Skylark Labs Deploys AI Fixed FOD Detection at Indian Airports

This article is based on an official press release from Skylark Labs via PR Newswire.

On March 23, 2026, California-based artificial intelligence company Skylark Labs announced the deployment of its Fixed Foreign Object Debris (FOD) detection system at major airports, beginning with locations in India. According to the company’s press release, this rollout marks Skylark Labs’ first major expansion into civil aviation following successful implementations within the defense sector.

The newly deployed system leverages adaptive optical artificial intelligence to provide continuous, 24/7 runway monitoring. This automated approach is designed to replace traditional, manual vehicle patrols, which the company notes are often constrained by operational limitations, human error, and coverage gaps.

Foreign Object Debris, which includes metal fragments, wildlife, tools, and loose aircraft hardware, poses a severe and persistent risk to aviation safety. Ingested debris can destroy turbine blades or puncture tires during critical flight phases. By transitioning to an autonomous, edge-computing model, Skylark Labs intends to mitigate these risks and reduce the costly runway downtime that commercial operators face worldwide.

The Mechanics of Fixed FOD Detection

Transitioning from Manual to Autonomous Monitoring

Traditional FOD management has historically relied on manual runway walks or mobile vehicle patrols. As detailed in the provided research data, these methods are time-consuming and cannot offer continuous, round-the-clock coverage. While alternative automated solutions exist, they frequently depend on expensive radar or LiDAR infrastructure.

Skylark Labs’ fixed deployment utilizes permanently installed optical sensors, referred to as Sentinel AI Cameras. Positioned strategically along runways, taxiways, and aprons, these cameras provide uninterrupted monitoring. When debris is detected, the AI classifies the object by type and size in under five seconds. It then instantly transmits precise GPS coordinates to ground operations and air traffic control, allowing for rapid removal without severe scheduling constraints.

Edge AI and the Network Effect

The core of this technology is the Runway Monitoring Intelligence Layer (RMIL), a proprietary machine-learning platform that powers both the fixed airport installations and the company’s mobile Tracer AI Vehicles. According to Skylark Labs, the AI operates directly on edge devices, known as the Synapse AI Box, eliminating the need for constant cloud connectivity.

This edge-native, brain-inspired architecture allows the system to adapt to varying weather, lighting conditions, and surface anomalies in real-time. Furthermore, Skylark Labs highlights a “global network effect.” Intelligence gathered at a single airport, such as newly discovered debris signatures or emerging false-positive patterns, is instantly synchronized across the entire global network without requiring manual AI model retraining.

“Because the same intelligence layer runs across our entire network, carriers, airfields, and mobile vehicles, every deployment makes the whole system smarter,” stated Dr. Amarjot Singh, Founder and CEO of Skylark Labs, in the press release.

From Military Testing to Commercial Aviation

Proven in Extreme Environments

Skylark Labs’ entry into the commercial sector follows rigorous testing in demanding military environments. Prior to this commercial rollout, the company deployed its mobile Tracer AI Vehicles across two active Indian Navy airfields over a two-year period.

In March 2026, the company successfully demonstrated its fixed FOD detection system aboard an Indian Navy aircraft carrier. During this deployment, the AI learned to filter out extreme environmental noise unique to maritime operations, including salt spray, heavy vibrations, glare, and constant background motion. The technology is also currently being expanded to Indian Air Force sites.

“Commercial airports operate under extreme operational pressure. Every second counts, and debris is not an option,” Dr. Singh noted regarding the commercial deployment. “Our fixed detection system eliminates the constraints of mobile patrols while delivering the same adaptive intelligence.”

AirPro News analysis

The global market for FOD detection and runway safety is currently valued at approximately $14 billion, driven by an urgent need for modernization across both defense forces and commercial airports. The aviation industry spends billions of dollars annually on FOD-related damage, and every second of runway downtime carries a significant financial penalty for commercial operators.

We observe that Skylark Labs’ approach, leveraging brain-inspired AI architectures developed from DARPA research, represents a notable shift in aviation safety infrastructure. By building longitudinal runway safety profiles and mapping recurring debris hotspots, airports can transition from reactive debris removal to predictive maintenance planning. If the system’s compounding network advantage holds true, it could offer a highly scalable and cost-effective alternative to traditional radar and LiDAR systems, fundamentally changing how airports manage surface safety.

Frequently Asked Questions (FAQ)

What is Foreign Object Debris (FOD)?

Foreign Object Debris (FOD) refers to any foreign substance, debris, or article in an aviation environment that could potentially cause damage to aircraft. Common examples include metal fragments, wildlife, tools, and loose aircraft hardware.

How fast does the Skylark Labs system detect debris?

According to the company, the AI classifies debris by type and size in under five seconds, instantly transmitting GPS coordinates to ground operations.

Does the system require an active internet connection to function?

No. The AI operates directly on edge devices (the Synapse AI Box) and does not require constant cloud connectivity to detect and classify debris.

Sources: Skylark Labs via PR Newswire