Contextual Intelligent Load Management Considering Real-Time Pricing in a Smart Grid Environment

The use of demand response programs enables the adequate use of resources of small and medium players, bringing high benefits to the smart grid, and increasing its efficiency. One of the difficulties to proceed with this paradigm is the lack of intelligence in the management of small and medium size players. In order to make demand response programs a feasible solution, it is essential that small and medium players have an efficient energy management and a fair optimization mechanism to decrease the consumption without heavy loss of comfort, making it acceptable for the users. This paper addresses the application of real-time pricing in a house that uses an intelligent optimization module involving artificial neural networks.

Intelligent decision support systems for collaboration in industrial plants

Dissertação apresentada para obtenção do Grau de Doutor em Sistemas de Informação Industriais, Engenharia Electrotécnica, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Distributed Intelligent Management of Microgrids using a Multi-Agent Simulation Platform

Multi-agent approaches have been widely used to model complex systems of distributed nature with a large amount of interactions between the involved entities. Power systems are a reference case, mainly due to the increasing use of distributed energy sources, largely based on renewable sources, which have potentiated huge changes in the power systems’ sector. Dealing with such a large scale integration of intermittent generation sources led to the emergence of several new players, as well as the development of new paradigms, such as the microgrid concept, and the evolution of demand response programs, which potentiate the active participation of consumers. This paper presents a multi-agent based simulation platform which models a microgrid environment, considering several different types of simulated players. These players interact with real physical installations, creating a realistic simulation environment with results that can be observed directly in the reality. A case study is presented considering players’ responses to a demand response event, resulting in an intelligent increase of consumption in order to face the wind generation surplus.

An intelligent clustering scheme for distributed intrusion detection in vehicular cloud computing

In recent years, vehicular cloud computing (VCC) has emerged as a new technology which is being used in wide range of applications in the area of multimedia-based healthcare applications. In VCC, vehicles act as the intelligent machines which can be used to collect and transfer the healthcare data to the local, or global sites for storage, and computation purposes, as vehicles are having comparatively limited storage and computation power for handling the multimedia files. However, due to the dynamic changes in topology, and lack of centralized monitoring points, this information can be altered, or misused. These security breaches can result in disastrous consequences such as-loss of life or financial frauds. Therefore, to address these issues, a learning automata-assisted distributive intrusion detection system is designed based on clustering. Although there exist a number of applications where the proposed scheme can be applied but, we have taken multimedia-based healthcare application for illustration of the proposed scheme. In the proposed scheme, learning automata (LA) are assumed to be stationed on the vehicles which take clustering decisions intelligently and select one of the members of the group as a cluster-head. The cluster-heads then assist in efficient storage and dissemination of information through a cloud-based infrastructure. To secure the proposed scheme from malicious activities, standard cryptographic technique is used in which the auotmaton learns from the environment and takes adaptive decisions for identification of any malicious activity in the network. A reward and penalty is given by the stochastic environment where an automaton performs its actions so that it updates its action probability vector after getting the reinforcement signal from the environment. The proposed scheme was evaluated using extensive simulations on ns-2 with SUMO. The results obtained indicate that the proposed scheme yields an improvement of 10 % in detection rate of malicious nodes when compared with the existing schemes.

Simple Kinematic Design for Evading the Forced Oscillation of a Car-Wheel Suspension System

An adaptive control damping the forced vibration of a car while passing along a bumpy road is investigated. It is based on a simple kinematic description of the desired behavior of the damped system. A modified PID controller containing an approximation of Caputo’s fractional derivative suppresses the high-frequency components related to the bumps and dips, while the low frequency part of passing hills/valleys are strictly traced. Neither a complete dynamic model of the car nor ’a priori’ information on the surface of the road is needed. The adaptive control realizes this kinematic design in spite of the existence of dynamically coupled, excitable internal degrees of freedom. The method is investigated via Scicos-based simulation in the case of a paradigm. It was found that both adaptivity and fractional order derivatives are essential parts of the control that can keep the vibration of the load at bay without directly controlling its motion.

A Methodology for Creating an Adapted Command Language for Driving an Intelligent Wheelchair

Intelligent wheelchairs (IW) are technologies that can increase the autonomy and independence of elderly people and patients suffering from some kind of disability. Nowadays the intelligent wheelchairs and the human-machine studies are very active research areas. This paper presents a methodology and a Data Analysis System (DAS) that provides an adapted command language to an user of the IW. This command language is a set of input sequences that can be created using inputs from an input device or a combination of the inputs available in a multimodal interface. The results show that there are statistical evidences to affirm that the mean of the evaluation of the DAS generated command language is higher than the mean of the evaluation of the command language recommended by the health specialist (p value = 0.002) with a sample of 11 cerebral palsy users. This work demonstrates that it is possible to adapt an intelligent wheelchair interface to the user even when the users present heterogeneous and severe physical constraints.

Six thinking hats: A novel metalearner for intelligent decision support in electricity markets

The energy sector has suffered a significant restructuring that has increased the complexity in electricity market players' interactions. The complexity that these changes brought requires the creation of decision support tools to facilitate the study and understanding of these markets. The Multiagent Simulator of Competitive Electricity Markets (MASCEM) arose in this context, providing a simulation framework for deregulated electricity markets. The Adaptive Learning strategic Bidding System (ALBidS) is a multiagent system created to provide decision support to market negotiating players. Fully integrated with MASCEM, ALBidS considers several different strategic methodologies based on highly distinct approaches. Six Thinking Hats (STH) is a powerful technique used to look at decisions from different perspectives, forcing the thinker to move outside its usual way of thinking. This paper aims to complement the ALBidS strategies by combining them and taking advantage of their different perspectives through the use of the STH group decision technique. The combination of ALBidS' strategies is performed through the application of a genetic algorithm, resulting in an evolutionary learning approach.

Controlo e monitorização de um sistema de Auto-Pull

Esta dissertação descreve o estudo do controlo e da monitorização de um sistema de autopull, bem como o estudo da implementação de um destes sistemasnuma área de negócio. Inicialmente, de modo a percecionar as melhores opções a tomar para a realização deste projeto foram estudadas duas redes de comunicação locais, redes Ethernet e redes CAN, tendo-se optado pelas redes Ethernet, sendo as razões que determinaram esta escolha explanadas no desenvolvimento do relatório. Após ter sido selecionada a rede que foi utilizada, foram estudados os requisitos do sistema e procuradas no mercado soluções que os satisfaçam. Para a comunicação em tempo real foram utilizadas Web Sockets e para a utilização destas,foi necessário um servidor de Web Sockets, tendo a escolha recaídosobre onodejs. Posteriormente, foi elaborada uma interface gráfica que permitiu a criação de um sistema inteligente que auxilia os clientes do espaço a efetuarem pedidos bem como a chamarem os funcionários, não necessitando de passar os longos tempos de espera que normalmenteestão associados a estes espaços. Posto isto, foi realizado um website que deverá apresentar o espaço, os próximos eventos a realizar e outras informações importantes. Este sistema torna-se uma mais-valia para a divulgação da tecnologia implementada e para a divulgação dos espaços que eventualmente venham a adotar um sistema análogo. De seguida foi efetuado um plano de negócios, simulando um espaço físico que eventualmente implementasse esta tecnologia. Para tal, foi estudada a envolvente externa e interna em que este negócio estaria inserido, as políticas de marketing que deveriam ser seguidas e ainda um plano financeiro que descrevesse o investimento, as vendas esperadas e todos os restantes componentes económicos do projeto. Por último foram tecidas as principais conclusões inerentes ao projeto desenvolvido e analisadas as possibilidades de melhorias futuras.

Controller implementation using analog reconfigurable hardware (FPAA)

This Thesis has the main target to make a research about FPAA/dpASPs devices and technologies applied to control systems. These devices provide easy way to emulate analog circuits that can be reconfigurable by programming tools from manufactures and in case of dpASPs are able to be dynamically reconfigurable on the fly. It is described different kinds of technologies commercially available and also academic projects from researcher groups. These technologies are very recent and are in ramp up development to achieve a level of flexibility and integration to penetrate more easily the market. As occurs with CPLD/FPGAs, the FPAA/dpASPs technologies have the target to increase the productivity, reducing the development time and make easier future hardware reconfigurations reducing the costs. FPAA/dpAsps still have some limitations comparing with the classic analog circuits due to lower working frequencies and emulation of complex circuits that require more components inside the integrated circuit. However, they have great advantages in sensor signal condition, filter circuits and control systems. This thesis focuses practical implementations of these technologies to control system PID controllers. The result of the experiments confirms the efficacy of FPAA/dpASPs on signal condition and control systems.

Human activity recognition for an intelligent knee orthosis

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

A layer 2 multipath fabric using a centralized controller

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

A proactive intelligent decision support system for predicting the popularity of online news

"Lecture notes in computer science series, ISSN 0302-9743, vol. 9273"

Intelligent decision support to predict patient barotrauma risk in intensive care units

The occurrence of Barotrauma is identified as a major concern for health professionals, since it can be fatal for patients. In order to support the decision process and to predict the risk of occurring barotrauma Data Mining models were induced. Based on this principle, the present study addresses the Data Mining process aiming to provide hourly probability of a patient has Barotrauma. The process of discovering implicit knowledge in data collected from Intensive Care Units patientswas achieved through the standard process Cross Industry Standard Process for Data Mining. With the goal of making predictions according to the classification approach they several DM techniques were selected: Decision Trees, Naive Bayes and Support Vector Machine. The study was focused on identifying the validity and viability to predict a composite variable. To predict the Barotrauma two classes were created: “risk” and “no risk”. Such target come from combining two variables: Plateau Pressure and PCO2. The best models presented a sensitivity between 96.19% and 100%. In terms of accuracy the values varied between 87.5% and 100%. This study and the achieved results demonstrated the feasibility of predicting the risk of a patient having Barotrauma by presenting the probability associated.

Development of an intelligent bio-based packaging system

[Extrat] Currently there is a growing interest in the development of eco-efficient bio-based packaging, being active, smart and intelligent packaging the most highlighted among various innovations. Intelligent packaging has the ability to detect and mark, in real time, changes that might occur within the package/in the food product. Their main purpose is to help the consumer decide whether to buy a certain food product, ensuring that when it is bought it has not suffered significant changes influencing its quality and safety. (...)

Development of an intelligent earthwork optimization system

Tese de Doutoramento em Engenharia Civil.