O crescimento na utilização de redes de sensores sem fio possibilitou desenvolver melhorias para atender as necessidades da indústria de comunicação de dispositivos em função de diversas vantagens relacionadas a baixo custo, baixo consumo de energia, mobilidade, instalação e configuração de novos dispositivos, além disso, criar funcionalidades adicionais, como por exemplo, localização de engenheiros de campo e ativos em ambientes industriais. O protocolo WirelessHART é um padrão aberto de comunicação sem fio que busca atender a estes requisitos. Neste trabalho é apresentado o estudo e desenvolvimento de uma aplicação de localização de um objeto alvo através da rede WirelessHART. São analisados diferentes métodos para estimar a distância entre o objeto alvo e os outros elementos fixos da rede de sensores sem fio, algoritmos para computar dados e determinar a localização em um plano de coordenadas. O funcionamento do sistema proposto e o método de localização utilizado foram avaliados por meio de simulações e de testes práticos. Para as condições utilizadas de instalação dos dispositivos, foi possível obter um alcance na comunicação via rádio de mais de 100 m, o que permitiu determinar uma área de monitoração do sistema de cerca de 100 m x 100 m. Os resultados obtidos do erro de localização atingiram entre um 72% e 80% de estimativas de localização menores que a 5 metros. O trabalho abordou a criação e avaliação de critérios de escolha para obter conjuntos de três transmissores com probabilidade de erros menores do que 5 metros. A avaliação dos critérios é feita através da construção de uma tabela de probabilidade conjunta obtida a partir da aplicação da regra de Bayes em dados experimentais com erro de posicionamento conhecido. / The growth in the use of wireless sensor networks has made possible the development of improvements that meet the needs of the communication industry, including several devices with to low cost, low power consumption, mobility and ease of integration, installation and configuration advantages. Not only that but they also create additional functionalities, such as showing the location of field engineers who are assets in industrial environments. The WirelessHART protocol is an open standard for wireless communication that seeks to meet these qualities. This study presents a development of an application for the localization of a mobile device via the WirelessHART network. Different methods are analyzed to estimate the distance between the mobile node and the other fixed elements of the wireless sensor network, such as deployment topologies and algorithms, which are used to compute the data and determine the location in a coordinate plane. The operation of the proposed system and the location method were evaluated by means of simulations and practical tests. Due to the conditions used for the installation of the devices, it was possible to obtain a range of radio transmission over 100 m, which allowed to determine an area of monitoring system of about 100 m x 100 m. The results obtained from the error location reached between a 72% and 80% of the estimated localization that was less than 5 meters. The study addressed the establishment and evaluation of selection criteria for sets of three transmitters with probability of less than 5 meters errors. The evaluation criteria is done by constructing a joint probability table obtained from the application of Bayes rule in experimental data with known positioning error.

O crescimento na utilização de redes de sensores sem fio possibilitou desenvolver melhorias para atender as necessidades da indústria de comunicação de dispositivos em função de diversas vantagens relacionadas a baixo custo, baixo consumo de energia, mobilidade, instalação e configuração de novos dispositivos, além disso, criar funcionalidades adicionais, como por exemplo, localização de engenheiros de campo e ativos em ambientes industriais. O protocolo WirelessHART é um padrão aberto de comunicação sem fio que busca atender a estes requisitos. Neste trabalho é apresentado o estudo e desenvolvimento de uma aplicação de localização de um objeto alvo através da rede WirelessHART. São analisados diferentes métodos para estimar a distância entre o objeto alvo e os outros elementos fixos da rede de sensores sem fio, algoritmos para computar dados e determinar a localização em um plano de coordenadas. O funcionamento do sistema proposto e o método de localização utilizado foram avaliados por meio de simulações e de testes práticos. Para as condições utilizadas de instalação dos dispositivos, foi possível obter um alcance na comunicação via rádio de mais de 100 m, o que permitiu determinar uma área de monitoração do sistema de cerca de 100 m x 100 m. Os resultados obtidos do erro de localização atingiram entre um 72% e 80% de estimativas de localização menores que a 5 metros. O trabalho abordou a criação e avaliação de critérios de escolha para obter conjuntos de três transmissores com probabilidade de erros menores do que 5 metros. A avaliação dos critérios é feita através da construção de uma tabela de probabilidade conjunta obtida a partir da aplicação da regra de Bayes em dados experimentais com erro de posicionamento conhecido. / The growth in the use of wireless sensor networks has made possible the development of improvements that meet the needs of the communication industry, including several devices with to low cost, low power consumption, mobility and ease of integration, installation and configuration advantages. Not only that but they also create additional functionalities, such as showing the location of field engineers who are assets in industrial environments. The WirelessHART protocol is an open standard for wireless communication that seeks to meet these qualities. This study presents a development of an application for the localization of a mobile device via the WirelessHART network. Different methods are analyzed to estimate the distance between the mobile node and the other fixed elements of the wireless sensor network, such as deployment topologies and algorithms, which are used to compute the data and determine the location in a coordinate plane. The operation of the proposed system and the location method were evaluated by means of simulations and practical tests. Due to the conditions used for the installation of the devices, it was possible to obtain a range of radio transmission over 100 m, which allowed to determine an area of monitoring system of about 100 m x 100 m. The results obtained from the error location reached between a 72% and 80% of the estimated localization that was less than 5 meters. The study addressed the establishment and evaluation of selection criteria for sets of three transmitters with probability of less than 5 meters errors. The evaluation criteria is done by constructing a joint probability table obtained from the application of Bayes rule in experimental data with known positioning error.

The aim of this paper is to explore the features that combine to make up the distinctive accent of the actor Sir Sean Connery. This study outlines the subject’s basic vowel system and compares it to data collected on the vowel systems of Received Pronunciation (RP) and Scottish Standard English (SSE) from previous research (Stuart-Smith 1999, Hawkins & Midgely 2005, Fisk 2006). Furthermore, this essay examines the degree to which other elements associated with SSE are present in the subject’s accent. These features include the Scottish Vowel Lengthening Rule (SVLR), the presence of dark /l/, rhoticity and T-glottalling. It is hypothesised that the subject speaks a modified variety of SSE yet retains the aforementioned qualities typically associated with SSE. The speech analysis software programs Wavesurfer (version 1.4.7.) and Praat (version 4.4.33.) were used to analyse sections of sound taken from a speech given by the subject at an awards ceremony. Instrumental analysis of this nature was deemed appropriate in order to establish a high degree of objectivity in this study. Of the wide range of recorded material available the subject’s acceptance speech was judged most suitable for analysis. This is a passage of spontaneous speech as opposed to a movie script, where the subject talks of his background and career. Having analysed the subject’s accent in this way, certain sociolinguistic implications can be drawn. The results suggest that Sir Sean Connery does indeed speak a variety of SSE however rather surprisingly the subject’s accent appears quite typical of his Edinburgh origins. The vowel system not only identifies the subject as an SSE speaker but also indicates traces of his working-class background e.g., the frontal quality to Connery’s realisation of /u/ and his low /I/ are typical of a working-class SSE speaker. Moreover, the general low quality found in Connery’s basic vowel system can be interpreted as revealing a little of his working-class origins. Evidence of the other features associated with SSE was also found in the subject’s accent. Durational evidence indicates (albeit tentatively at this stage) that the SVLR operates within his accent while dark /l/ and t-glottalling were also observed. While it is also apparent that Connery speaks a rhotic variety of English it is the nature and variety of his /r/ production that is most interesting. The subject appears to produce a retroflex realisation of /r/ which affects other consonants in its environment. This /r/ may be indicative of an earlier Irish influence over Connery’s accent. It should be stated that due to the nature and the limited size of this study, all findings are preliminary and more research is needed into this area before any firm conclusions can be drawn.

O crescimento na utilização de redes de sensores sem fio possibilitou desenvolver melhorias para atender as necessidades da indústria de comunicação de dispositivos em função de diversas vantagens relacionadas a baixo custo, baixo consumo de energia, mobilidade, instalação e configuração de novos dispositivos, além disso, criar funcionalidades adicionais, como por exemplo, localização de engenheiros de campo e ativos em ambientes industriais. O protocolo WirelessHART é um padrão aberto de comunicação sem fio que busca atender a estes requisitos. Neste trabalho é apresentado o estudo e desenvolvimento de uma aplicação de localização de um objeto alvo através da rede WirelessHART. São analisados diferentes métodos para estimar a distância entre o objeto alvo e os outros elementos fixos da rede de sensores sem fio, algoritmos para computar dados e determinar a localização em um plano de coordenadas. O funcionamento do sistema proposto e o método de localização utilizado foram avaliados por meio de simulações e de testes práticos. Para as condições utilizadas de instalação dos dispositivos, foi possível obter um alcance na comunicação via rádio de mais de 100 m, o que permitiu determinar uma área de monitoração do sistema de cerca de 100 m x 100 m. Os resultados obtidos do erro de localização atingiram entre um 72% e 80% de estimativas de localização menores que a 5 metros. O trabalho abordou a criação e avaliação de critérios de escolha para obter conjuntos de três transmissores com probabilidade de erros menores do que 5 metros. A avaliação dos critérios é feita através da construção de uma tabela de probabilidade conjunta obtida a partir da aplicação da regra de Bayes em dados experimentais com erro de posicionamento conhecido. / The growth in the use of wireless sensor networks has made possible the development of improvements that meet the needs of the communication industry, including several devices with to low cost, low power consumption, mobility and ease of integration, installation and configuration advantages. Not only that but they also create additional functionalities, such as showing the location of field engineers who are assets in industrial environments. The WirelessHART protocol is an open standard for wireless communication that seeks to meet these qualities. This study presents a development of an application for the localization of a mobile device via the WirelessHART network. Different methods are analyzed to estimate the distance between the mobile node and the other fixed elements of the wireless sensor network, such as deployment topologies and algorithms, which are used to compute the data and determine the location in a coordinate plane. The operation of the proposed system and the location method were evaluated by means of simulations and practical tests. Due to the conditions used for the installation of the devices, it was possible to obtain a range of radio transmission over 100 m, which allowed to determine an area of monitoring system of about 100 m x 100 m. The results obtained from the error location reached between a 72% and 80% of the estimated localization that was less than 5 meters. The study addressed the establishment and evaluation of selection criteria for sets of three transmitters with probability of less than 5 meters errors. The evaluation criteria is done by constructing a joint probability table obtained from the application of Bayes rule in experimental data with known positioning error.

Work described in this thesis is concerned with localisation techniques, for determining the position, of wireless sensors whilst these are immersed in confined industrial processes, such as those occurring in the chemical, pharmaceutical and food processing industries. Two different approaches to localisation were investigated. The first approach employed an existing hardware system that used ultra wide band (UWB) signals whist the second approach used a network localisation method based on information from narrow-band received signals. A prototype UWB-based localisation algorithm processed experimental received UWB pulses to detect their leading edges (LE) that were used to derive Time Difference of Arrival (TDoA) data. In turn TDoA data were converted into distances and used to compute the locations of the sensor nodes. Nevertheless, the process of detecting the LEs caused significant errors in the localisation process. To deal with this problem new automated adaptive LE detection methods were derived that succeeded in reducing localisation errors by half, compared to the prototype method, reaching accuracies of ±2cm. Thorough analysis of TDoA profiles revealed that these follow specific trends depending on the positions of the sensor nodes. A number of properties of TDoA profiles are proved mathematically and incorporated into seven localisation algorithms. These algorithms were examined using experimental TDoA data and shown to achieve average localisation errors up to 3cm. Network-based localisation was examined at a later stage of this research since complexities of large scale measurements and difficulties with equipment, delayed acquiring experimental data. The deployed network consisted of a number of nodes whose positions were known (anchors) that were used to estimate the positions of sensor nodes whose positions where considered to be unknown. Localisation was based on received signal strength (RSS) data, at every node to be localised, in anticipation that RSS could provide distance information that could be used in the localisation procedure. Nevertheless, fluctuations in RSS only allowed using localisation algorithms that associated RSS to the positions of anchors. The average localisation error in the network-based localisation algorithms was between 30cm to 100cm.

This master thesis investigates the possibility of locating LTE base stations, known as eNodeBs, using signal measurements collected by routers on trains. Four existing algorithms for transmitter localization are adopted: the centroid, strongest signal, Monte Carlo path loss simulation and power difference of arrival (PDoA) methods. An improved version of Monte Carlo path loss simulation called logloss fitting is proposed. Furthermore, a novel localization method called sector fitting is presented, which operates solely on the cell identity and geographical distribution of the measurements. The methods are evaluated for a set of manually located eNodeBs, and the results are compared to other external systems that can be used to locate eNodeBs. It is found that the novel sector fitting algorithm is able to considerably improve the accuracy of the logloss fitting and PDoA methods, but weighted centroid is overall the most accurate of the considered methods, providing a median error of approximately 1 km. The Google Geolocation API and Mozilla Location Service still provides estimates that are generally closer to the true location than any of the considered methods. However, for a subset of eNodeBs where measurements from all sectors are available, the novel sector fitting algorithm combined with logloss fitting outperforms the external systems. Therefore, a hybrid approach is suggested, where sector fitting combined with logloss fitting or weighted centroid is used to locate eNodeBs that have measurements from all sectors, while Google Geolocation API or Mozilla Location Service is used to locate the remaining eNodeBs. It is concluded that while the localization performance for those eNodeBs that have measurements from all sectors is relatively good, further improvements to the overall results can likely be obtained in future work by considering environmental factors, the angular losses introduced by directional antennas, and the effects of downlink power control.

There is a stone in Muxía, a Galician seaside village, called the Waving Stone. It used to move and produce a loud and easy-to-identify sound in that process. However, it broke during a storm in 2017, forcing the place to adapt to its new characteristics: the value of that object in the landscape is not anymore its motion but the memory of that movement that people in the area keep and transmit.  Both this essay and the exhibition it accompanies use this story as an analogy to talk about the linguistic transmission break of the Galician tongue and of the minoritized culture of which it is a part. Thus, the work research how the young generation who is used to hear Galician but to talk in Spanish relate to its own culture from a forced distance, making us need to do a big effort to relearn our own language. Distorted representations we received or artistic expressions that we couldn´t experience make it more difficult for us to see how a minoritized culture is never an image but an event, being constantly broken and rebuilt. Like a huge stone on the coast that, even silent, is still able to make a group of people identify around it.

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Yes / A modified indoor path loss prediction model is presented, namely Effective Wall Loss Model (EWLM). The modified model is compared to other indoor path loss prediction models using simulation data and real-time measurements. Different operating frequencies and antenna polarizations are considered to verify the observations. In the simulation part, EWLM shows the best performance among other models as it outperforms two times the dual slope model which is the second-best performance. Similar observations were recorded from the experimental results. Linear attenuation and one slope models have similar behaviour, the two models parameters show dependency on operating frequency and antenna polarization.

This thesis considers statistical issues in source localization from the received signal strength (RSS) measurements at sensor locations, under the practical assumption of log-normal shadowing. Distance information of source from sensor locations can be estimated from RSS measurements and many algorithms directly use powers of distances to localize the source, even though distance measurements are not directly available. The first part of the thesis considers the statistical analysis of distance estimation from RSS measurments. We show that the underlying problem is inefficient and there is only one unbiased estimator for this problem and its mean square error (MSE) grows exponentially with noise power. Later, we provide the linear minimum mean square error (MMSE) estimator whose bias and MSE are bounded in noise power. The second part of the thesis establishes an isomorphism between estimates of differences between squares of distances and the source location. This is used to completely characterize the class of unbiased estimates of the source location and to show that their MSEs grow exponentially with noise powers. Later, we propose an estimate based on the linear MMSE estimate of distances that has error variance and bias that is bounded in the noise variance.