6 resultados para Moreira, Adriano,1922-

em Universidade do Minho


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Positioning technologies are becoming ubiquitous and are being used more and more frequently for supporting a large variety of applica- tions. For outdoor applications, global navigation satellite systems (GNSSs), such as the global positioning system (GPS), are the most common and popular choice because of their wide coverage. GPS is also augmented with network-based systems that exploit existing wireless and mobile networks for providing positioning functions where GPS is not available or to save energy in battery-powered devices. Indoors, GNSSs are not a viable solution, but many applications require very accurate, fast, and exible positioning, tracking, and navigation functions. These and other requirements have stim- ulated research activities, in both industry and academia, where a variety of fundamental principles, techniques, and sensors are being integrated to provide positioning functions to many applications. The large majority of positioning technologies is for indoor environments, and most of the existing commercial products have been developed for use in of ce buildings, airports, shopping malls, factory plants, and similar spaces. There are, however, other spaces where positioning, tracking, and navigation systems play a central role in safety and in rescue operations, as well as in supporting speci c activities or for scienti c research activities in other elds. Among those spaces are underground tunnels, mines, and even underwater wells and caves. This chapter describes the research efforts over the past few years that have been put into the development of positioning systems for underground tun- nels, with particular emphasis in the case of the Large Hadron Collider (LHC) at CERN (the European Organization for Nuclear Research), where localiza- tion aims at enabling more automatic and unmanned radiation surveys. Examples of positioning and localization systems that have been devel- oped in the past few years for underground facilities are presented in the fol- lowing section, together with a brief characterization of those spaces’ special conditions and the requirements of some of the most common applications. Section 5.2 provides a short overview of some of the most representative research efforts that are currently being carried out by many research teams around the world. In addition, some of the fundamental principles and tech- niques are identi ed, such as the use of leaky coaxial cables, as used at the LHC. In Section 5.3, we introduce the speci c environment of the LHC and de ne the positioning requirements for the envisaged application. This is followed by a detailed description of our approach and the results that have been achieved so far. Some last comments and remarks are presented in a nal section.

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We present a study on human mobility at small spatial scales. Differently from large scale mobility, recently studied through dollar-bill tracking and mobile phone data sets within one big country or continent, we report Brownian features of human mobility at smaller scales. In particular, the scaling exponents found at the smallest scales is typically close to one-half, differently from the larger values for the exponent characterizing mobility at larger scales. We carefully analyze 12-month data of the Eduroam database within the Portuguese university of Minho. A full procedure is introduced with the aim of properly characterizing the human mobility within the network of access points composing the wireless system of the university. In particular, measures of flux are introduced for estimating a distance between access points. This distance is typically non-Euclidean, since the spatial constraints at such small scales distort the continuum space on which human mobility occurs. Since two different ex- ponents are found depending on the scale human motion takes place, we raise the question at which scale the transition from Brownian to non-Brownian motion takes place. In this context, we discuss how the numerical approach can be extended to larger scales, using the full Eduroam in Europe and in Asia, for uncovering the transi- tion between both dynamical regimes.

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Research and development around indoor positioning and navigation is capturing the attention of an increasing number of research groups and labs around the world. Among the several techniques being proposed for indoor positioning, solutions based on Wi-Fi fingerprinting are the most popular since they exploit existing WLAN infrastructures to support software-only positioning, tracking and navigation applications. Despite the enormous research efforts in this domain, and despite the existence of some commercial products based on Wi-Fi fingerprinting, it is still difficult to compare the performance, in the real world, of the several existing solutions. The EvAAL competition, hosted by the IPIN 2015 conference, contributed to fill this gap. This paper describes the experience of the RTLS@UM team in participating in track 3 of that competition.

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In the past decade, the research community has been dedicating considerable effort into indoor positioning systems based on Wi-Fi fingerprinting techniques, mainly due to their capability to exploit existing infrastructures. Crowdsourcing approaches, also known as organic, have been proposed recently to address the problem of creating and maintaining the corresponding radio maps. In these organic systems, the users of the system build the radio map themselves while using it to estimate their own position/location. However, most of these collaborative methods, proposed by several authors, assume that all the users are honest and committed to contribute to a good quality radio map. In this paper we assess the quality of a radio map built collaboratively and propose a method to classify the credibility of individual contributions and the reputation of individual users. Experimental results are presented for an organic indoor location system that has been used by more than one hundred users over a period of around 12 months.

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Data traces, consisting of logs about the use of mobile and wireless networks, have been used to study the statistics of encounters between mobile nodes, in an attempt to predict the performance of opportunistic networks. Understanding the role and potential of mobile devices as relaying nodes in message dissemination and delivery depends on the knowledge about patterns and number of encounters among nodes. Data traces about the use of WiFi networks are widely available and can be used to extract large datasets of encounters between nodes. However, these logs only capture indirect encounters between nodes, and the resulting encounters datasets might not realistically represent the spatial and temporal behaviour of nodes. This paper addresses the impact of overlapping between the coverage areas of different Access Points of WiFi networks in extracting encounters datasets from the usage logs. Simulation and real-world experimental results show that indirect encounter traces extracted directly from these logs strongly underestimate the opportunities for direct node-to- node message exchange in opportunistic networks.

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Doctoral Programme in Telecommunication - MAP-tele