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.

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.

TCR signal strength is critical for CD8+ T cell clonal expansion after antigen stimulation. Levels of the transcription factor IRF4 control the magnitude of this process through induction of genes involved in proliferation and glycolytic metabolism. The signaling mechanism connecting graded TCR signaling to the generation of varying amounts of IRF4 is not well understood. Here, using multiple methods to vary TCR signal strength and measure changes in transcriptional activation in single CD8+ T cells, we connect antigen potency to the kinetics of NFAT activation and Irf4 mRNA expression. T cells that transduce weaker TCR signals exhibit a marked delay in Irf4 mRNA induction resulting in decreased overall IRF4 expression in individual cells and increased heterogeneity within the clonal population. The activity of the tyrosine kinase ITK acts as a signaling catalyst that accelerates the rate of the cellular response to TCR stimulation, controlling the time to onset of Irf4 gene transcription. These findings provide insight into the signal transduction pathway accounting for the reduced clonal expansion of low affinity CD8+ T cells following infection. We also describe another context for ITK activity, autoreactive T cell migration. Here, we connect TCR signaling strength to modulation of selectin binding and autoreactive T cell-mediated pathology in an adoptive transfer model system of autoimmune disease. Understanding the signaling mechanisms linking changes in TCR signaling to CD8 T cell function is important in furthering the understanding of vaccine development and T cell adoptive immunotherapy.

No description available.

This thesis presents a model to predict signal strength for frequencies between 902 MHz and 28 GHz. The model approximates diffraction using the knife-edge concept and equations proposed by Lee (1985). LOS pathways are calculated using the Bresenham algorithm and the corresponding elevations are obtained from a 30m DEM base map. The base map was generated by the procedure outlined in Rose (2001) and includes building elevations. The effect of Fresnel zones on prediction accuracy is considered. The effect of interpolating elevations along the Bresenham line is also considered. An Inverse Distance Weighting algorithm was used to interpolate the elevations. The accuracy of the model was evaluated using received signal strength data compiled from studies conducted at 902 MHz, 24.12 GHz and 27.525 GHz. In addition to the compiled data, data was also collected for this study at 2.4 GHz. 257 receiver locations were evaluated; 70 samples were Line-of-Sight. The study area incorporates the Virginia Polytechnic Institute and State University campus. Incorporating Fresnel zones, Interpolating elevations and calculating double blockages do not have an effect on the program's overall ability to predict signal strength. However, for obstructed pathways, it is not adequate to simply use path loss as an estimate of signal strength. Accurate estimates of diffraction gain are crucial for obstructed pathways. In addition, examination of the standard deviation for the data sets indicates that the model is independent of frequency. The average error across the frequencies is positively correlated with frequency, indicating that the model predicts signal strength better for higher frequencies. The smaller wavelengths associated with the higher frequencies require a more directional antenna and are therefore less sensitive to multipath interference. In addition, the smaller wavelengths are less able to diffract around buildings and terrain features. / Master of Science

The purpose of this study was to determine if light detection and ranging (LiDAR) imagery could provide a significantly more accurate data set for modeling near line-of-sight (LOS) propagation at higher frequencies, specifically 27.810 GHz. than a USGS digital elevation model (DEM). In addition, the study tested for significant differences in LiDAR elevation data created at various resolutions ranging from 1 to 100 meters. Finally, this study examined the effects of various classification thresholds for transforming continuous signal strength measurements into LOS or non-LOS (NLOS) classifications used in determining prediction accuracy. The capability to transmit information via higher frequency wireless equipment requires a near LOS path between the transmitter and the antenna receiving the signal. USGS DEMs, commonly used in GIS programs to predict communication viewsheds (commsheds), represent the bare earth topography and do not reflect surface features such as vegetation and buildings. In actuality these surface features can significantly influence near LOS paths and therefore a data set that contains these features can greatly improve the ability to predict commshed areas. LiDAR is a form of active imagery that records both the bare-earth as well as these surface features, at a high resolution, making it well suited for wireless modeling applications. Results indicate that signal strength threshold classification has a direct influence on the accuracy of predicted commsheds across all resolutions. Secondly, LiDAR resolutions lower than 40m as well as bare-earth DEMs were unsuccessful in predicting an accurate commshed while LiDAR resolutions coarser than 15m provided significant predictions of equal accuracy. These results indicate that high resolution LiDAR is needed to accurately model commsheds but signal strength threshold classification determines which of these higher resolutions are significant. / Master of Science

Context: Windmills became one of main sources of energy. Sincethey are placed in open areas, there are many chances that birds mayenter the wind farms and get killed or damaged. Some wind farms usepulse radar systems for saving the birds from windmills. In this pulseradar technology, the turbines are turned off automatically when a birdis detected. Another technology is ultrasonic "boom boxes", which areattached to turbines and produce high-frequency noises continuouslyto repel birds. The system we are going to propose detects the birdsentering the farm using Bluetooth technology and alerts the windmill farm operator. Using Bluetooth technology can be power efficient, ac-curate, and mainly useful for avifauna method of protection. Objectives: The main objective of the Bluetooth bird detection sys-tem is to make distance estimation possible with the help of signal strength that is measured between two Bluetooth devices where oneis placed at the wind farm and another on bird. Methods: Bird detection and distance measurement is done using a BGX13P Bluetooth transmitter and receiver. According to the distance to the bird, further steps can be taken to protect it. Simplicity Studio application is used to take the readings of the Bluetooth signalstrength of the transmitter and receiver. Results: As a result, the birds are detected at two distances from awindmill, the first distance is 250 m and the second is 175 m from thewindmill. The windmill operator is alerted when the bird is detectedat either of these distances. Conclusion: A bird detection system is built with the help of Blue-tooth technology. This system helps saving the birds from collisions with windmills. However, there is a need for further quantitative andqualitative validation of the models in full-scale industry trials.