Smart fisheries technologies for an efficient, compliant and environmentally friendly fishing sector

Informazioni relative al progetto

SMARTFISH

ID dell’accordo di sovvenzione: 773521

DOI 10.3030/773521

Progetto chiuso

Data della firma CE 9 Ottobre 2017

Data di avvio 1 Gennaio 2018

Data di completamento 31 Dicembre 2022

Finanziato da

• SOCIETAL CHALLENGES - Food security, sustainable agriculture and forestry, marine, maritime and inland water research, and the bioeconomy

Costo totale € 6 944 650,38

Contributo UE € 5 976 764,51

Coordinato da

SINTEF OCEAN AS
Norway

Risultati finali

Documents, reports (13)

Promotion report and material WP8

Report of promotion activities and promotional material aimed at West of Scotland and Northern North Sea fisheries

Test and promotion report WP9

Report from test and demonstration activities in southern North Sea and Celtic Sea fisheries

Test and demonstration report WP8

Report from test and demonstration activities in West of Scotland and Northern North Sea fisheries

FishData system specification

FishData system specification.

Promotion report and material WP9

Report of promotion activities and promotional material aimed at southern North Sea and Celtic Sea fisheries

Promotion report and material WP6

Report of promotion activities and promotional material aimed at Norwegian and Barents Sea fisheries

Test and demonstration report WP7

Report from test and demonstration activities in Mediterranean and Black Sea fisheries

Test and demonstration report WP6

Report from test and demonstration activities in Norwegian and Barents Sea fisheries

Promotion report and material WP7

Report of promotion activities and promotional material aimed at Mediterranean and Black Sea fisheries

Promotion report and material WP10

Report of promotion activities and promotional material aimed at Kattegat and Skagerrak fisheries

GA and progress report Y4

Periodic progress report and minutes of the General assembly year 4

Test and demonstration report WP10

Report from test and demonstration activities in Kattegat and Skagerrak fisheries

Updated Data Management Plan

The Data Management Plan will be updated periodically throughout the project.

Websites, patent fillings, videos etc. (1)

Internet presence

Internet portal and social media pages.

Open Research Data Pilot (1)

Data Management Plan

First version/iteration of Data Management Plan, to be updated periodically throughout the duration of the project.

Pubblicazioni

Peer reviewed articles (9)

Estimating catch rates in real time: Development of a deep learning based Nephrops (Nephrops norvegicus) counter for demersal trawl fisheries

Autori: Ercan Avsar, Jordan P. Feekings, Ludvig Ahm Krag
Pubblicato in: Frontiers in Marine Science, Numero Volume 10, 2023, ISSN 2296-7745
Editore: Frontiers Media AS
DOI: 10.3389/fmars.2023.1129852

Automatic length estimation of free-swimming fish using an underwater 3D range-gated camera

Autori: Petter Risholm, Ahmed Mohammed, Trine Kirkhus, Sigmund Clausen, Leonid Vasilyev, Ole Folkedal, Øistein Johnsen, Karl Henrik Haugholt, JensThielemann
Pubblicato in: Aquacultural Engineering, Numero Vol 97, 2022, ISSN 0144-8609
Editore: Elsevier BV
DOI: 10.1016/j.aquaeng.2022.102227

Species separation efficiency and effect of artificial lights with a horizonal grid in the Basque bottom trawl fishery

Autori: E.Cuendea.Herrmann, M.Sistiaga, M.Basterretxea, A.Edridge, E.K.Mackenzie, R.J.Kynoch, G.Diez
Pubblicato in: Ocean and Coastal Management, 2022, ISSN 0964-5691
Editore: Pergamon Press Ltd.
DOI: 10.1016/j.ocecoaman.2022.106105

A Deep Learning Approach to Assist Sustainability of Demersal Trawling Operations

Autori: Maria Sokolova, Adrià Mompó Alepuz,Fletcher Thompson,Patrizio Mariani,Roberto Galeazzi and Ludvig Ahm Krag
Pubblicato in: Sustainability, 2021, ISSN 2071-1050
Editore: MDPI Open Access Publishing
DOI: 10.3390/su132212362

Towards sustainable demersal fisheries: NepCon image acquisition system for automatic Nephrops norvegicus detection

Autori: Maria Sokolova, Fletcher Thompson, Patrizio Mariani, Ludvig Ahm Krag
Pubblicato in: PLoS One, 2021, ISSN 1932-6203
Editore: Public Library of Science
DOI: 10.1371/journal.pone.0252824

Motion stereo at sea: Dense 3D reconstruction from image sequences monitoring conveyor systems on board fishing vessels

Autori: Mark Fisher, Geoffrey French, Artjoms Gorpincenko, Helen Holah, Lauren Clayton, Rebecca Skirrow, Michal Mackiewicz
Pubblicato in: IET Image Processing, Numero Volume 17, Numero 2, 2022, Pagina/e 349-361, ISSN 1751-9659
Editore: Institute of Electrical Engineers
DOI: 10.1049/ipr2.12636

Test and development of a sediment suppressing system for catch monitoring in demersal trawls

Autori: MariaSokolova, Finbarr Gerard O’Neill, EstherSavina, Ludvig AhmKrag
Pubblicato in: Fisheries Research, Numero Volume 251, 2022, ISSN 0165-7836
Editore: Elsevier BV
DOI: 10.1016/j.fishres.2022.106323

Deep neural networks for analysis of fisheries surveillance video and automated monitoring of fish discards

Autori: Geoff French, Michal Mackiewicz, Mark Fisher, Helen Holah, Rachel Kilburn, Neil Campbell, Coby Needle
Pubblicato in: ICES Journal of Marine Science, 2019, ISSN 1054-3139
Editore: Oxford University Press
DOI: 10.1093/icesjms/fsz149

Countering a climate of instability: the future of relative stability under the Common Fisheries Policy

Autori: Michael Harte, Rachel Tiller, George Kailis, Merrick Burden
Pubblicato in: ICES journal of Marine Science, 2019, ISSN 1054-3139
Editore: Oxford University Press
DOI: 10.1093/icesjms/fsz109