This thesis takes place in the field of Ambient Intelligence (AmI). Ambient Intelligent Systems are interactive systems composed of many heterogeneous components. From a hardware perspective these components can be divided into two main classes: sensors, using which the system observes its surroundings, and actuators, through which the system acts upon its surroundings in order to execute specific tasks. From a functional point of view, the goal of Ambient Intelligent Systems is to activate some actuators, based on data provided by some sensors. However, sensors and actuators may suffer failures. Our motivation in this thesis is to equip ambient systems with self fault-detection and diagnosis capabilities allowing them to check autonomously whether the intended actions were performed correctly by the actuators. To address this issue, one could apply classical control theory to pre-determine closed control loops using the available sensors. However, the particularity of ambient systems is that instances of physical resources (mainly sensors and actuators) are not necessarily known at design time; instead they are dynamically discovered at run-time. In consequence, such control loops cannot be pre-determined. We propose an approach in which the fault detection and diagnosis in ambient systems is dynamically done at run-time, while decoupling actuators and sensors at design time. We introduce a Fault Detection and Diagnosis framework modeling the generic characteristics of actuators and sensors, and the effects that are expected on the physical environment when a given action is performed by the system's actuators. These effects are then used at run-time to link actuators (that produce them) with the corresponding sensors (that detect them). Most importantly the mathematical model describing each effect allows the calculation of the expected readings of sensors. Comparing the predicted values with the actual values provided by sensors allows us to achieve fault-detection in dynamic and heterogeneous ambient systems.
