Abstract
The FireGrid project aims to harness the potential of advanced forms of computation to support the response to large-scale emergencies (with an initial focus on the response to fires in the built environment). Computational models of physical phenomena are developed, and then deployed and computed on High Performance Computing resources to infer incident conditions by assimilating live sensor data from an emergency in real timeor, in the case of predictive models, faster-than-real time. The results of these models are then interpreted by a knowledge-based reasoning scheme to provide decision support information in appropriate terms for the emergency responder. These models are accessed over a Grid from an agent-based system, of which the human responders form an integral part. This paper proposes a novel FireGrid architecture, and describes the rationale behind this architecture and the research results of its application to a large-scale fire experiment. © 2010 Elsevier Inc. All rights reserved.
Original language | English |
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Pages (from-to) | 1128-1141 |
Number of pages | 14 |
Journal | Journal of Parallel and Distributed Computing |
Volume | 70 |
Issue number | 11 |
DOIs | |
Publication status | Published - 1 Nov 2010 |
Externally published | Yes |
Keywords
- Emergency response
- Fire simulation model
- Grid
- High performance computing
- Knowledge-based reasoning
- Multi-agent system
ASJC Scopus subject areas
- Theoretical Computer Science
- Software
- Hardware and Architecture
- Computer Networks and Communications
- Artificial Intelligence