Imagine a team of underwater drones that act like a coordinated squad of divers, but without the risk or high cost. They use special lasers to 'taste' the chemical makeup of sunken objects and high-tech cameras to spot cracks or rust. A solar-powered buoy acts as their home base and charging station, sending all the data back to a computer on shore.
Underwater monitoring is currently too expensive, dangerous, and logistically difficult because it relies on human divers. Saltwater corrosion and poor visibility make it hard to track the degradation of submerged assets without constant, costly manual intervention.
A modular, torpedo-shaped AUV equipped with LIBS and QCL sensors for chemical mapping and photogrammetry tools. This is supported by a solar-powered surface buoy and a submerged docking station.
If you are a government agency dealing with expensive and dangerous diver-led inspections of shipwrecks — this project developed a swarm of AUVs that provides remote chemical mapping and visual degradation detection. This reduces the need for human divers in risky environments.
If you are a maintenance firm dealing with the high cost of monitoring submerged metal structures for corrosion — this project developed a LIBS sensor for in-situ chemical analysis of elements like Fe, Al, Zn, and Cu. This allows for automated monitoring without manual water sampling.
If you are a research center dealing with the logistical challenge of long-term underwater data collection — this project developed a submerged docking station and solar-powered buoy. This enables long-duration missions with minimal human intervention.
It replaces expensive and dangerous traditional diver inspections with autonomous underwater vehicles (AUVs) and a solar-powered surface buoy to minimize human intervention. Based on available project data, it uses renewable energy to reduce both investment and operating costs.
Yes, the project utilizes a 'swarm' of self-coordinated AUVs that communicate bilaterally to achieve a common surveying goal. This allows for coordinated scanning of heritage sites through edge processing and dynamic path planning.
Based on available project data, specific licensing terms are not mentioned, but the project involves 6 SMEs and 5 industrial partners, suggesting a strong focus on commercializable technology.
The system uses a data management system based on FAIR principles to ensure data reuse. Information is collected by a mother BUOY and sent to a remote onshore monitoring station for real-time visual analysis.
The project period runs from 2024-01-01 to 2026-12-31. The first 15 months focused on technical specifications and system design.
The consortium is heavily weighted toward commercial application, with an industry ratio of 38% and 6 SMEs among the 13 partners. This mix of 5 industrial entities, 3 universities, and 4 research centers across 5 countries indicates a strong pipeline for moving the technology from the lab to the market.
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