Rome, New York – U.S. Air Force researchers are urging industry to use artificial intelligence (AI), machine learning and machine reasoning as they develop enabling technologies for new high-performance computing (HPC) systems for next-generation target tracking that uses many data sources.
Officials at the Air Force Research Laboratory's Intelligence Directorate in Rome, New York, issued a pre-solicitation (FA875024S7004) on Tuesday for the Advanced Tracking Architecture with AI (ATA-AI) project.
The ATA-AI project is seeking algorithms and applications from industry for the processing and acceleration of 3D pixel, vector and point clouds on high-performance computing systems, as well as how to use AI and machine learning for identification, classification and pattern learning from signal and image intelligence.
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The project also calls for industry to develop ways to process signals from satellites, inertial navigation, RF identification trackers and telematics-based data into traffic tracking that can measure how adversaries are using communication lines.
Additionally, the ATA-AI target tracking project calls on industry to develop methods to process cell phone, satellite and inertial navigation, RF identification trackers, accelerometers, altimeters, and personal fit devices into graphical data that can be used by emergency responders to locate people in disaster areas based on their last known location from their personal devices.
Air Force researchers are now soliciting white paper submissions from industry. Promising white paper submissions will be invited to submit formal proposals. The program is expected to award multiple grants worth about $99 million over the next four years.
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Interested companies should email the white paper to Carolyn Schaaf at the Air Force. [email protected] Peter Loche [email protected] By November 30, 2028.
For technical questions or inquiries, please email Carolyn Sheaff. [email protected] Peter Loche [email protected]For business enquiries please email Amber Buckley. [email protected].
For more information, visit https://sam.gov/opp/6c4457cee0ca48f09c0331e635711c53/view
