Title : Agricultural Technology: Applications of Artificial Intelligence and Digital Twins in Vertical Farming (Controlled Environment Agriculture)
Abstract:
FAO announced that due to the COVID-19 pandemic, about 800 million people lacked access to adequate food in 2020. More than half the people living in urban areas mostly rely on buying agricultural products rather than producing food locally. Spatial limitation of the land and climate stress are the primary agricultural development challenges in urban areas. Vertical farming based on controlled-environment agriculture is a promising approach to promoting sustainable local food production and enhancing food security for the growing population in urban areas. With the rapid advancement of digital technology, leveraging Artificial Intelligence and Machine Learning in agriculture has received much attention. Artificial Intelligence based on the simulation of human intelligence and having access to databases such as Satellite Maps, Satellite Imagery, Geospatial Database, and Geographic Information System Data has improved digital farm management by its accuracy and high efficiency and flexibility, and cost-effectiveness. The literature review indicated that little research is available detailing how Artificial Intelligence can be leveraged across vertical farming to boost food security. Through applying the analytical approach, this research investigates the role of Artificial Intelligence in Vertical Farming development. The innovation of this research is the application of coupled Artificial Intelligence-Vertical Farming approach in Controlled Environment Agriculture, which can manage the environment, inputs, processes, and infrastructure as the major elements of the food systems. This research illustrates how Digital Twins' application can help monitor and control agricultural processes and product qualities and adjustments in vertical farming to deliver food security
