AI To Fight Wildfires – USC Viterbi | School of Engineering
USC to Co-Lead an NSF-Funded Project for Controlled Burns and Fire Mitigation
For the past decade in Los Angeles and the State of California, the question is not if there will be wildfires—but rather when and where they will sprout up and how to protect people from these threats. As such, firefighters need to know how to plan and deploy limited resources.
One such solution is controlled burns of flammable brush to prevent worst-case scenarios of growing tinder that left unattended, provides fodder for megafires. With $5 million in support from the National Science Foundation’s Convergence Accelerator program, a team of researchers, which includes UC San Diego’s San Diego Supercomputer Center (SDSC), the University of Southern California’s Viterbi School of Engineering and the Tall Timbers Research Station in Florida, will bring the power of AI to help firefighters strategize how best to plan these controlled burns, as well as manage unexpected blazes.
SDSC will lead the effort through the development of “BurnPro3D”, a new decision support platform to help the fire response and mitigation community quickly and accurately understand risks and tradeoffs presented by a fire to more effectively plan controlled burns and manage wildfires.
The BurnPro3D platform will leverage SDSC’s WIFIRE Commons, a data-sharing and AI framework that uses next-generation fire science in prescribed burns for preemptive vegetation treatment and USC’s MINT modeling framework, which integrates highly heterogeneous models from separate disciplines, including geosciences, agriculture, economics and social sciences.
Ilkay Altintas, chief data science officer and director of the WIFIRE Lab at SDSC, is the project’s principal investigator (PI).
For the USC team, Yolanda Gil, Director of New Initiatives in AI and Data Science at USC’s Viterbi School of Engineering, will serve as the principal investigator.
For the past decade in Los Angeles and the State of California, the question is not if there will be wildfires—but rather when and where they will sprout up and how to protect people from these threats. As such, firefighters need to know how to plan and deploy limited resources.
One such solution is controlled burns of flammable brush to prevent worst-case scenarios of growing tinder that left unattended, provides fodder for megafires. With $5 million in support from the National Science Foundation’s Convergence Accelerator program, a team of researchers, which includes UC San Diego’s San Diego Supercomputer Center (SDSC), the University of Southern California’s Viterbi School of Engineering and the Tall Timbers Research Station in Florida, will bring the power of AI to help firefighters strategize how best to plan these controlled burns, as well as manage unexpected blazes.
SDSC will lead the effort through the development of “BurnPro3D”, a new decision support platform to help the fire response and mitigation community quickly and accurately understand risks and tradeoffs presented by a fire to more effectively plan controlled burns and manage wildfires.
The BurnPro3D platform will leverage SDSC’s WIFIRE Commons, a data-sharing and AI framework that uses next-generation fire science in prescribed burns for preemptive vegetation treatment and USC’s MINT modeling framework, which integrates highly heterogeneous models from separate disciplines, including geosciences, agriculture, economics and social sciences.
Ilkay Altintas, chief data science officer and director of the WIFIRE Lab at SDSC, is the project’s principal investigator (PI).
For the USC team, Yolanda Gil, Director of New Initiatives in AI and Data Science at USC’s Viterbi School of Engineering, will serve as the principal investigator.
viterbischool.usc.edu
