ST LOUIS — L3Harris Technologies announced a contract May 22 from the Intelligence Advanced Research Projects Activity to supply technology to assist 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 geared toward 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 may very well be analyzed, for instance, to detect anomalies attributable to a bridge collapse and trigger an autonomous response.
Modeling and Simulation
L3Harris has developed modeling and simulation evaluation capabilities for 4 many years. Lately, the corporate has used that expertise to “understand and analyze big data,” said Ed Zoiss, L3Harris Space and Airborne Systems president, said in a press release. “Our world-class research team also includes small business and academic experts who’re 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,” in line with the L3Harris news release. The models will show, for instance, how people routinely move through the world and interact with each other.
Subtle Anomalies
Through this technology, the intelligence community and the Department of Defense seek to discover subtle anomalies that could be necessary to agencies responding to conflicts, humanitarian crises or natural disasters.
“While bringing HAYSTAC to fruition shall be a multi-year process, once it’s complete we’ll have reframed how we have a look at activity on the earth,” Jack Cooper, IARPA HAYSTAC program manager, said in a press release. “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 abnormal.”
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 able to each identifying abnormal movement trajectories and generating normal ones,” in line with the HAYSTAC broad agency announcement.
Phase one among the HAYSTAC program is scheduled to finish in late 2024. Subsequent phases of this system are expected to conclude in 2026.