# Application Scenarios of Digital Twins for Smart Crop Farming through Cloud-Fog-Edge Infrastructure
###### Abstract  
In the last decade, digital twin (DT) technology has received considerable attention across various domains, such as manufacturing, smart healthcare, and smart cities. The digital twin represents a digital representation of a physical entity, object, system, or process. Although it is relatively new in the agricultural domain, it has gained increasing attention recently. Recent reviews of DTs show that this technology has the potential to revolutionise agriculture management and activities. It can also provide numerous benefits to all agricultural stakeholders, including farmers, agronomists, researchers, and others, in terms of making decisions on various agricultural processes. In smart crop farming, DTs help simulate various farming tasks like irrigation, fertilisation, nutrient management, and pest control, as well as access real-time data and guide farmers through 'what-if' scenarios. By utilising the latest technologies, such as cloud-fog-edge computing, multi-agent systems, and the semantic web, farmers can access real-time data and analytics. This enables them to make accurate decisions about optimising their processes and improving efficiency. This paper presents a proposed architectural framework for DTs, exploring various potential application scenarios that integrate this architecture. It also analyses the benefits and challenges of implementing this technology in agricultural environments. Additionally, we investigate how cloud-fog-edge computing contributes to developing decentralised, real-time systems essential for effective management and monitoring in agriculture. digital twin; crop farming; smart agriculture; cloud-fog-edge computing; multi-agent systems +
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farmers can improve sustainability, enhance productivity, and optimise resource utilisation. As these technologies continue to develop and become more accessible, we can expect to see more significant advancements in smart agriculture in the future. Digital twin is an evolving technology that is gaining more attention in all domains. DT can be defined as a digital equivalent of a real-life object that mirrors its behaviour and states over its lifetime in a virtual space [11]. Although there are a number of studies available in other domains using the concept of a DT, it is still in the early stages in agriculture [5]. In recent years, agriculture has also received a lot of interest; development and implementation are still in progress as stakeholders and researchers work to find sustainable and efficient methods to produce food while also reducing the impact on the environment. Farming can be generally categorised into two types: Open Environment Agriculture (OEA) and Closed Environment Agriculture (CEA). The implementation of DT in CEA is relatively easier because of the controlled nature of environmental factors. However, implementing DT in OEA is challenging because it involves unpredictable natural weather conditions and various other external factors. While a significant amount of research focuses on CEA, with studies exploring its application in greenhouse [12], aquaponics [13], vertical farming [14], hydroponics [15], studies on OEA are comparatively fewer. DT in agriculture is an emerging topic that has the potential to bring about significant change. Since a few studies are available for OEA, it is clear that there is a need for customised DT frameworks specifically for OEA. This gap has motivated us to propose architecture and application scenarios for open-environment crop farming. The detailed related work on DT for agriculture is discussed in Section 3. This research introduces a novel architecture for a DT by integrating multi-agent systems and cloud-fog-edge computing. This is designed to rapidly provide necessary decision-making information to farmers for \"what-its\" scenarios. It also directs farmers in critical areas and offers a dynamic list of prioritised actions that adapt to evolving environmental conditions.