ST LOUIS — L3Harris Technologies announced a contract May 22 from the Intelligence Advanced Research Projects Activity to provide technology to help characterize and predict human mobility.
Under the IARPA contract in support of the Hidden Activity Signal and Trajectory Anomaly Characterization (HAYSTAC) program, L3Harris will conduct modeling and simulation studies aimed at generating and analyzing human activities based on data obtained by satellites, GPS, Bluetooth and other sources.
By simulating human activity in various locations and cultures, the technology could support disaster relief efforts. Automobile GPS data could be analyzed, for example, to detect anomalies caused by a bridge collapse and trigger an autonomous response.
Modeling and Simulation
L3Harris has developed modeling and simulation analysis capabilities for four decades. In recent years, the company has used that expertise to “understand and analyze big data,” said Ed Zoiss, L3Harris Space and Airborne Systems president, said in a statement. “Our world-class research team also includes small business and academic experts who are poised to make breakthroughs in developing a system to characterize and predict human mobility.”
Working with partners, L3Harris “will use simulated information to develop complex models mirroring realistic human behavior and social networks,” according to the L3Harris news release. The models will show, for example, how people routinely move through the world and interact with one another.
Subtle Anomalies
Through this technology, the intelligence community and the Department of Defense seek to identify subtle anomalies that may be important to agencies responding to conflicts, humanitarian crises or natural disasters.
“While bringing HAYSTAC to fruition will be a multi-year process, once it’s complete we’ll have reframed how we look at activity in the world,” Jack Cooper, IARPA HAYSTAC program manager, said in a statement. “And it won’t be a static concept of where things are on a map, but a dynamic one based on how they’re moving and what’s out of the ordinary.”
IARPA established the HAYSTAC program in 2022 to fund basic research and development of “novel capabilities that produce large-scale microsimulations of fine-grained human movement and create AI reasoning engines capable of both identifying abnormal movement trajectories and generating normal ones,” according to the HAYSTAC broad agency announcement.
Phase one of the HAYSTAC program is scheduled to end in late 2024. Subsequent phases of the program are expected to conclude in 2026.
