Data Science Journal
Online ISSN : 1683-1470
Proceedings of the 1st WDS Conference in Kyoto 2011
Multi-Disciplinary Approaches to Intelligently Sharing Large-Volumes of Real-Time Sensor Data During Natural Disasters
Stuart E MiddletonZoheir A SabeurPeter LöweMartin HammitzschSiamak TavakoliStefan Poslad
Author information
JOURNAL FREE ACCESS

2013 Volume 12 Pages WDS109-WDS113

Details
Abstract

We describe our knowledge-based service architecture for multi-risk environmental decision-support, capable of handling geo-distributed heterogeneous real-time data sources. Data sources include tide gauges, buoys, seismic sensors, satellites, earthquake alerts, Web 2.0 feeds to crowd source 'unconventional' measurements, and simulations of Tsunami wave propagation. Our system of systems multi-bus architecture provides a scalable and high performance messaging backbone. We are overcoming semantic interoperability between heterogeneous datasets by using a self-describing 'plug-in' data source approach. As crises develop we can agilely steer the processing server and adapt data fusion and mining algorithm configurations in real-time.

Content from these authors

This article cannot obtain the latest cited-by information.

Previous article Next article
feedback
Top