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Aquahubs-project: Supporting aquaculture innovation experiments. Case automatic estimation of fish stock


 
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URNISBN9789523444416.pdf (1.360Mt)
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Editoija
Jantunen, Sami
Kaakkois-Suomen ammattikorkeakoulu
2022
All rights reserved. This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited.
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https://urn.fi/URN:ISBN:978-952-344-441-6
Tiivistelmä
Aquaculture and fishery are sub-sectors of agri-food that are among the least digitized, automated or in other ways influenced by recent developments in high-tech. Yet, they are sub-sectors that are becoming increasingly important in the context of economic efficiency, environmental sustainability, rural development and food supply chain resilience. Τo enable the digital transformation of aquaculture and fishing, favourable policy conditions, relatively low market competition, and the pre-existing technological know-how within other agri-food sub-sectors need to be exploited. Above all else, those working with aqua-tech innovations require targeted support in end-user outreach, demonstration, validation, commercialization and market uptake of their novel products or services – such support is a core mission of Digital Innovation Hubs (DIH).

The purpose of AquaHubs project was to strengthen cross-border collaboration between three DIHs and promote the use of digital technologies in aquaculture sector. The primary mechanism in AquaHubs project to achieve such objectives were to develop DIH services and use them on a practical level when conducting Innovation Experiments (IE). Through the implementation of three separate IEs, one by each AquaHubs partner, we aimed at producing novel knowledge regarding the aquaculture and fishery industry and, in parallel, at establishing the necessary channels, tools and methods for this knowledge and experience to be shared amongst the interested stakeholders throughout Europe.

This publication illustrates how the DIH services, developed in the AquaHubs project, guided the innovation experiment conducted in Finland. To this end, we describe activities and outcomes of developing a digital solution for the automatic estimation of fish stocks, using data gathered by sonar and underwater imaging. The publication offers information and experiences particularly to aquaculture policy makers and developers with respect of strengthening aquaculture ecosystems and developing digital solutions for estimating fish stocks.
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