Enhanced Event Modeling for Human-System Interactions Using IOPT Petri Nets

Abstract

This work presents some new ways to analyze a signal that allows the modeling of human-system interactions. In addition to the possibility of creating conditions associated with the current value of the signal, the work focuses mainly on the definition of events and on their use within Input-Output Place-Transition (IOPT) nets models. Currently, non-autonomous events can be defined in two different ways, namely as a threshold detection of a signal, or variation of the first derivative of the signal. Here, this concept is generalized, allowing the analysis of events in higher derivatives of the signal. On the other hand, a new set of types of events are defined for each derivative of the signal, improving existing UP and DOWN events. Finally, an example is used to illustrate discussed concepts. © Springer International Publishing Switzerland 2014.