Technological Innovation for the Internet of Things

The fast development of networked smart devices equipped with sensors and radio-frequency identification, connected to the Internet, is enabling the emergence of many new applications and the redesign of traditional systems towards more effective operation. Raising awareness among engineering PhD students for the potential of this new wave in their research work is a crucial element in their education. With this aim, the doctoral conference DoCEIS’13 focused on technological innovation for the Internet of Things, challenging the contributors to analyze in which ways their technical and scientific work could contribute to or benefit from this paradigm. The results of this initiative, which was reasonably successful, are briefly analyzed.

In face of the current economic turbulence, companies face new challenges. In order to respond to new business opportunities, it is crucial that companies attain strategic alliances so that they can obtain or maintain market competiveness. The formation of alliances and partnerships for collaborative problem solving is of extreme importance, being therefore essential to understand their structures and requirements. To overcome a number of difficulties that may appear in the formation of such alliances, it is necessary to properly model the elements that constitute the alliance agreements through a suitable negotiation support environment that besides the basic functionalities of data storage and alerts can also conduct the entire negotiation process making it traceable. In this context, this paper presents the main requirements of an electronic negotiation support environment in a collaborative network, identifies the main risk sources and drivers in collaborations, and analyses how a negotiation support system can help in reducing the potential risk in collaboration.

This paper proposes the concept of Inter-Enterprise Architecture (IEA), which seeks the application of tools and methodologies developed in the Enterprise Architecture (EA) field for the individual firm, adapting to an environment of collaboration between several companies that make networks or supply chains, in order to facilitate the integration and interoperability of their collaborative processes in line with its IS/IT (Information Systems/ Information Technology) to harmonize the joint processes, reduce risk and duplication, increase service and customer responsiveness, reduce technology costs and align the joint business to IS/IT.

The GloNet network is an agile virtual enterprise environment for networks of SMEs involved in highly customized and service-enhanced products through end-to-end collaboration with customers and local suppliers (co-creation) in the solar park construction sector. A challenge that arises in this network is the effective management of the interactions among participating organizations and their customers. Some participants’ problems, that are not solvable with the working hard procedures of the project execution, might arise leading to some potential tension. Most of the times this tension is a result of soft “emotional” issues experienced in the collaboration “environment”. Considering these challenges and having in mind enhancing the quality of the interactions between the involved participating organizations, this paper describes a scenario for supervising collective emotions in the GloNet network context.

The problem of service composition is of key importance in the Internet of Things paradigm. A composite Web Service can clearly determine how real life objects described as Web Services could interact with each other. This article proposes a non-functional parameters aggregation algorithm, used in composite service plan optimisation stage, taking into account the uncertainty of the nonfunctional parameters. Also, an optimisation algorithm, using the proposed aggregation method, is presented to show the complete solution for the problem. In this proposition, the algorithm focuses on composite service plan optimisation with uncertain parameters with the given uncertainty description on example of uncertainty parameter. However, the proposed algorithm can be generalized, so it can be used also with other uncertain parameters

In this work the topic of service composition scenarios is introduced and discussed with the use of leading example of service composition in the transport domain. The example is used to visualize the connection to the Internet of Things paradigm. The service composition itself is defined with a holistic approach, describing all steps of the proposed composition process like: requirements definition, requirements decomposition or aggregation using domain ontology, composite service structure construction, service discovery, structure and service plan optimization. Lastly, implementation of service composition with service composition scenarios is discussed.

Recent advances in the development of information systems have led to increased complexity and cost in terms of the required maintenance and management. On the other hand, systems built in accordance with modern architectural paradigms, such as Service Oriented Architecture (SOA), posses features enabling extensive adaptation, not present in traditional systems. Automatic adaptation mechanisms can be used to facilitate system management. The goal of this work is to show that automatic adaptation can be effectively implemented in SOA systems using machine learning algorithms. The presented concept relies on a combination of clustering and reinforcement learning algorithms. The paper discusses assumptions which are necessary to apply machine learning algorithms to automatic adaptation of SOA systems, and presents a machine learning-based management framework prototype. Possible benefits and disadvantages of the presented approach are discussed and the approach itself is validated with a representative case study.

The Internet has become the main source of information for business and research activities. Despite the value of libraries supported by computational cataloging, there are far more opportunities to retrieve information on the Internet than in paper books. However, when we seek the Internet we get essentially chunks of text with titles and descriptors resulting from search engine’s activity. Albeit some information may contain sensorial or emotional contents, the search results come essentially from algorithmic execution over keywords by relevance. Our brain retrieves information about things in real world by capturing sensorial information and storing it with emotional experience. We can question why things in Internet are not represented in a similar way to human brain. The present research aims to support a new type of search by sensations and emotions in a path to model Things in Internet towards a human-like representation of objects and events, based on lessons learned from the human brain.

The need to secure software application in today’s hostile computer environment cannot be overlooked. The increase in attacks aimed at software directly in the last decade and the demand for more secure software applications has drawn the attention of the software industry into looking for better ways in which software can be developed more securely. To achieve this, it has been suggested that security needs to be integrated into every phase of software development lifecycle (SDLC). In line with this view, security tools are now used during SDLC to integrate security into software applications. Here, we propose a neural network based security tool for analyzing software design for security flaws. Our findings show that the trained neural network was able to match possible attack patterns to design scenarios presented to it. With the information on the attack pattern identified, developers can make informed decision in mitigating risks in their designs.

Due to the worldwide diversity of enterprises, a high number of ontologies representing the same segment of reality which are not semantically coincident have appeared. To solve this problem, a possible solution is to use a reference ontology to be the intermediary in the communications between the community enterprises and to outside. Since semantic mappings between enterprise’s ontologies are established, this solution allows each of the enterprises to keep internally its own ontology and semantics unchanged. However information systems are not static, thus established mappings become obsolete with time. This paper’s presents a PhD research with the objective to identify a suitable approach that combines semantic mappings with user’s feedback, providing an automatic learning to ontologies & enabling auto-adaptability and, consequently, dynamism to the information systems.

Presently, the amount of documents in corporations can make searching and browsing for a specific topic or information a very hard task. Therefore, it is important to develop tools to ease the retrieval of specific information and to support the exploration by users on corporate intranets (composed of several hundreds of gigabytes of documents). Although not explicitly identified, many of these documents are related among themselves (directly or implicitly). In this paper we discuss a navigation support system to explore graphs applied to document correlations, using a tourism case study.

The proposed spam filtering architecture for MTA servers is a component based architecture that allows distributed processing and centralized knowledge. This architecture allows heterogeneous systems to coexist and benefit from a centralized knowledge source and filtering rules. MTA servers in the infrastructure contribute to a common knowledge, allowing for a more rational resource usage. The architecture is fully scalable, ranging from all-in-one system with minimal components instances, to multiple components instances distributed across multiple systems. Filtering rules can be implemented as independent modules that can be added, removed or modified without impact on MTA servers operation. A proof-of-concept solution was developed. Most of spam is filtered due to a grey-listing effect from the architecture itself. Using simple filters as Domain Name System black and white lists, and Sender Policy Framework validation, it is possible to guarantee a spam filtering effective, efficient and virtually without false positives.

Even given today’s rich hardware platforms, computation-intensive algorithms and applications, such as large-scale simulations, are still challenging to run with acceptable response times. One way to increase the performance of these algorithms and applications is by using the computing power of Graphics Processing Units (GPU). However, effectively mapping distributed software models to GPU is a non-trivial endeavor. In this paper, we investigate ways of improving execution performance of multi-agent systems (MAS) models by means of relevant task allocation mechanisms, which are suitable for GPU execution. Several task allocation architecture variants for MAS using GPU are identified and their properties analyzed. In particular, we study three cases: Agents and their runtime environment can be (i) completely on the host (CPU); (ii) partly on host and device (GPU); (iii) completely on the device. For each of these architecture variants, we propose task allocation models that take GPU restrictions into account.

In the Internet of Things a lot of business opportunities may be identified. The devices in IoT may create ad-hoc temporary networks to provide services or share some resources. Such services are characterized by a great economical potential, especially while provided at mass-scale and for incidental users. However, the development of paid services or resources in IoT is hampered by relatively big transaction costs of payment operations. To deal with this problem, we propose a novel architecture of coupon based, semi off line, anonymous micropayment system to enable transactions in the scope of Internet of Things. User anonymity and security is assured by the usage of standard cryptographic techniques together with novel architectural design of the payment processes. Utilization of a hash function allows generating and verifying electronic coins in computationally efficient way, so as to be executed even in hardware- and software-restricted environment such as Internet of Things.

In this paper, the main activity was to investigate how different substrates, temperature of sintering and percentage of silver ink containing silver nanoparticles influence on Young’s modulus and hardness of printed silver thin samples. Samples were prepared by low cost ink-jet printing technique using Dimatix Material Printer on polyimide flexible substrate and slide glass. Characterization of these samples was carried out by Nano Indenter using a three sided pyramidal (Berkovich) diamond tip. Measurement results show that the thickness of ink-jet printed silver layer varies for different percent of nanoparticles in silver ink. All measurements were done at same depth of indentation to avoid possibility of perforation of printed layer. The higher temperature of sintering and the higher percent of silver nanoparticles give the bigger Young’s modulus and hardness of printed silver sample. This research provides very useful information about mechanical characterization of the silver layers on flexible substrates for printed-electronics.

Competency modeling framework serves as a; (a) very important basis for the explanation of a generic competency modeling approach, (b) base element in the consolidation of existing knowledge in this area, (c) tool for model developers on selecting appropriate competency models, and (d) basis for competency modeling. This research uses literature review approach to propose a modeling framework for organizational competency. The proposed modeling framework has been developed based on the most relevant well known competency models. The research suggests that organizational competency can be categorized into three groups; individual competency, enterprise competency and collaboration-oriented competency. For modeling each of these groups, it is essential that the modeling process have to be aligned with model developer purpose (Modeling perspective), thus the model developing process will be based on the same segmentation model. Furthermore, competencies have to be model at different levels of abstraction (modeling intent).

Food product traceability from harvesting, through food processing to the final food product and through the retailer to the end consumer is a significant process that has to ensure food quality and safety. The traceability enables the end consumer to get information from all previous stages of the food product, leading back to the food origin. In this way, the consumer can get more information on the specific product, and thus make a decision on buying the product that suits his needs best. In each stage of the food product transformation, important data are generated for the subsequent chain participants. Every participant should have access to certain data of interest to them. This can be achieved by using automated identification technologies, like RFID (Radio Frequency IDentification) and two-dimensional barcode, which allow faster data acquisition, recording and reading processes than the traditional means, and provide up-to-date information in each product stage. Furthermore, these technologies allow the possibility to record large amounts of data for each specific product, and interconnect all the data in a database. This paper discusses the process of providing traceability of food products, recording, transmitting and reading of significant data in specific stages of food product chain, with the application of automated identification technologies, including the possibility of obtaining additional data from a database, according to appropriate access level of each participant in the chain. Advantages and disadvantages of automated identification technologies are discussed, with the proposition for using specific technologies in certain food product stages.

The increase of life expectancy in the European Union, and the high risk of cardiovascular diseases associated with age, are some of the main factors to contribute to the rise of healthcare costs. An intelligent stent (e-stent), capable of obtaining and transmitting real-time measurements of physiological parameters for its clinical consultation, can be a useful tool for long-term monitoring, diagnostic, and early warning system for arterial blockage without patient hospitalization. In this paper, a behavioural model of capacitive Micro-Electro-Mechanical (MEMS) pressure sensor is proposed and simulated under several restenosis conditions. Special attention has been given to the need of an accurate fault model, obtained from realistic finite-element simulations,to ensure long-term reliability; particularly for those faults whose behavior cannot be easily described by an analytical model.

Within the Internet of Things (IoT) paradigm, an everyday object can be transformed into a smart object, able to sense, interpret and react to the environment. IoT is bringing new ways of communicating between people and

things

(objects) to reach common goals, bringing a high impact on everyday-life. The aim of this paper is to present how people with psoriasis and their doctors can benefit from the IoT advantages. There is presented a proposed system for surveillance and treatment plan for patients suffering from psoriasis using assisted IoT and Computer Vision technologies.

Remote monitoring is an essential task to help maintaining Earth ecosystems. A notorious example is the monitoring of riverine environments. The solution purposed in this paper is to use an electric boat (ASV - Autonomous Surface Vehicle) operating in symbiosis with a quadrotor (UAV – Unmanned Air Vehicle). We present the architecture and solutions adopted and at the same time compare it with other examples of collaborative robotics systems, in what we expected could be used as a survey for other persons doing collaborative robotics systems. The architecture here purposed will exploit the symbiotic partnership between both robots by covering the perception, navigation, coordination, and integration aspects.

Virtual Reality (VR) is one of the newest technological domains with revolutionary applicability for the tomorrow’s Future Internet, including visions of the Internet of Things. The sensation of total immersion in Virtual Environment (VE) is still unresolved. Therefore, our work proposes a new omnidirectional locomotion interface for navigation in VEs. The novel interface was built from an ordinary unidirectional treadmill, a new mechanical device, a motion capturing system to track the human walking and a control method using artificial intelligence techniques. A neural network is used to predict the motion of the new interface based on user’s body motion and information about VE. The feasibility of the proposed system is verified through experiments and the preliminary results suggest that the new interface performs very well in a simplest VE based on our control method.

This research presents a new vision system that explores a spherical geometry and will be provide innovative solutions for tracking, surveillance, navigation and mapping with micro Unmanned Aerial Vehicle (

μ

UAV) in unknown indoor environments. The system will be used with

μ

UAV in indoor environment and it is composed by twenty six cameras that are arranged in order to sample different parts of the visual sphere around the

μ

UAV. This configuration allows that some of the cameras will have overlapped field of view. This system has been designed for the purpose of recovering ego-motion and structure from multiple video images, having a distributed omnidirectional field of view. We use the spherical geometry to extend the field of view, from one single direction to a single point of perspective, but with multiple views. This manuscript will prove that spherical geometric configuration has advantages when compared to stereo cameras for the estimation of the system’s own motion and consequently the estimation of shape models from each camera. The preliminary field tests presented the theoretical potential of this system and the experimental results with the images acquired by 3 cameras.

A new approach for the realization of self-adaptive and highly available production systems based on a context aware approach, allowing self-adaptation of flexible manufacturing processes in production systems and effective knowledge sharing to support maintenance, is presented. The usage of dynamically changing context as basis for adaptation of flexible manufacturing lines/processes and effective knowledge sharing is proposed. The presented solution includes services for context extraction, adaptation and self-learning allowing high adaptation of production systems depending on the identified context. A generic architecture following Service Oriented Principles is presented allowing for integration of the proposed solution into various production systems. A successful initial application of the developed solution in real world manufacturing environment is presented.

High-level Petri net classes are suited to specify concurrent processes with emphasis both in control and data processing, making them appropriate to specify distributed embedded systems (DES). Embedded systems components are usually synchronous, which means that DES can be seen as Globally-Asynchronous Locally-Synchronous (GALS) systems. This paper proposes to include in high-level Petri nets a set of concepts already introduced for low-level Petri nets allowing the specification of GALS systems, namely time domains, test arcs and priorities. Additionally, this paper proposes external messages and three types of (high-level) asynchronous communication channels, to specify the interaction between distributed components based on message exchange. With these extensions, GALS-DES can be specified using high-level Petri nets. The resulting models include the specification of each component with well-defined boundaries and interface, and also the explicit specification of the asynchronous interaction between components. These models will be used not only to specify the system behavior, but also to be the input for model-checking tools (supporting its verification) and automatic code generation tools (supporting its implementation in software and hardware platforms), giving a contribution to the model-based development approach and hardware-software co-design of DES based on high-level Petri nets.

This paper presents a proposal for structuring events for system models expressed using IOPT nets (Input-Output Place-Transition Petri nets). Currently, a non-autonomous event within an IOPT model is defined based on change of input signals with respect to a specific threshold, when two consecutive execution steps are considered. New types of events are proposed allowing the definition of an event activated not only by crossing a fixed threshold, but also considering a change in associated signal value on a specific amount (belonging to an interval of values). The concept is further extended allowing the definition of an event based on signal values presented on previous execution steps. The proposal results on a classification of several types of events, namely threshold events, momentum events, impetus events, as well as delayed events and logical events. Usage of these types of events allows improvements in terms of expressiveness and compactness of the resulted model.

This paper presents a new architecture to semi-automatically generate Web user interfaces for Embedded Systems designed using IOPT Petri Net models. The user interfaces can be used to remotely control, monitor and debug embedded systems using a standard Web Browser. The proposed architecture takes advantage of the distributed nature of the Internet to store all static user interface data and software on third-party Web services (the Cloud), and execute the user-interface code on the user’s Web Browser. A simplified protocol is proposed to enable remote control, status-monitoring, debugging and step-by-step execution, minimizing resource consumption on the physical embedded devices, including processing load, memory and communication bandwidth. As the user interface data and code are kept on third-party Web services, these resources can be shared among multiple embedded device units, and the hardware requirements to implement the devices can be simplified, leading to reduced cost solutions. To prevent down-time due to network problems or server failures, a fault-tolerant topology is suggested. The distributed architecture is transparent to end-users, observing just a Web interface for an embedded device on the other side of an Internet URL.

The paper deals with the application of the hypergraph theory in selection of State Machine Components (SM-Components) of Petri nets [1,2].As it is known, Petri nets are widely used for modeling of concurrency processes. However, in order to implement the concurrent automaton, an initial Petri net ought to be decomposed into sequential automata (SM-Components), which can be easily designed as an Finite-State-Machine (FSM) or Microprogrammed Controller [3]. The last step of the decomposition process of the Petri nets is selection of SM-Components. This stage is especially important because it determines the final number of sequential automata. In the article we propose a new idea of SM-Components selection. The aim of the method is reduction of the computational complexity from exponential to polynomial. Such a reduction can be done if the selection hypergraph belongs to the exact transversal hypergraphs (xt-hypergraphs) class. Since the recognition and generation of the first transversal in the xt-hypergraphs are both polynomial, the complete selection process can be performed in polynomial time. The proposed ideas are an extension of the concept presented in [1].The proposed method has been verified experimentally. The conducted investigations have shown that for more than 85% of examined Petri nets the selection process can be done via xt-hypergraphs.

Recent studies show the designs of automated systems are becoming increasingly complex to meet the global competitive market. Additionally, organizations have focused on policies to achieve people’s safety and health, environmental management system, and controlling of risks, based on standards. In this context, any industrial system in the event of a fault that is not diagnosed and treated correctly could be considered to pose a serious risk to people’s health, to the environment and to the industrial equipment. According to experts, the concept of Safety Instrumented Systems (SIS) is a practical solution to these types of issues. They strongly recommend layers for risk reduction based on control systems organized hierarchically in order to manage risks, preventing or mitigating faults, or to bringing the process to a safe state. Additionally, the concept of Risk and Hazard Control can be applied to accomplish the required functionalities. It is based on problem solving components and considers a cooperative way to find a control solution. In this context, the software architecture can be based on a service-oriented architecture (SOA) approach. This paper initially proposes a new architecture for design of safety control systems for critical systems, based on Safety Supervisory Control Architecture, in accordance with standards IEC 61508 and IEC 61511. Furthermore, a method is also proposed for design the control layer of risk prevention within Safety Supervisory Control Architecture.

Differences in EEG sleep spindles constitute a promising indicator of sleep disorders. In this paper Sleep Spindles are extracted from real EEG data using a triple (Short Time Fourier Transform-STFT; Wavelet Transform-WT; Wave Morphology for Spindle Detection-WMSD) algorithm. After the detection, an Autoregressive–moving-average (ARMA) model is applied to each Spindle and finally the ARMA’s coefficients’ mean is computed in order to find a model for each patient. Regarding only the position of real poles and zeros, it is possible to distinguish normal from Parasomnia REM subjects.

Nowadays in industry there many processes where human intervention is replaced by electrical machines, especially induction machines due to his robustness and performance. Although, induction machines are a high reliable device, they are also susceptible to faults. Therefore, the study of induction machine state is essential to reduce human and financial costs. It is presented in this paper an on-line system for detection and diagnosis of electrical faults in induction machines based on computer-aided monitoring of the supply currents. The main objective is to detect and identify the presence of broken rotor bars and stator short-circuits in the induction motor. The presence of faults in the machine causes different disturbances in the supply currents. Through a stationary reference frame, such as

αβ

-vector transform it is possible to extract and manipulate the results obtained from the supply currents using Principal Component Analysis (PCA).

This paper presents a single-phase inverter with multilevel topology adopted to interface photovoltaic systems with the electrical power grid, and at the same time, to eliminate harmonics currents and to compensate reactive power, operating as shunt active power filter. Multilevel inverters have been attracting increasing attention in the past few years as power converters of choice in high voltage and high power applications. Various topologies to implement these inverters have been introduced and studied recently. The theory of instantaneous reactive power applied to compensation of single-phase circuits is also presented in this paper. This theory is a particular case of the well-known p-q theory, which was originally developed for three-phase circuits. Simulation results demonstrate this control algorithm applied to multilevel single-phase topologies.

An UPQC (Unified Power Quality Conditioner) is an equipment composed by two active conditioners operating in a combined way. One of the active conditioners is connected in series with the electrical power system, allowing the compensation of problems in the system voltages. The other active conditioner is connected in parallel with the electrical system, and allows the compensation of current harmonics, current unbalances and power factor. In three-phase four-wire systems the parallel connected active conditioner also compensates the zero sequence current components, eliminating the neutral wire current. The UPQC operates in an automatic way, adjusting itself dynamically to the variations of the load and of the electrical system, keeping high levels of power quality in the voltages delivered to the load. At the same time, it only consumes from the electrical system the active power necessary to the load operation, in a balanced way through the three phases, and with sinusoidal currents. The compensation capabilities of the UPQC can be very useful to ensure high levels of power quality in the future Smart Grids, which are not characterized as a single technology or device, but rather as a vision of a distributed electrical system, supported by reference technologies, as Power Electronics Devices, Renewable Energy Resources, Energy Storage Systems (ESS), Advanced Metering Infrastructures (AMI), and Information and Communication Technologies (ICT).

This paper presents a Smart Storage System able to manage the energy and the smart home devices of a house for optimizing the local consumption of energy, even if there is not renewable generation. The proposed system is composed by two main systems. On the one hand, the Local Energy Management units that will be located in the houses, which are able to maintain the power consumption under a maximum reference value and to switch on/off the devices in the house by using domotic protocols. On the other hand, the Central Energy Management and Intelligent System, that receives operation data from each local unit, analyzes them using behavioral and optimization algorithms and determines the best way in which each local unit has to operate, communicating the operation references back to them.

This paper reviews the most important energy storage systems for applications in residential environments. Normally, these systems are associated with renewable energy in order to achieve specific characteristics, although new possibilities and challenges are implemented over them in any residential places. Nowadays, the development of such kind of energy systems represents a technical challenge in the market. In residential and small building applications, energy storage solutions supply the demanded power by consumers of residential areas or small stand-alone buildings placed on isolated zones. In context of smart grids, energy storage management systems are not only concerned about energy storage, also inefficiency optimization and power consume. This work presents INTELEM, a new smart storage architecture which integrates the energy storage and the intelligent energy management in communities and in residential applications.

This paper is devoted to the design and construction of a photovoltaic array emulator for high power applications in order to test all kind of photovoltaic inverters. To develop such device, a rapid prototyping tool based on xPC Target of Matlab/Simulink has been used, providing a real-time testing environment. PV array emulator can be used to evaluate the performance of photovoltaic inverters as any test conditions can be programmed. The proposed emulator operates as a distributed control system taking advantage of the TCP/IP protocol features.

This article is focused on a photovoltaic system based on the three-level neutral-point-clamped quasi-z-source inverter. The maximum power point tracking (MPPT) algorithm based on dP/dV feedback was used in the photovoltaic system to adjust the duration of the shoot-through states of power switches and achieve a maximum power. Proper system operation in the case of irradiance step is demonstrated by simulation in Matlab/Simulink software.

An increased number of distributed small generators connected to the power grid allows higher total efficiency and higher stability of electrical power supply by exporting energy to the grid to be achieved during peak demand hours. On the other hand, it poses new challenges in structuring and developing the control approaches for these distributed energy resources. This paper proposes an improved method of real-time power balancing targeted to reaching long-term energy management objectives. The novel long-term energy management technique is proposed, that is based on load categorization and regulation of energy consumption by regulating electricity price function estimated with the proposed mathematical model. The method was evaluated by a LabVIEW model by simulating various types of loads. The price function for the defined energy generation pattern from renewable energy sources was obtained.

The recent and massive investments in Electric Vehicles (EVs) reveal a change of paradigm in the transports sector and the proliferation of EVs will contribute to an effective reduction in the emissions of greenhouse gases. Nevertheless, for the electrical power grids EVs will be extra loads, which will require the demand energy to charge their batteries. With the advent of the Smart Grids, besides the usual battery charging mode (Grid-to-Vehicle – G2V), where the batteries receives energy from the power grid, arises a new concept for the users of EVs and for the power grid market, denominated as Vehicle-to-Grid (V2G).In the V2G operation mode, EVs return to the power grid part of the energy stored in their batteries. The V2G concept requires the use of battery chargers for the EVs with bidirectional power flow capability and bidirectional communication with the Smart Grids through Information and Communication Technology (ICT) applications. It is important to highlight that the proliferation of EVs and the impact of their battery chargers on the power grid quality is a matter of concern, since conventional chargers present current harmonics and power factor problems. In this paper it is presented the preliminary studies resulting from a PhD work about a bidirectional battery charger for EVs, which was designed to operate in collaboration with the power grid as G2V and V2G through an ICT application. In this way, it is expectable to contribute to the technological innovation of the electric mobility in Smart Grids. To assess the behavior of the proposed battery charger under different scenarios of operation, a prototype has been developed, and some simulation and experimental results of the battery charger are presented.

A bi-objective optimization approach is presented for solving a generation company short-term thermal schedule problem with a few units, considering the goodness of being schedule, but with emission concern. The startup and shutdown for each unit throughout the time horizon is derived from Pareto-optimal solutions, using a method merging dynamic programming and nonlinear programming to provide schedule of the units. A case study is presented to prove the effectiveness of the approach.

This paper proposes a load frequency control scheme for an autonomous hybrid generation system consisting of wind turbine generator (WTG), diesel engine generator (DEG), fuel cell (FC), aquaelectrolyzer (AE) and battery energy storage system (BESS). In wind power generation systems, operating conditions are changing continually due to wind speed and load changes, having an effect on system frequency. Therefore, a robust controller is required for load frequency control. The control scheme is based on Linear Matrix Inequality (LMI)-Linear Quadratic Regulator (LQR). The control optimization problem is obtained in terms of a system of LMI constraints and matrix equations that are simultaneously solved. The proposed load frequency control scheme with the advanced LMI-based-LQR (ALQR) design is applied for the autonomous hybrid generation system. The effectiveness and robustness of the proposed controller is demonstrated for different load and wind power perturbations. The results suggest superior performance of the proposed ALQR controller against an optimal output state feedback controller. The integrated control could be realized though the web by applying Internet of Things technologies within the future smart grid.

The Vertical Axis Wind Turbines Darrieus is facing a rapid installations growth due to the interest for a decentralizing generation. The Darrieus aerodynamic behavior analysis is a hard computational task. This paper starts by offering an insight into the Darrieus wind turbines performance prediction and proposes an algorithm based on the Multiple Streamtube modeling as a prediction approach in order to have an admissible handing in an Internet of things environment.

Electric vehicles (EV) offer a great potential to address the integration of renewable energy sources (RES) in the power grid, and thus reduce the dependence on oil as well as the greenhouse gases (GHG) emissions. The high share of wind energy in the Portuguese energy mix expected for 2020 can led to eventual curtailment, especially during the winter when high levels of hydro generation occur. In this paper a methodology based on a unit commitment and economic dispatch is implemented, and a hydro-thermal dispatch is performed in order to evaluate the impact of the EVs integration into the grid. Results show that the considered 10 % penetration of EVs in the Portuguese fleet would increase load in 3 % and would not integrate a significant amount of wind energy because curtailment is already reduced in the absence of EVs. According to the results, the EV is charged mostly with thermal generation and the associated emissions are much higher than if they were calculated based on the generation mix.

This paper focuses on an analysis of demand response in a smart grid context, presenting the model considerations and architecture. Domestic consumption is divided into groups in order to cover the adequate modeling. A fuzzy subtractive clustering method is applied to demand response on several domestic consumption scenarios and results analyses are presented. The demand response developed model aims to support consumers decisions regarding their consumption needs and possible economical benefits.

In the paper is presented a method for fault location in the power grid through waveform matching of the recorded wave from failure with simulation from the static system model wave failure. The basis of the approach is comparing of the phase of the waves. The search process to find the best waveform match is actually an optimization problem. The genetic algorithm is used to find the optimal solution. The proposed method is suitable in cases where data from digital fault recorders are scarce. In these circumstances, the proposed approach provides more accurate results compared to the other known techniques. But for the correct operation of this method for fault locating in the system exercise influence both the form of the acquired form from digital fault recorders input data thus the correlation between the power transmission system and the static system model. Namely these issues are the subject of this paper.

This paper presents an analytical method to compute the leakage inductances of power transformers with a turn-to-turn winding fault. A leakage inductance model to represent the transformer with faulty turns is also proposed. The results obtained from the application of the analytical method are validated by using data obtained from finite-element analysis and experimental tests.

In this paper a procedure for determining the number of different synchronous speeds that can be obtained from the stator of a drum motor as a function of the number of slots is presented. This preliminary study is foreseen for a hysteresis high-temperature superconducting motor, but the approach is directly applied in conventional motors. The targeted device has multiphase windings, in order to achieve full flexibility in torque-speed space through electronic variation of magnetic poles. Simulations are performed in order to achieve a qualitative understanding of the behaviour of the motor, namely in what concerns to torque and settling times from initial to synchronous speed. A prototype with eighteen slots in the stator and a bulk YBCO rotor is described and built, and experimental values of torque are obtained.

A voltage limiter circuit for indoor light energy harvesting applications is presented.This circuit is a part of a bigger system, whose function is to harvest indoor light energy, process it and store it, so that it can be used at a later time. This processing consists on maximum power point tracking (MPPT) and stepping-up, of the voltage from the photovoltaic (PV) harvester cell. The circuit here described, ensures that even under strong illumination, the generated voltage will not exceed the limit allowed by the technology, avoiding the degradation, or destruction, of the integrated die. A prototype of the limiter circuit was designed in a 130 nm CMOS technology. The layout of the circuit has a total area of 23414

μ

m

2

. Simulation results, using Spectre, are presented.

Superconducting coils (SC) are the core elements of Superconducting Magnetic Energy Storage (SMES) systems. It is thus fundamental to model and implement SC elements in a way that they assure the proper operation of the system, while complying with design specifications. As a part of a larger model, a coil design model is here presented and verified with tests made in a laboratory prototype. The limitations of the superconducting tape used, namely the negative effect of magnetic field components on its critical current value, are also verified and a possible solution to avoid that effect is studied.

The continuing size reduction of electronic devices imposes design challenges to optimize the performances of modern electronic systems, such as: wireless services, telecom and mobile computing. Fortunately, those design challenges can be overcome thanks to the development of Electronic Design Automation (EDA) tools. In the analog, mixed signal and radio-frequency (AMS/RF) domains, circuit optimization tools have demonstrated their usefulness in addressing design problems taking into account downscaling technological aspects. Recent advances in EDA have shown that the simulation-based sizing technique is a very interesting solution to the ‘complex’ modelling task in the circuit design optimization problem. In this paper we propose a multi-objective simulation-based optimization tool. A CMOS LC-VCO circuit is presented to show the viability of this tool. The tool is used to generate the Pareto front linking two conflicting objectives, namely the VCO Phase Noise and Power Consumption. The accuracy of the results is checked against HSPICE/RF simulations.

This paper presents a distributed model predictive control (DMPC) for indoor thermal comfort that simultaneously optimizes the consumption of a limited shared energy resource. The control objective of each subsystem is to minimize the heating/cooling energy cost while maintaining the indoor temperature and used power inside bounds. In a distributed coordinated environment, the control uses multiple dynamically decoupled agents (one for each subsystem/house) aiming to achieve satisfaction of coupling constraints. According to the hourly power demand profile, each house assigns a priority level that indicates how much is willing to bid in auction for consume the limited clean resource. This procedure allows the bidding value vary hourly and consequently, the agents order to access to the clean energy also varies. Despite of power constraints, all houses have also thermal comfort constraints that must be fulfilled. The system is simulated with several houses in a distributed environment.

In this paper a solution to an highly constrained and non-convex economical dispatch (ED) problem with a meta-heuristic technique named Sensing Cloud Optimization (SCO) is presented. The proposed meta-heuristic is based on a cloud of particles whose central point represents the objective function value and the remaining particles act as sensors “to fill” the search space and “guide” the central particle so it moves into the best direction. To demonstrate its performance, a case study with multi-fuel units and valve- point effects is presented.

The paper analyzes the impact of the component losses on the efficiency of the novel DC/DC converter. The converter is a combination of the quazi-Z-source (qZS) network and dual active bridge (DAB). In the analysis the mathematical loss models of the proposed DC/DC converter are derived and efficiency is estimated. Eventually the efficiency is verified experimentally.

This work addresses two problems related with the assessment of channel availability for cognitive radio systems. We start to characterize the performance of an energy detector for the case when PUs can change their state during the sensing period. The theoretical performance is validated through simulations and compared with a theoretical model where the PUs’ state remains constant during the sensing period. The second point addressed in this work is the characterization of the channel availability, which is based on the output of the energy detector weighted by the probabilities of detection or false alarm computed in real-time. Several scenarios were evaluated and for each scenario the channel availability was correctly assessed by the SUs.

Radio-over-Fiber (RoF) systems which act as backbone networks are very promising means of reducing overall costs of 60 GHz WPANs, as well leading to networks with limited intercellular interference. The main objective of this paper is to compare the performance of two systems that generate Optical Single Side Band (OSSB) OFDM signals at the mm-wave band with and without optical up-conversion. Both systems use a DD-MZM: one is a standard model, whereas the other is a DD-MZM cascaded with a phase modulator (PM). The comparative study presented here also includes practical impairments such as the finite extinction ratio of DD-MZMs.

This paper describes the influence of local oscillator phase noise on single and multi-carrier modulations schemes. The oscillator has the main role on modulation and demodulation process of the radio frequency channels. The synchronization of the entire system depends on the accuracy of this circuit. This work is based on the simulation of these two scenarios under influence of a non-ideal oscillator. The output of the simulation scenario results of error vector magnitude, bit error rate and symbol error rate. The relation of these metrics with the local oscillator phase noise allows the performance estimation the global system. A simple phase noise model is presented with configurable power spectral density and offset frequency.

This PhD work has the goal to develop an inexpensive, easily deployable and widely compatible localization system for indoor use, suitable for pre-installed public address sound systems, avoiding costly installations or significant architectural changes in spaces. Using the audible sound range will allow the use of low cost off-the-shelf equipment suitable for keeping a low deployment cost. The state-of-the-art presented in this paper evidences a technological void in low-cost, reliable and precise localization systems and technologies. This necessity was also confirmed by the authors in a previous project (NAVMETRO®) where no suitable technological solution was found to exist to overcome the need to automatically localize people in a public space in a reliable and precise way.

Although research work is in its first steps, it already provides a thorough view on the problem while discussing some possible approaches and predicting strategies to overcome the key difficulties. Some experiments were already conducted validating some initial premises and demonstrating how to measure the signal’s time-of-flight necessary to infer on distance calculations.

This paper applies to the scientific area of electronic design automation (EDA) and addresses the automatic sizing of analog integrated circuits (ICs). Particularly, this work presents an innovative approach to enhance a state-of-the-art layout-aware circuit-level optimizer (GENOM-POF), by embedding statistical knowledge from an automatically generated gradient model into the multi-objective multi-constraint optimization kernel based on the NSGA-II algorithm. The approach was validated with typical analog circuit structures, using the UMC 0.13

μ

m integration technology, showing that, by enhancing the circuit sizing optimization kernel with the gradient model, the optimal solutions are achieved, considerably, faster and with identical or superior accuracy. Finally, the results are Pareto Optimal Fronts (POFs), which consist of a set of fully compliant sizing solutions, allowing the designer to explore the different trade-offs of the solution space, both through the achieved device sizes, or the respective layout solutions.

WDM multilayered SiC/Si devices based on a-Si:H and a-SiC:H filter design are approached from a reconfigurable point of view. Results show that the devices, under appropriated optical bias, act as reconfigurable active filters that allow optical switching and optoelectronic logic functions development. Under front violet irradiation the magnitude of the red and green channels are amplified and the blue and violet reduced. Violet back irradiation cuts the red channel, slightly influences the magnitude of the green and blue ones and strongly amplifies de violet channel. This nonlinearity provides the possibility for selective removal of useless wavelengths. Particular attention is given to the amplification coefficient weights, which allow taking into account the wavelength background effects when a band needs to be filtered from a wider range of mixed signals, or when optical active filter gates are used to select and filter input signals to specific output ports in WDM communication systems. A truth table of an encoder that performs 8-to-1 multiplexer (MUX) function is presented.

This paper discusses the photodiode capacitance dependence on imposed light and applied voltage using different devices. The first device is a double amorphous silicon pin-pin photodiode; the second one a crystalline pin diode and the last one a single pin amorphous silicon diode. Double amorphous silicon diodes can be used as (de)multiplexer devices for optical communications. For short range applications, using plastic optical fibres, the WDM (wavelength-division multiplexing) technique can be used in the visible light range to encode multiple signals. Experimental results consist on measurements of the photodiode capacitance under different conditions of imposed light and applied voltage. The relation between the capacitive effects of the double diode and the quality of the semiconductor internal junction will be analysed. The dynamics of charge accumulations will be measured when the photodiode is illuminated by a pulsed monochromatic light.

Combined tunable WDM converters based on SiC multilayer photonic active filters are analyzed. The operation combines the properties of active long-pass and short-pass wavelength filter sections into a capacitive active band-pass filter. The sensor element is a multilayered heterostructure produced by PE-CVD. The configuration includes two stacked SiC p-i-n structures sandwiched between two transparent contacts. Transfer function characteristics are studied both theoretically and experimentally. Results show that optical bias activated photonic device combines the demultiplexing operation with the simultaneous photodetection and self amplification of an optical signal acting the device as an integrated photonic filter in the visible range. Depending on the wavelength of the external background and irradiation side, the device acts either as a short- or a long-pass band filter or as a band-stop filter. The output waveform presents a nonlinear amplitude-dependent response to the wavelengths of the input channels. A numerical simulation and a two building-blocks active circuit is presented and gives insight into the physics of the device.

This paper presents a full-bridge discrete power output stage for a Class D audio amplifier using a single-ended power supply. The circuit receives a digital control signal with 5 V of amplitude and it generates a floating differential output voltage up to 20 V of amplitude from a single 20 V power supply voltage. Using as control signal a pulse density modulation (PDM) wave generated by an optimized 3

rd

order continuous-time (CT) sigma delta modulator (ΣΔM), the system achieves a signal-to-noise-plus-distortion ratio (SNDR) of 83.1 dB, total harmonic distortion (THD) of -89 dB and a power efficiency of 92 %, while delivering 11 W over an 8-Ω load with a signal bandwidth of 20 kHz and a sampling frequency of 1.28 MHz.

In this paper we present a balun low noise amplifier (LNA) in which the gain is boosted using a double feedback structure. The circuit is based in a conventional Balun LNA with noise and distortion cancellation. The LNA is based in two basic stages: common-gate (CG) and common-source (CS). We propose to replace the resistors by active loads, which have two inputs that will be used to provide the feedback (in the CG and CS stages). This proposed methodology will boost the gain and reduce the NF. Simulation results, with a 130 nm CMOS technology, show that the gain is 23.8 dB and the NF is less than 1.8 dB. The total power dissipation is only 5.3(since no extra blocks are required), leading to an FOM of 5.7 mW

− 1

from a nominal 1.2 supply.

This paper presents a switched-capacitor (SC) band-pass biquad using a simple quasi-unity gain amplifier. In sub-nanometer CMOS technologies the intrinsic gain of the transistors is low; this increases the difficulty of designing high gain amplifiers. The proposed SC filter is based on the Sallen-Key biquad and it requires only a simple low gain amplifier. A differential filter circuit, including a suitable amplifier based on a fully-differential voltage-combiner is presented and analyzed. The correct functionality of this circuit is validated through electrical simulations of a second-order band-pass filter. These simulations show that, for a clock frequency of 100 MHz, the frequency response of the circuit is similar to the corresponding prototype filter.

A body-biasing compensation scheme based on two proportional-to-absolute-temperature (PTAT) circuits is proposed to reduce the PVT variability of the DC gain of cascode amplifiers. A brief description of a basic PTAT is given as well as its application to cascode-based operational transconductance amplifiers. Simulation results show that the proposed compensated circuit amplifier exhibit a (DC) gain variability smaller than the original (uncompensated) circuit, while reaching a gain enhancement of about 3 dB.

A CMOS three-stage ring oscillator is examined in UMC 0.13

μ

m and 0.18

μ

m technologies. The influence of PMOS transistor and resistor, as inverter feedbacks, on the ring oscillator frequency and the peak-to-peak amplitude is investigated in both technologies. Furthermore, as the ring oscillator usually drives a buffer in pulse generator/transmitter chain, dependence of its Figures of Merit on the buffer feedback is presented in the paper. Simulation results showed that the ring oscillator frequency is strongly dependent on the inverter feedback. The presented techniques can be used to increase (resistive feedback) and control (PMOS transistor feedback) the ring oscillator frequency. As the ring oscillator is a part of an IR-UWB (Impulse Radio Ultra Wide Band) pulse generator, its oscillating frequency determines the spectrum central frequency and has significant effect on spectrum fitting within UWB FCC mask.

This paper presents a new CMOS buffer circuit topology for radio-frequency (RF) applications based on a fully-differential voltage-combiner circuit, capable of operating at low-voltage. The proposed circuit uses a combination of common-source (CS) and common-drain (CD) devices. The simulation results show good levels of linearity and bandwidth. To improve total harmonic distortion (THD) a source degeneration technique is used. The proposed circuit has been designed in a 130nm logic CMOS technology and it achieves a simulated gain of 1.54 dB, a bandwidth of 1.14 GHz for a total power dissipation of 13.34 mW, when driving an RF active probe (with 0.8 pF in parallel with 200 kΩ).

The advancement of CMOS technology led to the integration of more complex functions. In the particular of wireless transceivers, integrated LC tanks are becoming popular both for VCOs and integrated filters [1]. For RF applications the main challenge is still the design of integrated inductors with the maximum quality factor. For that purpose, tapered, i.e., variable width inductors have been proposed in the literature. In this paper, analytical expressions for the determination the pi-model parameters, for the characterization of variable width integrated inductors are proposed. The expressions rely exclusively on geometrical and technological parameters, thus granting the rapid adaptation of the model to different technologies. The results obtained with the model are compared against simulation with

ASITIC

, showing errors below 10%. The model is then integrated into an optimization procedure where inductors with a quality factor improvement in the order of 20-30% are obtained, when compared with fixed width inductors.

Glucose sensing is an issue with great interest in medical and biological applications. One possible approach to glucose detection takes advantage of measuring changes in fluorescence resonance energy transfer (FRET) between a fluorescent donor and an acceptor within a protein which undergoes glucose-induced changes in conformation. This demands the detection of fluorescent signals in the visible spectrum. In this paper we analyzed the emission spectrum obtained from fluorescent labels attached to a protein which changes its conformation in the presence of glucose using a commercial spectrofluorometer. Different glucose nanosensors were used to measure the output spectra with fluorescent signals located at the cyan and yellow bands of the spectrum. A new device is presented based on multilayered a-SiC:H heterostructures to detect identical transient visible signals. The transducer consists of a p-i’(a-SiC:H)-n/p-i(a-Si:H)-n heterostructure optimized for the detection of the fluorescence resonance energy transfer between fluorophores with excitation in the violet (400 nm) and emissions in the cyan (470 nm) and yellow (588 nm) range of the spectrum. Results show that the device photocurrent signal measured under reverse bias and using appropriate steady state optical bias, allows the separate detection of the cyan and yellow fluorescence signals.presented.

This paper presents a 3

rd

order 1.5-bit Continuous-Time Fully Differential ΣΔ modulator with distributed feedback for a class D audio amplifier, using BJT differential pairs to implement the integrator stages. By relying on simple gain blocks instead of operational amplifiers to build the loop filter, a simpler overall circuit is obtained, where the non-ideal effects are embedded in the loop filter transfer function. This leads to a more difficult design process for the loop filter circuit, solved through the use of an optimization procedure based on genetic algorithms. Simulations of the electrical circuit show that it is capable of achieving a SNDR value of 73.4 dB and THD+N of about -80 dB for a signal bandwidth of 20 kHz and a sampling frequency of 1.28 MHz.

This paper deals with system-level optimization of a digital-to-analog converter (DAC) for hearing-aid audio Class D output stage. We discuss the ΣΔ modulator system-level design parameters – the order, the oversampling ratio (OSR) and the number of bits in the quantizer. We show that combining a reduction of the OSR with an increase of the order results in considerable power savings while the audio quality is kept. For further savings in the ΣΔ modulator, overdesign and subsequent coarse coefficient quantization are used. A figure of merit (FOM) is introduced to confirm this optimization approach by comparing two ΣΔ modulator designs. The proposed optimization has impact on the whole hearing-aid audio back-end system including less hardware in the interpolation filter and half the switching rate in the digital-pulse-width-modulation (DPWM) block and Class D output stage.