Abstract
Digital twin (DT) is one of the key concepts of the fourth industrial revolution (Industry 4.0). A DT is a data-driven, digital replica of a real-world object or environment, including all the states and behaviour of the real-life counterpart. Based on research across multiple domains, DTs show great potential to improve both efficiency and sustainability. In addition, a DT is able to remove key constraints of human observations and interactions. Yet, the technology is still in its infancy. Thus, this article presents a literature search across five different databases focusing on suitable approaches for data coupling and the stages of DT implementation integration with Industry 4.0 technologies. The review process follows the systematic literature review (SLR) methodology. The selected articles cover a wide range of DT implementations across the agricultural industry, ranging from arable farming to aquaponics. Findings include identification of the stages needed to create the DTs, the data coupling processes, and how Industry 4.0 technologies (e.g., cloud-based technologies, IoT, and AI subfields) are integrated. Findings presented in this article will support others in the design of DTs and integration of Industry 4.0 technologies for agricultural greenhouses.
Subject
Electrical and Electronic Engineering,Artificial Intelligence,Urban Studies
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