In recent years, the indoor positioning system (IPS) has attracted significant interests in both academical research and industrial development. It has seen many applications, such as hostage search and rescue, indoor navigation, and warehouse management, all of which can take advantage of precise positioning. However, in indoor environments, traditional methods, like the Global Positioning System (GPS), are usually either unreliable or incorrect because of the complicated physical characteristics of various objects reflecting and dispersing signals, such as the presence of people, walls, obstructions, and furniture. In contrast to other technologies such as WiFi and Bluetooth, which are not suitable to extract accurate timing information, UWB technology has the potential to reach center-meter level accuracy in indoor positioning. In this thesis, we developed a real-time, low-cost, IPS based on commercial-off-the-shelf UWB transceivers. Both the Two Way Ranging (TWR) and Time Difference of Arrival (TDOA) approaches have been implemented to obtain a target's location. To alleviate the effect of multipath propagation, we detect the presence of outliers by comparing the first path signal level and estimated receiving signal level. Moreover, we have designed the Printed Circuit Board (PCB) and evaluated performance by deploying the system both in a lab environment and in a two-story historical building during the 2018 Microsoft Indoor Localization Competition. The results show that we achieve a 28.9cm 95%-quantile 2D tracking error in the lab environment and a 92cm average tracking error for 3D localization on the Microsoft Indoor Localization Competition site. / Thesis / Master of Science (MSc)

No Brasil existem milhões de brasileiros com algum tipo de dificuldade de locomoção, sendo que grande parte dessas pessoas com deficiência necessita de cadeira de rodas para se locomover. Com o fato de existirem inúmeros de brasileiros cadeirantes, o desenvolvimento de tecnologias ditas ¨assistivas¨, ou seja, tecnologias que visam assistir estas pessoas em suas atividades, tem recebido uma crescente atenção, tanto do ponto de vista de negócios (com o aumento de produtos), como de pesquisas acadêmicas. Dentre estas linhas de pesquisa, a integração entre cadeiras de rodas automatizadas com sistemas de automação predial e residencial está entre as linhas de pesquisa de maior destaque, pois tem como objetivo tornar a vida do usuário de cadeira de rodas mais produtiva e cômoda, contribuindo para sua independência. Os sistemas de automação predial e residencial mais complexos elevam o nível de um ambiente automatizado para um ambiente inteligente, pois tornam o nível de abstração maior, fornecendo serviços de forma pervasiva. O ambiente inteligente necessita de informações para que possa oferecer seus serviços ao cadeirante, e uma informação importante seria a localização da cadeira de rodas automatizada. Neste contexto, este trabalho propõe um sistema de localização em interiores para cadeiras de rodas automatizadas em ambientes inteligentes. A proposta combina Redes de Sensores Sem Fio (RSSF) e a tecnologia RFID, onde as etiquetas RFID são utilizadas como marcos de referências para a calibração automática dos parâmetros da RSSF, que convencionalmente são obtidos de forma experimental. O estudo de caso para validar o sistema de localização proposto foi realizado numa sala automatizada no prédio da Engenharia Elétrica da Universidade Federal do Rio Grande do Sul (UFRGS) como ambiente inteligente, e uma cadeira de rodas automatizada adaptada para se comunicar com a RSSF. Além deste estudo de caso, foram realizados outros experimentos com intuito de avaliar qual método geraria os melhores resultados para o sistema de localização baseado em RSSF e a tecnologia RFID, combinando diferentes modelos de propagação de sinal RF e diferentes formas de calibrar os parâmetros da rede. Além disso, outras questões sobre o sistema de localização proposto foram analisadas, como por exemplo, a influência do aumento da quantidade de nós da rede na exatidão do sistema, o comportamento do sistema quando, para um mesmo cenário, o sentido do percurso é invertido, e a influência do leiaute dos nós da rede no desempenho do sistema. / In Brazil there are millions of people with some kind of limited mobility, and that most of these disabled people need a wheelchair to get around. With the fact that there are millions of wheelchair users, the development of assistive technologies, i.e. technologies to assist these people in their activities, has received increasing attention both from the standpoint of business (with the increase of products), as academic research. Among these lines of research, the integration of automated wheelchairs with home automation systems are among the research areas of greatest importance because it aims to make the user's life more productive and comfortable, contributing to their independence. The home automation systems more complex increase the level of an automated environment for intelligent environment, as they make the higher level of abstraction, providing pervasive services. The intelligent environment needs information so it can offer your services to the wheelchair user, and important information would be the location of the automated wheelchair. Within this context, this paper proposes an indoor positioning system for wheelchairs in intelligent environments. The proposal combines Wireless Sensor Networks (WSN) and RFID technology, where RFID tags are used as landmark for automatic calibration of the parameters of WSN, which are conventionally obtained experimentally. The case study to validate the proposed indoor positioning system was performed at an automated room in the building of Electrical Engineering, Universidade Federal do Rio Grande do Sul (UFRGS) with the intelligent environment and automated wheelchair adapted to communicate with the WSN. In addition to the case study, other experiments in order to assess which method would produce the best results for the localization system based on RFID and WSN, combining different radio propagation model and different forms of calibrate the parameters of the WSN. In addition, other questions about the proposed indoor positioning system were analyzed, for example, the influence of increasing the amount of network nodes on the system accuracy, the behavior of the system for the same scenario when the direction of travel is reversed, and the influence of the layout of the network nodes on the system performance.

Tracking objects or people in an indoor environment has a wide variety of uses in many different areas, similarly to positioning systems outdoors. Indoor positioning systems operate in a very different environment however, having to deal with obstructions while also having high accuracy. A common solution for indoor positioning systems is to have three or more stationary anchor antennas spread out around the perimeter of the area that is to be monitored. The position of a tag antenna moving in range of the anchors can then be found using trilateration. One downside of such a setup is that the anchors must be setup in advance, meaning that rapid deployment to new areas of such a system may be impractical. This thesis aims to investigate the possibility of using a different setup, where three anchors are placed close together, so as to fit in a small hand-held device. This would allow the system to be used without any prior setup of anchors, making rapid deployment into new areas more feasible. The measurements done by the antennas for use in trilateration will always contain noise, and as such algorithms have had to be developed in order to obtain an approximation of the position of a tag in the presence of noise. These algorithms have been developed with the setup of three spaced out anchors in mind, and may not be sufficiently accurate when the anchors are spaced very closely together. To investigate the feasibility of such a setup, this thesis tested four different algorithms with the proposed setup, to see its impact on the performance of the algorithms. The algorithms tested are the Weighted Block Newton, Weighted Clipped Block Newton, Linear Least Squares and Non-Linear Least Squares algorithms. The Linear Least Squares algorithm was also run with measurements that were first run through a simple Kalman filter. Previous studies have used the algorithms to find an estimated position of the tag and compared their efficiency using the positional error of the estimate. This thesis will also use the positional estimates to determine the angular position of the estimate in relation to the anchors, and use that to compare the algorithms. Measurements were done using DWM1001 Ultra Wideband (UWB) antennas, and four different cases were tested. In case 1 the anchors and tag were 10 meters apart in line-of-sight, case two were the same as case 1 but with a person standing between the tag and the anchors. In case 3 the tag was moved behind a wall with an adjacent open door, and in case 4 the tag was in the same place as in case 3 but the door was closed. The Linear Least Squares algorithm using the filtered measurements was found to be the most effective in all cases, with a maximum angular error of less than 5$^\circ$ in the worst case. The worst case here was case 2, showing that the influence of a human body has a strong effect on the UWB signal, causing large errors in the estimates of the other algorithms. The presence of a wall in between the anchors and tag was found to have a minimal impact on the angular error, while having a larger effect on the spatial error. Further studies regarding the effects of the human body on UWB signals may be necessary to determine the feasibility of handheld applications, as well as the effect of the tag and/or the anchors moving on the efficiency of the algorithms.

No Brasil existem milhões de brasileiros com algum tipo de dificuldade de locomoção, sendo que grande parte dessas pessoas com deficiência necessita de cadeira de rodas para se locomover. Com o fato de existirem inúmeros de brasileiros cadeirantes, o desenvolvimento de tecnologias ditas ¨assistivas¨, ou seja, tecnologias que visam assistir estas pessoas em suas atividades, tem recebido uma crescente atenção, tanto do ponto de vista de negócios (com o aumento de produtos), como de pesquisas acadêmicas. Dentre estas linhas de pesquisa, a integração entre cadeiras de rodas automatizadas com sistemas de automação predial e residencial está entre as linhas de pesquisa de maior destaque, pois tem como objetivo tornar a vida do usuário de cadeira de rodas mais produtiva e cômoda, contribuindo para sua independência. Os sistemas de automação predial e residencial mais complexos elevam o nível de um ambiente automatizado para um ambiente inteligente, pois tornam o nível de abstração maior, fornecendo serviços de forma pervasiva. O ambiente inteligente necessita de informações para que possa oferecer seus serviços ao cadeirante, e uma informação importante seria a localização da cadeira de rodas automatizada. Neste contexto, este trabalho propõe um sistema de localização em interiores para cadeiras de rodas automatizadas em ambientes inteligentes. A proposta combina Redes de Sensores Sem Fio (RSSF) e a tecnologia RFID, onde as etiquetas RFID são utilizadas como marcos de referências para a calibração automática dos parâmetros da RSSF, que convencionalmente são obtidos de forma experimental. O estudo de caso para validar o sistema de localização proposto foi realizado numa sala automatizada no prédio da Engenharia Elétrica da Universidade Federal do Rio Grande do Sul (UFRGS) como ambiente inteligente, e uma cadeira de rodas automatizada adaptada para se comunicar com a RSSF. Além deste estudo de caso, foram realizados outros experimentos com intuito de avaliar qual método geraria os melhores resultados para o sistema de localização baseado em RSSF e a tecnologia RFID, combinando diferentes modelos de propagação de sinal RF e diferentes formas de calibrar os parâmetros da rede. Além disso, outras questões sobre o sistema de localização proposto foram analisadas, como por exemplo, a influência do aumento da quantidade de nós da rede na exatidão do sistema, o comportamento do sistema quando, para um mesmo cenário, o sentido do percurso é invertido, e a influência do leiaute dos nós da rede no desempenho do sistema. / In Brazil there are millions of people with some kind of limited mobility, and that most of these disabled people need a wheelchair to get around. With the fact that there are millions of wheelchair users, the development of assistive technologies, i.e. technologies to assist these people in their activities, has received increasing attention both from the standpoint of business (with the increase of products), as academic research. Among these lines of research, the integration of automated wheelchairs with home automation systems are among the research areas of greatest importance because it aims to make the user's life more productive and comfortable, contributing to their independence. The home automation systems more complex increase the level of an automated environment for intelligent environment, as they make the higher level of abstraction, providing pervasive services. The intelligent environment needs information so it can offer your services to the wheelchair user, and important information would be the location of the automated wheelchair. Within this context, this paper proposes an indoor positioning system for wheelchairs in intelligent environments. The proposal combines Wireless Sensor Networks (WSN) and RFID technology, where RFID tags are used as landmark for automatic calibration of the parameters of WSN, which are conventionally obtained experimentally. The case study to validate the proposed indoor positioning system was performed at an automated room in the building of Electrical Engineering, Universidade Federal do Rio Grande do Sul (UFRGS) with the intelligent environment and automated wheelchair adapted to communicate with the WSN. In addition to the case study, other experiments in order to assess which method would produce the best results for the localization system based on RFID and WSN, combining different radio propagation model and different forms of calibrate the parameters of the WSN. In addition, other questions about the proposed indoor positioning system were analyzed, for example, the influence of increasing the amount of network nodes on the system accuracy, the behavior of the system for the same scenario when the direction of travel is reversed, and the influence of the layout of the network nodes on the system performance.

No Brasil existem milhões de brasileiros com algum tipo de dificuldade de locomoção, sendo que grande parte dessas pessoas com deficiência necessita de cadeira de rodas para se locomover. Com o fato de existirem inúmeros de brasileiros cadeirantes, o desenvolvimento de tecnologias ditas ¨assistivas¨, ou seja, tecnologias que visam assistir estas pessoas em suas atividades, tem recebido uma crescente atenção, tanto do ponto de vista de negócios (com o aumento de produtos), como de pesquisas acadêmicas. Dentre estas linhas de pesquisa, a integração entre cadeiras de rodas automatizadas com sistemas de automação predial e residencial está entre as linhas de pesquisa de maior destaque, pois tem como objetivo tornar a vida do usuário de cadeira de rodas mais produtiva e cômoda, contribuindo para sua independência. Os sistemas de automação predial e residencial mais complexos elevam o nível de um ambiente automatizado para um ambiente inteligente, pois tornam o nível de abstração maior, fornecendo serviços de forma pervasiva. O ambiente inteligente necessita de informações para que possa oferecer seus serviços ao cadeirante, e uma informação importante seria a localização da cadeira de rodas automatizada. Neste contexto, este trabalho propõe um sistema de localização em interiores para cadeiras de rodas automatizadas em ambientes inteligentes. A proposta combina Redes de Sensores Sem Fio (RSSF) e a tecnologia RFID, onde as etiquetas RFID são utilizadas como marcos de referências para a calibração automática dos parâmetros da RSSF, que convencionalmente são obtidos de forma experimental. O estudo de caso para validar o sistema de localização proposto foi realizado numa sala automatizada no prédio da Engenharia Elétrica da Universidade Federal do Rio Grande do Sul (UFRGS) como ambiente inteligente, e uma cadeira de rodas automatizada adaptada para se comunicar com a RSSF. Além deste estudo de caso, foram realizados outros experimentos com intuito de avaliar qual método geraria os melhores resultados para o sistema de localização baseado em RSSF e a tecnologia RFID, combinando diferentes modelos de propagação de sinal RF e diferentes formas de calibrar os parâmetros da rede. Além disso, outras questões sobre o sistema de localização proposto foram analisadas, como por exemplo, a influência do aumento da quantidade de nós da rede na exatidão do sistema, o comportamento do sistema quando, para um mesmo cenário, o sentido do percurso é invertido, e a influência do leiaute dos nós da rede no desempenho do sistema. / In Brazil there are millions of people with some kind of limited mobility, and that most of these disabled people need a wheelchair to get around. With the fact that there are millions of wheelchair users, the development of assistive technologies, i.e. technologies to assist these people in their activities, has received increasing attention both from the standpoint of business (with the increase of products), as academic research. Among these lines of research, the integration of automated wheelchairs with home automation systems are among the research areas of greatest importance because it aims to make the user's life more productive and comfortable, contributing to their independence. The home automation systems more complex increase the level of an automated environment for intelligent environment, as they make the higher level of abstraction, providing pervasive services. The intelligent environment needs information so it can offer your services to the wheelchair user, and important information would be the location of the automated wheelchair. Within this context, this paper proposes an indoor positioning system for wheelchairs in intelligent environments. The proposal combines Wireless Sensor Networks (WSN) and RFID technology, where RFID tags are used as landmark for automatic calibration of the parameters of WSN, which are conventionally obtained experimentally. The case study to validate the proposed indoor positioning system was performed at an automated room in the building of Electrical Engineering, Universidade Federal do Rio Grande do Sul (UFRGS) with the intelligent environment and automated wheelchair adapted to communicate with the WSN. In addition to the case study, other experiments in order to assess which method would produce the best results for the localization system based on RFID and WSN, combining different radio propagation model and different forms of calibrate the parameters of the WSN. In addition, other questions about the proposed indoor positioning system were analyzed, for example, the influence of increasing the amount of network nodes on the system accuracy, the behavior of the system for the same scenario when the direction of travel is reversed, and the influence of the layout of the network nodes on the system performance.

Indoor Positioning Systems (IPS) using the existing WLAN have won growing interest in the last years, it can be a perfect supplement to provide location information of users in indoor environments where other positioning techniques such as GPS, are not much effective. The thesis manuscript proposes a new approach to define a WLAN-based indoor positioning system (WLAN-IPS) as a combinatorial optimization problem to guarantee the requested communication quality while optimizing the positioning error. This approach is characterised by several difficult issues we tackled in three steps.At first, we designed a WLAN-IPS and implemented it as a test framework. Using this framework, we looked at the system performance under various experimental constraints. Through these experiments, we went as far as possible in analysing the relationships between the positioning error and the external environmental factors. These relationships were considered as evaluation indicators of the positioning error. Secondly, we proposed a model that defines all major parameters met in the WLAN-IPS from the literature. As the original purpose of the WLAN infrastructures is to provide radio communication access, we introduced an additional purpose which is to minimize the location error within IPS context. Two main indicators were defined in order to evaluate the network Quality of Service (QoS) and the positioning error for Location-Based Service (LBS). Thirdly, after defining the mathematical formulation of the optimisation problem and the key performance indicators, we proposed a mono-objective algorithm and a multi-objective algorithm which are based on Tabu Search metaheuristic to provide good solutions within a reasonable amount of time. The simulations demonstrate that these two algorithms are highly efficient for the indoor positioning optimization problem.

<div>Over the past few decades, the focus of wireless communication technology has been shrinking in terms of coverage area. It started with WMAN (Wireless Metropolitan Area Network), moved to WLAN (Wireless Local Area Network) and WPAN (Wireless Personal Area Network), and is soon expected to move to WBAN (Wireless Body Area Network). Wireless positioning/location services present a perfect analogy to wireless communication services. It started with the use of GPS (Global Positioning System), is moving to Local Area Positioning System (LPS) and will be soon moving to Personal and Body Area Positioning Systems (BPS) in the future.</div><div><br></div>This thesis presents the development of a high-speed and high-accuracy wireless magnetic positioning system which can locate the position and orientation of the sensor in real-time with a sub-mm level accuracy in body area. The system consists of an antenna (transmitter) and one or multiple sensors (receivers). The sensor module consists of a tri-axis AC magnetic field sensor, an orientation sensor, a micro-controller and a communication unit. The system is robust to multi-path, low-power, low-cost and provides complete location privacy to its users. Possible implementations of this technology could be in the field of gaming, media entertainment, security, robotics, bio medical, motion-capture and home-automation. The ultra-low latency of the system and its ability to track the sensor anywhere around the antenna without occlusion makes it a perfect candidate to be used as a Virtual/Augment Reality (VR/AR) input device.

Traditional methods for locating books and resources in libraries often entail browsing catalogsor manual searching that are time-consuming and inefficient. This thesis investigates thepotential of automated digital services to streamline this process, by utilizing Wi-Fi signal datafor precise indoor localization. Central to this study is the development of a model that employsWi-Fi signal strength (RSSI) and round-trip time (RTT) to estimate the locations of library userswith arm-length accuracy. This thesis aims to enhance the accuracy of location estimation byexploring the complex, nonlinear relationship between Received Signal Strength Indicator(RSSI) and Round-Trip Time (RTT) within signal fingerprints. The model was developed usingan artificial neural network (ANN) to capture the relationship between RSSI and RTT. Besides,this thesis introduces and evaluates the performance of a novel variant of the Particle SwarmOptimization (PSO) algorithm, named Randomized Particle Swarm Optimization (RPSO). Byincorporating randomness into the conventional PSO framework, the RPSO algorithm aims toaddress the limitations of the standard PSO, potentially offering more accurate and reliablelocation estimations. The PSO algorithms, including RPSO, were integrated into the trainingprocess of ANN to optimize the network’s weights and biases through direct optimization, aswell as to enhance the hyperparameters of the ANN’s built-in optimizer. The findings suggestthat optimizing the hyperparameters yields better results than direct optimization of weights andbiases. However, RPSO did not significantly enhance the performance compared to thestandard PSO in this context, indicating the need for further investigation into its application andpotential benefits in complex optimization scenarios.

Location-based services (LBSs) have become pervasive, and the demand for these systems and services is rising. Indoor Positioning Systems (IPSs) are key to extend location-based services indoors where the Global Positioning System (GPS) is not reliable due to low signal strength and complicated signal propagation environment. Most existing IPSs either require the installation of special hardware devices or build a fingerprint map, which is expensive, time-consuming, and labor-intensive. Developments in microelectromechanical systems (MEMS) have resulted in significant advancements in the low-cost compact MARG inertial sensors, making it possible to achieve low-cost and high-accuracy IPSs. This research considers the indoor positioning problem and aims to design and develop an infrastructure-free self-contained indoor positioning and tracking system based on Pedestrian Dead Reckoning (PDR) using MEMS MARG inertial sensors. PDR-based systems rely on MARG inertial sensor measurements to estimate the current position of the object by using a previously determined position without external references. Many issues still exist in developing such systems, such as cumulative errors, high-frequency sensor noises, the gyro drift issue, magnetic distortions, etc. As the MARG sensors are inherently error-prone, the most significant challenge is how to design sensor fusion models and algorithms to accurately extract useful location-based information from individual motion and magnetic sensors. The objective of this thesis is to solve these issues and mitigate the challenges. The proposed positioning system is designed with four main modules at the system level and a dual-mode feature. Specifically, the four main modules are mode detection, step detection and moving distance estimation, heading and orientation estimation, and position estimation. To address the cumulative error issue of using low-cost inertial sensors, signal processing and sensor fusion techniques are utilized for algorithm design. Experimental evaluations show that the proposed position estimation algorithm is able to achieve high positioning accuracy at low costs for the indoor environment. / Thesis / Master of Applied Science (MASc) / With the maturity of microelectromechanical systems (MEMS) technology in recent years, Magnetic, Angular Rate, and Gravity (MARG) sensors are embedded in most smart devices. This research considers the indoor positioning problem and aims to design and develop an infrastructure-free self-contained MEMS MARG inertial sensor-based indoor positioning and tracking system with high precision. The proposed positioning system uses the Pedestrian Dead Reckoning (PDR) approach and includes four main modules at the system level with a dual-mode feature. Specifically, the four main modules are mode detection, step detection and moving distance estimation, heading and orientation estimation, and position estimation. The two modes are static mode and dynamic mode. To address the cumulative error issue of using low-cost inertial sensors, signal processing and sensor fusion techniques are utilized for algorithm design. The detection and estimation algorithms of each module are presented in the system design chapter. Experimental evaluations including trajectory results under five scenarios show that the proposed position estimation algorithm achieves a higher position accuracy than that of conventional estimation methods.

There is a high demand for Indoor Positioning Systems (IPS) due to the wide application possibilities. The main issue for localization by wireless signals in an indoor environment is the multipath propagation problem. Multipath propagation occurs when signals reflects and refract from an object, changing the signals characteristics. Today there is no IPS that can balance the cost, accuracy, and complexity. In January 2019 Bluetooth released a new standard, Bluetooth Low Energy (BLE) 5.1, which enables the ability to measure the Angle of Arrival (AoA) of an incoming signal. The purpose of this thesis is to mitigate the disturbances caused by multipath propagation by conducting a case study. This was done by designing systems that combine different positioning techniques with sensor fusion and evaluating them based on power efficiency, execution time and precision. Two wireless localization techniques were evaluated, trilateration and triangulation, which are based on Received Signal Strength Indication (RSSI) and AoA respectively, along with an Inertial Measurement Unit (IMU). An Extended Kalman Filter EKF was used to fuse the sensor data. The system with the best overall performance uses the AoA signals and a multipath mitigation technique. The system with AoA and IMU had a similar performance but has an overall higher complexity due to the added IMU component. The RSSI system could not satisfy the requirement of precision. / Det finns en stor efterfrågan på inomhus positionssystem (IPS) tack vare de många möjliga tillämpningarna. Det största problemet för inomhuslokalisering med trådlösa signaler i inomhusmiljö är flervägsutbredningsproblemet. Felvägsutbredning inträffar när signaler reflekterar och bryts på ett objekt, och ändrar dess karaktär. Idag finns det inga IPS som kan balansera kostnaden, noggrannhetoch komplexitet. I januari 2019, släppte Bluetooth en ny standard, Bluetooth Low Energy (BLE) 5.1, som gör det möjligt att mäta ankomstvinkeln (AoA) för en inkommande signal. Syftet med denna avhandling är att minska störningarna orsakade av flervägsutbredning genom att utföra en fallstudie. Detta gjordes genom att designa system som kombinerar olika positioneringstekniker med sensor fusion och utvärdera dessa med avseende på energieffektivitet, exekveringstid och precision. Två trådlösa lokaliseringstekniker utvärderades, trilaterering och triangulering, som är baserade på mottagen signalstyrka indikation RSSI och AoA respektive, tillsammans med en tröghetssensor (IMU). Ett Utökat Kalman-Filter (EKF) användes för att kombinera data. Systemet med den överlag bästa prestandan använder AoA-signaler och en teknik för att dämpa flervägsutredningen. Systemet med AoA och IMU hade liknande prestanda men den totala komplexiteten ökade med att lägga till en IMU komponent. RSSI systemet var inte tillräckligt tillfredsställande med avseende på precisionskraven.