Abstract:
Activity recognition refers to the detection of temporal combinations of ‘low-level’ or ‘short-term’ activities on sensor data. Various types of uncertainty exist in activity recognition systems and this often leads to erroneous detection. Typically, the frameworks aiming to handle uncertainty compute the probability of the occurrence of activities at each...
Abstract:
The concept of event processing is established as a generic computational paradigm in various application fields. Events report on state changes of a system and its environment. Complex event recognition (CER) refers to the identification of composite events of interest, which are collections of simple, derived events that satisfy some...
Abstract:
In complex event processing (CEP), simple derived event tuples are combined in pattern matching procedures to derive complex events (CEs) of interest. Big Data applications analyze event streams online and extract CEs to support decision making procedures. At massive scale, such applications operate over distributed networks of sites where efficient...
Abstract:
We present a system for online, incremental composite event recognition. In streaming environments, the usual case is for data to arrive with a (variable) delay from, and to be retracted/revised by the underlying sources. We propose RTECinc, an incremental version of RTEC, a composite event recognition engine with a formal,...
Abstract:
Maritime monitoring systems support safe shipping as they allow for the real-time detection of dangerous, suspicious and illegal vessel activities. We present such a system using the Run-Time Event Calculus, a composite event recognition system with formal, declarative semantics. For effective recognition, we developed a library of maritime patterns in...
