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.

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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.

No description available.

Yes / A subsurface chamber transceiver system and associated propagation channel link budget considerations for an underground wireless sensor system (UWSS) are presented: the application was a sewerage system for a water utility company. The UWSS operates over the GSM850/900, GSM1800/1900 and UMTS bands in order to operate with the standard public mobile phone system. A novel antenna was developed to minimize path loss from the underground location: a folded loop type, which is small enough to fit conveniently inside a utility manhole access chamber while giving adequate signal strength to link to mobile base stations from such a challenging environment. The electromagnetic performance was simulated and measured in both free space and in a real manhole chamber. An experimental test bed was created to determine the return loss and received signal strength with different transceiver positions below the manhole chamber access cover. Both numerical and experimental results suggested an optimum position of the unit inside the manhole, combining easy access for maintenance with viable received signal strength. This confirmed that the characteristics were adequate for incorporation in a transceiver designed to communicate with mobile base stations from underground. A field trial confirmed the successful operation of the system under severe conditions. / This work was supported partially by Yorkshire Innovation Fund, IETG Ltd. Contract, Research Development Project (RDP) and the European Union’s Horizon 2020 research and innovation programme under grant agreement H2020-MSCA-ITN-2016 SECRET-722424.

Network lifetime is an important performance metric in Wireless Sensor Networks (WSNs). Transmission Power Control (TPC) is a well-established method to minimise energy consumption in transmission in order to extend node lifetime and, consequently, lead to solutions that help extend network lifetime. The accurate lifetime estimation of sensor nodes is useful for routing to make more energy-efficient decisions and prolong lifetime. This research proposes an Energy-Efficient TPC (EETPC) mechanism using the measured Received Signal Strength (RSS) to calculate the ideal transmission power. This includes the investigation of the impact factors on RSS, such as distance, height above ground, multipath environment, the capability of node, noise and interference, and temperature. Furthermore, a Dynamic Node Lifetime Estimation (DNLE) technique for WSNs is also presented, including the impact factors on node lifetime, such as battery type, model, brand, self-discharge, discharge rate, age, charge cycles, and temperature. In addition, an Energy-Efficient and Lifetime Aware Routing (EELAR) algorithm is designed and developed for prolonging network lifetime in multihop WSNs. The proposed routing algorithm includes transmission power and lifetime metrics for path selection in addition to the Expected Transmission Count (ETX) metric. Both simulation and real hardware testbed experiments are used to verify the effectiveness of the proposed schemes. The simulation experiments run on the AVRORA simulator for two hardware platforms: Mica2 and MicaZ. The testbed experiments run on two real hardware platforms: the N740 NanoSensor and Mica2. The corresponding implementations are on two operating systems: Contiki and TinyOS. The proposed TPC mechanism covers those investigated factors and gives an overall performance better than the existing techniques, i.e. it gives lower packet loss and power consumption rates, while delays do not significantly increase. It can be applied for single-hop with multihoming and multihop networks. Using the DNLE technique, node lifetime can be predicted more accurately, which can be applied for both static and dynamic loads. EELAR gives the best performance on packet loss rate, average node lifetime and network lifetime compared to the other algorithms and no significant difference is found between each algorithm with the packet delay.