A Distributed Event Calculus for Event Recognition
A. Mavrommatis, A. Artikis, A. Skarlatidis, and G. Paliouras. Proceedings of the 2nd Workshop on Artificial Intelligence and Internet of Things (AI-IoT 2016), The Hague, Netherlands, volume 1724 of CEUR Workshop Proceedings, page 31--37. RWTH Aachen, Sun SITE Central Europe, (2016)
Events provide a fundamental abstraction for representing time-evolving information. Complex event recognition focuses on tracking and analysing streams of events, in order to detect patterns of special significance. The event streams may originate from various types of sensor, such as cameras and GPS sensors. Furthermore, the stream velocity and volume pose significant challenges to event processing systems. We propose dRTEC, an event recognition system that employs the Event Calculus formalism and operates in multiple processing threads. We evaluate dRTEC using two real-world applications and show that it is capable of real-time and scalable event recognition.