Multicomponent gas-mixture measurements using an array of gas sensors and an artificial neural-network

An Electronic Nose is being jointly developed between the University of Greenwich and the Institute of Intelligent Machines to detect the gases given off from an oil filled transformer when it begins to break down. The gas sensors being used are very simple, consisting of a layer of Tin Oxide (SnO2) which is heated to approximately 640 K and the conductivity varies with the gas concentrations. Some of the shortcomings introduced by the commercial gas sensors available are being overcome by the use of an integrated array of gas sensors and the use of artificial neural networks which can be 'taught' to recognize when the gas contains several components. At present simulated results have achieved up to a 94% success rate of recognizing two component gases and future work will investigate alternative neural network configurations to maintain this success rate with practical measurements.

Oxygen indicators and intelligent inks for packaging food

The detection of oxygen using optical sensors is of increasing interest, especially in modified atmosphere food packaging (MAP), in which the package, usually containing food, is flushed with a gas, such as carbon dioxide or nitrogen. This tutorial review examines the ideal properties of an oxygen optical sensor for MAP and compares them with those developed to date, including the most recent advances. The basic technologies underpinning the different indicator types are described, examples given and their potential for application in MAP assessed. This tutorial review should be of interest to the MAP industry and researchers in optical sensors and oxygen sensing.

Assessment Of various sensors for structural health monitoring for bridge weigh-in-motion (B-WIM).

In recent years, Structural Health Monitoring (SHM) systems have been developed to monitor bridge deterioration, assess real load levels and hence extend bridge life and safety. A road bridge is only safe if the stresses caused by the passing vehicles are less than the capacity of the bridge to resist them. Conventional SHM systems can be used to improve knowledge of the bridges capacity to resist stresses but generally give no information on the causes of any increase in stresses (based on measuring strain). The concept of in Bridge Weigh-in-Motion (B-WIM) is to establish axle loads, without interruption to traffic flow, by using strain sensors at a bridge soffit and subsequently converting the data to real time axle loads or stresses. Recent studies have shown it would be most beneficial to develop a portable system which can be easily attached to existing and new bridge structures for a specified monitoring period. The sensors could then be left in place while the data acquisition can be moved for various other sites. Therefore it is necessary to find accurate sensors capable of capturing peak strains under dynamic load and suitable methods for attaching these strain sensors to existing and new bridge structures. Additionally, it is important to ensure accurate strain transfer between concrete and steel, the adhesives layer and the strain sensor. This paper describes research investigating the suitably of using various sensors for the monitoring of concrete structures under dynamic vehicle load. Electrical resistance strain (ERS) gauges, vibrating wire (VW) gauges and fibre optic sensors (FOS) are commonly used for SHM. A comparative study will be carried out to select a suitable sensor for a bridge Weigh in Motion System. This study will look at fixing methods, durability, scanning rate and accuracy range. Finite element modeling is used to predict the strains which are then validated in laboratory trials.

SWORD: an intelligent vibratory wearable device to improve rehabilitation in stroke patients

Anualmente ocorrem cerca de 16 milhões AVCs em todo o mundo. Cerca de metade dos sobreviventes irá apresentar défice motor que necessitará de reabilitação na janela dos 3 aos 6 meses depois do AVC. Nos países desenvolvidos, é estimado que os custos com AVCs representem cerca de 0.27% do Produto Interno Bruto de cada País. Esta situação implica um enorme peso social e financeiro. Paradoxalmente a esta situação, é aceite na comunidade médica a necessidade de serviços de reabilitação motora mais intensivos e centrados no doente. Na revisão do estado da arte, demonstra-se o arquétipo que relaciona metodologias terapêuticas mais intensivas com uma mais proficiente reabilitação motora do doente. Revelam-se também as falhas nas soluções tecnológicas existentes que apresentam uma elevada complexidade e custo associado de aquisição e manutenção. Desta forma, a pergunta que suporta o trabalho de doutoramento seguido inquire a possibilidade de criar um novo dispositivo de simples utilização e de baixo custo, capaz de apoiar uma recuperação motora mais eficiente de um doente após AVC, aliando intensidade com determinação da correcção dos movimentos realizados relativamente aos prescritos. Propondo o uso do estímulo vibratório como uma ferramenta proprioceptiva de intervenção terapêutica a usar no novo dispositivo, demonstra-se a tolerabilidade a este tipo de estímulos através do teste duma primeira versão do sistema apenas com a componente de estimulação num primeiro grupo de 5 doentes. Esta fase validará o subsequente desenvolvimento do sistema SWORD. Projectando o sistema SWORD como uma ferramenta complementar que integra as componentes de avaliação motora e intervenção proprioceptiva por estimulação, é descrito o desenvolvimento da componente de quantificação de movimento que o integra. São apresentadas as diversas soluções estudadas e o algoritmo que representa a implementação final baseada na fusão sensorial das medidas provenientes de três sensores: acelerómetro, giroscópio e magnetómetro. O teste ao sistema SWORD, quando comparado com o método de reabilitação tradicional, mostrou um ganho considerável de intensidade e qualidade na execução motora para 4 dos 5 doentes testados num segundo grupo experimental. É mostrada a versatilidade do sistema SWORD através do desenvolvimento do módulo de Tele-Reabilitação que complementa a componente de quantificação de movimento com uma interface gráfica de feedback e uma ferramenta de análise remota da evolução motora do doente. Finalmente, a partir da componente de quantificação de movimento, foi ainda desenvolvida uma versão para avaliação motora automatizada, implementada a partir da escala WMFT, que visa retirar o factor subjectivo da avaliação humana presente nas escalas de avaliação motora usadas em Neurologia. Esta versão do sistema foi testada num terceiro grupo experimental de cinco doentes.

Amorçage cognitif pour amélioration de l’acquisition de la connaissance dans un système tutoriel intelligent

Cette thèse vise à définir une nouvelle méthode d’enseignement pour les systèmes tutoriels intelligents dans le but d’améliorer l’acquisition des connaissances. L’apprentissage est un phénomène complexe faisant intervenir des mécanismes émotionnels et cognitifs de nature consciente et inconsciente. Nous nous intéressons à mieux comprendre les mécanismes inconscients du raisonnement lors de l’acquisition des connaissances. L’importance de ces processus inconscients pour le raisonnement est bien documentée en neurosciences, mais demeure encore largement inexplorée dans notre domaine de recherche. Dans cette thèse, nous proposons la mise en place d’une nouvelle approche pédagogique dans le domaine de l’éducation implémentant une taxonomie neuroscientifique de la perception humaine. Nous montrons que cette nouvelle approche agit sur le raisonnement et, à tour de rôle, améliore l’apprentissage général et l’induction de la connaissance dans un environnement de résolution de problème. Dans une première partie, nous présentons l’implémentation de notre nouvelle méthode dans un système tutoriel visant à améliorer le raisonnement pour un meilleur apprentissage. De plus, compte tenu de l’importance des mécanismes émotionnels dans l’apprentissage, nous avons également procédé dans cette partie à la mesure des émotions par des capteurs physiologiques. L’efficacité de notre méthode pour l’apprentissage et son impact positif observé sur les émotions a été validée sur trente et un participants. Dans une seconde partie, nous allons plus loin dans notre recherche en adaptant notre méthode visant à améliorer le raisonnement pour une meilleure induction de la connaissance. L’induction est un type de raisonnement qui permet de construire des règles générales à partir d’exemples spécifiques ou de faits particuliers. Afin de mieux comprendre l’impact de notre méthode sur les processus cognitifs impliqués dans ce type de raisonnement, nous avons eu recours à des capteurs cérébraux pour mesurer l’activité du cerveau des utilisateurs. La validation de notre approche réalisée sur quarante-trois volontaires montre l’efficacité de notre méthode pour l’induction de la connaissance et la viabilité de mesurer le raisonnement par des mesures cérébrales suite à l’application appropriée d’algorithmes de traitement de signal. Suite à ces deux parties, nous clorons la thèse par une discussion applicative en décrivant la mise en place d’un nouveau système tutoriel intelligent intégrant les résultats de nos travaux.

Intelligent wireless web services: context-aware computing in construction-logistics supply chain

The construction industry has incurred a considerable amount of waste as a result of poor logistics supply chain network management. Therefore, managing logistics in the construction industry is critical. An effective logistic system ensures delivery of the right products and services to the right players at the right time while minimising costs and rewarding all sectors based on value added to the supply chain. This paper reports on an on-going research study on the concept of context-aware services delivery in the construction project supply chain logistics. As part of the emerging wireless technologies, an Intelligent Wireless Web (IWW) using context-aware computing capability represents the next generation ICT application to construction-logistics management. This intelligent system has the potential of serving and improving the construction logistics through access to context-specific data, information and services. Existing mobile communication deployments in the construction industry rely on static modes of information delivery and do not take into account the worker’s changing context and dynamic project conditions. The major problems in these applications are lack of context-specificity in the distribution of information, services and other project resources, and lack of cohesion with the existing desktop based ICT infrastructure. The research works focus on identifying the context dimension such as user context, environmental context and project context, selection of technologies to capture context-parameters such wireless sensors and RFID, selection of supporting technologies such as wireless communication, Semantic Web, Web Services, agents, etc. The process of integration of Context-Aware Computing and Web-Services to facilitate the creation of intelligent collaboration environment for managing construction logistics will take into account all the necessary critical parameters such as storage, transportation, distribution, assembly, etc. within off and on-site project.

A comparison of the Oxford and Manus intelligent hand prostheses

Historically, commercial hand prosthesis have adopted a low level of innovation mainly due to the strict conditions such a system must undergo. The difficult feedback to the prosthesis user has limited the functional range of commercial systems. Nevertheless, the use of advanced sensors in combination with performing hand mechanisms and microcontrollers could lead to more natural and functional prototypes. The Oxford and Manus intelligent hand prostheses are examples of innovative approaches. This paper compares and contrasts the technological solutions implemented in both systems to address the design conditions.

A low-cost intelligent gas sensing device for military applications

The field of electronic noses and gas sensing has been developing rapidly since the introduction of the silicon based sensors. There are numerous systems that can detect and indicate the level of a specific gas. We introduce here a system that is low power, small and cheap enough to be used in mobile robotic platforms while still being accurate and reliable enough for confident use. The design is based around a small circuit board mounted in a plastic case with holes to allow the sensors to protrude through the top and allow the natural flow of gas evenly across them. The main control board consists of a microcontroller PCB with surface mount components for low cost and power consumption. The firmware of the device is based on an algorithm that uses an Artificial Neural Network (ANN) which receives input from an array of gas sensors. The various sensors feeding the ANN allow the microcontroller to determine the gas type and quantity. The Testing of the device involves the training of the ANN with a number of different target gases to determine the weightings for the ANN. Accuracy and reliability of the ANN is validated through testing in a specific gas filled environment.

Intelligent based mobility models for data management in wireless sensor networks

Wireless sensor networks (WSNs) are proposed as powerful means for fine grained monitoring in different classes of applications at very low cost and for extended periods of time. Among various solutions, supporting WSNs with intelligent mobile platforms for handling the data management, proved its benefits towards extending the network lifetime and enhancing its performance. The mobility model applied highly affects the data latency in the network as well as the sensors’ energy consumption levels. Intelligent-based models taking into consideration the network runtime conditions are adopted to overcome such problems. In this chapter, existing proposals that use intelligent mobility for managing the data in WSNs are surveyed. Different classifications are presented through the chapter to give a complete view on the solutions lying in this domain. Furthermore, these models are compared considering various metrics and design goals.

Optimal algorithm for a mobile intelligent gas detection device

This thesis is based on the development of a gas detection device that can be mounted on a mobile robotic platform. The focus was on development of the A.I recognition algorithm with an array of sensors to detect trace amounts of explosive and volatile gases in the environments it is exposed to.

Intelligent control and look-ahead energy management of hybrid electric vehicles

A review of the state of knowledge in the field of control and energy management in HEVs is carried out. The key innovation of the project is the development of a model of a PHEV using the real road data with an intelligent look-ahead online controller. Another novelty of this work is the method of route planning. It combines the information of vehicle sensors such as accelerometer and speedometer with the data of a GPS to create a road grade map for use within the look-ahead energy management strategy in the vehicle. For the PHEV, an adaptive cruise controller is modelled and an optimisation method is applied to obtain the best speed profile during a trajectory. Finally, the nonlinear model of the vehicle is applied with the sliding mode controller. The effect of using this controller is compared with the universal cruise controller. The stability of the system is studied and proved.

H-2 and H-infinity - norm control of intelligent structures using LMI techniques

Linear Matrix Inequalities (LMIs) is a powerful too] that has been used in many areas ranging from control engineering to system identification and structural design. There are many factors that make LMI appealing. One is the fact that a lot of design specifications and constrains can be formulated as LMIs [1]. Once formulated in terms of LMIs a problem can be solved efficiently by convex optimization algorithms. The basic idea of the LMI method is to formulate a given problem as an optimization problem with linear objective function and linear matrix inequalities constrains. An intelligent structure involves distributed sensors and actuators and a control law to apply localized actions, in order to minimize or reduce the response at selected conditions. The objective of this work is to implement techniques of control based on LMIs applied to smart structures.