Towards a Cyber-physical Resilience Framework for Smart Grids

As modern power grids move towards becoming a smart grid, there is an increasing reliance on the data that is transmitted and processed by ICT systems. This reliance introduces new digital attack vectors. Many of the proposed approaches that aim to address this problem largely focus on applying well-known ICT security solutions. However, what is needed are approaches that meet the complex concerns of the smart grid as a cyber-physical system. Furthermore, to support the automatic control loops that exist in a power grid, similarly automatic security and resilience mechanisms are needed that rely on minimal operator intervention. The research proposed in this paper aims to develop a framework that ensures resilient smart grid operation in light of successful cyber-attacks.

Demand-side characterisation of the smart city for energy modelling.

This paper presents a new methodology for characterising the energy performance of buildings suitable for city-scale, top-down energy modelling. Building properties that have the greatest impact on simulated energy performance were identified via a review of sensitivity analysis studies. The methodology greatly simplifies the description of a building to decrease labour and simulation processing overheads. The methodology will be used in the EU FP7 INDICATE project which aims to create a master-planning tool that uses dynamic simulation to facilitate the design of sustainable, energy efficient smart cities.

Cybersecurity Test-Bed for IEC 61850 based Smart Substations

With the development and deployment of IEC 61850 based smart substations, cybersecurity vulnerabilities of supervisory control and data acquisition (SCADA) systems are increasingly emerging. In response to the emergence of cybersecurity vulnerabilities in smart substations, a test-bed is indispensable to enable cybersecurity experimentation. In this paper, a comprehensive and realistic cyber-physical test-bed has been built to investigate potential cybersecurity vulnerabilities and the impact of cyber-attacks on IEC 61850 based smart substations. This test-bed is close to a real production type environment, and has the ability to carry out end-to-end testing of cyber-attacks and physical consequences. A fuzz testing approach is proposed for detecting IEC 61850 based intelligent electronic devices (IEDs) and validated in the proposed test-bed.

An invasive-native mammalian species replacement process captured by camera trap survey random encounter models

Camera traps are used to estimate densities or abundances using capture-recapture and, more recently, random encounter models (REMs). We deploy REMs to describe an invasive-native species replacement process, and to demonstrate their wider application beyond abundance estimation. The Irish hare Lepus timidus hibernicus is a high priority endemic of conservation concern. It is threatened by an expanding population of non-native, European hares L. europaeus, an invasive species of global importance. Camera traps were deployed in thirteen 1 km squares, wherein the ratio of invader to native densities were corroborated by night-driven line transect distance sampling throughout the study area of 1652 km2. Spatial patterns of invasive and native densities between the invader’s core and peripheral ranges, and native allopatry, were comparable between methods. Native densities in the peripheral range were comparable to those in native allopatry using REM, or marginally depressed using Distance Sampling. Numbers of the invader were substantially higher than the native in the core range, irrespective of method, with a 5:1 invader-to-native ratio indicating species replacement. We also describe a post hoc optimization protocol for REM which will inform subsequent (re-)surveys, allowing survey effort (camera hours) to be reduced by up to 57% without compromising the width of confidence intervals associated with density estimates. This approach will form the basis of a more cost-effective means of surveillance and monitoring for both the endemic and invasive species. The European hare undoubtedly represents a significant threat to the endemic Irish hare.

Clustering-Based Ensemble Learning for Activity Recognition in Smart Homes

Application of sensor-based technology within activity monitoring systems is becoming a popular technique within the smart environment paradigm. Nevertheless, the use of such an approach generates complex constructs of data, which subsequently requires the use of intricate activity recognition techniques to automatically infer the underlying activity. This paper explores a cluster-based ensemble method as a new solution for the purposes of activity recognition within smart environments. With this approach activities are modelled as collections of clusters built on different subsets of features. A classification process is performed by assigning a new instance to its closest cluster from each collection. Two different sensor data representations have been investigated, namely numeric and binary. Following the evaluation of the proposed methodology it has been demonstrated that the cluster-based ensemble method can be successfully applied as a viable option for activity recognition. Results following exposure to data collected from a range of activities indicated that the ensemble method had the ability to perform with accuracies of 94.2% and 97.5% for numeric and binary data, respectively. These results outperformed a range of single classifiers considered as benchmarks.

A frontal view gait recognition based on 3D imaging using a time of flight camera

Studies have been carried out to recognize individuals from a frontal view using their gait patterns. In previous work, gait sequences were captured using either single or stereo RGB camera systems or the Kinect 1.0 camera system. In this research, we used a new frontal view gait recognition method using a laser based Time of Flight (ToF) camera. In addition to the new gait data set, other contributions include enhancement of the silhouette segmentation, gait cycle estimation and gait image representations. We propose four new gait image representations namely Gait Depth Energy Image (GDE), Partial GDE (PGDE), Discrete Cosine Transform GDE (DGDE) and Partial DGDE (PDGDE). The experimental results show that all the proposed gait image representations produce better accuracy than the previous methods. In addition, we have also developed Fusion GDEs (FGDEs) which achieve better overall accuracy and outperform the previous methods.

Smart design of scaffolds obtained by biofabrication for tissue engineering applications

A engenharia de tecidos é um domínio tecnológico emergente em rápido desenvolvimento que se destina a produzir substitutos viáveis para a restauração, manutenção ou melhoria da função dos tecidos ou órgãos humanos. Uma das estratégias mais predominantes em engenharia de tecidos envolve crescimento celular sobre matrizes de suporte (scaffolds), biocompatíveis e biodegradáveis. Estas matrizes devem possuir não só elevadas propriedades mecânicas e vasculares, mas também uma elevada porosidade. Devido à incompatibilidade destes dois parâmetros, é necessário desenvolver estratégias de simulação de forma a obter estruturas optimizadas. A previsão real das propriedades mecânicas, vasculares e topológicas das matrizes de suporte, produzidas por técnicas de biofabricação, é muito importante para as diversas aplicações em engenharia de tecidos. A presente dissertação apresenta o estado da arte da engenharia de tecidos, bem como as técnicas de biofabricação envolvidas na produção de matrizes de suporte. Para o design optimizado de matrizes de suporte foi adoptada uma metodologia de design baseada tanto em métodos de elementos finitos para o cálculo do comportamento mecânico, vascular e as optimizações topológicas, como em métodos analíticos para a validação das simulações estruturais utilizando dados experimentais. Considerando que as matrizes de suporte são estruturas elementares do tipo LEGO, dois tipos de famílias foram consideradas, superfícies não periódicas e as superfícies triplas periódicas que descrevem superfícies naturais. Os objectivos principais desta dissertação são: i) avaliar as técnicas existentes de engenharia de tecidos; ii) avaliar as técnicas existentes de biofabricação para a produção de matrizes de suporte; iii) avaliar o desempenho e comportamento das matrizes de suporte; iv) implementar uma metodologia de design de matrizes de suporte em variáveis tais como a porosidade, geometria e comportamento mecânico e vascular por forma a auxiliar o processo de design; e por fim, v) validar experimentalmente a metodologia adoptada.

Perception and software architecture for mobile robotics

When developing software for autonomous mobile robots, one has to inevitably tackle some kind of perception. Moreover, when dealing with agents that possess some level of reasoning for executing their actions, there is the need to model the environment and the robot internal state in a way that it represents the scenario in which the robot operates. Inserted in the ATRI group, part of the IEETA research unit at Aveiro University, this work uses two of the projects of the group as test bed, particularly in the scenario of robotic soccer with real robots. With the main objective of developing algorithms for sensor and information fusion that could be used e ectively on these teams, several state of the art approaches were studied, implemented and adapted to each of the robot types. Within the MSL RoboCup team CAMBADA, the main focus was the perception of ball and obstacles, with the creation of models capable of providing extended information so that the reasoning of the robot can be ever more e ective. To achieve it, several methodologies were analyzed, implemented, compared and improved. Concerning the ball, an analysis of ltering methodologies for stabilization of its position and estimation of its velocity was performed. Also, with the goal keeper in mind, work has been done to provide it with information of aerial balls. As for obstacles, a new de nition of the way they are perceived by the vision and the type of information provided was created, as well as a methodology for identifying which of the obstacles are team mates. Also, a tracking algorithm was developed, which ultimately assigned each of the obstacles a unique identi er. Associated with the improvement of the obstacles perception, a new algorithm of estimating reactive obstacle avoidance was created. In the context of the SPL RoboCup team Portuguese Team, besides the inevitable adaptation of many of the algorithms already developed for sensor and information fusion and considering that it was recently created, the objective was to create a sustainable software architecture that could be the base for future modular development. The software architecture created is based on a series of di erent processes and the means of communication among them. All processes were created or adapted for the new architecture and a base set of roles and behaviors was de ned during this work to achieve a base functional framework. In terms of perception, the main focus was to de ne a projection model and camera pose extraction that could provide information in metric coordinates. The second main objective was to adapt the CAMBADA localization algorithm to work on the NAO robots, considering all the limitations it presents when comparing to the MSL team, especially in terms of computational resources. A set of support tools were developed or improved in order to support the test and development in both teams. In general, the work developed during this thesis improved the performance of the teams during play and also the e ectiveness of the developers team when in development and test phases.

Micro/nanoreservoirs for controlled release of active species in smart functional coatings

This work reports one possible way to develop new functional coatings used to increase the life time of metallic structures. The functionalities selected and attributed to model coatings in the frame of this work were corrosion protection, self-sensing and prevention of fouling (antifouling). The way used to confer those functionalities to coatings was based on the encapsulation of active compounds (corrosion inhibitors, pH indicators and biocides) in micro and nanocontainers followed by their incorporation into the coating matrices. To confer active corrosion protection, one corrosion inhibitor (2-mercaptobenzothiazole, MBT) was encapsulated in two different containers, firstly in silica nanocapsules (SiNC) and in polyurea microcapsules (PU-MC). The incorporation of both containers in different models coatings shows a significant improvement in the corrosion protection of aluminum alloy 2024 (AA2024). Following the same approach, SiNC and PU-MC were also used for the encapsulation of phenolphthalein (one well known pH indicator) to introduce sensing properties in polymeric coatings. SiNC and PU-MC containing phenolphthalein acted as corrosion sensor, showing a pink coloration due to the beginning of cathodic reaction, resulting in a pH increase identified by those capsules. Their sensing performance was proved in suspension and when integrated in coatings for aluminium alloy 2024 and magnesium alloy AZ31. In a similar way, the biocide activity (antifouling) was assigned to two polymeric matrices using SiNC for encapsulation of one biocide (Dichloro-2-octyl-2H-isothiazol-3-one, DCOIT) and also SiNC-MBT was tested as biocide. The antifouling activity of those two encapsulated compounds was assessed through inhibition and consequent decrease in the bioluminescence of modified E. coli. That effect was verified in suspension and when incorporated in coatings for AISI 1008 carbon steel. The developed micro and nanocontainers presented the desired performance, allowing the introduction of new functionalities to model coatings, showing potential to be used as functional additives in the next generation of multifunctional coatings.

Estudo da contribuição dos smart polymers na eficácia e segurança do tratamento antineoplásico

O cancro é uma das mais conhecidas e temidas doenças existentes e, como tal, existe um grande interesse no desenvolvimento de métodos de tratamento das afeções tumorais. Os grandes avanços da quimioterapia têm dado ótimos resultados no tratamento do cancro. Contudo, a administração de fármacos antineoplásicos não garante uma elevada eficácia pois os tecidos tumorais apresentam propriedades estruturais que dificultam o transporte de agentes terapêuticos, como a disposição heterogénea dos vasos sanguíneos, a ausência de sistema linfático funcional, as inúmeras barreiras de transporte que o fármaco enfrenta até chegar às células alvo ou a disparidade da expressão de antigénios e recetores nas próprias células. Para além disso, os agentes quimioterapêuticos exibem elevada toxicidade não específica, afetando tanto as células tumorais como as células saudáveis, o que resulta frequentemente em severos efeitos secundários. Se a dose for reduzida para diminuir estes efeitos, a eficácia do tratamento diminuirá também; por outro lado, o aumento da dose, apesar de permitir um melhor controlo do crescimento do tumor, leva também a uma maior toxicidade nos tecidos saudáveis. Para contornar este efeito têm-se desenvolvido diferentes tipos de sistemas de libertação de fármacos com o objetivo de maximizar o direcionamento para os tumores e minimizar a toxicidade sistémica. Entre estas alternativas figuram os chamados smart polymers, que são macromoléculas que sofrem rápidas e reversíveis mudanças na sua estrutura em resposta a estímulos, os quais correspondem geralmente a pequenas alterações no meio, como pH, temperatura, incidência de radiação ou presença de determinadas substâncias químicas. Assim, associando um fármaco a um destes polímeros, em geral recorrendo a técnicas de encapsulação, é possível fazer com que a libertação do fármaco ocorra apenas nas células tumorais, seja por estas apresentarem as características necessárias para alterar a estrutura dos polímeros (acidez ou temperatura diferente das células saudáveis, por exemplo) ou por se conferir externamente à zona do tumor essas mesmas características (por exemplo, incidindo radiação na zona afetada). Os smart polymers têm outras vantagens. Os fármacos conjugados com estes polímeros têm tendência para se acumularem nos tecidos tumorais devido aos altos efeitos de permeabilidade e retenção nestas células e também demonstram menor toxicidade sistémica comparativamente com o fármaco livre. Além disso, os sistemas de libertação poliméricos podem permitir o aumento do tempo de semivida plasmático e da solubilidade dos fármacos de baixo peso molecular, assim como a sua libertação controlada. Com este trabalho pretende-se estudar mais profundamente de que forma é que a utilização dos smart polymers pode aumentar a eficácia e diminuir a toxicidade sistémica das terapias anticancerígenas no tratamento de afeções tumorais.

Big data warehouse framework for smart revenue management

Revenue Management’s most cited definitions is probably “to sell the right accommodation to the right customer, at the right time and the right price, with optimal satisfaction for customers and hoteliers”. Smart Revenue Management (SRM) is a project, which aims the development of smart automatic techniques for an efficient optimization of occupancy and rates of hotel accommodations, commonly referred to, as revenue management. One of the objectives of this project is to demonstrate that the collection of Big Data, followed by an appropriate assembly of functionalities, will make possible to generate a Data Warehouse necessary to produce high quality business intelligence and analytics. This will be achieved through the collection of data extracted from a variety of sources, including from the web. This paper proposes a three stage framework to develop the Big Data Warehouse for the SRM. Namely, the compilation of all available information, in the present case, it was focus only the extraction of information from the web by a web crawler – raw data. The storing of that raw data in a primary NoSQL database, and from that data the conception of a set of functionalities, rules, principles and semantics to select, combine and store in a secondary relational database the meaningful information for the Revenue Management (Big Data Warehouse). The last stage will be the principal focus of the paper. In this context, clues will also be giving how to compile information for Business Intelligence. All these functionalities contribute to a holistic framework that, in the future, will make it possible to anticipate customers and competitor’s behavior, fundamental elements to fulfill the Revenue Management

Evaluation of the human factor in the scheduling of smart appliances in smart grids

Recently there has been an increase of interest in implementing a new set of home appliances, known as Smart Appliances that integrate Information Technologies, the Internet of Things and the ability of communicating with other devices. While Smart Appliances are characterized as an important milestone on the path to the Smart Grid, by being able to automatically schedule their loads according to a tariff or reflecting the power that is generated using renewable sources, there is not a clear understanding on the impact that the behavior of such devices will have in the comfort levels of users, when they shift their working periods to earlier, or later than, a preset time. Given these considerations, in this work we analyse the results of an assessment survey carried out to a group of Home Appliance users regarding their habits when dealing with these machines and the subjective impact in quality caused by either finishing its programs before or after the time limit set by the user. The results of this work are expected to be used as input for the evaluation of load scheduling algorithms running in energy management systems. © 2014 Springer International Publishing.

Optimatization of hybrid renewable energy systems on isolated microgrids : a smart grid approach

Tese de doutoramento, Sistemas Sustentáveis de Energia, Universidade de Lisboa, Faculdade de Ciências, 2016