Agriculture industry faces the challenge of increasing productivity by 50% from 2012 to 2050 while reducing water usage, given that it currently consumes 69% of the world’s freshwater. To achieve this goal, smart technologies such as Artificial Intelligence (AI), Digital Twins (DT), and Internet of Things (IoT) are being increasingly utilized. However, the use of DT in agriculture is still in its early stages. This study proposes a smart irrigation framework inspired by digital twins in an application domain. The irrigation framework’s sensors and actuators are linked to their virtual counterparts to create a digital twin. The IoT platform collects, aggregates, and processes data to determine daily irrigation requirements, and the behavior of the irrigation system is simulated. The proposed framework has two main advantages: evaluating the behavior of the digital twin and IoT platform in the context of agriculture before integrating them into the field and comparing various irrigation methods with current farming methods. By providing farmers with information about soil, weather, and crops, the system has the potential to improve farm operations and reduce water consumption.

鉴于目前农业消耗了世界淡水的 69%，因此农业面临着从 2012 年到 2050 年将生产率提高 50%，同时减少用水量的挑战。为了实现这一目标，人工智能（AI）、数字孪生（DT）和物联网（IoT）等智能技术得到越来越多的利用。然而，DT在农业中的应用仍处于早期阶段。本研究提出了一种受应用领域数字孪生启发的智能灌溉框架。灌溉框架的传感器和执行器与其虚拟对应物相连，以创建数字孪生。物联网平台收集、汇总和处理数据以确定日常灌溉需求，并模拟灌溉系统的行为。所提出的框架有两个主要优点：在将数字孪生和物联网平台集成到田间之前评估它们在农业背景下的行为，并将各种灌溉方法与当前的农业方法进行比较。通过为农民提供有关土壤、天气和作物的信息，该系统有可能改善农场运营并减少水消耗。