Lima Adriano C, Royer Edouard, Bolzonella Matteo, Pastres Roberto
Department of Environmental Sciences, Informatics and Statistics, Università Ca' Foscari Venezia, Campus Scientifico, via Torino 155, Mestre, Venice, 30172, Italy.
Atlantic International Research Centre (AIR Centre), Parque de Ciência e Tecnologia da Ilha Terceira, Angra do Heroísmo, Azores, 9700-702, Portugal.
Open Res Eur. 2023 Nov 28;2:16. doi: 10.12688/openreseurope.14145.1. eCollection 2022.
The virtual, digital counterpart of a physical object, referred as digital twin, derives from the Internet of Things (IoT), and involves real-time acquisition and processing of large data sets. A fully implemented system ultimately enables real-time and remote management, as well as the reproduction of real and forecasted scenarios. Under the emerging framework of Precision Fish Farming, which brings control-engineering principles to fish production, we set up digital twin prototypes for land-based finfish farms. The digital twin is aimed at supporting producers in optimizing feeding practices, oxygen supply and fish population management with respect to 1) fish growth performances; 2) fish welfare, and 3) environmental loads. It relies on integrated mathematical models which are fed with data from in-situ sensors and from external sources, and simulate several dynamic processes, allowing the estimation of key parameters describing the ambient environment and the fishes. A conceptual application targeted at rearing cycles of rainbow trout ( ) in an operational in-land aquafarm in Italy is presented. The digital twin takes into account the disparate levels of automation and control that are found within this farm, and considerations are made on preferential directions for future developments. In spite of its potential, and not only in the aquaculture sector, the development of digital twins is still at its early stage. Furthermore, Precision Fish Farming applications in land-based systems as well as targeted at rainbow trout are novel developments.
物理对象的虚拟数字对应物，即数字孪生，源自物联网（IoT），涉及大数据集的实时采集和处理。一个完全实现的系统最终能够实现实时远程管理，以及真实场景和预测场景的再现。在将控制工程原理应用于鱼类生产的新兴精准养鱼框架下，我们为陆基有鳍鱼类养殖场建立了数字孪生原型。该数字孪生旨在支持生产者在以下方面优化投喂方式、氧气供应和鱼群管理：1）鱼类生长性能；2）鱼类福利；3）环境负荷。它依赖于综合数学模型，这些模型由来自现场传感器和外部来源的数据提供支持，并模拟多个动态过程，从而能够估算描述周围环境和鱼类的关键参数。本文介绍了一个针对意大利一家运营中的内陆养殖场虹鳟鱼养殖周期的概念性应用。该数字孪生考虑了该养殖场内不同程度的自动化和控制水平，并对未来发展的优先方向进行了思考。尽管数字孪生具有潜力，且不仅限于水产养殖领域，但其发展仍处于早期阶段。此外，陆基系统中针对虹鳟鱼的精准养鱼应用也是新的发展方向。
