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HIFAI - Sustainable industrial fish production using AI and advanced data analysis - implementation

Reference number
Coordinator IVL Svenska Miljöinstitutet AB
Funding from Vinnova SEK 3 299 290
Project duration February 2023 - December 2025
Status Ongoing
Venture Strategic innovation programme for process industrial IT and automation – PiiA
Call PiiA: The Process Industry of the Future-Data-Driven and Sustainable - Autumn 2022

Purpose and goal

The purpose of the study is to enable the fish production industry to optimize its production with the help of sensors and advanced data analysis. The goal is to develop a demonstrator that can identify the fish´s activity and feed consumption during feeding, as well as to develop cost-effective methods to estimate biomass, size distribution and growth rate. This can then be used to optimize feeding and time to slaughter, increasing production efficiency and optimizing processes.

Expected effects and result

The project aims to produce a demonstrator that can directly demonstrate the possibilities of integrating sensors, AI and data analysis in a land-based fish farming environment. The result enables far-reaching digitalization of the land-based fish farming industry with major sustainability and profitability gains. It also makes it possible in the long run for the industry to take market shares and for the oceans to be spared.

Planned approach and implementation

The project begins by carrying out measurements to obtain initial reference data. This is followed by starting to design algorithms for sound, image and water quality analysis. When the algorithms are in place, the development of the demonstrator begins, where both hardware and software are implemented, which is followed by a larger measurement campaign at fish farms for evaluation of the system. Hardware and software, including algorithms will then be iterated to achieve the best possible performance. The project ends with a longer-term evaluation of the system at the fish farms.

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 5 March 2023

Reference number 2022-03589

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