Fuzzy/Human Risk Analysis for Maritime Situational Awareness and Decision Support

Human computation (HC) is an active research field in which people play a notable role as computational elements in an automated system with the aim of arriving at a truly symbiotic human-computer interaction. Situational awareness (SA) and decision support systems (DSSs) are two domains where human computation is rapidly advancing, with the latter arising as an invaluable vehicle to achieve the former. Fuzzy systems and fuzzy logic are two commonly employed tools in these domains due to their inherent capabilities of representing and processing vague and imprecise information while conveying the analysis results in an interpretable fashion. In this paper, we elaborate on the human computation aspects of risk analysis within SA and DSS conducted with the aid of fuzzy sets. The study makes the following contributions: (1) we argue that risk analysis must be a highly automated yet still human-centric endeavour and highlight four manners in which the human component provides value to the underlying data/information fusion processes; (2) we illustrate this fuzzy/human risk analysis methodology through a multimodular Risk Management Framework (RMF) architecture and its application to the maritime domain, particularly in hard-soft data fusion, automated response generation to maritime incidents, port anomaly filtering and dynamic risk management triggered by contextual knowledge and (3) the framework under discussion can be extrapolated to other domains with negligible effort.