Model-based systems engineering: a system for traffic & environment

The contemporary world is crowded of large, interdisciplinary, complex systems made of other systems, personnel, hardware, software, information, processes, and facilities. The Systems Engineering (SE) field proposes an integrated holistic approach to tackle these socio-technical systems that is crucial to take proper account of their multifaceted nature and numerous interrelationships, providing the means to enable their successful realization. Model-Based Systems Engineering (MBSE) is an emerging paradigm in the SE field and can be described as the formalized application of modelling principles, methods, languages, and tools to the entire lifecycle of those systems, enhancing communications and knowledge capture, shared understanding, improved design precision and integrity, better development traceability, and reduced development risks. This thesis is devoted to the application of the novel MBSE paradigm to the Urban Traffic & Environment domain. The proposed system, the GUILTE (Guiding Urban Intelligent Traffic & Environment), deals with a present-day real challenging problem “at the agenda” of world leaders, national governors, local authorities, research agencies, academia, and general public. The main purposes of the system are to provide an integrated development framework for the municipalities, and to support the (short-time and real-time) operations of the urban traffic through Intelligent Transportation Systems, highlighting two fundamental aspects: the evaluation of the related environmental impacts (in particular, the air pollution and the noise), and the dissemination of information to the citizens, endorsing their involvement and participation. These objectives are related with the high-level complex challenge of developing sustainable urban transportation networks. The development process of the GUILTE system is supported by a new methodology, the LITHE (Agile Systems Modelling Engineering), which aims to lightening the complexity and burdensome of the existing methodologies by emphasizing agile principles such as continuous communication, feedback, stakeholders involvement, short iterations and rapid response. These principles are accomplished through a universal and intuitive SE process, the SIMILAR process model (which was redefined at the light of the modern international standards), a lean MBSE method, and a coherent System Model developed through the benchmark graphical modeling languages SysML and OPDs/OPL. The main contributions of the work are, in their essence, models and can be settled as: a revised process model for the SE field, an agile methodology for MBSE development environments, a graphical tool to support the proposed methodology, and a System Model for the GUILTE system. The comprehensive literature reviews provided for the main scientific field of this research (SE/MBSE) and for the application domain (Traffic & Environment) can also be seen as a relevant contribution.

Visible light communication systems for road safety applications

Esta tese apresenta um estudo exploratório sobre sistemas de comunicação por luz visível e as suas aplicações em sistemas de transporte inteligentes como forma a melhorar a segurança nas estradas. Foram desenvolvidos neste trabalho, modelos conceptuais e analíticos adequados à caracterização deste tipo de sistemas. Foi desenvolvido um protótipo de baixo custo, capaz de suportar a disseminação de informação utilizando semáforos. A sua realização carece de um estudo detalhado, nomeadamente: i) foi necessário obter modelos capazes de descrever os padrões de radiação numa área de serviço pré-definida; ii) foi necessário caracterizar o meio de comunicações; iii) foi necessário estudar o comportamento de vários esquemas de modulação de forma a optar pelo mais robusto; finalmente, iv) obter a implementação do sistema baseado em FPGA e componentes discretos. O protótipo implementado foi testado em condições reais. Os resultados alcançados mostram os méritos desta solução, chegando mesmo a encorajar a utilização desta tecnologia em outros cenários de aplicação.

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.

Genetic programming and bacterial algorithm for neural networks and fuzzy systems design

In the field of control systems it is common to use techniques based on model adaptation to carry out control for plants for which mathematical analysis may be intricate. Increasing interest in biologically inspired learning algorithms for control techniques such as Artificial Neural Networks and Fuzzy Systems is in progress. In this line, this paper gives a perspective on the quality of results given by two different biologically connected learning algorithms for the design of B-spline neural networks (BNN) and fuzzy systems (FS). One approach used is the Genetic Programming (GP) for BNN design and the other is the Bacterial Evolutionary Algorithm (BEA) applied for fuzzy rule extraction. Also, the facility to incorporate a multi-objective approach to the GP algorithm is outlined, enabling the designer to obtain models more adequate for their intended use.

A Rapid Detection of Meat Spoilage using an Electronic Nose and Fuzzy-Wavelet systems

Freshness and safety of muscle foods are generally considered as the most important parameters for the food industry. To address the rapid detection of meat spoilage microorganisms during aerobic or modified atmosphere storage, an electronic nose with the aid of fuzzy wavelet network has been considered in this research. The proposed model incorporates a clustering pre-processing stage for the definition of fuzzy rules. The dual purpose of the proposed modelling approach is not only to classify beef samples in the respective quality class (i.e. fresh, semi-fresh and spoiled), but also to predict their associated microbiological population directly from volatile compounds fingerprints. Comparison results against neural networks and neurofuzzy systems indicated that the proposed modelling scheme could be considered as a valuable detection methodology in food microbiology

TINSEL – a web-based intelligent tutoring system on electrical installation design

This paper presents a project consisting on the development of an Intelligent Tutoring System, for training and support concerning the development of electrical installation projects to be used by electrical engineers, technicians and students. One of the major goals of this project is to devise a teaching model based on Intelligent Tutoring techniques, considering not only academic knowledge but also other types of more empirical knowledge, able to achieve successfully the training of electrical installation design.

A multi-agent based approach for intelligent smart grid management

The spread and globalization of distributed generation (DG) in recent years has should highly influence the changes that occur in Electricity Markets (EMs). DG has brought a large number of new players to take action in the EMs, therefore increasing the complexity of these markets. Simulation based on multi-agent systems appears as a good way of analyzing players’ behavior and interactions, especially in a coalition perspective, and the effects these players have on the markets. MASCEM – Multi-Agent System for Competitive Electricity Markets was created to permit the study of the market operation with several different players and market mechanisms. MASGriP – Multi-Agent Smart Grid Platform is being developed to facilitate the simulation of micro grid (MG) and smart grid (SG) concepts with multiple different scenarios. This paper presents an intelligent management method for MG and SG. The simulation of different methods of control provides an advantage in comparing different possible approaches to respond to market events. Players utilize electric vehicles’ batteries and participate in Demand Response (DR) contracts, taking advantage on the best opportunities brought by the use of all resources, to improve their actions in response to MG and/or SG requests.

Intelligent management of end consumers loads including electric vehicles through a SCADA system

The large penetration of intermittent resources, such as solar and wind generation, involves the use of storage systems in order to improve power system operation. Electric Vehicles (EVs) with gridable capability (V2G) can operate as a means for storing energy. This paper proposes an algorithm to be included in a SCADA (Supervisory Control and Data Acquisition) system, which performs an intelligent management of three types of consumers: domestic, commercial and industrial, that includes the joint management of loads and the charge/discharge of EVs batteries. The proposed methodology has been implemented in a SCADA system developed by the authors of this paper – the SCADA House Intelligent Management (SHIM). Any event in the system, such as a Demand Response (DR) event, triggers the use of an optimization algorithm that performs the optimal energy resources scheduling (including loads and EVs), taking into account the priorities of each load defined by the installation users. A case study considering a specific consumer with several loads and EVs is presented in this paper.

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.

An intelligent tutoring approach to support students and technicians in electrical installation design

Designing electric installation projects, demands not only academic knowledge, but also other types of knowledge not easily acquired through traditional instructional methodologies. A lot of additional empirical knowledge is missing and so the academic instruction must be completed with different kinds of knowledge, such as real-life practical examples and simulations. On the other hand, the practical knowledge detained by the most experienced designers is not formalized in such a way that is easily transmitted. In order to overcome these difficulties present in the engineers formation, we are developing an Intelligent Tutoring System (ITS), for training and support concerning the development of electrical installation projects to be used by electrical engineers, technicians and students.

Genetic algorithm methodology applied to intelligent house control

In recent years the use of several new resources in power systems, such as distributed generation, demand response and more recently electric vehicles, has significantly increased. Power systems aim at lowering operational costs, requiring an adequate energy resources management. In this context, load consumption management plays an important role, being necessary to use optimization strategies to adjust the consumption to the supply profile. These optimization strategies can be integrated in demand response programs. The control of the energy consumption of an intelligent house has the objective of optimizing the load consumption. This paper presents a genetic algorithm approach to manage the consumption of a residential house making use of a SCADA system developed by the authors. Consumption management is done reducing or curtailing loads to keep the power consumption in, or below, a specified energy consumption limit. This limit is determined according to the consumer strategy and taking into account the renewable based micro generation, energy price, supplier solicitations, and consumers’ preferences. The proposed approach is compared with a mixed integer non-linear approach.

Intelligent behavior in a Cyber-Ambient training system for control center operators

This paper deals with the application of an intelligent tutoring approach to delivery training in diagnosis procedures of a Power System. In particular, the mechanisms implemented by the training tool to support the trainees are detailed. This tool is part of an architecture conceived to integrate Power Systems tools in a Power System Control Centre, based on an Ambient Intelligent paradigm. The present work is integrated in the CITOPSY project which main goal is to achieve a better integration between operators and control room applications, considering the needs of people, customizing requirements and forecasting behaviors.

Intelligent SCADA for load control

A supervisory control and data acquisition (SCADA) system is an integrated platform that incorporates several components and it has been applied in the field of power systems and several engineering applications to monitor, operate and control a lot of processes. In the future electrical networks, SCADA systems are essential for an intelligent management of resources like distributed generation and demand response, implemented in the smart grid context. This paper presents a SCADA system for a typical residential house. The application is implemented on MOVICON™11 software. The main objective is to manage the residential consumption, reducing or curtailing loads to keep the power consumption in or below a specified setpoint, imposed by the costumer and the generation availability.

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