32 resultados para Smart City, monitoraggio ambientale, Particolato, Smart sensor, Sistemi embedded


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Increasingly, people's digital identities are attached to, and expressed through, their mobile devices. At the same time digital sensors pervade smart environments in which people are immersed. This paper explores different perspectives in which users' modelling features can be expressed through the information obtained by their attached personal sensors. We introduce the PreSense Ontology, which is designed to assign meaning to sensors' observations in terms of user modelling features. We believe that the Sensing Presence ( PreSense ) Ontology is a first step toward the integration of user modelling and "smart environments". In order to motivate our work we present a scenario and demonstrate how the ontology could be applied in order to enable context-sensitive services. © 2012 Springer-Verlag.

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We describe a low cost approach to interrogating a distributive tactile surface instrumented with fibre Bragg grating sensors. The system can determine the position, shape, and orientation of an object on the surface.

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Smart cameras allow pre-processing of video data on the camera instead of sending it to a remote server for further analysis. Having a network of smart cameras allows various vision tasks to be processed in a distributed fashion. While cameras may have different tasks, we concentrate on distributed tracking in smart camera networks. This application introduces various highly interesting problems. Firstly, how can conflicting goals be satisfied such as cameras in the network try to track objects while also trying to keep communication overhead low? Secondly, how can cameras in the network self adapt in response to the behavior of objects and changes in scenarios, to ensure continued efficient performance? Thirdly, how can cameras organise themselves to improve the overall network's performance and efficiency? This paper presents a simulation environment, called CamSim, allowing distributed self-adaptation and self-organisation algorithms to be tested, without setting up a physical smart camera network. The simulation tool is written in Java and hence allows high portability between different operating systems. Relaxing various problems of computer vision and network communication enables a focus on implementing and testing new self-adaptation and self-organisation algorithms for cameras to use.

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In this paper we study the self-organising behaviour of smart camera networks which use market-based handover of object tracking responsibilities to achieve an efficient allocation of objects to cameras. Specifically, we compare previously known homogeneous configurations, when all cameras use the same marketing strategy, with heterogeneous configurations, when each camera makes use of its own, possibly different marketing strategy. Our first contribution is to establish that such heterogeneity of marketing strategies can lead to system wide outcomes which are Pareto superior when compared to those possible in homogeneous configurations. However, since the particular configuration required to lead to Pareto efficiency in a given scenario will not be known in advance, our second contribution is to show how online learning of marketing strategies at the individual camera level can lead to high performing heterogeneous configurations from the system point of view, extending the Pareto front when compared to the homogeneous case. Our third contribution is to show that in many cases, the dynamic behaviour resulting from online learning leads to global outcomes which extend the Pareto front even when compared to static heterogeneous configurations. Our evaluation considers results obtained from an open source simulation package as well as data from a network of real cameras. © 2013 IEEE.

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A recent trend in smart camera networks is that they are able to modify the functionality during runtime to better reflect changes in the observed scenes and in the specified monitoring tasks. In this paper we focus on different configuration methods for such networks. A configuration is given by three components: (i) a description of the camera nodes, (ii) a specification of the area of interest by means of observation points and the associated monitoring activities, and (iii) a description of the analysis tasks. We introduce centralized, distributed and proprioceptive configuration methods and compare their properties and performance. © 2012 IEEE.

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Smart grid technologies have given rise to a liberalised and decentralised electricity market, enabling energy providers and retailers to have a better understanding of the demand side and its response to pricing signals. This paper puts forward a reinforcement-learning-powered tool aiding an electricity retailer to define the tariff prices it offers, in a bid to optimise its retail strategy. In a competitive market, an energy retailer aims to simultaneously increase the number of contracted customers and its profit margin. We have abstracted the problem of deciding on a tariff price as faced by a retailer, as a semi-Markov decision problem (SMDP). A hierarchical reinforcement learning approach, MaxQ value function decomposition, is applied to solve the SMDP through interactions with the market. To evaluate our trading strategy, we developed a retailer agent (termed AstonTAC) that uses the proposed SMDP framework to act in an open multi-agent simulation environment, the Power Trading Agent Competition (Power TAC). An evaluation and analysis of the 2013 Power TAC finals show that AstonTAC successfully selects sell prices that attract as many customers as necessary to maximise the profit margin. Moreover, during the competition, AstonTAC was the only retailer agent performing well across all retail market settings.

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Background: Cochleostomy formation is a key stage of the cochlear implantation procedure. Minimizing the trauma sustained by the cochlea during this step is thought to be a critical feature in hearing preservation cochlear implantation. The aim of this paper is firstly, to assess the cochlea disturbances during manual and robotic cochleostomy formation. Secondly, to determine whether the use of a smart micro-drill is feasible during human cochlear implantation. Materials and methods: The disturbances within the cochlea during cochleostomy formation were analysed in a porcine specimen by creating a third window cochleostomy, preserving the underlying endosteal membrane, on the anterior aspect of the basal turn of the cochlea. A laser vibrometer was aimed at this third window, to assess its movement while a traditional cochleostomy was performed. Six cochleostomies were performed in total, three manually and three with a smart micro-drill. The mean and peak membrane movement was calculated for both manual and smart micro-drill arms, to represent the disturbances sustained within cochlea during cochleostomy formation. The smart micro-drill was further used to perform live human robotic cochleostomies on three adult patients who met the National Institute of Health and Clinical Excellence criteria for undergoing cochlear implantation. Results: In the porcine trial, the smart micro-drill preserved the endosteal membrane in all three cases. The velocity of movement of the endosteal membrane during manual cochleostomy is approximately 20 times higher on average and 100 times greater in peak velocity, than for robotic cochleostomy. The robot was safely utilized in theatre in all three cases and successfully created a bony cochleostomy while preserving the underlying endosteal membrane. Conclusions: Our experiments have revealed that controlling the force of drilling during cochleostomy formation and opening the endosteal membrane with a pick will minimize the trauma sustained by the cochlea by a factor of 20. Additionally, the smart micro-drill can safely perform a bony cochleostomy in humans under operative conditions and preserve the integrity of the underlying endosteal membrane. © W. S. Maney & Son Ltd 2013.

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We study heterogeneity among nodes in self-organizing smart camera networks, which use strategies based on social and economic knowledge to target communication activity efficiently. We compare homogeneous configurations, when cameras use the same strategy, with heterogeneous configurations, when cameras use different strategies. Our first contribution is to establish that static heterogeneity leads to new outcomes that are more efficient than those possible with homogeneity. Next, two forms of dynamic heterogeneity are investigated: nonadaptive mixed strategies and adaptive strategies, which learn online. Our second contribution is to show that mixed strategies offer Pareto efficiency consistently comparable with the most efficient static heterogeneous configurations. Since the particular configuration required for high Pareto efficiency in a scenario will not be known in advance, our third contribution is to show how decentralized online learning can lead to more efficient outcomes than the homogeneous case. In some cases, outcomes from online learning were more efficient than all other evaluated configuration types. Our fourth contribution is to show that online learning typically leads to outcomes more evenly spread over the objective space. Our results provide insight into the relationship between static, dynamic, and adaptive heterogeneity, suggesting that all have a key role in achieving efficient self-organization.

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The global population of people aged 60 years and older is growing rapidly. In the UK, there are currently around 10 million people aged 65 and over, and the number is projected to rise by 50% in the next 20 years (RNIB, 2013). While ongoing advances in information technology (IT) are undoubtedly increasing the scope for IT to enhance and support older adults' daily living, the digital divide between older and younger adults - 43% of people below the age of 55 own and use a smartphone, compared to only 3% of people aged 65 and over (AgeUK, 2013) - raises concerns about the suitability of technological solutions for older adults, especially for older adults with impairments. Evidence suggests that sympathetic design of mobile technology does render it useful and acceptable to older adults: the key issue is, however, how best to achieve such sympathetic design when working with impaired older adults. We report here on a case study in order to outline the practicalities and highlight the benefits of participatory research for the design of sympathetic technology for (and importantly with) older adults with impairments.

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The global population of people aged 60 years and older is growing rapidly. In the UK, there are currently around 10 million people aged 65 and over, and the number is projected to rise by 50% in the next 20 years (RNIB, 2013). While ongoing advances in information technology (IT) are undoubtedly increasing the scope for IT to enhance and support older adults’ daily living, the digital divide between older and younger adults – 43% of people below the age of 55 own and use a smartphone, compared to only 3% of people aged 65 and over (AgeUK, 2013) – raises concerns about the suitability of technological solutions for older adults, especially for older adults with impairments. Evidence suggests that sympathetic design of mobile technology does render it useful and acceptable to older adults: the key issue is, however, how best to achieve such sympathetic design when working with impaired older adults. We report here on a case study in order to outline the practicalities and highlight the benefits of participatory research for the design of sympathetic technology for (and importantly with) older adults with impairments.

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Wireless Sensor Network (WSN) systems have become more and more popular in our modern life. They have been widely used in many areas, such as smart homes/buildings, context-aware devices, military applications, etc. Despite the increasing usage, there is a lack of formal description and automated verification for WSN system design. In this paper, we present an approach to support the rigorous verification of WSN modeling using the Semantic Web technology We use Web Ontology Language (OWL) and Semantic Web Rule Language (SWRL) to define a meta-ontology for the modeling of WSN systems. Furthermore, we apply ontology reasoners to perform automated verification on customized WSN models and their instances. We demonstrate and evaluate our approach through a Light Control System (LCS) as the case study.

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In this paper a surgical robotic device for cochlear implantation surgery is described that is able to discriminate tissue interfaces and other controlling parameters ahead of a drill tip. The advantage in surgery is that tissues at interfaces can be preserved. The smart tool is able to control interaction with respect to the flexing tissue to avoid penetration control the extent of protrusion with respect to the real-time position of the tissue. To interpret drilling conditions, and conditions leading up to breakthrough at a tissue interface, the sensing scheme used enables discrimination between the variety of conditions posed in the drilling environment. The result is a robust fully autonomous system able to respond to tissue type, behaviour and deflection in real-time. The paper describes the robotic tool that has been designed to be used in the surgical environment where it has been used in the operating room.

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The automated sensing scheme described in this paper has the potential to automatically capture, discriminate and classify transients in gait. The mechanical simplicity of the walking platform offers advantages over standard force plates. There is less restriction on dimensions offering the opportunity for multi-contact and multiple steps. This addresses the challenge of patient targeting and the evaluation of patients in a variety of ambulatory applications. In this work the sensitivity of the distributive tactile sensing method has been investigated experimentally. Using coupled time series data from a small number of sensors, gait patterns are compared with stored templates using a pattern recognition algorithm. By using a neural network these patterns were interpreted classifying normal and affected walking events with an accuracy of just under 90%. This system has potential in gait analysis and rehabilitation as a tool for early diagnosis in walking disorders, for determining response to therapy and for identifying changes between pre and post operative gait. Copyright © 2009 by ASME.

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A rapid and efficient method to identify the weak points of the complex chemical structure of low band gap (LBG) polymers, designed for efficient solar cells, when submitted to light exposure is reported. This tool combines Electron Paramagnetic Resonance (EPR) using the 'spin trapping method' coupled with density functional theory modelling (DFT). First, the nature of the short life-time radicals formed during the early-stages of photo-degradation processes are determined by a spin-trapping technique. Two kinds of short life-time radical (R and R′O) are formed after 'short-duration' illumination in an inert atmosphere and in ambient air, respectively. Second, simulation allows the identification of the chemical structures of these radicals revealing the most probable photochemical process, namely homolytical scission between the Si atom of the conjugated skeleton and its pendent side-chains. Finally, DFT calculations confirm the homolytical cleavage observed by EPR, as well as the presence of a group that is highly susceptible to photooxidative attack. Therefore, the synergetic coupling of a spin trapping method with DFT calculations is shown to be a rapid and efficient method for providing unprecedented information on photochemical mechanisms. This approach will allow the design of LBG polymers without the need to trial the material within actual solar cell devices, an often long and costly screening procedure.