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BIA-Brukerstyrt innovasjonsarena

AquaTwin-Aquaculture Digital Twin for advanced insight to improve productivity and control

Alternative title: AquaTwin-Digital Tvilling for avansert innsikt og kontroll av produksjon i havbruk

Awarded: NOK 0.22 mill.

Today's operation of offshore aquaculture typically involves manual and demanding operations, for monitoring equipment, structures and biomass, which can result in inefficient operation and too high risk to personnel and fish welfare. There is therefore a need for automated solutions for monitoring fish, equipment, structures and the environment around modern aquaculture, especially when facilities and operations are established in more exposed and demanding waters, and when using new types of structures. In the AquaTwin project, the plan was to focus on developing solutions that integrate data from sensors with simulated models into a digital twin representation of construction, fish and the environment, to provide breeders with a better basis for decision support. However, due to changes in priorities and structural changes at the project owner, it was decided through a video meeting between ScaleAQ, SINTEF Ocean and the Research Council 21/9/2020 to terminate the project. During 2020, internal kick-off meeting in SINTEF Ocean was arranged where most of the SINTEF Ocean researchers in digital twin technologies in aquaculture were represented. This gave SINTEF Ocean an opportunity to get an introduction to the project, as well as coordinate ongoing similar projects and look at the opportunities within this field across SINTEF. Work was also initiated to arrange a later kick-off meeting with all project partners represented and it was in this phase that the project was terminated. Work was also initiated by SINTEF Ocean for the preparation of deliveries D1.1 (Technical note describing preliminary system design and requirements) and D1.2 (Report on the recommended sensor system and instrumentation). In particular, initial activities focused on investigating the use of Seatonomy method in order to identify the overall system requirements and specifications with respect to hardware, software and integration methods. The outcomes of this analysis would be essential to develop and realize the digital framework ant thus identify how monitoring operations can be optimized, which sensor technology should be adapted and the conditions for structure and sensors integrations. These studies were not completed due to the early termination of the project . Regarding the project's goal of measuring objects and equipment's behavior and performance in the cage environment, as well as linking this to the fish's behavior, work was immediately started at ScaleAQ to be able to measure the fish's behavior with acoustic data. Work was also initiated to develop methods for collecting, measuring and analyzing acoustic data. In collaboration with an external supplier, a software platform was developed for signal processing of acoustic data, and some time was spent planning a unique species-specific algorithm for salmon. Time was also spent preparing a platform for the integration of acoustic modules, as well as appetite estimation for fish and general project management. In addition, another resource worked on making CAD drawings of a new product that ScaleAQ was interested in documenting with a solid calculation and simulation basis from a digital twin. Meetings and discussions were also held with potential customers about the use of digital twins, where one of the customers in particular confirmed that the concept is interesting and thus provided ScaleAQ with learning and confirmation that the challenges that a digital twin must solve are real, and that demand is present. if one succeeds in building digital business models around the solution. Regarding measurement and associated documentation of relevant products, it was mapped which ones need this today, especially new ones to be used on exposed sites. This led to an increased internal understanding of the importance of documentation of biological and physical performance for products. Digital twin was identified as a very attractive method to increase the commercial value of the product through solid documentation and simulation. In addition, the company gained an increased understanding of the possibilities within measuring and analyzing fish's activity in the sea thanks to the work described in «3. Project implementation».

The project has terminated in few months after the starting date and therefore there are no specific results obtained to comment on the achievements and potential effects from the project results. The initial investigation shows the great interest of the industry to adapt digital twin concept for aquaculture.

The AquaTwin project will develop a digital twin framework integrating data from sensors with simulation models into a virtual representation of the farm, fish and environment to give insight and decision support to the farmer. This will pave the way for the Industry 4.0 paradigm in fish farming and enable the needed increase in productivity and control required for tomorrow's competitiveness in sea-based aquaculture. This technology will improve management practices for sea-based fish farms, which today entail manual and often challenging inspections and monitoring of equipment, structures and biomass, resulting in sub-optimal and costly operations, insufficient maintenance, lack of control in daily routines and increased risks for personnel and fish welfare. The Digital Twin Framework will integrate real time data from sensors and numerical models, estimators, statistical models and machine learning techniques with the operational and maintenance history of a fish farm. This will provide a holistic digital representation ("twin") of the farm and farm operations that can serve farmers' needs to enhance available single measurements and other datapoints for providing insight into parameters related to the structure (e.g. loads, deformations), biomass (e.g. growth, feed consumption, swimming fatigue and stress level) and environmental conditions. The project will focus on R&D challenges associated with sensor technologies for monitoring fish performance and structural conditions, real-time simulation models for both fish and structures, data-analysis and estimation techniques, and integration methods for hardware and software - all of which are needed to realize the Digital Twin Framework. The realization of the outlined innovation comprises a very high potential for value creation for the involved partners, allowing them to offer a new pioneering and revolutionary technology for the aquaculture industry.

Funding scheme:

BIA-Brukerstyrt innovasjonsarena