Fault recovery mechanism for smart city environments

In this paper we present the work done to develop a fault recovery component for the situation when the quality of the data streams from a smart city environment drops. The fault recovery component is able to generate estimated values when the stream generates invalid or missing observations. The component is easy to configure and deploy for a large number of data streams from a smart city environment. As a result of that, the fault recovery component contains an incremental learning model, which is able to train itself during component execution. The paper describes the architecture of the fault recovery component and the result of the evaluation done for three candidate incremental learning models.