Imagine a high-tech flashlight that can see through water to find hidden oil. While most tools only see oil floating on top, this system uses special laser light to spot oil that has sunk. It works like a molecular fingerprint scanner to tell exactly what kind of pollution is in the water.
Traditional radar and cameras only detect surface oil, missing the 30-40% of hydrocarbons that sink. This leads to inaccurate spill quantification and ineffective cleanup strategies.
Three versions of the OWL system: Sea OWL (shipborne), Air OWL (airborne), and Elf (drone-mounted), all utilizing HLIF LiDAR and AI for oil classification.
If you are an energy company dealing with undetected leaks in offshore rigs — this project developed the OWL system that detects submerged oil which can make up 30-40% of a spill. This allows for faster containment and accurate quantification of the leak.
If you are an enforcement agency dealing with illegal oil dumping — this project developed a range of sensors (Sea, Air, and Elf) that classify oil types using AI. This provides the evidence needed to identify the source of pollution in real-time.
If you are a cleanup contractor dealing with inefficient recovery due to invisible submerged oil — this project developed HLIF LiDAR sensors that map the water column. This ensures cleanup crews target the actual location of the oil rather than just the surface.
Based on available project data, specific pricing and cost structures are not disclosed.
Yes, the project developed three distinct classes: Sea OWL for ships, Air OWL for aircraft, and Elf for drones, indicating scalability across different deployment platforms.
Based on available project data, the HLIF LiDAR technique is described as proprietary to Ocean Visuals.
The system integrates with meteorological data to create prediction models and uses AI and machine learning for in-situ classification of oil types.
The project period is from 2024-07-01 to 2026-06-30.
The consortium is highly streamlined and industry-focused, consisting of 2 SMEs from Norway and Estonia. With a 100% industry ratio and no university or research institute partners, the project is driven by commercial application and rapid product development rather than academic exploration.
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