The Coast Guard published a notice of intent on October 26 announcing a Cooperative Research and Development Agreement with LOOKOUT to assess Super Intelligence (SI) situational awareness tools for automated target detection and to establish a reliable coverage-factor value supporting data-driven Lateral Range Curve results in search and rescue. The notice, docketed USCG-2026-0374, says the service uses varied sensor inputs across multiple units and assets, and that SI tools may let it automatically detect, classify and track targets while handling low light, fog, precipitation and rough sea states. Requirements for proposed tools are specific: high technology readiness level, commercially available, self-contained, portable, capable of edge computing and compatible with video-feed-agnostic sensors. Stated goals include benchmarking, evaluating system interoperability and proposing data-handling best practices, plus characterising system confidence and operational performance to build a measurable evaluation tool that would lower the barrier to integrating such tools. Comments are due November 25, 2026 via regulations.gov under USCG-2026-0374, and other federal entities with relevant capabilities may propose similar CRADAs.
Our takeThe requirement that carries the technical weight is the coverage factor. A lateral range curve is only as good as the detection probability fed into it, so a vendor has to state how the detector performs against sea state, fog and target size rather than quote one accuracy figure. Edge-only deployment and sensor-agnostic video input also rule out designs that assume a fat backhaul. What to watch after November 25 is whether the evaluation method itself becomes public; an unpublished benchmark would leave the same integration barrier in place.