About SMARTFISH H20202018-04-26T14:19:27+00:00

ABOUT SMARTFISH H2020

Objectives

The objective of SMARTFISH H2020 is to develop, test and promote a suite of high-tech systems for the EU fishing sector, to optimize resource efficiency, to improve automatic data collection for fish stock assessment, to provide evidence of compliance with fishery regulations and to reduce ecological impact. SMARTFISH H2020 exploits technological developments in machine vision, camera technology, data processing, machine learning, artificial intelligence, big data analysis, smartphones/tablets, LED technology, acoustics and ROV technology to build systems for monitoring, analyzing and improving processes for all facets of the fishing sector, from extraction, to assessment, to monitoring and control. The SMARTFISH H2020 systems will:

  • Assist fishermen in making informed decisions during pre-catch, catching, and post-catch phases of the extraction process. This improves catch efficiencies and compositions in fisheries across the EU, leading to improved economic efficiency while reducing unintended fish mortality, unnecessary fishing pressure and ecosystem damage.
  • Provide new data for stock assessment from commercial fishing and improve the quality and quantity of data that comes from traditional assessment surveys. This provides more accurate assessment of currently assessed stocks and allow the assessment of data-poor stocks.
  • Permit the automatic collection of catch data to ensure compliance with fisheries management regulations.

The SMARTFISH H2020 systems are tested and demonstrated in several EU fisheries. This contributes to promoting the uptake of the systems by extraction sector and fisheries agencies. An interdisciplinary consortium with technology developers and instrument suppliers, fishing companies, research and fisheries management institutes and universities will realize SMARTFISH H2020. They are active at national and international levels and well placed to ensure the uptake of SMARTFISH H2020 systems by fishing industry and fisheries managers and stock assessment scientists.

Impact

SMARTFISH H2020 will:

  • Improve catch efficiency, catch composition and catch quality in pelagic and demersal fisheries
  • Improve the accuracy and quantity of fish stock assessment data
  • Reduce unintended fishing mortality and the capture of protected species
  • Reduce fishing pressure and the environmental impact of fisheries
  • Advance the monitoring and compliance of fishery regulations
  • Ensure that data collected onboard fishing vessels can be used quickly and efficiently for fisheries monitoring, management and assessment purposes.

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Results

SMARTFISH H2020 will achieve its objectives by:

  • Introducing seabed fish-finding systems to ensure fishing gears are deployed only where target species are sufficiently abundant.
  • Introducing pre-catch size and species recognition systems to ensure that the size and species composition of the catch are appropriate.
  • Using real-time monitoring and analysis to ensure that sufficient quantities of target species are entering the fishing gear during trawling, that unwanted by-catch and protected species are not being caught and that biologically sensitive sites are not being trawled.
  • Introducing Smart Gear systems that will permit the modification of selectivity during trawling and hence the affect which fish species and sizes are retained and released by the trawl.
  • Using artificial intelligence and machine learning methods for automatic data processing and analysis of the catches brought aboard fishing and research vessels.
  • Using artificial intelligence and machine learning methods for automatic data processing and analysis of seabed morphology and biomass on the sea bed.
  • Introducing infrastructure on fishing vessels and on shore that enables robust storage and rapid transmission of data to stakeholders.

Enabling Technologies

To develop the SMARTFISH H2020 systems, the project will exploit recent technological developments in:

  • Machine vision technology
  • Camera technology
  • Data processing
  • Machine learning methods and artificial intelligence
  • Big data analysis
  • Smartphones/tablets
  • LED light technology
  • Hydroacoustic technology
  • Remotely operated underwater vehicle (ROV) technology

Work Packages

Work Package Leader: Guzmán Diez, AZTI
Partners: AZTI, SINTEF Ocean, SINTEF Digital, NTNU, Zunibal
Duration: January 2018 – June 2021


This work package will develop SeinePrecog, a system for pre-catch size and species recognition for purse seine fisheries based on optical and hydroacoustic technologies.

Work Package Leader: Ludvig Krag, DTU Aqua
Partners: DTU Aqua, SINTEF Ocean, Marine Scotland, SINTEF Digital, Marport
Duration: January 2018 – June 2021


The concept of this work package is to make use of state-of-the-art underwater camera technology and automatic image analysis techniques to enable real-time monitoring of the abundance of marine organisms. Specifically, the following technologies will be developed:

  • FishFinder, a real-time monitoring system for detection of organisms (e.g. nephrops and flatfish) which are undetectable using conventional fish finding techniques (i.e., echo sounders and sonars).
  • TrawlMonitor, a real-time system able to provide detailed information on species and sizes entering the trawl.
  • NephropsScan, a system for automatic detection and counting of nephrops burrows.
Work Package Leader: Barry O’Neill, DTU Aqua
Partners: DTU Aqua, Marine Scotland, Cefas, Marport, SafetyNet Technologies
Duration: January 2018 – December 2021


The aim of this work package is to provide fishing skippers with technologies that will allow the modification of the fishing gear during the fishing operation. Two technologies will be developed:

  • SmartGear, a system that uses LED technology to optimise the catching performance of trawl fishing gear, based on the reaction of fish to light.
  • An acoustically controlled codend closure system.
Work Package Leader: John Reidar Mathiassen, SINTEF Ocean
Partners: SINTEF Ocean, DTU Aqua, Marine Scotland, Melbu Systems, Çukurova University, Cefas, University of East Anglia
Duration: January 2018 – June 2021


The key concept of this work package is to exploit current synergistic developments in modern 3D machine vision, GPU image processing, and deep learning artificial intelligence, and increase the uptake of these high-level technologies in the fisheries sector. Three technologies will be developed:

  • CatchScanner, a 3D machine vision system for catch analysis on on-board conveyor belts.
  • CatchSnap, a versatile, handheld 3D machine vision unit for inspecting catch samples on smaller fishing vessels.
  • CatchMonitor,  a system for automatic monitoring and analysis using CCTV cameras.

Work Package Leader: Lars T. Kyllingstad, SINTEF Ocean
Partners: SINTEF Ocean, AZTI, DTU Aqua, Cefas, Marport
Duration: January 2018 – June 2021


The objective of this work package is to develop FishData, a hardware and software infrastructure for acquisition, analysis and presentation of data from onboard catch monitoring systems and other relevant data sources.

For information about the testing and demonstration work packages (WP6–10), see Seas>>

For more information about the technologies developed in these work packages, please see Technologies>>