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 is an enabling technology primed to impact the indoor application space as Global Navigation Satellite Systems (GNSS) did for the outdoor space. Amongst the competing positioning technologies are methods of different mediums: light, radio frequency and ultra-wideband, ultrasonic, and imaging; methods of different modalities: received signal strength, angle-of-arrival, time-of-flight; and methods of different mathematics: trilateration, triangulation, machine learning, and signal processing. Light-based positioning compared to other positioning schemes exploits fixed-location directional luminaires placed regularly throughout a space as anchor points -- there is an efficiency argument for multi-purpose lighting and a cost-share argument for infrastructure-based positioning. Similar to the satellite infrastructure with GNSS, with anchor points and models for light propagation and construction, position is estimated based on received signals at active photodiode-equipped target devices. Received signal strength, a common first order attribute, alone is not noise resilient enough for centimeter-level 3D positioning. Methods using angle diversity produce better results particularly in 3D but with more complex hardware. For this dissertation, we exploit angle diversity and modulated optical sources in light-based positioning systems to estimate position to centimeter-level accuracy in 3D. We propose, analyze, and contribute two novel positioning schemes that use these concepts. One of the proposed schemes is a new hybrid 3D indoor positioning technique, Ray-Surface Positioning (RSP), which incorporates a narrow field-of-view (FOV) optical source (Ray) with wide diffuse optical sources (Surfaces) to position active devices in 3D. The second scheme, a Zone-based Positioning Service (ZPS), is a positioning scheme and architecture that incorporates an angle diverse narrow FOV optical source at the positioned device. This unique design decision allows the active device to position itself directly with respect to photovoltaic anchor points but also to position other devices in its FOV called transitive positioning. Along with these contributions, we also investigate several other related topics. Concisely, as part of the dissertation, we contribute (a) review of the state-of-the-art, (b) analysis for steering Lambertian sources, (c) method of creating angle diversity from a narrow FOV optical source, (d) novel positioning approaches in (1) RSP and (2) ZPS, (e) proof of concept prototypes for (1) RSP and (2) ZPS, and (f) architectures for indoor positioning applications.

Under det senaste decenniet har inomhuspositionering fått en ökad popularitet och stått i fokus för forskning och utveckling, eftersom det ger praktiska möjligheter till att spåra och navigera objekt och människor i inomhusmiljöer. Det finns ingen global lösning för inomhuspositionering baserat på en enstaka teknologi såsom det gör för utomhuspositionering med sin satellitbaserade globala positioneringssystem. Många inomhusteknologier står inför många utmaningar såsom låg positioneringsnoggrannhet samt dyr och stor hårdvara. Den här uppsatsen beskriver hur en simpel och kostnadseffektiv lösning, som addresserar problemen med noggrannheten och hårdvarukostnaden, genom en iterativ forskningsmetod, utvecklades. Vår lösning är ett ultraljudsbaserat passivt sändare-mottagare system som kombinerar multilateration som positioneringsteknik och tidsskillnad av ankomst (TDOA) som mätprincip för att beräkna en 3D-position inuti en 4x2x2 m testyta med en övergripande noggrannhet på 16 cm inom ett 95% konfidensintervall. Vi registrerade noggranna TDOA-värden med en komparatorkrets som fungerade som en amplitud-trigger. Det här tillvägagångssättet var mycket enklare än vad andra relaterade arbeten använde sig av, vilket var sampling för att bearbeta inkommande signaler från sändarna. / During the past decade, indoor positioning has gained more popularity and has become a focus of research and development as it provides practical possibilities to track and navigate objects and people in indoor environments. There is no overall solution for indoor positioning based on a single technology like the solution for outdoor positioning with its satellite-based global positioning system. Many indoor positioning technologies today face many challenges such as low positioning accuracy, expensive and large hardware. This thesis describes how a simple and cost-effective solution, that addresses the problem of accuracy and space cost with regards to hardware being used, was developed through an iterative research methodology. Our solution is an ultrasound-based passive receiver-transmitter system that combines multilateration as a positioning technique and time difference of arrival (TDOA) as a measuring principle. This combination is used to calculate a 3D position within a 4x2x2 m test area with an overall accuracy of 16 cm within a 95% confidence interval. We registered accurate TDOA values with a comparator circuit that acts as an amplitude trigger. This approach was much more simple than that of other related works which used sampling to process incoming signals from the transmitters.

Three-dimensional visualization refers to the process by which graphical content is created using the Three-dimensional software. While working with Threedimensional visualization, different indoor positioning techniques can be used to detect and track the movement of objects. Combining these two technologies provide the ability to monitor a room and its objects in real time. Positioning is the process of recording the movement of objects or people. Positioning techniques can be used in many different areas such as emergent situations and tracking objects with potential risks as an aid. It is not self-evident how well this kind of a system would work in the given contexts. To address this, the method has consisted of a literature study focused on existing theories of positioning and different factors that affect the positioning outcome and a case study on positioning systems in a number of existing indoor positioning systems. The purpose of this project is to present and evaluate a prototype where an indoor positioning system will be combined with a specific platform which works with simple types of hardware signals to generate three-dimensional models. The goal is to present a system that will have the ability to be used without any infrastructure or external hardware. Different indoor positioning systems will be analyzed as well as their use in various scenarios. This thesis evaluates various technical choices, and provides an overview of some of the existing wireless indoor positioning solutions and the theory and methods used, before describing the case study, including the development process, problems faced, the result, and the experimental testing results. In conclusion, the thesis presents a prototype which is validated to fulfill the basic expectation of a three-dimensional visualized indoor positioning system. / Tredimensionell visualisering refererar till processen genom vilken grafisk innehåll skapas med hjälp av tredimensionell programvara. Under arbetet med tredimensionell visualisering kan olika inomhus positioneringstekniker användas för att upptäcka och spåra rörelser av object. Kombinationen av dessa två tekniker ger möjlighet att övervaka ett rum och dess föremål i realtid. Positionering är processen att spela in rörelser av objekt eller personer. Positionering kan användas i många olika områden såsom nödsituationer och spårning av föremål eller brandmän i enbyggnad som brinner eller detektering av polishundar som är utbildade för att hitta sprängämnen i en byggnad. Det är inte självklart hur bra ett sådant system skulle fungera i de givna sammanhangen. För att ta itu med detta, har metoden bestått av en litteraturstudie inriktat på befintliga teorier om positionering, olika faktorer som påverkar positionerings resultatet samt en fallstudie om positioneringssystem i ett antal befintliga inomhus positioneringssystem. Syftet med detta projekt är att presentera och utvärdera en prototyp där ett inomhuspositioneringssystem kombineras med en specifik plattform som arbetar med enkla typer av hårdvaru signaler för att generera tredimensionella modeller. Målet är att presentera ett system som kommer kunna användas utan någon infrastruktur eller extern hårdvara. Olika inomhus positioneringssystem kommer att analyserar såväl som deras användning i olika scenarier. Denna avhandling utvärderar olika tekniska val och ger en översikt över några av de befintliga trådlösa inomhuspositioneringlösningarna och ger teorin och metoderna, innan fallstudien beskrivs, inklusive: utvecklingsprocessen, problem, resultat och experimentella testresultat. Sammanfattningsvis presenterar avhandlingen en prototyp som valideras för att uppfylla de grundläggande förväntningarna för ett tredimensionellt visualiserat inomhus positioneringssystem.

Teknologier som beacons och sensor noder för att exakt ta ut en inomhusposition har funnits i över ett decennium. Men kunskap om denna teknologi är inte vitt spridd. Denna studien har som mål att designa ett sätt att använda inomhuspositionering för företag med öppen arbetsplats, med hjälp av metoder som är kopplat till användarvänlighet tillsammans med tillgänglig teknik. Denna studien utfördes vid Apegroup, ett företag som har en öppen arbetsplats där deras anställda kan ändra på sin plats utöver dagen. Studien startade med en enkät som uppföljdes prototyper som testades med semi- strukturerade intervjuer med fokus på uppgifter att utföra under testerna. Under dessa samlades det information från testarna om deras önskemål och nödvändigheter kring ett sånt här system samt deras tankar kring personlig integritet och att bli positionerad. Resultatet av den här studien visade att de som svarade på enkäten hade några problem som handlade om öppna arbetsytor, mestadels när det kom till att boka rum samt att hitta kollegor. När dom blev presenterade en möjlig lösning att kontra dessa problem, så var testarna enhetliga om att dom skulle använda ett sådant system om det fanns idag. Angående integriteten, testarna hade inga problem med att visa deras position till andra inom företaget så länge denna informationen inte användes negativt. / Today, technology like beacons and sensor nodes for an accurate indoor positioning system has been around for near over a decade. However, this technology is not widely known. This study aims to design a way to make indoor positioning available to companies with open workspaces, using methods tied to user experience together available technology. This study was conducted at Apegroup, a company that has an open workspace where the employees can change their place throughout the day. The study started with a survey followed by prototypes with task-based think aloud semi-structured interviews. Gathering information from the participants on their wants and needs for a system like this as well as their thoughts on personal integrity in regards to being positioned. The results of this study conclude that the respondents of the survey did have issues when it came to the open workspace environment, mainly booking meeting rooms and finding colleagues. When presented a possible way to encounter these issues, the participants were unanimous that they would use a system like this if they were provided with it today. Regarding integrity, the participants did not have any issues presenting their location to others within the company as long as it was not used to monitor negatively.

Blind and visually impaired (BVI) users desire an indoor navigation tool that is inexpensive, convenient, and reliable. The purpose of this thesis is to examine the feasibility of using a smartphone as a platform for such a navigation tool. A good navigation tool should have both a good positioning accuracy and a user-friendly interface. Thus, one focus of this thesis is to improve the performance of an indoor positioning systems running on smartphones, as compared to existing systems. Another focus is to customize this indoor positioning system specifically for BVI users.  The proposed indoor positioning system is based upon Bluetooth Low Energy (BLE). It consists of two parts: BLE beacons deployed in the user’s environment and an Android phone which calculates its position and provides navigation assistance by audio and vibration. Two versions of the positioning software were developed based on different algorithms. One version uses a hybrid technique combining triangulation and fingerprinting. This version achieves a positioning accuracy of 1.83 meter, and volunteers (blind-folded sighted people) took on average 91.7 seconds to complete a complex 12-meter route. The other version uses a proximity algorithm, thus it does not give as accurate positioning results. With this algorithm, a blind user was able to finish a route of 115 meters consisting of two different floors in a building including entering/exiting an elevator and multiple office doors in 4 minutes 48 seconds. The blind user found the product to be helpful and user-friendly. Finally, we draw the conclusion that a smartphone can be a good platform for a BVI navigation tool, under the condition that the algorithm is proximity based and navigation utilizes a priori information about the environment. Another insight we gained is that we should put beacons on braille signs so that blind people can find them by using the navigation app. / Blinda och synskadade (BVI) användare önskar sej ett inomhus navigeringsverktyg som är billigt, bekvämt och pålitligt. Syftet med detta examensarbete var att undersöka möjligheten att med en smartphone och utplacerade fyrar/beacons ge en bra plattform för en inomhus navigeringsmetod. Ett bra navigationsverktyg bör ha både en bra positioneringsnoggrannhet och ett användarvänligt gränssnitt. Således är ett fokus för detta arbete att förbättra prestanda för på ett inomhus positioneringssystem som körs på smartphones, jämfört med andra befintliga system. Ett annat fokus är att anpassa denna inomhus positioneringssystem för speciella BVI användare. Det vidare utvecklade inomhuspositionering systemet bygger på Bluetooth Low Energy (BLE). Den består av två delar: BLE fyrar/beacons utplacerade i kontorsmiljön och en smartphone som beräknar sin position och ger navigeringshjälp av ljud/röst och vibrationer. Vi utformade två versioner av positionerings programvaran med olika algoritmer. En version använder en hybridteknik med triangulering och en med fingerprints. Det uppnår en positioneringsnoggrannhet som är <1,83 meter och den testades på tolv seende personer med bindel för ögonen. Det tog vid testet 91.7 sekunder i genomsnitt att utföra en komplex 12 meter lång bana. Den andra versionen använder en närhets-algoritm som inte ger ett specifikt positioneringsresultat. Med denna algoritm kunde en blind användare avsluta en rutt 115 meter bestående av två olika våningar från ingång i golvplanet samt ta en hiss och gå in på ett kontor och genom hela kontoret på 4 minuter och 48 sekunder. Den blinda användaren ansåg att navigeringsverktyget var både användbart och användarvänligt. Slutligen, drar vi slutsatsen att en smartphone kan vara en bra plattform för ett BVI navigeringsverktyg och då under förutsättning att algoritmen tar med närhet/position och inomhusmiljöinformation för att ge bästa möjliga användbarthet. En annan insikt vi fått är att vi ska lägga fyrar på punktskrift tecken så att blinda kan hitta dem med hjälp av navigering app.

This doctoral thesis presents a comprehensive exploration of ultrawideband technology in addressing diverse challenges within localization systems. Beginning with the development of an innovative, cost-effective, and anonymous contact tracing solution for industrial environments during the COVID-19 pandemic, the research integrates ultra-wideband positioning, Bluetooth low-energy, and inertial measurement units. The subsequent sections delve into relative positioning systems, device-free localization, UWB bistatic radar sensors, and UAV-based tracking, showcasing novel methodologies and hardware implementations with promising outcomes. The work extends to groundbreaking approaches in deploying UWB infrastructure through self-deployable robots and cooperative positioning schemes using a UAV swarm. The contributions highlight versatility, costeffectiveness, and scalability, opening new possibilities for applications in security, logistics, IoT services, and space exploration. In summary, this thesis represents a significant advancement in localization systems, offering practical solutions and paving the way for future research and applications

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.

Grâce à l’émergence dans la vie quotidienne des appareils de plus en plus populaires que sont les smartphones et les tablettes, la tâche de postionner l'utilisateur par le biais de son téléphone est une problématique fortement étudiée dans les domaines non seulement de la recherche mais également des communautés industrielles. Parmi ces technologies, les approches GPS sont devenues une norme et ont beaucoup de succès pour une localisation en environnement extérieur. Par contre, le Wi-Fi, les capteurs inertiels et le Bluetooth sont plutôt préférés pour les tâches de positionnement dans un environnement intérieur.Pour ce qui concerne le positionnement des smartphones, les approches basées sur les « empreintes digitales » (fingerprint) Wi-Fi sont bien établies. D'une manière générale, ces approches tentent d'apprendre la fonction de correspondance (cartographie) des caractéristiques du signal Wi-Fi par rapport à la position de l’appareil dans le monde réel. Elles nécessitent généralement une grande quantité de données pour obtenir une bonne cartographie. Lorsque ces données d'entraînement disponibles sont limitées, l'approche basée sur les empreintes digitales montre alors des taux d’erreurs élevés et devient moins stable. Dans nos travaux, nous explorons d’autres approches, différentes, pour faire face à cette problématique du manque de données d'entraînement. Toutes ces méthodes sont testées sur un ensemble de données public qui est utilisé lors d’une compétition internationale à la Conférence IPIN 2016.En plus du système de positionnement basé sur la technologie Wi-Fi, les capteurs inertiels du smartphone sont également utiles pour la tâche de suivi. Les trois types de capteurs, qui sont les accéléromètres, le gyroscope et la boussole magnétique, peuvent être utilisés pour suivre l'étape et la direction de l'utilisateur (méthode SHS). Le nombre d'étapes et la distance de déplacement de l'utilisateur sont calculés en utilisant les données de l'accéléromètre. La position de l'utilisateur est calculée par trois types de données avec trois méthodes comprenant la matrice de rotation, le filtre complémentaire et le filtre de Madgwick. Il est raisonnable de combiner les sorties SHS avec les sorties de Wi-Fi, car les deux technologies sont présentes dans les smartphones et se complètent. Deux approches combinées sont testées. La première approche consiste à utiliser directement les sorties Wi-Fi comme points de pivot pour la fixation de la partie de suivi SHS. Dans la deuxième approche, nous comptons sur le signal Wi-Fi pour construire un modèle d'observation, qui est ensuite intégré à l'étape d'approximation du filtre à particules. Ces combinaisons montrent une amélioration significative par rapport au suivi SHS ou au suivi Wi-Fi uniquement.Dans un contexte multiutilisateur, la technologie Bluetooth du smartphone pourrait fournir une distance approximative entre les utilisateurs. La distance relative est calculée à partir du processus de numérisation du périphérique Bluetooth. Elle est ensuite utilisée pour améliorer la sortie des modèles de positionnement Wi-Fi. Nous étudions deux méthodes. La première vise à créer une fonction d'erreur qui permet de modéliser le bruit dans la sortie Wi-Fi et la distance approximative produite par le Bluetooth pour chaque intervalle de temps spécifié. La seconde méthode considère par contre cette relation temporelle et la contrainte de mouvement lorsque l'utilisateur se déplace. Le modèle d'observation du filtre à particules est une combinaison entre les données Wi-Fi et les données Bluetooth. Les deux approches sont testées en fonction de données réelles, qui incluent jusqu'à quatre utilisateurs différents qui se déplacent dans un bureau. Alors que la première approche n'est applicable que dans certains scénarios spécifiques, la deuxième approche montre une amélioration significative par rapport aux résultats de position basés uniquement sur le modèle d'empreintes digitales Wi-Fi. / With the popularity of smartphones and tablets in daily life, the task of finding user’s position through their phone gains much attention from both the research and industry communities. Technologies integrated in smartphones such as GPS, Wi-Fi, Bluetooth and camera are all capable for building a positioning system. Among those technologies, GPS has approaches have become a standard and achieved much success for the outdoor environment. Meanwhile, Wi-Fi, inertial sensors and Bluetooth are more preferred for positioning task in indoor environment.For smartphone positioning, Wi-Fi fingerprinting based approaches are well established within the field. Generally speaking, the approaches attempt to learn the mapping function from Wi-Fi signal characteristics to the real world position. They usually require a good amount of data for finding a good mapping. When the available training data is limited, the fingerprinting-based approach has high errors and becomes less stable. In our works, we want to explore different approaches of Wi-Fi fingerprinting methods for dealing with a lacking in training data. Based on the performance of the individual approaches, several ensemble strategies are proposed to improve the overall positioning performance. All the proposed methods are tested against a published dataset, which is used as the competition data of the IPIN 2016 Conference with offsite track (track 3).Besides the positioning system based on Wi-Fi technology, the smartphone’s inertial sensors are also useful for the tracking task. The three types of sensors, which are accelerate, gyroscope and magnetic, can be employed to create a Step-And-Heading (SHS) system. Several methods are tested in our approaches. The number of steps and user’s moving distance are calculated from the accelerometer data. The user’s heading is calculated from the three types of data with three methods, including rotation matrix, Complimentary Filter and Madgwick Filter. It is reasonable to combine SHS outputs with the outputs from Wi-Fi due to both technologies are present in the smartphone. Two combination approaches are tested. The first approach is to use directly the Wi-Fi outputs as pivot points for fixing the SHS tracking part. In the second approach, we rely on the Wi-Fi signal to build an observation model, which is then integrated into the particle filter approximation step. The combining paths have a significant improvement from the SHS tracking only and the Wi-Fi only. Although, SHS tracking with Wi-Fi fingerprinting improvement achieves promising results, it has a number of limitations such as requiring additional sensors calibration efforts and restriction on smartphone handling positions.In the context of multiple users, Bluetooth technology on the smartphone could provide the approximated distance between users. The relative distance is calculated from the Bluetooth inquiry process. It is then used to improve the output from Wi-Fi positioning models. We study two different combination methods. The first method aims to build an error function which is possible to model the noise in the Wi-Fi output and Bluetooth approximated distance for each specific time interval. It ignores the temporal relationship between successive Wi-Fi outputs. Position adjustments are then computed by minimizing the error function. The second method considers the temporal relationship and the movement constraint when the user moves around the area. The tracking step are carried out by using particle filter. The observation model of the particle filter are a combination between the Wi-Fi data and Bluetooth data. Both approaches are tested against real data, which include up to four different users moving in an office environment. While the first approach is only applicable in some specific scenarios, the second approach has a significant improvement from the position output based on Wi-Fi fingerprinting model only.

Indoor positioning is desired in many areas for various reasons, such as positioning products in industrial environments, hospital equipment or firefighters inside a building on fire. One even tougher situation where indoor positioning can be useful is locating a specific object on a shelf in a commercial setting. This thesis aims to investigate and design different network deployment strategies in an indoor environment in order to achieve both high position estimation accuracy and availability. The investigation considers the two positioning techniques downlink time difference of arrival, DL-TDOA, and round trip time, RTT. Simulations of several deployments are performed in two standard scenarios which mimic an indoor open office and an indoor factory, respectively. Factors having an impact on the positioning accuracy and availability are found to be deployment geometry, number of base stations, line-of-sight conditions and interference, with the most important being deployment geometry. Two deployment strategies are designed with the goal of optimising the deployment geometry. In order to achieve both high positioning accuracy and availability in a simple, sparsely cluttered environment, the strategy is to deploy the base stations evenly around the edges of the deployment area. In a more problematic, densely cluttered environment the approach somewhat differs. The proposed strategy is now to identify and strategically place some base stations in the most cluttered areas but still place a majority of the base stations around the edges of the deployment area. A robust positioning algorithm is able to handle interference well and to decrease its impact on the positioning accuracy. The cost, in terms of frequency resources, of using more orthogonal signals may not be worth the small improvement in accuracy and availability.