A functional approach for disruptive event discovery and policy monitoring in mobility scenarios

Abstract

This paper presents the results obtained of using LISP for real-time event detection and how these results are interpreted and used within the context of SUPERHUB, a European-Funded projected aimed to achieve a more sustainable mobility behaviour in cities. Real-time detection allows faster reaction for decision making processes as well as a valuable asset for policy makers to know what should be done when an unexpected event occurs. The use of LISP has facilitated most of this process and, specially, supported to parallelize the capture, aggregation and interpretation of data.