Award

Ask AI about this notice

Summarise, research or assess it with AI

View Markdown

Share this notice

Send this contract to a colleague

Development of computer vision (AI) tools for REM of pelagic Fisheries

Scottish Government

This public procurement record has 3 releases in its history.

Award

20 Oct 2026 at 01:00

PCS Notice - Website Contract Award Notice
Tender

03 Apr 2026 at 01:00

PCS Notice - Website Contract Notice
Planning

09 Jan 2026 at 00:00

PCS Notice - Website Prior Information Notice
Summary of the contracting process

The Scottish Government commissioned research and development of computer-vision tools to analyse CCTV from pelagic fishing vessels subject to remote electronic monitoring in Scottish waters. The work is intended to help the Marine Directorate detect possible regulatory infringements and estimate bycatch, while informing future monitoring requirements. It covers a system that can process video, identify and count relevant fishing events and animals, and classify and measure vulnerable or non-target species, including marine mammals, sharks and rays, seabirds and non-target fish. The scope also includes a video-viewing and annotation interface, camera calibration support, and tools to identify activity on deck or in the water and anonymise footage. The system is to cope with differing vessel layouts, lighting, occlusion and other video challenges, with human review where identification is uncertain.

The procurement is complete and the contract is active. The Scottish Government selected James Freese for the single lot; the contract was signed on 11 October 2026 and is valued at £68,750. The contract period runs from 1 August 2026 to 30 November 2027. The competition used an open procedure, with bids due by 19 May 2026. Five bids were received, all from small or medium-sized enterprises; four came from EU-based suppliers and one from outside the EU. The award was for the full requirement, including developing and testing the video-analysis tools and supplying suitable footage. The procurement documents included economic and technical selection criteria, but the recorded information does not set out their detailed thresholds or the award scoring basis.

For suppliers considering similar future work for the Scottish Government, this award shows demand for applied computer vision and AI in fisheries monitoring, combining algorithm development with practical understanding of CCTV from working pelagic vessels. A credible competitor would need access to representative footage from at least three vessels and the ability to arrange that access through its own monitoring operations or a partnership with a monitoring provider or fishing businesses. Useful capabilities include detecting, classifying and measuring animals in difficult footage; handling different vessel configurations, lighting, occlusion and camera distortion; and providing human review when automated confidence is low. The work also calls for a usable video annotation interface, camera calibration support, and privacy safeguards including facial blurring and metadata anonymisation. Solutions need to be maintainable, upgradeable and integrable with remote-monitoring review software.

How relevant is this notice?

Notice Information

Notice Title

Development of computer vision (AI) tools for REM of pelagic Fisheries

Notice Description

This requirement is for the development of computer vision (AI) tools for pelagic fisheries CCTV. The project will consider the development of an automated image analysis system to isolate (and quantify) activities (and animals) associated with pelagic fisheries, with a focus on the capture of UCB species in CCTV-observed fishing events of a given subset of vessels subject to mandatory Remote Electronic Monitoring (REM). The project will focus initially on counts of UCB events, but the intention would be to gather biological data on the individual animals caught e.g. classification to the finest possible level and estimates of size. The results will be used by Scottish Government Marine Directorate (SGMD) Compliance (for regulation infringement detection) and SGMD Science for bycatch rate estimation, as part of wider observer programmes, and to inform future revisions to REM technical specifications. The ultimate goal of this development work is to design, implement and test a UCB detection and classification system, including the supply of relevant CCTV footage from vessels in Scottish Waters.

Lot Information

Lot 1

This system should be capable of being integrated into REM review software to automatically process and analyse video sequences from fishing trips to identify relevant events, count UCB events, and subsequently identify, count and measure all UCB individuals. It is important to point out that such a system should also be able to handle a realistic range of environmental noise such as variability of the location within the field of view, due to differing vessel layouts, in which events / animals have been detected, occlusions, pose variations, and lighting conditions. It is envisaged that this will be done in a probabilistic way, and that human intervention and further analysis will be suggested when the uncertainty exceeds a preset threshold (as there will be sections of footage in which identification will be very difficult due to occlusion). The system should be easily maintained and upgraded and will remain the property of the Scottish Government. This project will consider the development of interim stages towards fully automated image analysis tools for identifying and characterising atypical fishing activity events indicative of UCB species presence. In addition, the AI tools will subsequently determine the number (and, potentially, the size) of a subset of UCB observations via cameras as part of the mandated REM of eligible pelagic fishing vessels in Scottish waters. Attention would focus initially on the recorded numbers of UCB events as well as counts and size measurements for sea mammals (inc. cetaceans, seals), sharks / skates / rays, seabirds, and non-target bony fish. The results / products will be used by SGMD scientists to increase the efficiency of video review tasks, optimise the technical specifications of electronic monitoring systems for this fishery, estimate bycatch mortality rates, and identify fishing practices where mitigation measures may be required to protect vulnerable species. Specifically, this study will aim to: a) Develop a graphical user interface (GUI) to facilitate the viewing, sharing, collation, analysis and annotation of CCTV video footage from pelagic fishing vessels; b) Instruct and assist with the calibration of camera systems (if required) to ensure field-of-view and lens distortion correction in length measurements; c) Develop detection algorithms to detect, classify (to the most detailed taxonomic level feasible), and measure individuals of UCB species passing through the dewatering separator from representative video footage; d) Develop detection algorithms to determine when activity is taking place on-deck or in-water in relation to catch handling and apply facial recognition to anonymise the recorded footage; e) Develop detection algorithms to detect, classify (at the minimum level of mammals, elasmobranchs, non-target fish, and seabirds) and measure (inter alia) individuals of ETP species on deck or in-water from representative video footage. Suppliers should provide imagery from a minimum of 3 vessels. However, it is desirable that imagery is inclusive of both freezer vessels and refrigerated / chilled water vessels, vessels with differing deck layouts and catch handling configurations; and vessels from multiple flag states. Imagery provided to Scottish Government for annotation within the GUI must be anonymised regarding its metadata and have had facial recognition blurring methods applied. Suppliers must arrange to have access to suitable CCTV footage from Scottish Waters, either within their own data storage architecture (if they are an REM service provider) or via partnership with an REM service provider / pelagic fishing boats. It is anticipated that the project will be entirely computer lab-based, as all required video footage is being collected on an on-going basis as a matter of routine.

Notice Details

Publication & Lifecycle

Open Contracting ID
ocds-r6ebe6-0000820119
Publication Source
Public Contracts Scotland
Latest Notice
https://www.publiccontractsscotland.gov.uk/search/show/search_view.aspx?ID=OCT566967
Current Stage
Award
All Stages
Planning, Tender, Award

Procurement Classification

Notice Type
PCS Notice - Website Contract Award Notice
Procurement Type
Standard
Procurement Category
Services
Procurement Method
Open
Procurement Method Details
Open procedure
Tender Suitability
Not specified
Awardee Scale
SME

Common Procurement Vocabulary (CPV)

CPV Divisions

71 - Architectural, construction, engineering and inspection services

73 - Research and development services and related consultancy services

CPV Codes

71354500 - Marine survey services

73112000 - Marine research services

Notice Value(s)

Tender Value
£75,000 Under £100K
Lots Value
Not specified
Awards Value
Not specified
Contracts Value
£68,750 Under £100K

Notice Dates

Publication Date
20 Oct 20261 weeks ago
Submission Deadline
19 May 2026Expired
Future Notice Date
31 Jan 2026Expired
Award Date
Not specified
Contract Period
1 Aug 2026 - 30 Nov 2027 1-2 years
Recurrence
Not specified

Notice Status

Tender Status
Complete
Lots Status
Complete
Awards Status
Not Specified
Contracts Status
Active

Buyer & Supplier

Contracting Authority (Buyer)

Main Buyer
Scottish Government
Contact Name
Available with D3 Tenders Premium →
Contact Email
Available with D3 Tenders Premium →
Contact Phone
Available with D3 Tenders Premium →

Buyer Location

Locality
EDINBURGH
Postcode
Not specified
Postcode Area
Not specified
Country
Not specified
Major Region (ITL 1)
Not specified
Basic Region (ITL 2)
Not specified
Small Region (ITL 3)
Not specified
Delivery Location
TLM Scotland
Local Authority
Not specified
Electoral Ward
Not specified
Westminster Constituency
Not specified

Supplier Information

Number of Suppliers
1
Supplier Name

James Freese

Further Information

Notice Documents

Open Contracting Data Standard (OCDS)

View full OCDS Record for this contracting process

JSON Markdown

The Open Contracting Data Standard (OCDS) is a framework designed to increase transparency and access to public procurement data in the public sector. It is widely used by governments and organisations worldwide to report on procurement processes and contracts.

Loading OCDS record...