The Internet of Things (IoT) provides a large amount of data, which can be shared or consumed by thousands of individuals and organizations around the world. These organizations can be connected using Service-Oriented Architectures (SOAs), which have emerged as an efficient solution for modular system implementation allowing easy communications among third-party applications; however, SOAs do not provide an efficient solution to consume IoT data for those systems requiring on-demand detection of significant or exceptional situations. In this regard, Complex Event Processing (CEP) technology continuously processes and correlates huge amounts of events to detect and respond to changing business processes. In this chapter, the authors propose the use of CEP to facilitate the demand-driven detection of relevant situations. This is achieved by aggregating simple events generated by an IoT platform in an event-driven SOA, which makes use of an enterprise service bus for the integration of IoT, CEP, and SOA. The authors illustrate this approach through the implementation of a case study. Results confirm that CEP provides a suitable solution for the case study problem statement.
Multimodal Event Processing: A Neural-Symbolic Paradigm for the Internet of Multimedia Things
