A cognitive fault-detection design architecture

This paper presents a novel architecture for the design of fault-detection schemes, aiming to automate the cognitive process performed by human experts when designing fault detection schemes for certain systems. The work starts with the identification of types of cyber-physical components participating in a fault-detection scheme. These are semantically characterized, adopting a model driven by previous efforts of the World Wide Web Consortium on the semantic composition of Web services. The semantic characterizations of the components are then exploited by a Cognitive Agent with semantic reasoning capabilities, to achieve the configuration of a fault-detection scheme, given a set of specifications and available components. The Cognitive Agent has access to a knowledge representation model and is able to interact with human operators and with the components to enrich its knowledge for making and enforcing decisions about the configuration. The applicability of the architecture and the reasoning steps are demonstrated through the configuration of a water contamination event-detection scheme with learning capabilities within a smart water distribution network