O papel dos consumidores residencias no ambiente das redes inteligentes: medidores eletrônicos de energia

Pós-graduação em Engenharia Mecânica - FEG

Intrinsically flexible electronic materials for smart device applications

A novel method to fabricate chemically linked conducting polymer–biopolymer composites that are intrinsically flexible and conducting for functional electrode applications is presented. Polypyrrole was synthesised in situ during the cellulose regeneration process using the 1-butyl-3-methylimidazolium chloride ionic liquid as a solvent medium. The obtained polypyrrole–cellulose composite was chemically blended and showed flexible polymer properties while retaining the electronic properties of a conducting polymer. Addition of an ionic liquid such as trihexyl(tetradecyl)phosphonium bis(trifluoromethylsulfonyl)imide, enhanced the flexibility of the composite. The functional application of these materials in the electrochemically controlled release of a model drug has been demonstrated. This strategy opens up a new design for a wide spectrum of materials for smart electronic device applications wherein the functionality of doping and de-doping of conducting polymers is retained and their processability issue is addressed by exploiting an ionic liquid route.

Progetto di reti Sensori Wireless e tecniche di Fusione Sensoriale

Ambient Intelligence (AmI) envisions a world where smart, electronic environments are aware and responsive to their context. People moving into these settings engage many computational devices and systems simultaneously even if they are not aware of their presence. AmI stems from the convergence of three key technologies: ubiquitous computing, ubiquitous communication and natural interfaces. The dependence on a large amount of fixed and mobile sensors embedded into the environment makes of Wireless Sensor Networks one of the most relevant enabling technologies for AmI. WSN are complex systems made up of a number of sensor nodes, simple devices that typically embed a low power computational unit (microcontrollers, FPGAs etc.), a wireless communication unit, one or more sensors and a some form of energy supply (either batteries or energy scavenger modules). Low-cost, low-computational power, low energy consumption and small size are characteristics that must be taken into consideration when designing and dealing with WSNs. In order to handle the large amount of data generated by a WSN several multi sensor data fusion techniques have been developed. The aim of multisensor data fusion is to combine data to achieve better accuracy and inferences than could be achieved by the use of a single sensor alone. In this dissertation we present our results in building several AmI applications suitable for a WSN implementation. The work can be divided into two main areas: Multimodal Surveillance and Activity Recognition. Novel techniques to handle data from a network of low-cost, low-power Pyroelectric InfraRed (PIR) sensors are presented. Such techniques allow the detection of the number of people moving in the environment, their direction of movement and their position. We discuss how a mesh of PIR sensors can be integrated with a video surveillance system to increase its performance in people tracking. Furthermore we embed a PIR sensor within the design of a Wireless Video Sensor Node (WVSN) to extend its lifetime. Activity recognition is a fundamental block in natural interfaces. A challenging objective is to design an activity recognition system that is able to exploit a redundant but unreliable WSN. We present our activity in building a novel activity recognition architecture for such a dynamic system. The architecture has a hierarchical structure where simple nodes performs gesture classification and a high level meta classifiers fuses a changing number of classifier outputs. We demonstrate the benefit of such architecture in terms of increased recognition performance, and fault and noise robustness. Furthermore we show how we can extend network lifetime by performing a performance-power trade-off. Smart objects can enhance user experience within smart environments. We present our work in extending the capabilities of the Smart Micrel Cube (SMCube), a smart object used as tangible interface within a tangible computing framework, through the development of a gesture recognition algorithm suitable for this limited computational power device. Finally the development of activity recognition techniques can greatly benefit from the availability of shared dataset. We report our experience in building a dataset for activity recognition. Such dataset is freely available to the scientific community for research purposes and can be used as a testbench for developing, testing and comparing different activity recognition techniques.

Sistemi riconfigurabili a basso consumo per applicazioni di monitoraggio distribuito

The term Ambient Intelligence (AmI) refers to a vision on the future of the information society where smart, electronic environment are sensitive and responsive to the presence of people and their activities (Context awareness). In an ambient intelligence world, devices work in concert to support people in carrying out their everyday life activities, tasks and rituals in an easy, natural way using information and intelligence that is hidden in the network connecting these devices. This promotes the creation of pervasive environments improving the quality of life of the occupants and enhancing the human experience. AmI stems from the convergence of three key technologies: ubiquitous computing, ubiquitous communication and natural interfaces. Ambient intelligent systems are heterogeneous and require an excellent cooperation between several hardware/software technologies and disciplines, including signal processing, networking and protocols, embedded systems, information management, and distributed algorithms. Since a large amount of fixed and mobile sensors embedded is deployed into the environment, the Wireless Sensor Networks is one of the most relevant enabling technologies for AmI. WSN are complex systems made up of a number of sensor nodes which can be deployed in a target area to sense physical phenomena and communicate with other nodes and base stations. These simple devices typically embed a low power computational unit (microcontrollers, FPGAs etc.), a wireless communication unit, one or more sensors and a some form of energy supply (either batteries or energy scavenger modules). WNS promises of revolutionizing the interactions between the real physical worlds and human beings. Low-cost, low-computational power, low energy consumption and small size are characteristics that must be taken into consideration when designing and dealing with WSNs. To fully exploit the potential of distributed sensing approaches, a set of challengesmust be addressed. Sensor nodes are inherently resource-constrained systems with very low power consumption and small size requirements which enables than to reduce the interference on the physical phenomena sensed and to allow easy and low-cost deployment. They have limited processing speed,storage capacity and communication bandwidth that must be efficiently used to increase the degree of local ”understanding” of the observed phenomena. A particular case of sensor nodes are video sensors. This topic holds strong interest for a wide range of contexts such as military, security, robotics and most recently consumer applications. Vision sensors are extremely effective for medium to long-range sensing because vision provides rich information to human operators. However, image sensors generate a huge amount of data, whichmust be heavily processed before it is transmitted due to the scarce bandwidth capability of radio interfaces. In particular, in video-surveillance, it has been shown that source-side compression is mandatory due to limited bandwidth and delay constraints. Moreover, there is an ample opportunity for performing higher-level processing functions, such as object recognition that has the potential to drastically reduce the required bandwidth (e.g. by transmitting compressed images only when something ‘interesting‘ is detected). The energy cost of image processing must however be carefully minimized. Imaging could play and plays an important role in sensing devices for ambient intelligence. Computer vision can for instance be used for recognising persons and objects and recognising behaviour such as illness and rioting. Having a wireless camera as a camera mote opens the way for distributed scene analysis. More eyes see more than one and a camera system that can observe a scene from multiple directions would be able to overcome occlusion problems and could describe objects in their true 3D appearance. In real-time, these approaches are a recently opened field of research. In this thesis we pay attention to the realities of hardware/software technologies and the design needed to realize systems for distributed monitoring, attempting to propose solutions on open issues and filling the gap between AmI scenarios and hardware reality. The physical implementation of an individual wireless node is constrained by three important metrics which are outlined below. Despite that the design of the sensor network and its sensor nodes is strictly application dependent, a number of constraints should almost always be considered. Among them: • Small form factor to reduce nodes intrusiveness. • Low power consumption to reduce battery size and to extend nodes lifetime. • Low cost for a widespread diffusion. These limitations typically result in the adoption of low power, low cost devices such as low powermicrocontrollers with few kilobytes of RAMand tenth of kilobytes of program memory with whomonly simple data processing algorithms can be implemented. However the overall computational power of the WNS can be very large since the network presents a high degree of parallelism that can be exploited through the adoption of ad-hoc techniques. Furthermore through the fusion of information from the dense mesh of sensors even complex phenomena can be monitored. In this dissertation we present our results in building several AmI applications suitable for a WSN implementation. The work can be divided into two main areas:Low Power Video Sensor Node and Video Processing Alghoritm and Multimodal Surveillance . Low Power Video Sensor Nodes and Video Processing Alghoritms In comparison to scalar sensors, such as temperature, pressure, humidity, velocity, and acceleration sensors, vision sensors generate much higher bandwidth data due to the two-dimensional nature of their pixel array. We have tackled all the constraints listed above and have proposed solutions to overcome the current WSNlimits for Video sensor node. We have designed and developed wireless video sensor nodes focusing on the small size and the flexibility of reuse in different applications. The video nodes target a different design point: the portability (on-board power supply, wireless communication), a scanty power budget (500mW),while still providing a prominent level of intelligence, namely sophisticated classification algorithmand high level of reconfigurability. We developed two different video sensor node: The device architecture of the first one is based on a low-cost low-power FPGA+microcontroller system-on-chip. The second one is based on ARM9 processor. Both systems designed within the above mentioned power envelope could operate in a continuous fashion with Li-Polymer battery pack and solar panel. Novel low power low cost video sensor nodes which, in contrast to sensors that just watch the world, are capable of comprehending the perceived information in order to interpret it locally, are presented. Featuring such intelligence, these nodes would be able to cope with such tasks as recognition of unattended bags in airports, persons carrying potentially dangerous objects, etc.,which normally require a human operator. Vision algorithms for object detection, acquisition like human detection with Support Vector Machine (SVM) classification and abandoned/removed object detection are implemented, described and illustrated on real world data. Multimodal surveillance: In several setup the use of wired video cameras may not be possible. For this reason building an energy efficient wireless vision network for monitoring and surveillance is one of the major efforts in the sensor network community. Energy efficiency for wireless smart camera networks is one of the major efforts in distributed monitoring and surveillance community. For this reason, building an energy efficient wireless vision network for monitoring and surveillance is one of the major efforts in the sensor network community. The Pyroelectric Infra-Red (PIR) sensors have been used to extend the lifetime of a solar-powered video sensor node by providing an energy level dependent trigger to the video camera and the wireless module. Such approach has shown to be able to extend node lifetime and possibly result in continuous operation of the node.Being low-cost, passive (thus low-power) and presenting a limited form factor, PIR sensors are well suited for WSN applications. Moreover techniques to have aggressive power management policies are essential for achieving long-termoperating on standalone distributed cameras needed to improve the power consumption. We have used an adaptive controller like Model Predictive Control (MPC) to help the system to improve the performances outperforming naive power management policies.

I benefici dell'applicazione estesa della telelettura nella caratterizzazione della dotazione idrica

Si sono analizzate le opportunità offerte dalla telelettura dei consumi idrici per la caratterizzazione della domanda idrica con particolare attenzione al caso di studio di Fano (PU)

Desenvolvimento de um smart meter: um estudo sobre eficiência energética através das redes inteligentes

Pós-graduação em Engenharia Elétrica - FEB

An electronic pressure-meter nociception paw test for rats

The objective of the present investigation was to compare the sensitivity of an electronic nociceptive mechanical paw test with classical mechanical tests to quantify the intensity variation of inflammatory nociception. The electronic pressure-meter test consists of inducing the hindpaw flexion reflex by poking the plantar region with a polypropylene pipette tip adapted to a hand-held force transducer. This method was compared with the classical von Frey filaments test and with the rat paw constant pressure test, a modification of the Randall and Selitto test developed by our group. When comparing the three methods, the electronic pressure-meter and the rat paw constant pressure test, but not the von Frey filaments test, detected time vs treatment interactions in prostaglandin E2 (PGE2)-induced hypernociception. Both methods also detected the PGE2-induced hypernociception in dose- (50-400 ng/paw) and time- (1-4 h) dependent manners, and time vs treatment interactions induced by carrageenin (25-400 µg/paw). Furthermore, the electronic pressure-meter test was more sensitive at early times, whereas the constant pressure test was more sensitive at later times. Moreover, the electronic pressure-meter test detected the dose-dependent antinociceptive effect of local indomethacin (30-300 µg/paw) and dipyrone (80-320 µg/paw) on carrageenin- (200 µg/paw) and PGE2- (100 ng/paw) induced hypernociception, respectively, and also detected the ineffectiveness of indomethacin (300 µg) on the effect of PGE2. Our results show that the electronic pressure-meter provides a sensitive, objective and quantitative mechanical nociceptive test that could be useful to characterize new nociceptive inflammatory mediators and also to evaluate new peripheral analgesic substances.

An electronic pressure-meter nociception paw test for mice

The aim of the present investigation was to describe and validate an electronic mechanical test for quantification of the intensity of inflammatory nociception in mice. The electronic pressure-meter test consists of inducing the animal hindpaw flexion reflex by poking the plantar region with a polypropylene pipette tip adapted to a hand-held force transducer. This method was compared to the classical von Frey filaments test in which pressure intensity is automatically recorded after the nociceptive hindpaw flexion reflex. The electronic pressure-meter and the von Frey filaments were used to detect time versus treatment interactions of carrageenin-induced hypernociception. In two separate experiments, the electronic pressure-meter was more sensitive than the von Frey filaments for the detection of the increase in nociception (hypernociception) induced by small doses of carrageenin (30 µg). The electronic pressure-meter detected the antinociceptive effect of non-steroidal drugs in a dose-dependent manner. Indomethacin administered intraperitoneally (1.8-15 mg/kg) or intraplantarly (30-300 µg/paw) prevented the hypersensitive effect of carrageenin (100 µg/paw). The electronic pressure-meter also detected the hypernociceptive effect of prostaglandin E2 (PGE2; 10-100 ng) in a dose-dependent manner. The hypernociceptive effect of PGE2 (100 ng) was blocked by dipyrone (160 and 320 µg/paw) but not by intraplantar administration of indomethacin (300 µg/paw). The present results validate the use of the electronic pressure-meter as more sensitive than the von Frey filaments in mice. Furthermore, it is an objective and quantitative nociceptive test for the evaluation of the peripheral antinociceptive effect of anti-inflammatory analgesic drugs, which inhibit prostaglandin synthesis (indomethacin) or directly block the ongoing hypernociception (dipyrone).

Analysis and clustering of residential customers energy behavioral demand using smart meter data

Clustering methods are increasingly being applied to residential smart meter data, providing a number of important opportunities for distribution network operators (DNOs) to manage and plan the low voltage networks. Clustering has a number of potential advantages for DNOs including, identifying suitable candidates for demand response and improving energy profile modelling. However, due to the high stochasticity and irregularity of household level demand, detailed analytics are required to define appropriate attributes to cluster. In this paper we present in-depth analysis of customer smart meter data to better understand peak demand and major sources of variability in their behaviour. We find four key time periods in which the data should be analysed and use this to form relevant attributes for our clustering. We present a finite mixture model based clustering where we discover 10 distinct behaviour groups describing customers based on their demand and their variability. Finally, using an existing bootstrapping technique we show that the clustering is reliable. To the authors knowledge this is the first time in the power systems literature that the sample robustness of the clustering has been tested.

The electronic detail of a digital pH-meter

This paperwork presents the complete circuitry used to build a microcontroller-based pH-meter. Key control software is also discussed. An industry-standard glass combination electrode has been employed for pH detection. Electrode parameter extraction procedure is presented. Good measurement results, with 1 % error, have been attained. Copyright© (2006) by the International Measurement Federation (IMEKO).

Practical comparisons among electronic energy meters, a precision energy meter and IEEE1459 for reactive energy measurements, under unbalanced and non-sinusoidal conditions

This paper presents a practical experimentation for comparing reactive/non-active energy measures, considering three-phase four-wire non-sinusoidal and unbalanced circuits, involving five different commercial electronic meters. The experimentation set provides separately voltage and current generation, each one with any waveform involving up to fifty-first harmonic components, identically compared with acquisitions obtained from utility. The experimental accuracy is guaranteed by a class A power analyzer, according to IEC61000-4-30 standard. Some current and voltage combination profiles are presented and confronted with two different references of reactive/non-active calculation methodologies; instantaneous power theory and IEEE 1459-2010. The first methodology considers the instantaneous power theory, present into the advanced mathematical internal algorithm from WT3000 power analyzer, and the second methodology, accomplish with IEEE 1459-2010 standard, uses waveform voltage and current acquisition from WT3000 as input data for a virtual meter developed on Mathlab/Simulink software. © 2012 IEEE.

Power quality, smart meters and additional information from different power terms

This paper shows how the detailed examination of active and nonactive power components may produce new information for modern smart meters. For this purpose, a prototype of electronic power meter has been implemented and applied to the evaluation of the Conservative Power Theory (CPT). Considering five sorts of loads, under four different operating conditions, the experimental results indicate that the CPT is able to provide a good methodology for load characterization, which could possibly benefits consumers and power utilities in several different ways. The results also show that depending on the situation, the analysis of nonactive power terms may be more important than the observation of traditional power quality indices, such as total harmonic distortion, unbalance factors or the fundamental positive sequence power factor.

Meter data management for smart monitoring power networks

The electrical power distribution and commercialization scenario is evolving worldwide, and electricity companies, faced with the challenge of new information requirements, are demanding IT solutions to deal with the smart monitoring of power networks. Two main challenges arise from data management and smart monitoring of power networks: real-time data acquisition and big data processing over short time periods. We present a solution in the form of a system architecture that conveys real time issues and has the capacity for big data management.

Smart meter privacy by suprression of low power frequency components

This paper focuses on the problems associated with privacy protection in smart grid. We will give an overview of a possible realization of a privacy-preserving approach that encompasses privacy-utility tradeoff into a single model. This approach proposes suppression of low power frequency components as a solution to reduce the amount of information leakage from smart meter readings. We will consider the applicability of the procedure to hide the appliance usage with respect to the type of home devices.

Short-term Load Forecasting Using Neural Network For Future Smart Grid Application

Short-term load forecasting of power system has been a classic problem for a long time. Not merely it has been researched extensively and intensively, but also a variety of forecasting methods has been raised. This thesis outlines some aspects and functions of smart meter. It also presents different policies and current statuses as well as future projects and objectives of SG development in several countries. Then the thesis compares main aspects about latest products of smart meter from different companies. Lastly, three types of prediction models are established in MATLAB to emulate the functions of smart grid in the short-term load forecasting, and then their results are compared and analyzed in terms of accuracy. For this thesis, more variables such as dew point temperature are used in the Neural Network model to achieve more accuracy for better short-term load forecasting results.