# Application Scenarios of Digital Twins for Smart Crop Farming through Cloud-Fog-Edge Infrastructure
## 5 Possible Application Scenarios with Digital Twin
### Scenario 1: Irrigation Systems  
Agricultural irrigation systems are frequently closed systems, which require the farmer to turn the irrigation system on or off. More advanced systems are available on the market, which utilise either soil moisture sensors [40] or rainfall sensors [41] to automate irrigation and reduce water usage. The sensors for automated irrigation systems are typically expensive. As technology advances, progressively more straightforward, low-cost sensors capable of sensing soil moisture and rainfall are entering the market. Connecting these simple sensors to nodes would create an affordable irrigation management system. This would lower the cost barrier and allow greater access to precision technologies, particularly for smaller farms [40].  
A DT for an irrigation system in agriculture is a digital replica of the physical irrigation system used in the field. It is created by collecting data from sensors and other sources such as weather forecasts, soil moisture sensors, and crop growth models. Using this data, the DT replicates the functioning of the irrigation setup and the behaviour of the crops under irrigation. This enables farmers and other stakeholders to monitor system performance, optimise irrigation schedules, and make better decisions to maximise crop yield while minimising water usage. For example, the DT can help farmers decide when and how much water to apply to their crops based on weather conditions, soil moisture levels, and other factors (harvest date, fertiliser plans). It can also help farmers identify potential issues with the irrigation system, such as leaks or malfunctions, and take required action before they impact crop yield.  
Farmers who do not have access to DT technology must rely on traditional methods such as visual inspection and manual measurement to make irrigation decisions. These methods are often based on intuition and experience rather than hard data, which could lead to inefficient and suboptimal irrigation practices. While there are modern irrigation systems that use technologies such as soil moisture sensors and temperature gauges to inform decision-making [42], these systems may not take into account other important factors such as crop growth stage, nutrient levels, and fertiliser use. Digital twin technology, on the other hand, can integrate and analyse a wide range of data points, making it a more advanced tool for decision-making in agriculture. A DT for an irrigation system of crop fields can provide farmers with a valuable tool to improve their irrigation practices and ultimately achieve more sustainable and efficient crop production.  
Additionally, the fog processing feature outlined in this paper's architecture, as illustrated in Figure 1, allows for the utilisation of weather forecasts in conjunction with simple sensor data. This integration helps to reduce water usage further. Reducing water consumption is crucial for countries experiencing water scarcity. Due to climate change-induced water shortages, agricultural security concerns are increasing [43]. Therefore, utilising DT in irrigation systems presents an effective solution for this issue.  
Figure 5: Early Alters on Fields.