Abstract During the last decades significant changes in the buying behavior of customers can be observed. While in former days price sensitivity lead to more uniformed products, in present days manifold high-quality products and customization with reasonable prices and rapid delivery are demanded. As a consequence, the industry asks for manufacturing systems which allow for fast ramp-up, multi-variant production and rapid adaptability. In this environment, several scientific approaches such as agent-based and holonic manufacturing systems have been investigated within the last years. In order to cover all aspects of the foreseen future demands, the architectures for such systems are very complex and the system’s entities are characterized by very flexible behavior. Hence, the efforts for their implementation are rather high and the systems tend to exhibit non-deterministic behavior. Furthermore, the top down approach of most systems leads to a complete re-organization of the factory management. As a consequence the acceptance for such systems in real industrial environment at present day is very limited. Therefore, the objective of this thesis is to develop an architecture for flexible manufacturing systems which allows for easy take-up in the industry. It is based on a bottom-up approach with a new kind of flexible, intelligent shop-floor components called Manufactrons. The architecture covers all layers of traditional factory organization with special emphasis on the shop floor organization. The approach and results are based on the research activities of the European Research Project XPRESS in which representatives of three major industry branches collaborated in order to find a solution for their future demands on flexible manufacturing systems. The architecture has been implemented in the context of XPRESS in aerospace, automotive and electrical industry. The tests show the feasibility of the approach. The capability for a smooth integration of the new approach into existing manufacturing environment has successfully been demonstrated. / Tiivistelmä Viime vuosikymmeninä asiakkaiden ostokäyttäytyminen on muuttunut merkittävästi. Ennen asiakkaiden hintatietoisuus johti yhtenäisiin tuotteisiin, kun taas nykyään vaaditaan moninaisempia tuotteita ja muokattavuutta kohtuulliseen hintaan. Samaan aikaan odotetaan korkealaatuisia tuotteita ja nopeaa toimitusta. Nämä seikat ovat aiheuttaneet tuotantoteollisuudelle uusia haasteita. Reagoidakseen nopeasti asiakkaiden vaatimuksiin tuotannonsuunnittelussa on alettu keskittymään korkealaatuisten tuotemuunnelmien määrän kasvattamiseen. Tämän vuoksi tarvitaan tuotantojärjestelmiä, jotka mahdollistavat nopean Ramp Up -prosessin, moneenmuuntuvan tuotannon ja nopean mukautuvuuden. Tätä aihetta on viime vuosina lähestytty esimerkiksi agentteihin perustuvien ja holonisten tuotantojärjestelmien kautta. Kuitenkin näihin tulevaisuuden haasteisiin pystytään vastaamaan vain kompleksisilla arkkitehtuureilla ja järjestelmän entiteeteille ominaisia ovat hyvin mukautuvat käyttäytymismallit. Näiden toteuttamiseen tarvitaan paljon työtä ja järjestelmillä on tapana käyttäytyä epä-deterministisesti. Lisäksi ylhäältä alas lähestymistapa johtaa usein tehtaan täydelliseen uudelleenorganisointiin, minkä vuoksi lähestymistapaa ei suosita oikeissa teollisuusympäristöissä. Tämän väitöstyön tarkoituksena on kehittää mukautuville tuotantojärjestelmille arkkitehtuuri, joka mahdollistaa järjestelmien helpon käyttöönoton teollisuudessa. Arkkitehtuuri perustuu alhaalta ylös -lähestymistapaan ja sisältää uudenlaisen joustavan ja älykkään tuotantotilakomponentin, manufactronin. Arkkitehtuuri kattaa kaikki perinteisen tehdasorganisaation kerrokset keskittyen kuitenkin erityisesti tuotantotilojen organisointiin. Lähestymistapa ja tulokset perustuvat Euroopan Unionin XPRESS-tutkimusprojektiin. Projektissa tehtiin yhteistyötä kolmen suuren teollisuushaaran kanssa tarkoituksena löytää joustava tuotantojärjestelmäratkaisu tulevaisuutta varten. Arkkitehtuuria sovellettiin XPRESS-projektissa lentokone-, auto- ja elektoniikkateollisuuteen ja testit osoittivat lähestymistavan soveltuvuuden. Myös lähestymistavan sujuva integrointi olemassa oleviin teollisuusjärjestelmiin osoitettiin onnistuneesti.

Um ambiente inteligente é um sistema de computação ubíqua e sensível ao contexto onde os sistemas computacionais embutidos no ambiente, a comunicação entre dispositivos e o ambiente, e a acessibilidade aos serviços do ambiente são transparentes ao usuário. O presente trabalho tem como objetivo propor um modelo para ambientes inteligentes baseado em serviços web semânticos, em que os serviços disponíveis para os dispositivos do ambiente são proporcionados como serviços web e a interação dispositivo - ambiente é feita em um contexto de computação móvel, onde a disponibilidade dos serviços e a informação de contexto do dispositivo mudam freqüentemente. No modelo proposto todas as funcionalidades do ambiente são fornecidas como serviços. Estes serviços são descobertos e executados automaticamente com a finalidade de ajudar o usuário a desenvolver tarefas específicas, permitindo ao usuário se concentrar nas tarefas e não na interação com o ambiente. O modelo se fundamenta na oferta de serviços dirigida pela tarefa a ser desenvolvida, o que é conhecido como Task-driven Computing. Por outro lado, para a automação do processo de descoberta e execução dos serviços é necessário ter uma especificação não ambígua da semântica dos serviços. Empregamos para isso a ontologia WSMO (Web Services Modeling Ontology) que fornece os elementos necessários para a descrição dos serviços disponíveis no ambiente e o contexto do dispositivo. Finalmente, como prova de conceitos do modelo proposto, foi implementado um ambiente inteligente para uma biblioteca. A ativação de um ambiente inteligente baseado no modelo proposto se baseia na definição de ontologias, descrição semântica dos serviços no ambiente e a implementação de serviços web tradicionais. / A smart environment is a system computing ubiquitous computing and context awareness, in which the computational systems embedded in the environment, the communication between devices and the environment, and the accessibility to services are transparent to the users. The aim of this work is to propose a semantic web services based model for smart environments, in which services are offered to devices as web services and the device - environment interactions are based on a mobile computing environment, in which the contextual information and availability of services change frequently. In the proposed model all functionalities in the environment are offered as services. These services are automatically discovered and executed to support the user in a specific task, allowing to the user to focus on his task and not in the interactions with the environment. The model is based on a task-driven offer of services and on task-driven computing. To automate the discovery and execution of services, we need a nonambiguous specification of the semantic of services. We use the WSMO ontology (Web Services Modeling Ontology), which provides the required elements for description of the services in the environment and the context device. Finally, as a conceptual proof of the proposed model, we implemented a smart environment for a library. In the proposed model the activation of a smart environment is based in the ontologies definition, semantic description of the services.

Um ambiente inteligente é um sistema de computação ubíqua e sensível ao contexto onde os sistemas computacionais embutidos no ambiente, a comunicação entre dispositivos e o ambiente, e a acessibilidade aos serviços do ambiente são transparentes ao usuário. O presente trabalho tem como objetivo propor um modelo para ambientes inteligentes baseado em serviços web semânticos, em que os serviços disponíveis para os dispositivos do ambiente são proporcionados como serviços web e a interação dispositivo - ambiente é feita em um contexto de computação móvel, onde a disponibilidade dos serviços e a informação de contexto do dispositivo mudam freqüentemente. No modelo proposto todas as funcionalidades do ambiente são fornecidas como serviços. Estes serviços são descobertos e executados automaticamente com a finalidade de ajudar o usuário a desenvolver tarefas específicas, permitindo ao usuário se concentrar nas tarefas e não na interação com o ambiente. O modelo se fundamenta na oferta de serviços dirigida pela tarefa a ser desenvolvida, o que é conhecido como Task-driven Computing. Por outro lado, para a automação do processo de descoberta e execução dos serviços é necessário ter uma especificação não ambígua da semântica dos serviços. Empregamos para isso a ontologia WSMO (Web Services Modeling Ontology) que fornece os elementos necessários para a descrição dos serviços disponíveis no ambiente e o contexto do dispositivo. Finalmente, como prova de conceitos do modelo proposto, foi implementado um ambiente inteligente para uma biblioteca. A ativação de um ambiente inteligente baseado no modelo proposto se baseia na definição de ontologias, descrição semântica dos serviços no ambiente e a implementação de serviços web tradicionais. / A smart environment is a system computing ubiquitous computing and context awareness, in which the computational systems embedded in the environment, the communication between devices and the environment, and the accessibility to services are transparent to the users. The aim of this work is to propose a semantic web services based model for smart environments, in which services are offered to devices as web services and the device - environment interactions are based on a mobile computing environment, in which the contextual information and availability of services change frequently. In the proposed model all functionalities in the environment are offered as services. These services are automatically discovered and executed to support the user in a specific task, allowing to the user to focus on his task and not in the interactions with the environment. The model is based on a task-driven offer of services and on task-driven computing. To automate the discovery and execution of services, we need a nonambiguous specification of the semantic of services. We use the WSMO ontology (Web Services Modeling Ontology), which provides the required elements for description of the services in the environment and the context device. Finally, as a conceptual proof of the proposed model, we implemented a smart environment for a library. In the proposed model the activation of a smart environment is based in the ontologies definition, semantic description of the services.

Throughout the last decade, vehicle localization has been attracting significant attention in a wide range of applications, including Navigation Systems, Road Tolling, Smart Parking, and Collision Avoidance. To deliver on their requirements, these applications need specific localization accuracy. However, current localization techniques lack the required accuracy, especially for mission critical applications. Although various approaches for improving localization accuracy have been reported in the literature, there is still a need for more efficient and more effective measures that can ascribe some level of accuracy to the localization process. These measures will enable localization systems to manage the localization process and resources so as to achieve the highest accuracy possible, and to mitigate the impact of inadequate accuracy on the target application. In this thesis, a framework for fusing different localization techniques is introduced in order to estimate the location of a vehicle along with location integrity assessment that captures the impact of the measurement conditions on the localization quality. Knowledge about estimate integrity allows the system to plan the use of its localization resources so as to match the target accuracy of the application. The framework introduced provides the tools that would allow for modeling the impact of the operation conditions on estimate accuracy and integrity, as such it enables more robust system performance in three steps. First, localization system parameters are utilized to contrive a feature space that constitutes probable accuracy classes. Due to the strong overlap among accuracy classes in the feature space, a hierarchical classification strategy is developed to address the class ambiguity problem via the class unfolding approach (HCCU). HCCU strategy is proven to be superior with respect to other hierarchical configuration. Furthermore, a Context Based Accuracy Classification (CBAC) algorithm is introduced to enhance the performance of the classification process. In this algorithm, knowledge about the surrounding environment is utilized to optimize classification performance as a function of the observation conditions. Second, a task-driven integrity (TDI) model is developed to enable the applications modules to be aware of the trust level of the localization output. Typically, this trust level functions in the measurement conditions; therefore, the TDI model monitors specific parameter(s) in the localization technique and, accordingly, infers the impact of the change in the environmental conditions on the quality of the localization process. A generalized TDI solution is also introduced to handle the cases where sufficient information about the sensing parameters is unavailable. Finally, the produce of the employed localization techniques (i.e., location estimates, accuracy, and integrity level assessment) needs to be fused. Nevertheless, these techniques are hybrid and their pieces of information are conflicting in many situations. Therefore, a novel evidence structure model called Spatial Evidence Structure Model (SESM) is developed and used in constructing a frame of discernment comprising discretized spatial data. SESM-based fusion paradigms are capable of performing a fusion process using the information provided by the techniques employed. Both the location estimate accuracy and aggregated integrity resultant from the fusion process demonstrate superiority over the employing localization techniques. Furthermore, a context aware task-driven resource allocation mechanism is developed to manage the fusion process. The main objective of this mechanism is to optimize the usage of system resources and achieve a task-driven performance. Extensive experimental work is conducted on real-life and simulated data to validate models developed in this thesis. It is evident from the experimental results that task-driven integrity assessment and control is applicable and effective on hybrid localization systems.

Throughout the last decade, vehicle localization has been attracting significant attention in a wide range of applications, including Navigation Systems, Road Tolling, Smart Parking, and Collision Avoidance. To deliver on their requirements, these applications need specific localization accuracy. However, current localization techniques lack the required accuracy, especially for mission critical applications. Although various approaches for improving localization accuracy have been reported in the literature, there is still a need for more efficient and more effective measures that can ascribe some level of accuracy to the localization process. These measures will enable localization systems to manage the localization process and resources so as to achieve the highest accuracy possible, and to mitigate the impact of inadequate accuracy on the target application. In this thesis, a framework for fusing different localization techniques is introduced in order to estimate the location of a vehicle along with location integrity assessment that captures the impact of the measurement conditions on the localization quality. Knowledge about estimate integrity allows the system to plan the use of its localization resources so as to match the target accuracy of the application. The framework introduced provides the tools that would allow for modeling the impact of the operation conditions on estimate accuracy and integrity, as such it enables more robust system performance in three steps. First, localization system parameters are utilized to contrive a feature space that constitutes probable accuracy classes. Due to the strong overlap among accuracy classes in the feature space, a hierarchical classification strategy is developed to address the class ambiguity problem via the class unfolding approach (HCCU). HCCU strategy is proven to be superior with respect to other hierarchical configuration. Furthermore, a Context Based Accuracy Classification (CBAC) algorithm is introduced to enhance the performance of the classification process. In this algorithm, knowledge about the surrounding environment is utilized to optimize classification performance as a function of the observation conditions. Second, a task-driven integrity (TDI) model is developed to enable the applications modules to be aware of the trust level of the localization output. Typically, this trust level functions in the measurement conditions; therefore, the TDI model monitors specific parameter(s) in the localization technique and, accordingly, infers the impact of the change in the environmental conditions on the quality of the localization process. A generalized TDI solution is also introduced to handle the cases where sufficient information about the sensing parameters is unavailable. Finally, the produce of the employed localization techniques (i.e., location estimates, accuracy, and integrity level assessment) needs to be fused. Nevertheless, these techniques are hybrid and their pieces of information are conflicting in many situations. Therefore, a novel evidence structure model called Spatial Evidence Structure Model (SESM) is developed and used in constructing a frame of discernment comprising discretized spatial data. SESM-based fusion paradigms are capable of performing a fusion process using the information provided by the techniques employed. Both the location estimate accuracy and aggregated integrity resultant from the fusion process demonstrate superiority over the employing localization techniques. Furthermore, a context aware task-driven resource allocation mechanism is developed to manage the fusion process. The main objective of this mechanism is to optimize the usage of system resources and achieve a task-driven performance. Extensive experimental work is conducted on real-life and simulated data to validate models developed in this thesis. It is evident from the experimental results that task-driven integrity assessment and control is applicable and effective on hybrid localization systems.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Ubiquitous computing foresees the support to human activities in the most possible integrated environment known by the professional. On this perspective, a major area of its application is the Health System as the health of the future provides the use of ubiquitous computing as a way to automate and optimize the clinical activities. Addressing the problem of rejection of computer systems in health due to the remoteness of the way clinicians perform their tasks, the project "ClinicSpace" proposes a prototype of a tool that enables clinicians to customize and better manage their daily tasks. One of the big challenges is how to model human activities in computer systems, respecting the way that each individual performs them. This way, the contribution of this work is to propose a modeling of the main tasks performed in the clinical hospital settings by clinical professionals with the way that each individual performs the work. Once created the task, the medical professionals can reuse them for the definition and creation of other tasks they may judge necessary. An architecture manages the tasks in the most automatic way possible to undermine the control that the owner must maintain to the environment. Thus, it is expected to reduce the degree of rejection found in computerized systems of hospitals and clinics. The interface developed uses mechanisms provided by the End-user programming to facilitate the use of the clinical professional and Task-driven Computing. Case studies were simulated to demonstrate the feasibility of the proposal. Field tests may only be made after the release of the prototype of the architecture of the management and execution of tasks; however, this work is outside the scope of this dissertation. / A Computação Ubíqua prevê o suporte às atividades humanas da forma mais integrada possível ao ambiente conhecido pelo profissional. Nessa perspectiva, uma das grandes áreas de aplicação é a Saúde, já que o Sistema de Saúde do futuro prevê o uso da Computação Ubíqua como forma de otimizar e automatizar as atividades clínicas. Focando o problema de rejeição dos sistemas computacionais na Saúde devido ao distanciamento destes da forma como os clínicos executam suas tarefas, o projeto ClinicSpace propõe a prototipação de uma ferramenta que permita aos clínicos a personalização e gerenciamento de suas tarefas diárias. Um dos grandes desafios enfrentados é como modelar atividades humanas em sistemas computacionais, respeitando a forma individualizada com que cada pessoa as realiza. Nesse sentido, a contribuição desse trabalho é a proposta de uma ferramenta-piloto que permite ao profissional programar e compor suas tarefas, a partir de uma modelagem das principais tarefas clínicas executadas nos ambientes hospitalares por profissionais clínicos, respeitando a forma individual que cada profissional as realiza. Uma vez criadas as tarefas, os profissionais clínicos podem reutilizá-las para a definição e reuso na criação de outras tarefas que julgarem necessário. Uma arquitetura gerencia a execução das tarefas da forma mais automática possível para não comprometer o controle que o profissional deve manter sobre o ambiente. Assim, espera-se reduzir o grau de rejeição encontrado nos sistemas informatizados dos hospitais e clínicas. A interface de programação de tarefas pelo profissional desenvolvida utiliza mecanismos providos pela Programação Orientada ao Usuário-Final com o objetivo de facilitar a utilização do sistema pelo profissional clínico e pela Computação Orientada a Atividades. Estudos de casos foram simulados para demonstrar a viabilidade da proposta. Testes de campo somente poderão ser realizados após a disponibilização do protótipo da arquitetura de gerenciamento e execução das tarefas, porém, esse trabalho está fora do escopo dessa dissertação.

Currently, Pervasive Computing is focused on the development of programmable and interactive environments, which are intended to help the user in daily activities. The health system of the future envisages the use of Pervasive Computing as a way of optimizing and automating clinical activities. Under such perspective, the present study has tried to add, in a middleware for pervasive environment management, the supporting for management and accomplishment of clinical tasks (pervasive applications that help physicians perform their activities), fulfilling some requirements of activities-oriented computing, and creating a tool that will help physicians in their daily tasks. In modeling of the tasks management system, the middleware EXEHDA Execution Environment for Highly Distributed Applications has been used to manage the pervasive environment where tasks will be performed. Due to the flexible features of EXEHDA, as the integration of new services, the supporting of the middleware to the new tasks management was added as a new subsystem, composed by the services that implement the new features. So, the main contribution of present study was the modeling of the architecture for the new subsystem of EXEHDA, responsible for management of tasks in pervasive environment. As a secondary contribution, was developed a prototype of the core of this new subsystem (a service for managing tasks), already providing same integration within other services modeled for the architecture. This prototype can be used, during the course of the ClinicSpaces Project, as a basis for testing and evaluation of other services and to facilitate the participation of professionals from other areas in the project. / Atualmente, a Computação Pervasiva está direcionada ao desenvolvimento de ambientes programáveis e interativos, os quais auxiliarão o usuário em suas atividades diárias. O sistema de saúde do futuro prevê o uso da Computação Pervasiva como forma de otimizar e automatizar as atividades clínicas. Tendo em vista essa perspectiva, neste trabalho buscou-se adicionar, a um middleware de gerenciamento do ambiente pervasivo, o suporte ao gerenciamento e à execução de tarefas clínicas (aplicações pervasivas que auxiliam o clínico a realizar suas atividades), atendendo a alguns requisitos da computação orientada a atividades, e criando uma ferramenta para auxiliar os clínicos em suas atividades diárias. Na modelagem do sistema de gerenciamento de tarefas, o middleware EXEHDA Execution Environment for Highly Distributed Applications foi utilizado para gerenciar o ambiente pervasivo no qual as tarefas irão executar. Devido às características flexíveis do EXEHDA quanto à integração de novos serviços, o suporte do middleware ao gerenciamento de tarefas foi adicionado através de um novo subsistema, composto pelos serviços que implementam as novas funcionalidades. Portanto, a principal contribuição deste trabalho foi a modelagem da arquitetura do novo subsistema do EXEHDA, responsável pelo gerenciamento de tarefas no ambiente pervasivo. Como contribuição secundária, foi desenvolvido um protótipo do núcleo desse novo subsistema (um serviço para gerenciamento de tarefas), já prevendo certa interação com os demais serviços modelados para a arquitetura. Esse protótipo poderá ser usado, durante o andamento do projeto ClinicSpaces, como base para teste e avaliação dos outros serviços, bem como, para facilitar a participação de profissionais de outras áreas no prosseguimento do projeto.

To improve the system usability and assist the user during the execution of their daily clinical tasks, were designed new components and services to realize the task inference in the ClinicSpace architecture. The ClinicSpace project, currently being developed by the GMob of the PPGI/UFSM, aims to build a pilot tool that allows the modeling of the clinical tasks by the physician and their automatic management. To model and develop an inference service to this architecture is the main goal of the work described in the current dissertation. To realize the task inference, were used the task execution history of each user together with the present characteristics of the environment during the tasks executions. In this way, is possible to trace the profile of each user, knowing which functionalities will be necessary for him in the near future. With the capture of the environment information during the task execution, was used the C4.5 algorithm to infer, foresee, the next task to be executed. Together with the constant environment monitoring, were detected patterns that allows suppose the future execution of a task, helping the system utilization. The system presents the inferred tasks as suggestion in the graphical interface to not take automatic decisions, taking the user role, predicting a general improvement in the system usability. To validate the developed architecture, were made performance analyses of the inference mechanism, resulting in a small interference of the execution time of the whole system. / De forma a melhorar a usabilidade do sistema e auxiliar o usuário durante a execução de suas tarefas clínicas cotidianas foram projetados novos componentes e serviços para realizar a inferência de tarefas na arquitetura ClinicSpace. O projeto ClinicSpace, em desenvolvimento no GMob do PPGI/UFSM, visa construir uma ferramenta-piloto que permita a programação das atividades clínicas pelo próprio médico e o gerenciamento automático destas. Modelar e implementar um serviço de inferência para essa arquitetura é o objetivo principal do trabalho descrito nesta dissertação. Como base para a inferência das tarefas de cada usuário, utilizou-se o histórico de execução de tarefas juntamente com as características presentes no ambiente durante a execução. Dessa forma, é possível traçar o perfil de cada usuário, conhecendo-se quais funcionalidades serão necessárias a ele no futuro. A partir da captura de informações do ambiente durante a execução das tarefas, foi utilizado o algoritmo C4.5 para inferir, prever, a próxima tarefa a ser executada. Em conjunto com o constante monitoramento do ambiente são detectados os padrões que levam a supor a execução futura de uma tarefa, auxiliando na utilização do sistema. A partir da tarefa inferida, o sistema a apresenta como sugestão na interface gráfica de forma a não tomar decisões automáticas em substituição ao papel do usuário, prevendo-se uma melhoria geral na usabilidade do sistema. Como forma de validação da arquitetura desenvolvida foram feitas análises de desempenho do mecanismo de inferência, obtendo-se o resultado de baixa interferência nos tempos de execução do sistema como um todo.