Complex event processing is about processing huge amounts of information in real time, in a rather complex way. The degree of complexity is determined by the level of the interdependencies between information to be processed. There are several more or less traditional operators for defining these interdependencies, which are supported by existing approaches and the main competition is around the speed (throughput) of processing. However, novel application domains like Future Internet are challenging complex event processing for a more comprehensive approach: from how to create complex event patterns over the heterogeneous event sources (including textual data), to how to efficiently detect them in a distributed setting, including the usage of background knowledge. In this chapter we present an approach for intelligent CEP (iCEP) based on the usage of semantic technologies. It represents an end-to-end solution for iCEP starting from the definition of complex event patterns, through intelligent detection, to advanced 3-D visualization of complex events. At the center of the approach is the semantic model of complex events that alleviates the process of creating and maintaining complex event patterns. The approach utilizes logic-based processing for including domain knowledge in the complex event detection process, leading to complex event reasoning. This approach has been implemented in the web-based framework called iCEP Studio.