A critical issue in the Web of Things (WoT) is the need to process and analyze the interactions of Web-interconnected real-world objects. Complex Event Processing (CEP) is a powerful technology for analyzing streams of information about real-time distributed events, coming from different sources, and for extracting conclusions from them. CEP permits hierarchically defining complex events based on the primitive events produced by the incoming sources, or from other complex events, in order to identify elaborated situations of interest, and to quickly respond to them. However, in many situations these events are not free from uncertainty, due to either unreliable data sources and networks, measurement uncertainty, or to the inability to determine whether an event has actually happened or not. We discuss how CEP systems can incorporate different kinds of uncertainty, both in the events and in the rules.
In this website the complete case studies and software artifacts we reference in our submission are available for download.
The file with the rules of our case study in plain Esper EPL  is available for download here and the other case, considering uncertainty and probabilities, here. We also provide a Java project for each case with the dataset we have used to run our experiments:
 EsperTech: Esper - Complex Event Processing. http://www.espertech.com/esper/ (accessed 18 November 2017).
 Tanja Mayerhofer, Manuel Wimmer, Antonio Vallecillo. "Adding Uncertainty and Units to Quantity Types in Software Models". In Proc. of SLE 2016.