This bachelor's thesis explores the integration of machine learning (ML) with sensor fusion techniques to enhance spatial data accuracy in Extended Reality (XR) environments. With XR's revolutionary impact across various sectors, accurate localization in virtual environments becomes imperative. The thesis conducts a comprehensive literature review, highlighting advancements in indoor positioning technologies and the pivotal role of machine learning in refining sensor fusion for precise localization. It underscores the challenges in the XR field, such as signal interference, device heterogeneity, and data processing complexities. Through critical analysis, this study aims to bridge the gap in practical application of ML, offering insights into developing scalable solutions for immersive virtual productions. It offers insights into the practical integration of advanced machine learning techniques in XR applications, thereby providing valuable implications for technology development and user experience in XR. This contribution is not merely theoretical; it showcases practical applications and advancements in real-time processing and adaptability in complex environments, aligning well with existing research and extending it by addressing scalability and practical implementation challenges in XR environments. This study identifies key themes in the integration of ML with sensor fusion for XR, such as the enhancement of spatial data accuracy, challenges in real-time processing, and the need for scalable solutions. It concludes that the fusion of ML and sensor technologies not only enhances the accuracy of XR environments but also paves the way for more immersive and realistic virtual experiences.

A crescente mobilidade de pessoas e recursos materiais exige um esforço constante na exploração das capacidades oferecidas pelas diferentes tecnologias disponíveis, que convergem para o fornecimento de informações e serviços em qualquer lugar com movimento, a qualquer tempo, e por meio de qualquer dispositivo, objetivos da rede mundial de cooperação e comunicação, conhecida como Internet. Em resposta a essa crescente demanda, a atual Internet está evoluindo do modelo de compartilhamento de informações para o modelo de contribuição e em um futuro próximo, para o modelo de colaboração entre provedores e consumidores, denominada de Internet do Futuro. Embora a atual Internet seja extraordinariamente bem sucedida, como um meio ubíquo de comunicação, sua atual arquitetura impõe limites para o provisionamento de serviços em ambientes heterogêneos e convergentes, demandando novas soluções que superem os desafios tecnológicos necessários ao estabelecimento da Internet do Futuro. Estas novas soluções basear-se-ão nos princípios da computação orientada a serviços, formando os componentes de um novo arcabouço de serviços para a Internet do Futuro, denominada de Internet de Serviços. Na Internet de Serviços, redes de comunicação móveis, convergentes e heterogêneas serão criadas sob demanda, disponibilizando um elevado número de serviços, funcionalmente similares, porém distintos sob o ponto de vista não funcional, dificultando a seleção dos serviços que melhor atendem o nível qualidade de serviço acordado entre provedores e consumidores. Este trabalho propõe uma nova solução para o problema de seleção de serviços, combinando algoritmos, usualmente empregados para prospecção de dados, para selecionar serviços de forma dinâmica e interativa, com base em atributos não funcionais, visando suprir as necessidades de mobilidade e colaboração em ambientes convergentes e heterogêneos, como a Internet de Serviços. Desta forma, este trabalho contribui para o projeto de pesquisa da Internet de Serviços, um dos pilares fundamentais para a elaboração da nova arquitetura orientada a serviços, que servirá de arcabouço à construção da Internet do Futuro, possibilitando inúmeras aplicações como Serviços Baseados em Localização e Computação em Nuvem. / The increasing mobility of people and resources demands additional efforts in exploring new capacities, offered by different technologies, which allows the supply of information and services in any place, any time and through any device, objective of the worldwide collaboration and communication web, known as Internet. Face to this increasing demand, current Internet is evolving from sharing to contribution model and in the near future, to collaboration model between providers and consumers. Although the current Internet has been extraordinarily successful, as a ubiquitous and universal means for communication, its architecture imposes limits for services deployment in heterogeneous and convergent environments, demanding new solutions to overcome the technological issues for Internet of Future achievement. These new solutions will be based on service oriented computing principles, providing the components of the new service framework for Internet of Future, called Internet of Services. In Internet of Services, convergent and heterogeneous mobile communication networks will be created on demand, providing a huge numbers of services, similar from functional point of view, but very different from the nonfunctional point of view, creating challenges for service selection which fits the service level agreement between providers and consumers. This work proposes a new solution for service selection process, combining algorithms commonly used for data mining, to perform dynamic and interactive service selection, fulfilling the mobility and collaborative requirements in a convergent and heterogeneous environment, such as Internet of Services. Therefore, this work contributes to Internet of Services research project, one of fundamental pillars to build the service oriented architecture, which will be used as framework for Internet of Future building, allowing many applications such as Location Based Services and Cloud Computing.

A crescente mobilidade de pessoas e recursos materiais exige um esforço constante na exploração das capacidades oferecidas pelas diferentes tecnologias disponíveis, que convergem para o fornecimento de informações e serviços em qualquer lugar com movimento, a qualquer tempo, e por meio de qualquer dispositivo, objetivos da rede mundial de cooperação e comunicação, conhecida como Internet. Em resposta a essa crescente demanda, a atual Internet está evoluindo do modelo de compartilhamento de informações para o modelo de contribuição e em um futuro próximo, para o modelo de colaboração entre provedores e consumidores, denominada de Internet do Futuro. Embora a atual Internet seja extraordinariamente bem sucedida, como um meio ubíquo de comunicação, sua atual arquitetura impõe limites para o provisionamento de serviços em ambientes heterogêneos e convergentes, demandando novas soluções que superem os desafios tecnológicos necessários ao estabelecimento da Internet do Futuro. Estas novas soluções basear-se-ão nos princípios da computação orientada a serviços, formando os componentes de um novo arcabouço de serviços para a Internet do Futuro, denominada de Internet de Serviços. Na Internet de Serviços, redes de comunicação móveis, convergentes e heterogêneas serão criadas sob demanda, disponibilizando um elevado número de serviços, funcionalmente similares, porém distintos sob o ponto de vista não funcional, dificultando a seleção dos serviços que melhor atendem o nível qualidade de serviço acordado entre provedores e consumidores. Este trabalho propõe uma nova solução para o problema de seleção de serviços, combinando algoritmos, usualmente empregados para prospecção de dados, para selecionar serviços de forma dinâmica e interativa, com base em atributos não funcionais, visando suprir as necessidades de mobilidade e colaboração em ambientes convergentes e heterogêneos, como a Internet de Serviços. Desta forma, este trabalho contribui para o projeto de pesquisa da Internet de Serviços, um dos pilares fundamentais para a elaboração da nova arquitetura orientada a serviços, que servirá de arcabouço à construção da Internet do Futuro, possibilitando inúmeras aplicações como Serviços Baseados em Localização e Computação em Nuvem. / The increasing mobility of people and resources demands additional efforts in exploring new capacities, offered by different technologies, which allows the supply of information and services in any place, any time and through any device, objective of the worldwide collaboration and communication web, known as Internet. Face to this increasing demand, current Internet is evolving from sharing to contribution model and in the near future, to collaboration model between providers and consumers. Although the current Internet has been extraordinarily successful, as a ubiquitous and universal means for communication, its architecture imposes limits for services deployment in heterogeneous and convergent environments, demanding new solutions to overcome the technological issues for Internet of Future achievement. These new solutions will be based on service oriented computing principles, providing the components of the new service framework for Internet of Future, called Internet of Services. In Internet of Services, convergent and heterogeneous mobile communication networks will be created on demand, providing a huge numbers of services, similar from functional point of view, but very different from the nonfunctional point of view, creating challenges for service selection which fits the service level agreement between providers and consumers. This work proposes a new solution for service selection process, combining algorithms commonly used for data mining, to perform dynamic and interactive service selection, fulfilling the mobility and collaborative requirements in a convergent and heterogeneous environment, such as Internet of Services. Therefore, this work contributes to Internet of Services research project, one of fundamental pillars to build the service oriented architecture, which will be used as framework for Internet of Future building, allowing many applications such as Location Based Services and Cloud Computing.

No description available.

Les réseaux corporels (WBAN) se réfère aux réseaux de capteurs (WSN) "portables" utilisés pour collecter des données personnelles, telles que la fréquence cardiaque ou l'activité humaine. Cette thèse a pour objectif de proposer des algorithmes coopératifs (PHY/MAC) pour effectuer des applications de localisation, tels que la capture de mouvement et la navigation de groupe. Pour cela, nous exploitons les avantages du WBAN avec différentes topologies et différents types de liens: on-body à l'échelle du corps, body-to-body entre les utilisateurs et off-body par rapport à l'infrastructure. La transmission repose sur une radio impulsionnelle (IR-UWB), afin d'obtenir des mesures de distance précises, basées sur l’estimation du temps d'arrivée (TOA). Ainsi, on s’intéresse au problème du positionnement à travers de la conception de stratégies coopératives et en considérant la mobilité du corps et les variations canal. Notre première contribution consiste en la création d'une base de données obtenue avec de scénarios réalistes pour la modélisation de la mobilité et du canal. Ensuite, nous introduisons un simulateur capable d'exploiter nos mesures pour la conception de protocoles. Grâce à ces outils, nous étudions d’abord l'impact de la mobilité et des variations de canal sur l'estimation de la distance avec le protocole "three way-ranging" (3-WR). Ainsi, nous quantifions et comparons l'erreur avec des modèles statistiques. Dans un second temps, nous analysons différentes algorithmes de gestion de ressources pour réduire l'impact de la mobilité sur l'estimation de position. Ensuite, nous proposons une optimisation avec un filtre de Kalman étendu (EKF) pour réduire l'erreur. Enfin, nous proposons un algorithme coopératif basé sur l'analyse d’estimateurs de qualité de lien (LQEs) pour améliorer la fiabilité. Pour cela, nous évaluons le taux de succès de positionnement en utilisant trois modèles de canaux (empirique, simulé et expérimental) avec un algorithme (basé sur la théorie des jeux) pour le choix des ancres virtuelles. / Wireless Body Area Networks (WBAN) refers to the family of “wearable” wireless sensor networks (WSN) used to collect personal data, such as human activity, heart rate, sleep sequences or geographical position. This thesis aims at proposing cooperative algorithms and cross-layer mechanisms with WBAN to perform large-scale individual motion capture and coordinated group navigation applications. For this purpose, we exploit the advantages of jointly cooperative and heterogeneous WBAN under full/half-mesh topologies for localization purposes, from on-body links at the body scale, body-to-body links between mobile users of a group and off-body links with respect to the environment and the infrastructure. The wireless transmission relies on an impulse radio Ultra-Wideband (IR-UWB) radio (based on the IEEE 802.15.6 standard), in order to obtain accurate peer-to-peer ranging measurements based on Time of Arrival (ToA) estimates. Thus, we address the problem of positioning and ranging estimation through the design of cross-layer strategies by considering realistic body mobility and channel variations. Our first contribution consists in the creation of an unprecedented WBAN measurement database obtained with real experimental scenarios for mobility and channel modelling. Then, we introduce a discrete-event (WSNet) and deterministic (PyLayers) co-simulator tool able to exploit our measurement database to help us on the design and validation of cooperative algorithms. Using these tools, we investigate the impact of nodes mobility and channel variations on the ranging estimation. In particular, we study the “three-way ranging” (3-WR) protocol and we observed that the delays of 3-WR packets have an impact on the distances estimated in function of the speed of nodes. Then, we quantify and compare the error with statistical models and we show that the error generated by the channel is bigger than the mobility error. In a second time, we extend our study for the position estimation. Thus, we analyze different strategies at MAC layer through scheduling and slot allocation algorithms to reduce the impact of mobility. Then, we propose to optimize our positioning algorithm with an extended Kalman filter (EKF), by using our scheduling strategies and the statistical models of mobility and channel errors. Finally, we propose a distributed-cooperative algorithm based on the analysis of long-term and short-term link quality estimators (LQEs) to improve the reliability of positioning. To do so, we evaluate the positioning success rate under three different channel models (empirical, simulated and experimental) along with a conditional algorithm (based on game theory) for virtual anchor choice. We show that our algorithm improve the number of positions estimated for the nodes with the worst localization performance.

Indiana University-Purdue University Indianapolis (IUPUI) / Pedestrian and vehicle interaction analysis in a naturalistic driving environment can provide useful information for designing vehicle-pedestrian crash warning/mitigation systems. Many researchers have used crash data to understand and study pedestrian behaviors and interactions between vehicles and pedestrian during crash. However, crash data may not provide detailed pedestrian-vehicle interaction information for us. In this thesis, we designed an automatic pedestrian tracking and status analysis method to process and study pedestrian and vehicle interactions. The proposed pedestrian tracking and status analysis method includes pedestrian detection, pedestrian tracking and pedestrian status analysis modules. The main contributions of this thesis are: we designed a new pedestrian tracking method by learning the pedestrian appearance and also their motion pattern. We designed a pedestrian status estimation method by using our tracking results and thus helped estimate the possibility of collision. Our preliminary experiment results using naturalistic driving data showed promising results.

Der Paradigmenwechsel zur Entwicklungsmethodik innerhalb verteilter Kommunikationssysteme schlägt sich auch in der Telematik zum Anwendungspotential und Systemkomplexität nieder. Dies liefert eine neue Auffasung dessen, was den transparenten Datenkanal ausmacht.

Der Paradigmenwechsel zur Entwicklungsmethodik innerhalb verteilter Kommunikationssysteme schlägt sich auch in der Telematik zum Anwendungspotential und Systemkomplexität nieder. Dies liefert eine neue Auffasung dessen, was den transparenten Datenkanal ausmacht.