Using Digital Twin for decision support in RAS feeding processes

In this paper I present how the NGSI-LD specification can be used to handle complex Digital Twin processes in the context of a Recirculating Aquaculture System (RAS).

The digital twin model is based on understanding the whole fish organism as an adaptive agent, robust, testable biological theory that is implemented in the computer code. This means that the model not only describes a specific aspect of fish nutrition, energetics, growth or behaviour in the form of an equation or system of equations. Instead, the digital twin aims to work as a digital organism simulating the most crucial aspects of physiology, neurobiology and behaviour in a digital environment. The agent can therefore act autonomously, make decisions in response to the internal and external environment with continuous feedbacks at multiple biological levels. This means, for example, that the simulation system aims to predict voluntary behaviour and food intake of the fish. This digital twin for feeding enables running various scenarios and predicts the response including unplanned, emergent and stochastic effects. Such a capacity provides an indispensable tool for decision support and operational optimization and can be run in the AI-controlled precision fish farm environment of iBOS, developed within the iFishienci project.