Real-time data exploitation supported by model- and event-driven architecture to enhance situation awareness, application to crisis management

ABSTRACT

An effective crisis response requires up-to-date information. The crisis cell must reach for new, external, data sources. However, new data lead to new issues: their volume, veracity, variety or velocity cannot be managed by humans only, especially under high stress and time pressure. This paper proposes (i) a framework to enhance situation awareness while managing the 5Vs of Big Data, (ii) general principles to be followed and (iii) a new architecture implementing the proposed framework. The latter merges event-driven and model-driven architectures. It has been tested on a realistic flood scenario set up by official French services.

KEYWORDS:

• Situation awareness
• EIS for public sector
• model-driven architecture
• event-driven architecture
• complex event processing
• crisis management

Acknowledgements

This work would not have been possible without the GéNéPi project research team or the computer engineers team from the Industrial Engineering Center of IMT Mines Albi.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1. Third Edition, p528.

2. https://R-IOSuite.com/display/RIOSUITE/Binaries.

3. https://R-IOSuite.com/display/RIOSUITE/Demo+Video.

Additional information

Funding

This work was supported by the French National Research Agency, through the GéNéPi project funding [program: Résilience and crisis management [DS0903] 2014; project ID: ANR-14-CE28-0029].