Scope
Description
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.
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Contract 1
Supplier
Contract value
- £29,830.28 excluding VAT
- £35,796.33 including VAT
Below the relevant threshold
Date signed
28 May 2025
Contract dates
- 29 May 2025 to 28 February 2026
- 9 months, 3 days
Main procurement category
Services
CPV classifications
- 30211400 - Computer configurations
- 72221000 - Business analysis consultancy services
Procedure
Procedure type
Below threshold - limited competition
Supplier
University of Essex
WIVENHOE PARK, WIVENHOE, COLCHESTER
COLCHESTER
CO4 3SQ
United Kingdom
Contact name: MARCIA KLINCKE
Email: marcia.klincke@essex.ac.uk
Region: UKH34 - Essex Haven Gateway
Small or medium-sized enterprise (SME): Yes
Voluntary, community or social enterprise (VCSE): No
Contract 1
Contracting authority
TRINITY HOUSE
- Public Procurement Organisation Number: PXWM-8968-LPJY
TRINITY HOUSE, TOWER HILL, LONDON
LONDON
EC3N 4DH
United Kingdom
Region: UKI31 - Camden and City of London
Organisation type: Public authority - central government