Event Processing and Real-Time Monitoring over Streaming Traffic Data

摘要

Tracking mobility of humans, animals or merchandise has recently given rise to a wide variety of location-based services and monitoring applications. In this paper, we particularly focus on real-time traffic surveillance over densely congested road networks in large metropolitan areas. In such a setting, streaming positional updates are being frequently relayed into a central server from numerous moving vehicles (buses, taxis, passenger cars etc.). Our analysis concerns two important aspects. First, we outline characteristics of a robust processing engine that is capable to efficiently manage such massive, transient, and perhaps noisy geospatial data. Our objective is to provide online aggregates and reliable estimates regarding the current traffic situation at multiple levels of resolution. At a second step, we design a framework for effective multi-modal dissemination of derived information to the end users, in the form of interactive maps for intuitive visualization as well as instant notifications via message feeds. As a proof of concept, we also report on our ongoing development of EPOPS; in its current version, this functional prototype of the proposed scheme is able to deliver cross-platform geographic, textual, and even multimedia content through web and smartphone interfaces.