Catalytic gates for gas sensors based on SiC technology

En este trabajo se presenta un estudio químico y estructural de las capas metálicas de Pt y TaSix utilizadas como puerta catalítica en sensores de gas de alta temperatura basados en dispositivos MOS de SiC. Para ello se han depositado capas de diferentes espesores sobre substratos de Si. Los resultados muestran que con la reducción del espesor de Pt y con un recocido se consigue aumentar la rugosidad de las capas de puerta, lo que debería aumentar la sensibilidad y la velocidad de respuesta de los dispositivos que las incorporasen. Otro efecto del recocido es la transformación química del material de la puerta que, para capas delgadas de Pt con TaSix, produce la transformación total Pt en Pt2Ta, lo que podría afectar a las características catalíticas de la puerta. Los primeros resultados eléctricos indican que, a pesar de que las capas de Pt empleadas son gruesas y compactas, los diodos MOS túnel de SiC son sensibles a los gases CO y NO2, aunque presentan una velocidad de respuesta bastante lenta.

From Regional Landslide Detection to Site-Specific Slope Deformation Monitoring and Modelling Based on Active Remote Sensors

Landslide processes can have direct and indirect consequences affecting human lives and activities. In order to improve landslide risk management procedures, this PhD thesis aims to investigate capabilities of active LiDAR and RaDAR sensors for landslides detection and characterization at regional scales, spatial risk assessment over large areas and slope instabilities monitoring and modelling at site-specific scales. At regional scales, we first demonstrated recent boat-based mobile LiDAR capabilities to model topography of the Normand coastal cliffs. By comparing annual acquisitions, we validated as well our approach to detect surface changes and thus map rock collapses, landslides and toe erosions affecting the shoreline at a county scale. Then, we applied a spaceborne InSAR approach to detect large slope instabilities in Argentina. Based on both phase and amplitude RaDAR signals, we extracted decisive information to detect, characterize and monitor two unknown extremely slow landslides, and to quantify water level variations of an involved close dam reservoir. Finally, advanced investigations on fragmental rockfall risk assessment were conducted along roads of the Val de Bagnes, by improving approaches of the Slope Angle Distribution and the FlowR software. Therefore, both rock-mass-failure susceptibilities and relative frequencies of block propagations were assessed and rockfall hazard and risk maps could be established at the valley scale. At slope-specific scales, in the Swiss Alps, we first integrated ground-based InSAR and terrestrial LiDAR acquisitions to map, monitor and model the Perraire rock slope deformation. By interpreting both methods individually and originally integrated as well, we therefore delimited the rockslide borders, computed volumes and highlighted non-uniform translational displacements along a wedge failure surface. Finally, we studied specific requirements and practical issues experimented on early warning systems of some of the most studied landslides worldwide. As a result, we highlighted valuable key recommendations to design new reliable systems; in addition, we also underlined conceptual issues that must be solved to improve current procedures. To sum up, the diversity of experimented situations brought an extensive experience that revealed the potential and limitations of both methods and highlighted as well the necessity of their complementary and integrated uses.

Microcontroller-based interface circuit for inductive sensors

This work proposes a fully-digital interface circuit for the measurement of inductive sensors using a low-cost microcontroller (µC) and without any intermediate active circuit. Apart from the µC and the sensor, the circuit just requires an external resistor and a reference inductance so that two RL circuits with a high-pass filter (HPF) topology are formed. The µC appropriately excites such RL circuits in order to measure the discharging time of the voltage across each inductance (i.e. sensing and reference) and then it uses such discharging times to estimate the sensor inductance. Experimental tests using a commercial µC show a non-linearity error (NLE) lower than 0.5%FSS (Full-Scale Span) when measuring inductances from 1 mH to 10 mH, and from 10 mH to 100 mH.

Integrating distributed generation and Smart Grids into single-family house

This study examines Smart Grids and distributed generation, which is connected to a single-family house. The distributed generation comprises small wind power plant and solar panels. The study is done from the consumer point of view and it is divided into two parts. The first part presents the theoretical part and the second part presents the research part. The theoretical part consists of the definition of distributed generation, wind power, solar energy and Smart Grids. The study examines what the Smart Grids will enable. New technology concerning Smart Grids is also examined. The research part introduces wind and sun conditions from two countries. The countries are Finland and Germany. According to the wind and sun conditions of these two countries, the annual electricity production from wind power plant and solar panels will be calculated. The costs of generating electricity from wind and solar energy are calculated from the results of annual electricity productions. The study will also deal with feed-in tariffs, which are supporting systems for renewable energy resources. It is examined in the study, if it is cost-effective for the consumers to use the produced electricity by themselves or sell it to the grid. Finally, figures for both countries are formed. The figures include the calculated cost of generating electricity from wind power plant and solar panels, retail and wholesale prices and feed-in tariffs. In Finland, it is not cost-effective to sell the produced electricity to the grid, before there are support systems. In Germany, it is cost-effective to sell the produced electricity from solar panels to the grid because of feed-in tariffs. On the other hand, in Germany it is cost-effective to produce electricity from wind to own use because the retail price is higher than the produced electricity from wind.

Software per al cronometratge de temps mitjançant sensors digitals

L’Slot, conegut per tots amb el nom d’Scalextric, s’ha implantat com a una forma d’oci habitual, la pràctica del qual no queda restringida als més petits, sinó que cada vegada crea més afició entre els grans. El fet que l’Slot s’hagi extès entre els adults n’ha revolucionat la pràctica. L’entrada al mercat de l’Slot de gent adulta, i amb poder adquisitiu molt superior als adolescents, ha provocat que les marques especialitzades vagin evolucionant els seus productes cada vegada més. Totes les marques s’han vist obligades a desenvolupar vehicles més competitius i alhora treure al mercat accessoris que augmentin la realitat del joc. Una de les necessitats que s’ha creat és la de competir entre jugadors. Aquesta competició tan pot ser en forma de carrera entre diversos participants, com de forma individual, cronometrant el temps de cada participant en un circuit. L’objectiu principal del projecte és crear un sistema capaç de realitzar cronometratges en temps real mitjançant sensors digitals ja existents en el mercat de l’Slot i poder controlar i visualitzar la informació des d’un PC. Per a poder captar els senyals dels sensors s’ha utilitzat un sistema microcontrolat, que garanteix gran velocitat d’adquisició, processament de dades i transmissió. La comunicació del Microcontrolador amb el PC s’ha realizat mitjançant el bus USB. El PC serà el controlador del sistema i donarà les ordres al Microcontrolador, podent així tenir control total sobre el funcionament del programa. També serà el PC el que tractarà els crocometratges enregistrats i els mostrarà per pantalla

Smart cities : Un enfoque práctico sobre una metrópolis y auditoría en Lima (Perú)

Análisis del origen del concepto de smart cities que deriva de la gestión y ahorro energético, comparación de ejemplos de smart cities actuales y realización de un caso práctico sobre Lima analizando exhaustivamente qué componentes tenemos según las diferentes métricas e indicadores y qué componentes faltarían para poder ser una ciudad "smart".

Technological and business challenges of smart grids

Growing recognition of the electricity grid modernization to enable new electricity generation and consumption schemes has found articulation in the vision of the Smart Grid platform. The essence of this vision is an autonomous network with two-way electricity power flows and extensive real-time information between the generation nodes, various electricity-dependent appliances and all points in-between. Three major components of the Smart Grids are distributed intelligence, communication technologies, and automated control systems. The aim of this thesis is to recognize the challenges that Smart Grids are facing, while extinguishing the main driving factors for their introduction. The scope of the thesis also covers possible place of electricity Aggregator Company in the current and future electricity markets. Basic functions of an aggregator and possible revenue sources along with demand response feasibility calculations are reviewed within this thesis.

Evaluation of gas diffusion electrodes as detectors in amperometric hydrogen sensors

This work is directed to the study and evaluation of gas diffusion electrodes as detectors in hydrogen sensors. Electrochemical experiments were carried out with rotating disk electrodes with a thin porous coating of the catalyst as a previous step to select useful parameters for the sensor. An experimental arrangement made in the laboratory that simulates the sensor was found appropriate to detect volumetric hydrogen percentages above 0.25% in mixtures H2:N2. The system shows a linear response for volumetric percentages of hydrogen between 0.25 and 2 %.

Smart homes as service platforms. Research report of ÄLYKOP sub-project “Competitive advantage from customer value”

In this report, we summarize results of our part of the ÄLYKOP-project on customer value creation in the intersection of the health care, ICT, forest and energy industries. The research directs to describe how industry transformation and convergence create new possibilities, business opportunities and even new industries.The report consists of findings which are presented former in academic publications. The publication discusses on customer value, service provision and resource basis of the novel concepts through multiple theorethical frameworks. The report is divided into three maim sections which are theoretical background, discussion on health care industry and evaluations regarding novel smart home concepts. Transaction cost economics and Resource- Based view on the firm provides the theoretical basis to analyze the prescribed phenomena. The health care industry analysis describes the most important changes in the demand conditions of health care services, and explores the features that are likely to open new business opportunities for a solution provider. The third part of the report on the smart home business provides illustrations few potential concepts that can be considered to provide solutions to economical problems which arise from aging of population. The results provide several recommendations for the smart home platform developers in public and private sectors. By the analysis, public organizations dominate service provision and private markets are emergent state at present. We argue that public-private partnerships are nececssary for creating key suppliers. Indeed, paying attion on appropriate regulation, service specifications and technology standards would foster diffusion of new services. The dynamics of the service provision networks is driven by need for new capabiltities which are required for adapting business concepts to new competitive situation. Finally, the smart home framework revealed links between conventionally distant business areas such as health care and energy distribution. The platform integrates functionalities different for purposes which however apply same resource basis.

Diffusion of Smart Meters in Central East Europe

The present study deals with innovation diffusion as the central component of innovation process and takes smart meters as a concrete example from the electric power industry. Smart meters are seen as key enablers of the industry-wide shift towards smart grids and are recognized by the European Union as means of reaching its environmental and energy goals. However, the spread of smart meters through the market, especially in Central East Europe (CEE), is not corresponding to the expectations and identified benefits. The current work synthesizes available data for the under-researched geographical region of CEE and clarifies the process of smart meter diffusion and drivers behind it. In addition to innovation theories the methods applied are rate of adoption and thematic analysis. The results prove the large gap between optimal and actual diffusion as well as the lagging position of CEE in comparison to the EU’s market leaders. The smart metering market is driven from bottom-up and the majority of CEE countries have already carried out or started the initial activities. Therefore, in coming years more intensive smart meters deployment will be seen.

Comparison and Evaluation of Eddy Current Sensors

In the work eddy current sensors are described and evaluated. Theoretical part includes physical basics of the eddy currents, overview of available commercial products and technologies. Industrial sensors operation was assessed based on several working modes. Apart from this, the model was created in Matlab Simulink with Xilinx Blockset and then translated into a Xilinx ISE Design Suite compatible project. The performance of the resulting implementation was compared to the existing implementation in the Xilinx Spartan 3 FPGA board with the custom made sensor. Additionally, an introduction to FPGAs and VHDL is presented.

Printed low-voltage organic transistors on plastics and paper

The main advantage of organic electronics over the more widespread inorganic counterparts lies not in the electrical performance, but rather in the solution processability that opens up for low-cost flexible electronics (e.g. displays, sensors and smart tags) fabricated by using printing techniques. Replacing the commonly used laboratory-scale fabrication techniques with mass-printing techniques is, however, truly challenging, especially when low-voltage operation is required. In this thesis it is, nevertheless, demonstrated that low-voltage organic transistors can be fully printed with a similar performance to that of transistors made by laboratory scale techniques. The use of an ion-modulated type of organic field effect transistor (OFET) not only enabled low-voltage operation and printability, but was also found to result in low sensitivity to the surface roughness of the substrate. This allows not only the use of low-cost plastic substrates, but even the use of paper as a substrate. However, while absorption into the porous paper surface is advantageous in a graphical printing process, by reducing the spreading and the coffee-stain effect and by improving the adhesion, it provides great challenges when applying thin electrically active layers. In spite of these difficulties we were able to demonstrate the first low-voltage OFET to be fabricated on paper. We have also shown that low-cost incandescent lamps can be used for sintering printed metal-nanoparticles, and that the process was especially suitable on paper and compatible with a roll-to-roll manufacturing process.

Modelling of potentiometric ion sensors

Potentiometric ion sensors are a very important subgroup of electrochemical sensors, very attractive for practical applications due to their small size, portability, low-energy consumption, relatively low cost and not changing the sample composition. They are investigated by the researchers from many fields of science. The continuous development of this field creates the necessity for a detailed description of sensor response and the electrochemical processes important in the practical applications of ion sensors. The aim of this thesis is to present the existing models available for the description of potentiometric ion sensors as well as their applicability and limitations. This includes the description of the diffusion potential occurring at the reference electrodes. The wide range of existing models, from most idealised phase boundary models to most general models, including migration, is discussed. This work concentrates on the advanced modelling of ion sensors, namely the Nernst-Planck-Poisson (NPP) model, which is the most general of the presented models, therefore the most widely applicable. It allows the modelling of the transport processes occurring in ion sensors and generating the potentiometric response. Details of the solution of the NPP model (including the numerical methods used) are shown. The comparisons between NPP and the more idealized models are presented. The applicability of the model to describe the formation of diffusion potential in reference electrode, the lower detection limit of both ion-exchanger and neutral carrier electrodes and the effect of the complexation in the membrane are discussed. The model was applied for the description of both types of electrodes, i.e. with the inner filling solution and solidcontact electrodes. The NPP model allows the electrochemical methods other than potentiometry to be described. Application of this model in Electrochemical Impedance Spectroscopy is discussed and a possible use in chrono-potentiometry is indicated. By combining the NPP model with evolutionary algorithms, namely Hierarchical Genetic Strategy (HGS), a novel method allowing the facilitation of the design of ion sensors was created. It is described in detail in this thesis and its possible applications in the field of ion sensors are indicated. Finally, some interesting effects occurring in the ion sensors (i.e. overshot response and influence of anionic sites) as well as the possible applications of NPP in biochemistry are described.

Characterization of capacitive sensors for measurements of the moisture in irrigated soils

The irrigation is a technique developed to supply the hydric needs of the plants. The use of the water should be optimized so that the culture just has enough for its growth, avoiding waste. The objective of this work was to characterize the behavior of capacitive sensors of humidity to monitor the moisture in the soils. In first instance, it was appraised sensors with dielectric built of synthetic pomes stone (Rd = 0,4 and Rd = 0,8) and of soil samples (Rd = 0,8 and Rd = 1,0), being the Rd parameter a geometric factor that relates the distance between the capacitor plates with radius of the plates. For the calibration, the sensors were installed in PVC recipient of cylindrical shape, filled with soil. The set (sensor and soil) was humidified by capillary effect and submitted by a natural drying very slowly. The parameter readings were taken daily, which allowed obtain the curves relating the humidity percentage, expressed in terms of dry weight, with the output voltage fort the sensor. The experiments were performed in sand soil and in dark red latossolo. The obtained results allowed to infer that the behavior of the sensor has a specific feature for each type of soil, being, therefore, necessary to develop a own calibration curve for the sensor, when used in soil with specific characteristic.

Semantic and fuzzy modelling for human behaviour recognition in smart spaces : a case study on ambient assisted living.

Human activity recognition in everyday environments is a critical, but challenging task in Ambient Intelligence applications to achieve proper Ambient Assisted Living, and key challenges still remain to be dealt with to realize robust methods. One of the major limitations of the Ambient Intelligence systems today is the lack of semantic models of those activities on the environment, so that the system can recognize the speci c activity being performed by the user(s) and act accordingly. In this context, this thesis addresses the general problem of knowledge representation in Smart Spaces. The main objective is to develop knowledge-based models, equipped with semantics to learn, infer and monitor human behaviours in Smart Spaces. Moreover, it is easy to recognize that some aspects of this problem have a high degree of uncertainty, and therefore, the developed models must be equipped with mechanisms to manage this type of information. A fuzzy ontology and a semantic hybrid system are presented to allow modelling and recognition of a set of complex real-life scenarios where vagueness and uncertainty are inherent to the human nature of the users that perform it. The handling of uncertain, incomplete and vague data (i.e., missing sensor readings and activity execution variations, since human behaviour is non-deterministic) is approached for the rst time through a fuzzy ontology validated on real-time settings within a hybrid data-driven and knowledgebased architecture. The semantics of activities, sub-activities and real-time object interaction are taken into consideration. The proposed framework consists of two main modules: the low-level sub-activity recognizer and the high-level activity recognizer. The rst module detects sub-activities (i.e., actions or basic activities) that take input data directly from a depth sensor (Kinect). The main contribution of this thesis tackles the second component of the hybrid system, which lays on top of the previous one, in a superior level of abstraction, and acquires the input data from the rst module's output, and executes ontological inference to provide users, activities and their in uence in the environment, with semantics. This component is thus knowledge-based, and a fuzzy ontology was designed to model the high-level activities. Since activity recognition requires context-awareness and the ability to discriminate among activities in di erent environments, the semantic framework allows for modelling common-sense knowledge in the form of a rule-based system that supports expressions close to natural language in the form of fuzzy linguistic labels. The framework advantages have been evaluated with a challenging and new public dataset, CAD-120, achieving an accuracy of 90.1% and 91.1% respectively for low and high-level activities. This entails an improvement over both, entirely data-driven approaches, and merely ontology-based approaches. As an added value, for the system to be su ciently simple and exible to be managed by non-expert users, and thus, facilitate the transfer of research to industry, a development framework composed by a programming toolbox, a hybrid crisp and fuzzy architecture, and graphical models to represent and con gure human behaviour in Smart Spaces, were developed in order to provide the framework with more usability in the nal application. As a result, human behaviour recognition can help assisting people with special needs such as in healthcare, independent elderly living, in remote rehabilitation monitoring, industrial process guideline control, and many other cases. This thesis shows use cases in these areas.