Event detection challenges, methods, and applications in natural and artificial systems

Abstract

A system is a combination of elements whose collaborative actions produce results generally not attainable by the elements acting alone, and an event is a significant occurrence or large-scale activity that is unusual relative to normal patterns of behavior. Event detection, or the process of identifying the occurrence of an event, within both natural and artificial (or man-made) systems has long been a topic of research, and a variety of techniques have been developed to address event detection problems. This article is a treatise on the topic of event detection and a prequel to research previously conducted by the authors regarding the application of robust metamodels to uncertainty quantification and event detection within a geophysical system. The article explores the most common difficulties and challenges in event detection problems, describes the event detection methods most frequently employed, and provides example event detection applications in both natural and artificial systems. It incorporates the discoveries of and lessons learned by multiple researchers and authors over many combined years of experience in event detection theory and application; this rather broad study has never been previously published within a single volume. the article concludes with an examination of the intimate relationship and indivisible link between event detection and modeling and simulation.