Researchers in China discuss the concept of “digital twins” as might be used to improve efficiency and yields, cut costs, and improve safety in agriculture. Details are published in the International Journal of Adaptive and Innovative Systems.
A “digital twin” is commonly thought of as being a dynamic, computerized representation of a physical or object or system that models that object or process in real-time. It can be manipulated to see how “virtual” changes made to the object or system might affect their real-world counterparts. The original concept of this kind of simulation emerged from work on “information mirroring models” at the University of Michigan by Michael Grieves, although the term “digital twin” was first used by the US Air Force Laboratory in 2009 and then by NASA in its efforts to model the behaviour and response of its spacecraft. Of course, as with many advanced systems and simulations there is no single definition.
Researchers at the China University of Petroleum (East China) in Qingdao and Qingdao University point out that digital twins have been used in a variety of contexts and suggest that the time is ripe for digital twins to be used in agriculture. The team explains that digital twins can act as “a bridge between the physical world and the digital world”. As such, they need to be built on various underlying technologies such as virtual reality and augmented reality but might also incorporate aspects of model-based systems engineering and digital threading. There is, of course, the scope for artificial intelligence and machine learning to play a role. The internet of things is the foundation on which a digital twin is constructed acting to connect the real world to the virtual.
Digital twins have been used in manufacturing, in city planning, and even on the battlefield. Given that agriculture in many parts of the world is based on often centuries-old approaches, the digital twin concept is set to revolutionise farming life. It will allow simulations of agricultural activities to be carried out as well as assist with remote monitoring, control, and coordination of those activities on the farm.
Zhao, Y., Jiang, Z., Qiao, L., Guo, J., Pang, S. and Lv, Z. (2022) ‘Agricultural digital twins’, Int. J. Adaptive and Innovative Systems, Vol. 3, No. 2, pp.144–156.