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This thesis describes a proposed design and implementation of a predictive maintenance engine developed to fulfill the requirements of the STO Company (Societe de transport de l'Outaouais) for maintaining vehicles in the fleet. Predictive maintenance is proven to be an effective approach and has become an industry standard in many fields. However, in the transportation industry, it is still in the stages of development due to the complexity of moving systems and the high level dimensions of involved parameters. Because it is almost impossible to cover all use cases of the vehicle operational process using one particular approach to predictive maintenance, in our work we take a systematic approach to designing a predictive maintenance system in several steps. Each step is implemented at the corresponding development stage based on the available data accumulated during system funсtioning cycle. % by dividing the entire system into modules and implementing different approaches. This thesis delves into the process of designing the general infrastructural model of the fleet management system (FMS), while focusing on the edge gateway module located on the vehicle and its function of detecting maintenance events based on current vehicle status. Several approaches may be used to detect maintenance events, such as a machine learning approach or an expert system-based approach. While the final version of fleet management system will use a hybrid approach, in this thesis paper we chose to focus on the second option based on expert knowledge, while machine learning has been left for future implementation since it requires extensive training data to be gathered prior to conducting experiments and actualizing operations. Inspired by the IDEA methodology which promotes mapping business rules as software classes and using the object-relational model for mapping objects to database entities, we take active database features as a base for developing a rule engine implementation. However, in contrast to the IDEA methodology which seeks to describe the specific system and its sub-modules, then build active rules based on the interaction between sub-systems, we are not aware of the functional structure of the vehicle due to its complexity. Instead, we develop a framework for creating specific active rules based on abstract classifications structured as ECA rules (event-condition-action), but with some expansions made due to the specifics of vehicle maintenance. The thesis describes an attempt to implement such a framework, and particularly the rule engine module, using active database features making it possible to encapsulate the active behaviour inside the database and decouple event detection from other functionalities. We provide the system with a set of example rules and then conduct a series of experiments analyzing the system for performance and correctness of events detection.

The development of system architectures and applications for smart homes and ambient assisted living has been the main activity of a number of academic and industrial research projects around the world. Existing system architectures for smart environments usually employ different architectural styles in a multi-layer logical architecture to support the integration and interoperation of heterogeneous hardware and software technologies, which are subsequently used to provide two major functionalities: monitoring and assistance. It is also usual among existing architectures that the database management system is the most common but the least exploited architectural component, existing in the periphery of the system and devoted exclusively for data storage and retrieval. However, database technology has advanced and matured considerably over the years, and, as a result, current database management systems can be and do more. This thesis considers the hypothesis of several features of modern database management systems being employed to address functional (e.g. well-being and security monitoring, automated control, data processing) and non-functional (e.g. interoperability, extensibility, data security and privacy) requirements of smart environments, i.e. the database management system serves as a platform for smart environments. The scope of this thesis is therefore to investigate the possibility of using different features supported by database management systems to create a database-centric system architecture for the development of smart home environments and ambient assisted living. The thesis also investigates the development of applications for health monitoring and assistance: 1) a serious game for fall prevention that assists people in practicing Tai Chi at home, and 2) a non-intrusive home-based method for sleep assessment. These features are explored in this thesis to address general functional aspects of smart environments, such as monitoring, processing, coordination and control of various types of events in a given environment. Extensibility and security features and cross-platform capabilities of database management systems are employed to accommodate non-functional, but still technical, properties of smart environments, including interoperability, extensibility, portability, scalability, security and privacy. Heterogeneous technologies are integrated into the system using programming language and platform independent software resource adapters. Interoperation among integrated technologies is mediated in an active database. The feasibility of the proposed database-centric system architecture was pragmatically investigated with the development of a "smart bedroom'' demonstrator and with the implementation of a number of short-term and long-term types of services to support active aging, aging in place and ambient assisted living. In the proposed architecture, active in-database processing maintains sensitive data within the database. This increases data security and independence from external software applications for data analysis. Changes in the system are managed during runtime, which improves flexibility and avoids system downtime. The proposed system architecture was evaluated taking into account different application scenarios and heterogeneous computing platforms. As a conclusion, modern database management systems support features that can be successfully employed in a database-centric system architecture to effectively and efficiently address functional and non-functional requirements of smart environments.

Nos últimos anos, a utilização do Data Warehouse mudou significativamente. Nos dias de hoje, as empresas precisam distribuir informações, num intervalo de tempo adequado, para os colaboradores que atuam na linha de frente do negócio, de modo que estes possam obter um desempenho superior na execução de suas tarefas. O presente trabalho apresenta as novas tendências em inteligência empresarial, dando destaque aos aspectos táticos e operacionais, a necessidade de redução na latência de atualização dos dados, as limitações do ambiente de Data Warehouse nesse contexto. O desenvolvimento deste trabalho baseou-se na revisão da literatura existente, no estudo de novos mecanismos de integração de dados, na apresentação de casos reais de aplicação e em um relato de caso prático. Este trabalho buscou destacar o papel fundamental que as novas tecnologias de integração de dados têm na criação de novos sistemas de apoio e automação de decisões nas empresas realizando negócios em tempo real. / During the last years many things have changed in the utilization the Data Warehouse. Nowadays, enterprises need to distribute information in a timely fashion to front-line workers, enabling them to deliver superior performance in the execution of their duties. This work presents new trends in business intelligence, emphasizing the tactical and operational aspects, the demand for reducing data latency, the limitations of the Data Warehouse in this context. The development of this work was based on the review of existing literature, the study of new mechanisms for data integration, the presentation of real case scenarios of application and a practical case story. This study highlights the key role that the new data integration technologies have while are creating new automating decisions systems in companies doing business in real time.

Nos últimos anos, a utilização do Data Warehouse mudou significativamente. Nos dias de hoje, as empresas precisam distribuir informações, num intervalo de tempo adequado, para os colaboradores que atuam na linha de frente do negócio, de modo que estes possam obter um desempenho superior na execução de suas tarefas. O presente trabalho apresenta as novas tendências em inteligência empresarial, dando destaque aos aspectos táticos e operacionais, a necessidade de redução na latência de atualização dos dados, as limitações do ambiente de Data Warehouse nesse contexto. O desenvolvimento deste trabalho baseou-se na revisão da literatura existente, no estudo de novos mecanismos de integração de dados, na apresentação de casos reais de aplicação e em um relato de caso prático. Este trabalho buscou destacar o papel fundamental que as novas tecnologias de integração de dados têm na criação de novos sistemas de apoio e automação de decisões nas empresas realizando negócios em tempo real. / During the last years many things have changed in the utilization the Data Warehouse. Nowadays, enterprises need to distribute information in a timely fashion to front-line workers, enabling them to deliver superior performance in the execution of their duties. This work presents new trends in business intelligence, emphasizing the tactical and operational aspects, the demand for reducing data latency, the limitations of the Data Warehouse in this context. The development of this work was based on the review of existing literature, the study of new mechanisms for data integration, the presentation of real case scenarios of application and a practical case story. This study highlights the key role that the new data integration technologies have while are creating new automating decisions systems in companies doing business in real time.