Project Manager: Gunnar Senneset, SINTEF Ocean
Partners: NTNU IDI, Anteo, Kongsberg Maritime, DNV GL
Duration: Q3 2015 – Q4 2017 (Phase 1)


Management and operation of modern aquaculture sites requires monitoring of biomass, environment and complex infrastructures to ensure efficient and safe production. The acquired data are used as a basis for operational decisions. As the industry is moving towards more exposed sites, it is highly likely that the need for monitoring and decision support systems will increase. Limited access for personnel in periods of rough weather will also require the possibility for remote operation of site equipment. Autonomous systems will also be increasingly important, both for resolving critical situations and for increasing the production efficiency.

Decision support tools for exposed aquaculture operations will require data from both new types of sensors as well as those currently used in the industry. As there is a wide range of methods and tools in the AI (Artificial Intelligence) and ML (Machine Learning) fields, it can also be expected that a combination of methods will be necessary to cover the main challenges regarding management and operation at exposed aquaculture sites.

In the first phase of the project, the main goal is to identify challenges and the requirements for decision support systems for exposed operations. This includes the need for new types of sensors and other sources of information. The SFI Exposed report ‘Future concepts’ (reference) will be used as a starting point, supplemented with more detailed mapping and analysis in cooperation with the relevant partners. Testing of new types of sensors and challenges regarding integration of data from different sources will also be addressed