If you understand Scandinavian languages, the project name TEKNOFISK may have you smiling, as you think about fish dancing to techno music. However, behind this curious image, lies a far more serious purpose: the Danish TEKNOFISK project, together with its twin project AUTOCATCH, aims at fostering smarter and more sustainable trawling practices through new technology.
The EU-funded TEKNOFISK and AUTOCATCH projects are developing an automatic catch information system that will provide detailed data on the catch entering the trawl, thus enabling fishers to make informed decisions on the ongoing catching process. For the first time, fishers could know what is being caught in real-time as well as the ratio of wanted and unwanted catches. By optimising what goes into the trawl, unwanted catches can be minimised and fuel consumption reduced.
With this technology, long trawling sessions with little outcome would become a thing of the past. Each fisher could then best capitalize on his vessel's catch quotas and thus strengthen the sector's competitiveness, while ensuring that the sustainability objectives of the EU’s common fisheries policy are achieved. This would not least benefit langoustines-directed fisheries, where the large Danish fishing fleet operating in that sector faces a significant amount of catches of unwanted species and sizes. This is a challenge for biological and economic sustainability under the landing obligation, even with the use of more selective fishing gears. In the future, this technology could be further developed to include all relevant species.
Both TEKNOFISK and AUTOCATCH are implemented by Danmarks Tekniske Universitet (DTU, the Technical University of Denmark). TEKNOFISK, simply put, deploys an innovative camera system that allows fishers to observe, evaluate, and react quickly to information about the ongoing fishing operation. If things are not looking good, for instance, fishers may decide to terminate the haul or shift to an alternative depth or fishing ground.
It is challenge to develop an underwater camera that can withstand the rough conditions at sea. But in cooperation with a private company, DTU researcher have overcome these difficulties. Testing its resilience in real-life conditions, the technology was installed on two Danish trawlers during the project. After repeated and successful testing, and the technology is now on the market.
The objective of the sister project, AUTOCATCH, is to develop an automatic catch information system that provides detailed information on the catch entering the trawl. When fully operational, the AUTOCATCH technology will be able to process the live video feed provided by the TEKNOFISK cameras and automatically recognise the species going into the net. This will enable fishers to make informed decisions in real time.
Traditionally, trawl fishing is mostly a “blindfolded” process, where the fishers trawl for up to six hours before they see the results of their efforts. It might be a great catch, but it might also be an empty net, or a load of unwanted species.
Together, the two projects solve a key problem of the trawl fishing activity – lack of predictability - by showing the nets in real time and give the possibility to react accordingly. This is no small feat, as sending high-quality images from 300 meters under water in rough sea conditions is very demanding to achieve. Moreover, the technology developed in this project, will be able to tell crews, whether the current trawl is profitable, for example via an alarm on a phone app or a screen on the bridge.
Without EU-funding, the DTU researchers would not have been able to carry out these projects. In combination, TEKNOFISK and AUTOCATCH may well hold the potential to revolutionise traditional trawl fishing, reducing its environmental impact while at the same time increasing cost efficiency.
Keep informed about the project
Development of a real-time catch monitoring system with automatic detection of the catch composition to minimise catch of unwanted species and sizes (AutoCatch) (39765) — Welcome to DTU Research Database
- Publikācijas datums
- 22 decembris 2021
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