MODELLING AND SIMULATION OF CLOUD-BASED DIGITAL TWINS IN SMART FARMING

Abstract

Digital Twins can be seen as powering the next generation of IoT-connected solutions. Digital Twins model the real world by using historical and real-time data to represent the past and present and simulate the predictable future. Digital twins are related to a set of concepts such as digital representation and 3D visualization, integration, monitoring, control, computation, prediction, and decision-making. They are digital replicas of physical objects having bidirectional data flow. The physical object and its digital twin are synchronized, and the simulations, optimizations and visualizations are in real-time. Using Digital Twins supports the processes of gaining insights that drive better products, optimize operations, reduce costs, and improve the customer experience. These benefits can be used in any type of environment, including buildings, factories, farms, power grids, and even entire cities. Data gathered as a result of the implementation of Precision Livestock Farming (PLF) techniques allows the creation of digital twins though out the farm. As a result, farmers can manage the farm remotely based on real-time digital information, rather than relying on direct observation and manual tasks on the ground. This allows them to act immediately in case of deviations, simulate the effect of interventions based on real-life data and automate various decision-making processes. The main goal of the article is modelling and simulations of digital twins for smart farming in a Cloud environment. During operational use, digital twins can be used not only to monitor and simulate the effects of interventions but also to remotely control objects by using automated actuators. Finally, digital twins are also very valuable for traceability, compliance, and training as they optimize farm operations and provide measurable data for increasing sustainability.