Project Grant 2502074
- The National Science Foundation awarded a $150,000 Project Grant to the National Center for Atmospheric Research (NCAR) under the Computer and Information Science and Engineering program (CFDA 47.070). The award will support development of a closed-loop sensing, modeling, and communications system to aid in wildfire detection, mapping, and prediction from July 2022 through June 2025. The system aims to leverage detailed 3D environmental models incorporating fuel, terrain, weather and other...
- This Project Grant from the National Science Foundation Division of Chemical, Bioengineering, Environmental, and Transport Systems provides $284,564 to develop an advanced optical sensor using background-oriented schlieren tomography to characterize wildfire dynamics. Funded under the NSF Engineering program (CFDA 47.041), the research aims to perform time-resolved, volumetric measurements of wildfire combustion processes through a physics-informed closure for tomographic reconstruction. The...
- The National Science Foundation (NSF) awarded a $430,171 Project Grant under the Engineering program (CFDA 47.041) to Worcester Polytechnic Institute (WPI) to develop a new predictive modeling framework that incorporates canopy biomechanics, aerodynamics, and fire-atmosphere interactions to better understand and predict wildfire behavior in forested areas. The research team will use multi-physics modeling and controlled laboratory experiments to simulate how flexible trees interact with wind and...
- The National Science Foundation's Geosciences Program (CFDA 47.050) awarded a $1,000,000 project grant to the University of Illinois on August 1, 2025 for the "EMBER INTELLIGENCE: BUILDING WILDFIRE-RESISTANT COMMUNITIES USING UNMANNED AIRCRAFT SYSTEMS AND DISTRIBUTED DEEP LEARNING" project. The objective is to develop a technological solution called "Ember Intelligence" - a system that uses drone-mounted infrared sensors, edge computing, and artificial intelligence to detect,...
- This three-year Project Grant from the National Science Foundation supports research into wildland fire observation, management, and evacuation systems. With $144,967 in funding, the award will develop intelligent collaborative flying and ground systems to aid in monitoring, responding to, and evacuating areas threatened by wildfires. The awardee is the University Corporation for Atmospheric Research, operating through its National Center for Atmospheric Research facility in Boulder, Colorado....
- This $989,332 Project Grant award from the National Science Foundation (NSF) Biological Sciences program (CFDA 47.074) will develop an advanced artificial intelligence (AI) and machine learning (ML) framework to improve understanding and prediction of wildland fires. The University of Maryland, College Park will integrate multimodal geoscientific data, such as satellite observations, to create a comprehensive dataset for detecting and forecasting wildland fires. The research aims to address...
- This Project Grant awarded by the National Science Foundation (NSF) under the Engineering program (CFDA 47.041) will provide $704,908 to support fundamental research to enable aerial robots smaller than 100 millimeters and weighing less than 100 grams to navigate through cluttered surroundings in the presence of smoke, darkness, dust, fog, and snow. The research will focus on developing sound-based sensing capabilities for these small aerial robots, as traditional vision-based systems struggle...
- This $389,332 federal Project Grant award from the National Science Foundation's Engineering program (CFDA 47.041) aims to develop improved computer models and simulation tools to better predict how wildfires spread in areas where forests and natural areas meet cities and towns, known as the wildland-urban interface (WUI). The key objectives are to: 1) Gain a fundamental physical understanding of how fire interacts with individual structures and materials in urban environments at the local...
- This Project Grant award from the National Science Foundation's Biological Sciences Program (CFDA 47.074) will develop an advanced Artificial Intelligence (AI) and Machine Learning (ML) framework to improve the understanding and prediction of wildland fires. The $867,245 grant, awarded to American University, will integrate multimodal geoscientific data from various platforms to create a comprehensive dataset for wildland fire detection and forecasting. The research team will address key...
- This $1,481,250 Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) will support a collaborative research project at North Carolina State University (NC State) to investigate the impacts of rapid shifts between extreme wet and dry weather conditions on fuel loading and wildfire risk in the Southeast United States. The project will characterize these hydroclimatic events and their relationship to observed wildfires, conduct field experiments to...
This National Science Foundation (NSF) Engineering (CFDA 47.041) award of $194,376 supports research to develop an early wildfire detection system using autonomous unmanned aircraft systems (UAS). The project aims to create a dual-sensing UAS equipped with both visual and olfactory sensors to detect smoke and chemical signatures before visible evidence of a fire emerges. This early warning capability could enable faster and more accurate fire identification, especially in low-visibility conditions. The research proposes a two-phase approach involving machine learning to predict high-risk wildfire areas and robotics to deploy the UAS detection system. This work has broader applications beyond wildfire detection, such as chemical leak monitoring and environmental surveillance. The award was made to Louisiana Tech University, a public research institution, and the project period is from August 15, 2025 to July 31, 2027.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $194.4k | 8/20/25 |