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| Source: | Find a Tender Service (FTS) |
| Notice Type: | Award notice |
| Buyer: | TRINITY HOUSE |
| Main Category: | Services |
| Procurement Method: | Below threshold - limited competition |
| Tender Status: | Closed |
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| Release Date: | 3 July 2025 |
| Application Deadline: | — |
| Procurement ID (OCID): | ocds-h6vhtk-055831 |
| Notice Reference: | 037063-2025 |
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Awarded to
| Award status: | Active |
As the adoption of the Maritime Autonomous Surface Ships (MASS) technology continues to grow, it is crucial to ensure the seamless interaction between MASS and the existing maritime infrastructure. Therefore, it is essential to ascertain whether machine vision systems, integral to the autonomy of MASS, perceive AtoN accurately enough to guarantee safe and efficient operations. GRAD in collaboration with the University of Essex (UoE), recently completed a research project, which demonstrated the feasibility of using machine vision systems for detecting and classifying AtoNs, with high accuracy. To view this notice, please click here: https://trinityhouse.delta-esourcing.com/delta/viewNotice.html?noticeId=962252395
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