Abstract
Wildland fires and related hazards are increasing globally. A common observation across these large events is that fire behavior is changing to be more destructive, making applied fire research more important and time critical. Significant improvements towards modeling of the extent and dynamics of evolving plethora of fire related environmental hazards, and their socio-economic and human impacts can be made through intelligent integration of modern data and computing technologies with techniques for data management, machine learning and fire modeling. However, there are still challenges and opportunities in integration of the scientific discoveries and data-driven methods for hazards with the advances in technology and computing in a way that provides and enables different modalities of sensing and computing. The WIFIRE cyberinfrastructure took the first steps to tackle this problem with a goal to create an integrated system, data and visualization services, and workflows for wildfire monitoring, simulation, and response. Today, WIFIRE provides an end-to-end management infrastructure from the data sensing and collection to artificial intelligence and modeling efforts using a continuum of computing methods that integrate edge, cloud, and high-performance computing. Through this cyberinfrastructure, the WIFIRE project provides data driven knowledge for a wide range of public and private sector users enabling scientific, municipal, and educational use. This paper (based on the keynote by the author) reviews some of our recent work on building this dynamic data driven cyberinfrastructure and impactful application solution architectures that showcase integration of a variety of existing technologies and collaborative expertise.
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References
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Acknowledgements
The author thanks to and acknowledges the NSF grants (#1331615 for WIFIRE, #1730158 for CHASE-CI, #1935984 for SAGE AI on the Edge, #1928224 for Expanse), the WIFIRE team, and the support of various WIFIRE partners.
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Altintas, I. (2020). Using Dynamic Data Driven Cyberinfrastructure for Next Generation Disaster Intelligence. In: Darema, F., Blasch, E., Ravela, S., Aved, A. (eds) Dynamic Data Driven Applications Systems. DDDAS 2020. Lecture Notes in Computer Science(), vol 12312. Springer, Cham. https://doi.org/10.1007/978-3-030-61725-7_4
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DOI: https://doi.org/10.1007/978-3-030-61725-7_4
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