A 802.11p prototype implementation

This paper presents an IEEE 802.11p full-stack prototype implementation to data exchange among vehicles and between vehicles and the roadway infrastructures. The prototype architecture is based on FPGAs for Intermediate Frequency (IF) and base band purposes, using 802.11a based transceivers for RF interfaces. Power amplifiers were also addressed, by using commercial and in-house solutions. This implementation aims to provide technical solutions for Intelligent Transportation Systems (ITS) field, namely for tolling and traffic management related services, in order to promote safety, mobility and driving comfort through the dynamic and real-time cooperation among vehicles and/or between vehicles and infrastructures. The performance of the proposed scheme is tested under realistic urban and suburban driving conditions. Preliminary results are promising, since they comply with most of the 802.11p standard requirements.

Automatic vehicle detection and classification

This paper presents a proposal for an automatic vehicle detection and classification (AVDC) system. The proposed AVDC should classify vehicles accordingly to the Portuguese legislation (vehicle height over the first axel and number of axels), and should also support profile based classification. The AVDC should also fulfill the needs of the Portuguese motorway operator, Brisa. For the classification based on the profile we propose:he use of Eigenprofiles, a technique based on Principal Components Analysis. The system should also support multi-lane free flow for future integration in this kind of environments.

Estudo de viabilidade de utilização de VLC em infra-estruturas ITS baseadas em semáforos rodoviários a LEDs

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Electrónica e Telecomunicações

The impact of driving styles on fuel consumption: a data-warehouse-and-data-mining-based discovery process

This paper discusses the results of applied research on the eco-driving domain based on a huge data set produced from a fleet of Lisbon's public transportation buses for a three-year period. This data set is based on events automatically extracted from the control area network bus and enriched with GPS coordinates, weather conditions, and road information. We apply online analytical processing (OLAP) and knowledge discovery (KD) techniques to deal with the high volume of this data set and to determine the major factors that influence the average fuel consumption, and then classify the drivers involved according to their driving efficiency. Consequently, we identify the most appropriate driving practices and styles. Our findings show that introducing simple practices, such as optimal clutch, engine rotation, and engine running in idle, can reduce fuel consumption on average from 3 to 5l/100 km, meaning a saving of 30 l per bus on one day. These findings have been strongly considered in the drivers' training sessions.

RFID together with multi-agent systems to control global value chains

Nowadays, the cooperative intelligent transport systems are part of a largest system. Transportations are modal operations integrated in logistics and, logistics is the main process of the supply chain management. The supply chain strategic management as a simultaneous local and global value chain is a collaborative/cooperative organization of stakeholders, many times in co-opetition, to perform a service to the customers respecting the time, place, price and quality levels. The transportation, like other logistics operations must add value, which is achieved in this case through compression lead times and order fulfillments. The complex supplier's network and the distribution channels must be efficient and the integral visibility (monitoring and tracing) of supply chain is a significant source of competitive advantage. Nowadays, the competition is not discussed between companies but among supply chains. This paper aims to evidence the current and emerging manufacturing and logistics system challenges as a new field of opportunities for the automation and control systems research community. Furthermore, the paper forecasts the use of radio frequency identification (RFID) technologies integrated into an information and communication technologies (ICT) framework based on distributed artificial intelligence (DAI) supported by a multi-agent system (MAS), as the most value advantage of supply chain management (SCM) in a cooperative intelligent logistics systems. Logistical platforms (production or distribution) as nodes of added value of supplying and distribution networks are proposed as critical points of the visibility of the inventory, where these technological needs are more evident.

Sistemas de automação e manutenção de edifícios: eficiência energética dos sistemas de elevação vertical para transporte de pessoas

O presente trabalho incide sobre a análise da eficiência energética dos elevadores. Para se poder entender esta questão, são apresentadas diversas informações que permitem conhecer os factores associados aos consumos de energia activa, procurando-se perceber qual o rendimento destes equipamentos. Inicialmente são analisados os diversos componentes, que fazem parte de um elevador e os locais em que esses componentes são instalados. Abordam-se as diferentes soluções de accionamento, os diversos tipos de utilização e as diferentes tecnologias que podem ser aplicadas. O estudo dos consumos de energia eléctrica dos elevadores, foi efectuado com base na metodologia desenvolvida pelo grupo E4, do programa Utilização Eficiente da Energia, da Comunidade Europeia, cujo suporte foi o DRAFT ISSO/DIS 25745 - 1 Energy Performance of Lifts and Escalators - Part 1: Energy Measurement and Conformance. Os consumos de energia eléctrica serão caracterizados com os elevadores a serem monitorizados individualmente e sem carga na cabina. A apresentação de resultados obtidos terá em linha de conta: a energia eléctrica consumida com o equipamento em modo de funcionamento, ou seja, com este a realizar ciclos completos, e a potência eléctrica consumida com a instalação em modo de standby, ou seja em não operação. No presente trabalho, são divulgados estudos do grupo E4, em que foram monitorizados elevadores em quatro países da Europa: Portugal, Alemanha, Itália e Polónia. Estes estudos permitem estimar os consumos anuais de energia eléctrica, a nível de funcionamento e a nível de standby e estimar o consumo total, seguindo como base a metodologia anteriormente referida. Para se caracterizar o parque Europeu de elevadores, o grupo E4 recorreu à ELA, Associação Europeia de Elevadores, tendo assim sido possível estimar o consumo anual numa Europa a 27, acrescido do parque da Suíça e da Noruega. Pretende-se com isso poder estimar o potencial de redução no consumo energético no parque analisado, com a aplicação das Melhores Tecnologias Disponíveis (MTD) e com a aplicação de tecnologias que ainda estão em fase de desenvolvimento. (MTND). Paralelamente o autor irá apresentar as monitorizações que efectuou a três elevadores, para os quais procurou validar as leituras efectuadas, comparando os consumos obtidos, com os consumos registados pelas monitorizações do grupo E4 e respectivas estimativas de consumos anuais de energia. As monitorizações do autor, serão utilizadas na catalogação desses três equipamentos a nível de classes de eficiência energética, tendo por base a VDI 4707/Part 1 - Lifts - Energy Efficiency - VDI manual Building Services - Volume 5: Transportation Systems. Procura-se, também, criar um método de apoio na tomada de decisão nas diversas fases de um ciclo do elevador, nomeadamente: desde a especificação, a selecção do sistema de accionamento, a selecção dos sistemas auxiliares, a instalação e a operação do elevador, com vista à melhoria da eficiência energética, e á instalação futura ou à modernização dos equipamentos existentes. Abordam-se as barreiras existentes que inibem a mudança no sector de elevação, para a implementação das MTD no parque de elevadores existente ou no desenvolvimento de novas tecnologias que possibilitem a melhoria da eficiência energética, MTND. Por ultimo, aborda-se de forma simples a temática da supervisão técnica nos elevadores, através da monitorização e supervisão dos diversos componentes, com vista à optimização da gestão da manutenção e procurando interligar esta gestão à melhoria da eficiência energética. Consegue-se concluir que apenas com a aplicação das MTD, podem ser obtidos ganhos de eficiência energética, e também que este tema não tem tido a importância que merece, pois, na análise da eficiência energética de um edifício, a eficiência dos elevadores não é tida em consideração. A ausência de legislação específica, que torne a análise da eficiência energética dos elevadores obrigatória, será um dos problemas referidos. Reforça-se que, a potencialidade de poupança energética na Europa não deve ser desprezada.

QSAR modeling of antitubercular activity of diverse organic compounds

Tuberculosis (TB) is a worldwide infectious disease that has shown over time extremely high mortality levels. The urgent need to develop new antitubercular drugs is due to the increasing rate of appearance of multi-drug resistant strains to the commonly used drugs, and the longer durations of therapy and recovery, particularly in immuno-compromised patients. The major goal of the present study is the exploration of data from different families of compounds through the use of a variety of machine learning techniques so that robust QSAR-based models can be developed to further guide in the quest for new potent anti-TB compounds. Eight QSAR models were built using various types of descriptors (from ADRIANA.Code and Dragon software) with two publicly available structurally diverse data sets, including recent data deposited in PubChem. QSAR methodologies used Random Forests and Associative Neural Networks. Predictions for the external evaluation sets obtained accuracies in the range of 0.76-0.88 (for active/inactive classifications) and Q(2)=0.66-0.89 for regressions. Models developed in this study can be used to estimate the anti-TB activity of drug candidates at early stages of drug development (C) 2011 Elsevier B.V. All rights reserved.

Análise de eficiência energética de transportes rodoviários

Projecto para obtenção do grau de Mestre em Engenharia Informática e de computadores

Enhanced PCA-based localization using depth maps with missing data

In this paper a new method for self-localization of mobile robots, based on a PCA positioning sensor to operate in unstructured environments, is proposed and experimentally validated. The proposed PCA extension is able to perform the eigenvectors computation from a set of signals corrupted by missing data. The sensor package considered in this work contains a 2D depth sensor pointed upwards to the ceiling, providing depth images with missing data. The positioning sensor obtained is then integrated in a Linear Parameter Varying mobile robot model to obtain a self-localization system, based on linear Kalman filters, with globally stable position error estimates. A study consisting in adding synthetic random corrupted data to the captured depth images revealed that this extended PCA technique is able to reconstruct the signals, with improved accuracy. The self-localization system obtained is assessed in unstructured environments and the methodologies are validated even in the case of varying illumination conditions.

Robot visual localization through local feature fusion: an evaluation of multiple classifiers combination approaches

In the last decade, local image features have been widely used in robot visual localization. In order to assess image similarity, a strategy exploiting these features compares raw descriptors extracted from the current image with those in the models of places. This paper addresses the ensuing step in this process, where a combining function must be used to aggregate results and assign each place a score. Casting the problem in the multiple classifier systems framework, in this paper we compare several candidate combiners with respect to their performance in the visual localization task. For this evaluation, we selected the most popular methods in the class of non-trained combiners, namely the sum rule and product rule. A deeper insight into the potential of these combiners is provided through a discriminativity analysis involving the algebraic rules and two extensions of these methods: the threshold, as well as the weighted modifications. In addition, a voting method, previously used in robot visual localization, is assessed. Furthermore, we address the process of constructing a model of the environment by describing how the model granularity impacts upon performance. All combiners are tested on a visual localization task, carried out on a public dataset. It is experimentally demonstrated that the sum rule extensions globally achieve the best performance, confirming the general agreement on the robustness of this rule in other classification problems. The voting method, whilst competitive with the product rule in its standard form, is shown to be outperformed by its modified versions.

Personalized public transportation information

Thesis to obtain the Master of Science Degree in Computer Science and Engineering