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.
Project leader: Eleni Kelasidi