MARINA · Project

Laser Sensor System That Detects Hidden Ocean Obstacles Before Ships Hit Them

transportPilotedTRL 8

Imagine driving at night with headlights that can only see 50 metres ahead — that's basically what ships deal with when it comes to spotting floating debris, submerged containers, or even whales. MARINA built a laser-based detection system (think of it as maritime night-vision on steroids) that scans the ocean surface up to 2 nautical miles ahead and uses AI to classify what it finds. It tells the crew: "that's driftwood, that's a container, that's a marine mammal" — in real time. The goal was to take this from a working prototype all the way to a product ready for commercial sale.

By the numbers

1 in 10

Ships forced to unplanned dry dock annually due to collisions

€400,000

Average cost per collision incident

2nm

Detection range ahead of the vessel

€786m

Projected accumulated revenue 5 years post-project

Industry partners across 5 countries

SMEs in the consortium

The business problem

What needed solving

Collisions remain the most frequent and costliest type of accident in maritime transport. One in ten ships is forced into unplanned dry dock every year, costing an average of €400,000 per incident. Semi-submerged and fully submerged objects — driftwood, containers, marine mammals — go completely undetected by current radar and sensor systems, creating a dangerous blind spot especially as shipping lanes get busier and autonomous vessels enter service.

The solution

What was built

The consortium built a LADAR (laser detection and ranging) sensor system that scans the ocean surface up to 2 nautical miles ahead of a ship and uses machine learning to detect and classify obstacles in real time. They also developed a digital LADAR training programme to prepare crews for operating the system. The project aimed to bring the technology from TRL8 to TRL9 through real-life operational testing.

Audience

Who needs this

Container shipping lines with vessels on busy trade routesAutonomous vessel developers needing reliable obstacle detectionPort authorities and vessel traffic services managing congested waterwaysMarine insurance companies looking to reduce collision claimsOffshore energy operators with vessels navigating near platforms and infrastructure

Business applications

Who can put this to work

Commercial Shipping

enterprise

Target: Shipping lines and fleet operators running container ships, tankers, or bulk carriers

If you are a fleet operator dealing with collision incidents that force 1 out of 10 ships into unplanned dry dock every year at an average cost of €400,000 per incident — MARINA developed a LADAR sensor system that detects semi-submerged and fully submerged objects up to 2nm ahead of your vessel. It uses machine learning to classify obstacles in real time, letting your crew take evasive action before impact. This directly reduces dry dock costs and protects your environmental compliance record.

Autonomous Shipping & Maritime Tech

any

Target: Companies developing autonomous or remotely operated vessels

If you are building autonomous shipping solutions and need reliable obstacle detection that goes beyond radar and AIS — MARINA's LADAR system provides the kind of surface-layer sensing that autonomous navigation requires. The AI-powered object detection and classification fills a critical gap in current sensor suites. With the system designed to reach TRL9, it was built for integration into real vessel operations, not just lab demonstrations.

Port & Vessel Traffic Management

enterprise

Target: Port authorities and vessel traffic service (VTS) operators

If you manage busy shipping lanes or port approaches where dense traffic and tight schedules increase collision risk — MARINA's sensor technology offers an additional detection layer for objects that standard radar misses. Semi-submerged containers and debris are invisible to conventional systems but detectable by LADAR. This means fewer accidents in your jurisdiction, less pollution, and lower insurance and liability exposure.

Frequently asked

Quick answers

What does this system cost, and what's the return on investment?

The project data does not specify a unit price for the LADAR system. However, the objective states that the average collision incident costs €400,000 in unplanned dry dock time. Even preventing one collision per vessel over several years would likely pay for the sensor many times over. The consortium projected accumulated revenue of €786m over 5 years post-project, suggesting they expect strong market demand at a viable price point.

Can this work at industrial scale across a fleet?

The system was designed for real vessel operations, with the project aiming to qualify the product in real-life conditions to reach TRL9. The consortium also developed a digital LADAR training programme, which signals they were preparing for fleet-wide deployment where multiple crews would need to operate the system. The all-industry consortium of 5 partners across 5 countries supports scalable production.

What's the IP situation — can I license or buy this technology?

The LADAR technology is proprietary, developed by the consortium led by O.M. Offshore Monitoring Limited (Cyprus). The project was funded as an Innovation Action specifically to bring this to market. Licensing or purchase arrangements would need to be negotiated directly with the coordinator. Based on available project data, the consortium was actively preparing for commercialization.

Does this meet maritime safety regulations?

The project aimed to qualify the LADAR system in real-life operations to reach TRL9, which implies regulatory testing and certification were part of the plan. The system addresses collision avoidance, which falls under IMO safety regulations. Based on available project data, the consortium was working toward full regulatory compliance for commercial deployment.

How does this integrate with existing bridge systems?

The LADAR system combines real-time processing with AI-based object detection and classification, designed to complement existing radar and navigation systems. It specifically targets semi-submerged and submerged objects that current sensors miss. Based on available project data, integration with standard bridge equipment was a design consideration for commercial viability.

What's the detection range and what can it spot?

The system detects and classifies objects in the ocean surface layer at a range of up to 2 nautical miles ahead of the ship. It can identify other ships, driftwood, marine mammals, and submerged containers — all objects that conventional radar struggles with or misses entirely. Classification is done automatically using machine learning algorithms.

Consortium

Who built it

This is a lean, all-industry consortium of 5 partners across 5 countries (Anguilla, Cyprus, France, Norway, UK) — notably zero universities or research institutes. That's a strong commercialization signal: every partner has a business interest in bringing this to market. Four of the five are SMEs, led by O.M. Offshore Monitoring Limited from Cyprus. The geographic spread covers key maritime nations (Norway and UK in particular), and the 100% industry ratio means the consortium was built to sell a product, not publish papers. For a business buyer, this means the technology was developed by people who understand commercial shipping operations, not just laboratory conditions.

O.M. OFFSHORE MONITORING LIMITEDCoordinator · CY
LADAR LIMITEDparticipant · AI
G.M.S. GLOBAL MARITIME SERVICES LIMITEDparticipant · UK
HJELMSTAD ASparticipant · NO

How to reach the team

O.M. Offshore Monitoring Limited (Cyprus) — contact via project website or SciTransfer introduction

Order a report on this consortium See O.M. OFFSHORE MONITORING LIMITED profile →

Next steps

Talk to the team behind this work.

Want to evaluate MARINA's LADAR system for your fleet or integrate it into your maritime tech stack? SciTransfer can arrange a direct introduction to the development team and provide a detailed technology brief.

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