body Area Networks (WBANs) have emerged as a promising technology for medical and non-medical applications. WBANs consist of a number of miniaturized, portable, and autonomous sensor nodes that are used for long-term health monitoring of patients. These sensor nodes continuously collect information of patients, which are used for ubiquitous health monitoring. In addition, WBANs may be used for managing catastrophic events and increasing the effectiveness and performance of rescue forces. The huge amount of data collected by WBAN nodes demands scalable, on-demand, powerful, and secure storage and processing infrastructure. Cloud computing is expected to play a significant role in achieving the aforementioned objectives. The cloud computing environment links different devices ranging from miniaturized sensor nodes to high-performance supercomputers for delivering people-centric and context-centric services to the individuals and industries. The possible integration of WBANs with cloud computing (WBAN-cloud) will introduce viable and hybrid platform that must be able to process the huge amount of data collected from multiple WBANs. This WBAN-cloud will enable users (including physicians and nurses) to globally access the processing and storage infrastructure at competitive costs. Because WBANs forward useful and life-critical information to the cloud – which may operate in distributed and hostile environments, novel security mechanisms are required to prevent malicious interactions to the storage infrastructure. Both the cloud providers and the users must take strong security measures to protect the storage infrastructure.

Distributed Sensing of Fluid Dynamic Phenomena with the XDense Sensor Grid Network

IEEE International Conference on Cyber Physical Systems, Networks and Applications (CPSNA'15), Hong Kong, China.

Structured Light System Calibration for Perception in Underwater Tanks

The process of visually exploring underwater environments is still a complex problem. Underwater vision systems require complementary means of sensor information to help overcome water disturbances. This work proposes the development of calibration methods for a structured light based system consisting on a camera and a laser with a line beam. Two different calibration procedures that require only two images from different viewpoints were developed and tested in dry and underwater environments. Results obtained show, an accurate calibration for the camera/projector pair with errors close to 1 mm even in the presence of a small stereos baseline.

Old cellulose for new multifunctional networks

Dissertação para obtenção do Grau de Doutor em Ciência e Engenharia de Materiais

Optimization of magnetoelectric composites based on electroactive polymers for energy harvesting and sensor application

Tese de Doutoramento em Engenharia de Materiais.