Aircraft carrier flight decks present unique FOD challenges that ground-based airfields do not. Constant aircraft movement, extreme weather exposure, salt spray, vibrations, and high operational tempo make manual FOD walks—where sailors physically walk the deck before flight operations—time-consuming, dangerous, and prone to human error. A single piece of undetected debris can damage jet engines, puncture tires, or endanger personnel, with consequences magnified in an at-sea environment where immediate repair and resupply are not possible.
Skylark Labs' Fixed FOD Detection system is powered by the Runway Monitoring Intelligence Layer—the same adaptive AI framework deployed across Skylark Labs' mobile Tracer AI Vehicles and fixed commercial airport installations. Each deployment runs its own local intelligence layer that learns from debris detections, false positive patterns, and environmental conditions specific to that environment. Aboard the carrier, this means the system continuously learns to filter noise unique to at-sea operations—salt spray, vibrations, glare, shadows, and background motion—while sharing those learnings across the entire network. Insights learned on the carrier deck instantly strengthen detection at land-based airfields, and vice versa, creating a unified FOD intelligence ecosystem that improves with every deployment across every environment.
During the demonstration, strategically positioned cameras monitored the carrier deck in real time, detecting and classifying debris without interrupting flight operations. When debris was detected, precise deck coordinates were instantly transmitted to flight deck crew and operations teams, enabling rapid response. Debris was automatically classified by type—metal fragments, rubber, foreign objects—supporting safety investigations and maintenance planning. The system operated reliably under real-world at-sea conditions, validating its ruggedized design for the harshest naval aviation environments.
Over time, the Runway Monitoring Intelligence Layer builds a longitudinal debris map of the carrier deck, identifying recurring hotspots, tracing debris origins to specific aircraft operations or maintenance activities, and enabling predictive maintenance strategies that prevent future incidents. Automated report generation eliminates manual documentation, giving operations teams actionable safety intelligence without administrative burden.
"Aircraft carriers are among the most unforgiving environments in naval aviation," said Amarjot Singh, Founder and CEO of Skylark Labs. "This demonstration validated that our fixed detection system can continuously monitor carrier decks, filter environmental noise unique to at-sea operations, and deliver precise alerts so flight crews can act immediately. Because the same intelligence layer runs across our entire network—carriers, airfields, and mobile vehicles—every deployment makes the whole system smarter. The results give us strong confidence to expand this capability across naval and commercial carrier operations globally."
The successful demonstration establishes Skylark Labs' fixed FOD detection capability as proven for both land-based and carrier aviation environments, opening a significant expansion opportunity across global naval forces and maritime aviation operators.
About Skylark Labs
Skylark Labs is an AI company building edge-native, self-learning intelligence platforms for defense, transportation, and critical infrastructure. Headquartered in Menlo Park, California, with operations in India, the company develops adaptive AI systems designed to operate in field-deployed, air-gapped, and resource-constrained environments. Its platforms learn on-device from real-world conditions, improve after deployment, and can share intelligence across distributed systems to create collaborative operational networks. Skylark Labs' solutions are used by defense forces, government agencies, and infrastructure operators across maritime security, airfield monitoring, highway intelligence, and industrial safety applications. For more information, visit www.skylarklabs.ai.
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SOURCE Skylark Labs, Inc.
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