919. Integrated OR and AI systems for fire prevention
Invited abstract in session TE-36: Analytics for Forest Fires Prevention and Risk Analysis, cluster Use of Analytics in Forest Fires Management.
Tuesday, 16:15-17:45Room: FENH309
Authors (first author is the speaker)
| 1. | Rodrigo Mahaluf-Recasens
|
| Santiago, Complex Engineering Systems Institut | |
| 2. | Jaime Carrasco
|
| University of Chile | |
| 3. | Andrés Weintraub
|
| Industrial engineering, University of Chile | |
| 4. | David Palacios
|
| Departamento de Ingeniería Civil Industrial, Universidad de Chile | |
| 5. | Alejandro Miranda
|
| Universidad de Chile |
Abstract
We present an overview of the work we have been carrying out in designing fuel management to minimize the damage caused by future forest fires. We can view action on fires in three major frameworks: prevention and preparedness, detection and response, and restoration and adaptation. Our work concentrates on prevention.
We can define four major phases in this process: data acquisition and management, determination of probabilities of spatial ignitions, stochastic simulations of fire spread, and creating fire breaks or other actions to minimize fire spread to valuable areas.
In other talks in these sessions, we will present detailed explanations of each phase, including considerations of carbon emissions and protection of wildlife. A main contribution in our work is the integration of a spread simulation model Cell2Fire, with optimization decision-making using OR and AI approaches. We will present results of real forests in Cataluña and Chile, showing the advantages of applying analytics techniques to fuel management. This work has been supported by institutions in Chile (Fondef) and in Europe (Fire Res). Fire Res is a collaboration of over 30 European institutions (universities, research institutes, and consulting companies) . We will present the importance of this multidisciplinary international collaboration.
Keywords
- Applications, Agriculture and Forestry
- Climate and Disaster Risk Management
- Artificial Intelligence
Status: accepted
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