Infoestrutura: um sistema em nuvem para prover contexto como serviço no cenário de internet das coisas integrado a ambientes veiculares

Through numerous technological advances in recent years along with the popularization of computer devices, the company is moving towards a paradigm “always connected”. Computer networks are everywhere and the advent of IPv6 paves the way for the explosion of the Internet of Things. This concept enables the sharing of data between computing machines and objects of day-to-day. One of the areas placed under Internet of Things are the Vehicular Networks. However, the information generated individually for a vehicle has no large amount and does not contribute to an improvement in transit, once information has been isolated. This proposal presents the Infostructure, a system that has to facilitate the efforts and reduce costs for development of applications context-aware to high-level semantic for the scenario of Internet of Things, which allows you to manage, store and combine the data in order to generate broader context. To this end we present a reference architecture, which aims to show the major components of the Infostructure. Soon after a prototype is presented which is used to validate our work reaches the level of contextualization desired high level semantic as well as a performance evaluation, which aims to evaluate the behavior of the subsystem responsible for managing contextual information on a large amount of data. After statistical analysis is performed with the results obtained in the evaluation. Finally, the conclusions of the work and some problems such as no assurance as to the integrity of the sensory data coming Infostructure, and future work that takes into account the implementation of other modules so that we can conduct tests in real environments are presented.

Deep learning architecture for gesture recognition

Pós-graduação em Engenharia Mecânica - FEG

Sistema de climatización por suelo radiante coalimentado por energías renovables

Se presenta el sistema de climatización basado en suelo radiante coalimentado por fuentes de energía renovables, que es capaz de proporcionar calor o frío. Se ha modelado una instalación genérica, que ha sido particularizada e integrada en una vivienda-laboratorio de unos 54m2. El sistema está compuesto por placas termo-solares, calentador eléctrico, bomba de calor aire-agua, acumuladores, circuito de suelo radiante y fancoil. El sistema de control está basado en un autómata que integra sensores y actuadores de diversas tecnologías que permiten monitorizar el sistema, visualizar y gestionar la instalación de forma remota y realizar un control minimizando el gasto energético. El sistema de control es reactivo en tiempo real por lo que cada vez que sucede algún cambio en el entorno se desencadenas las acciones oportunas.

Representation of 2D objects with a topology preserving network

Comunicación presentada en el 2nd International Workshop on Pattern Recognition in Information Systems, Alicante, April, 2002.

Hand gesture recognition based on morphologic features

Comunicación presentada en el IX Simposium Nacional de Reconocimiento de Formas y Análisis de Imágenes, Benicàssim, Mayo, 2001.

Context-awareness privacy in data communications

Internet users consume online targeted advertising based on information collected about them and voluntarily share personal information in social networks. Sensor information and data from smart-phones is collected and used by applications, sometimes in unclear ways. As it happens today with smartphones, in the near future sensors will be shipped in all types of connected devices, enabling ubiquitous information gathering from the physical environment, enabling the vision of Ambient Intelligence. The value of gathered data, if not obvious, can be harnessed through data mining techniques and put to use by enabling personalized and tailored services as well as business intelligence practices, fueling the digital economy. However, the ever-expanding information gathering and use undermines the privacy conceptions of the past. Natural social practices of managing privacy in daily relations are overridden by socially-awkward communication tools, service providers struggle with security issues resulting in harmful data leaks, governments use mass surveillance techniques, the incentives of the digital economy threaten consumer privacy, and the advancement of consumergrade data-gathering technology enables new inter-personal abuses. A wide range of fields attempts to address technology-related privacy problems, however they vary immensely in terms of assumptions, scope and approach. Privacy of future use cases is typically handled vertically, instead of building upon previous work that can be re-contextualized, while current privacy problems are typically addressed per type in a more focused way. Because significant effort was required to make sense of the relations and structure of privacy-related work, this thesis attempts to transmit a structured view of it. It is multi-disciplinary - from cryptography to economics, including distributed systems and information theory - and addresses privacy issues of different natures. As existing work is framed and discussed, the contributions to the state-of-theart done in the scope of this thesis are presented. The contributions add to five distinct areas: 1) identity in distributed systems; 2) future context-aware services; 3) event-based context management; 4) low-latency information flow control; 5) high-dimensional dataset anonymity. Finally, having laid out such landscape of the privacy-preserving work, the current and future privacy challenges are discussed, considering not only technical but also socio-economic perspectives.

Incorporación de agentes inteligentes en ambientes de aprendizaje.

El resumen es copia del publicado con el artículo

Um Sistema de alertas inteligentes para ambientes de ensino na internet

A difusão da educação baseada na Web está trazendo uma série de mudanças nesta área. Uma dessas mudanças está na forma de como se avaliar as atividades dos alunos remotos, não só através de tarefas tradicionais como testes, mas verificando, em tempo-real, as ações dos alunos e assim possibilitando ao professor um acompanhamento mais completo das atividades dos estudantes. De acordo com os recursos computacionais existentes, a utilização de um Sistema de Alertas é a opção que melhor se adequa a estas finalidades, pois com este tipo de sistema é possível acompanhar as atividades dos alunos em cursos a distância. O objetivo deste trabalho é apresentar um Sistema de Alertas Inteligentes para apoio ao ensino, que detecta problemas nas atividades dos alunos em cursos na Web e realiza ações corretivas adequadas. Este sistema está parcialmente integrado ao ambiente Tapejara do Instituto de Informática da UFRGS – Sistemas Inteligentes de Ensino na Web - que consiste em um sistema de construção e acompanhamento de cursos disponibilizados via Internet. A principal característica do Sistema de Alertas Inteligentes é a busca de situações críticas como, por exemplo: aluno apresenta baixo desempenho nos exercícios, a estratégia de ensino não corresponde ao perfil do estudante, aluno não está comparecendo às atividades do curso, etc. Com isto, este sistema pode auxiliar o professor (tutor virtual) a ter um acompanhamento mais preciso sobre as atividades realizadas pelo estudante e assim, adaptar as aulas às características do aluno, sem, com isto, acarretar numa sobrecarga de trabalho.

Integrando multiagentes em ambientes 3D: um serious game para estimulação cognitiva

Sistemas Multiagentes estão recebendo cada vez mais a atenção de pesquisadores e desenvolvedores de jogos virtuais. O uso de agentes permite controlar o desempenho do usuário, adaptando a interface e alterando automaticamente o nível de dificuldade das tarefas. Este trabalho descreve uma estratégia de integração de sistemas multiagentes e ambientes virtuais tridimensionais e exemplifica a viabilidade dessa integração através do desenvolvimento de um jogo com características de Serious game. Este jogo visa estimular as funções cognitivas, tais como atenção e memória e é voltado para pessoas portadoras de diferentes distúrbios neuropsiquiátricos. A construção do jogo foi apoiada em um processo de desenvolvimento composto por várias etapas: estudos teóricos sobre as áreas envolvidas, estudo de tecnologias capazes de apoiar essa integração, levantamento de requisitos com especialistas, implementação e avaliação com especialistas. O produto final foi avaliado por especialistas da área médica, que consideraram os resultados como positivos.

Interação social entre agentes em ambientes de recursos limitados

Trabalho final de Mestrado para obtenção do grau de Mestre em Engenharia de Redes de Comunicação e Multimédia

Modelo neuro-evolutivo de coordenação adaptativa em ambientes dinâmicos

Em ambientes dinâmicos e complexos, a política ótima de coordenação não pode ser derivada analiticamente, mas, deve ser aprendida através da interação direta com o ambiente. Geralmente, utiliza-se aprendizado por reforço para prover coordenação em tais ambientes. Atualmente, neuro-evolução é um dos métodos de aprendizado por reforço mais proeminentes. Em vista disto, neste trabalho, é proposto um modelo de coordenação baseado em neuro-evolução. Mais detalhadamente, desenvolveu-se uma extensão do método neuro-evolutivo conhecido como Enforced Subpopulations (ESP). Na extensão desenvolvida, a rede neural que define o comportamento de cada agente é totalmente conectada. Adicionalmente, é permitido que o algoritmo encontre, em tempo de treinamento, a quantidade de neurônios que deve estar presente na camada oculta da rede neural de cada agente. Esta alteração, além de oferecer flexibilidade na definição da topologia da rede de cada agente e diminuir o tempo necessário para treinamento, permite também a constituição de grupos de agentes heterogêneos. Um ambiente de simulação foi desenvolvido e uma série de experimentos realizados com o objetivo de avaliar o modelo proposto e identificar quais os melhores valores para os diversos parâmetros do modelo. O modelo proposto foi aplicado no domínio das tarefas de perseguição-evasão.

Algoritmos inteligentes para auto-correção, auto-verificação e auto-validação de medidas em sensores

This work presents a set of intelligent algorithms with the purpose of correcting calibration errors in sensors and reducting the periodicity of their calibrations. Such algorithms were designed using Artificial Neural Networks due to its great capacity of learning, adaptation and function approximation. Two approaches willbe shown, the firstone uses Multilayer Perceptron Networks to approximate the many shapes of the calibration curve of a sensor which discalibrates in different time points. This approach requires the knowledge of the sensor s functioning time, but this information is not always available. To overcome this need, another approach using Recurrent Neural Networks was proposed. The Recurrent Neural Networks have a great capacity of learning the dynamics of a system to which it was trained, so they can learn the dynamics of a sensor s discalibration. Knowingthe sensor s functioning time or its discalibration dynamics, it is possible to determine how much a sensor is discalibrated and correct its measured value, providing then, a more exact measurement. The algorithms proposed in this work can be implemented in a Foundation Fieldbus industrial network environment, which has a good capacity of device programming through its function blocks, making it possible to have them applied to the measurement process

Agentes Inteligentes com Foco de Atenção Afetivo em Simulações Baseadas em Agentes

Simulations based on cognitively rich agents can become a very intensive computing task, especially when the simulated environment represents a complex system. This situation becomes worse when time constraints are present. This kind of simulations would benefit from a mechanism that improves the way agents perceive and react to changes in these types of environments. In other worlds, an approach to improve the efficiency (performance and accuracy) in the decision process of autonomous agents in a simulation would be useful. In complex environments, and full of variables, it is possible that not every information available to the agent is necessary for its decision-making process, depending indeed, on the task being performed. Then, the agent would need to filter the coming perceptions in the same as we do with our attentions focus. By using a focus of attention, only the information that really matters to the agent running context are perceived (cognitively processed), which can improve the decision making process. The architecture proposed herein presents a structure for cognitive agents divided into two parts: 1) the main part contains the reasoning / planning process, knowledge and affective state of the agent, and 2) a set of behaviors that are triggered by planning in order to achieve the agent s goals. Each of these behaviors has a runtime dynamically adjustable focus of attention, adjusted according to the variation of the agent s affective state. The focus of each behavior is divided into a qualitative focus, which is responsible for the quality of the perceived data, and a quantitative focus, which is responsible for the quantity of the perceived data. Thus, the behavior will be able to filter the information sent by the agent sensors, and build a list of perceived elements containing only the information necessary to the agent, according to the context of the behavior that is currently running. Based on the human attention focus, the agent is also dotted of a affective state. The agent s affective state is based on theories of human emotion, mood and personality. This model serves as a basis for the mechanism of continuous adjustment of the agent s attention focus, both the qualitative and the quantative focus. With this mechanism, the agent can adjust its focus of attention during the execution of the behavior, in order to become more efficient in the face of environmental changes. The proposed architecture can be used in a very flexibly way. The focus of attention can work in a fixed way (neither the qualitative focus nor the quantitaive focus one changes), as well as using different combinations for the qualitative and quantitative foci variation. The architecture was built on a platform for BDI agents, but its design allows it to be used in any other type of agents, since the implementation is made only in the perception level layer of the agent. In order to evaluate the contribution proposed in this work, an extensive series of experiments were conducted on an agent-based simulation over a fire-growing scenario. In the simulations, the agents using the architecture proposed in this work are compared with similar agents (with the same reasoning model), but able to process all the information sent by the environment. Intuitively, it is expected that the omniscient agent would be more efficient, since they can handle all the possible option before taking a decision. However, the experiments showed that attention-focus based agents can be as efficient as the omniscient ones, with the advantage of being able to solve the same problems in a significantly reduced time. Thus, the experiments indicate the efficiency of the proposed architecture

Identificação do teor de nitrogênio foliar em cana-de-açúcar no estágio inicial de crescimento utilizando infravermelho próximo e sistemas inteligentes

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Implementação de um nó IEEE 1451, baseado em ferramentas abertas e padronizadas, para aplicações em ambientes de instrumentação distribuída

Pós-graduação em Engenharia Elétrica - FEIS