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Wildfire Integrated Modeling, Prediction, and Learning Environment (WIMPLE)

Award Information
Agency: National Aeronautics and Space Administration
Branch: N/A
Contract: 80NSSC22PA982
Agency Tracking Number: 221610
Amount: $149,988.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: S11
Solicitation Number: SBIR_22_P1
Solicitation Year: 2022
Award Year: 2022
Award Start Date (Proposal Award Date): 2022-07-20
Award End Date (Contract End Date): 2023-01-25
Small Business Information
625 Mount Auburn Street
Cambridge, MA 02138-4555
United States
DUNS: 115243701
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Avi Pfeffer
 (617) 491-3474
Business Contact
 Mark Felix
Phone: (617) 234-5073
Research Institution

The risk of wildfires has increased significantly in recent years and touched communities not previously at high risk. Effective mitigation of wildfire risk is essential to reduce the potential for catastrophic losses. Accurate assessment of the risk of wildfire on a parcel-by-parcel basis will enable fire departments and homeowners to effectively triage and plan to reduce the risk. We will develop a Wildfire Integrated Modeling, Prediction, and Learning Environment (WIMPLE), a hybrid AI tool for wildfire risk assessment. WIMPLE is based on our Scruff AI framework, which provides integration of different kinds of AI models, sharing and composition of models, with spatiotemporal flexibility in model composition. We will demonstrate WIMPLE by developing a new wildfire risk assessment method that integrates multiple model components such as fire propagation and climate models at different spatial and temporal scales, as well as learning from historical data. We provide a decision-support UI using explainable AI techniques to ensure that predictions and recommendations of WIMPLE can be understood and trusted by users.

* Information listed above is at the time of submission. *

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