Digital Twin for Smart Farming

Galiveeti Poornima1, *, Deepak S. Sakkari1, Sukruth Gowda M.A.1
1 Networking and IoT lab, Presidency University, Sri Krishna Institute of Technology, Bangalore, India

Abstract

One of the disruptive technologies that will emerge in the 21st century is the digital twin, which is a digital copy of any physical object that may exist in any setting. Many industries heavily rely on digital twin technology to produce high-quality products that can be shipped throughout the world with no loss in efficiency. The initial efforts have been made by the agricultural sector toward the implementation of digital twin technology in farming and other types of activities. It has already begun to apply vertical farming together with other crucial cutting-edge technologies in a chosen number of smart cities.

Keywords: Disruptive technologies, Efficiency, Digital twin, Smart cities.

* Corresponding author Galiveeti Poornima: Networking and IoT lab, Presidency University, Sri Krishna Institute of Technology, Bangalore, India; E-mail: galiveetipoornima@presidencyuniversity.in

INTRODUCTION

Without trustworthy and up-to-date information regarding farm operations, modern agricultural production is not viable. The use of digital technology in agriculture, such as sensing and monitoring devices, sophisticated analytics, and smart equipment, is becoming more necessary. Fast-evolving technologies like the cloud, the Internet of Things, big data, machine learning, augmented reality, and robots are driving a shift in agriculture toward "smart farming" systems [1-4]. One way to look at smart farming is as the natural progression of precision agriculture [5]. In smart farming, management activities are not just dependent on accurate location data but also on context data, situational awareness and event triggers. One way to think about a smart farming system is a cyber-physical control cycle that integrates sensing and monitoring, intelligent analyses and planning, and intelligent control of farm operations for all relevant farm processes (also known as a "whole farm management perspective").

Using digital information that is (near) real-time rather than on-site direct observation and physical labour, farmers may remotely monitor and manage

operarations in smart farming systems. Therefore, farmers are immediately notified of any issues or impending problems. One may examine a high-quality digital picture of the plant, animal or machine in question from the comfort of their workstation or smartphone to see how things are doing out in the field or stable. Simultaneously, machine learning algorithms enhance the digital view by adding object-specific evaluations and recommendations. Farmers are able to replicate both remedial and preventative activities and assess the effect of such simulations on the digital depiction. Last but not least, the selected intervention may be carried out remotely, and the farmer can utilize the digital view once again to determine whether or not the issue has been resolved as anticipated. As this smart farm management cycle grows more autonomous, the farmer will no longer need to intervene manually, which is another thing that may be anticipated. It's fair to state that everything on the farm (crop, field, cow, equipment) is gradually being virtualized and, therefore, increasingly, remote-controllable. The concept of a digital twin is an interesting metaphor that can be used to describe this development.

Even though there are different ways to define a "Digital Twin", which will be covered later, in general, a "Digital Twin" is a digital copy of a real-world object that acts and changes in the same way in a virtual space [6, 7]. Using Digital Twins as a core tool for farm management decouples physical flows from their planning and control. A digital twin eliminates important limitations related to space, time, and human observation. The need for farmers to be physically close to their crops would be eliminated, which would make it possible to execute, monitor, manage and coordinate farming tasks remotely via automation. This makes it possible to decouple the physical flows of agricultural activities from the informational components of those processes. Data from sensors and satellites, for example, may provide context to a digital twin that would otherwise be impossible to get directly from the physical object.

TECHNOLOGIES USED IN SMART FARMING

While innovation and digital transformation are occurring across many sectors, they are particularly crucial for the future of the planet and the well-being of humans in agriculture. The World Economic Forum projects that the world population will reach 9.8 billion by 2050, which implies that we may need to produce twice as much food as we do now without considerably straining natural resources like land and water.

However, there are good reasons to maintain a hopeful outlook. Throughout history, however, inventive people have found ways to overcome this problem. 8,000 years ago, during the first agricultural revolution, the plough revolutionized production. In the 1800s, developments such as the seed drill introduced a degree of mechanization to farming. The middle of the 20th century saw a number of significant advancements made in the fields of artificial fertilizer and plant science.

At this point in time, we have entered the fourth era of agriculture. The rate of innovation is over the roof, and venture capital funding is flooding in. During 2020, that is, during COVID-19, Finistere Ventures and PitchBook Data projected a 22.3% increase in funding for this sector in 2020, reaching a total of $22.3 billion. In order to put this into perspective, the sum amount of investments made since 2010 is now $65.4 billion.

There is clearly longer any room for speculation on the digital transformation of agriculture. It is not a hoax. In addition, it has a significant influence on the agricultural industry as a whole. Here are some instances.

• Drones that plant rice seeds:

In April 2020, Chinese drone company XAG demonstrated rice sowing in Guangdong. First, it asked two employees to scatter 5kg of rice seeds by wading through a flooded paddy area. It took an hour and a quarter to complete the arduous task.

Then it deployed its XAG Xplanet drone on the same duty (Fig. 1). The unmanned aircraft system flew along a path that had been pre-programmed for it and dropped rice seeds from the sky. The task was finished in one minute and one hundred and twenty seconds. Farming using intelligence 1: labour from humans 0.

Fig. (1))
XAG Xplanet drone (Courtesy: https://www.xa.com/en/xp2020).

It is impossible to understate how much of an influence drones have had on farming. Drones improve productivity while also being safer for workers and the environment. According to Xag, compared to conventional methods, this technology may use up to 90 compared to conventional methods, this technology may use up to 90% less water and 30% less chemicals. It also has a higher degree of precision. Using a technology known as JetSeed, it can discharge seeds at speeds of up to 18 metres per second. This prevents any seeds from being carried away by the wind. The end result is an efficiency that is 80 times greater than that of hand sowing.

The use of commercial drones is one of the areas of the Internet of Things (IoT) that is expanding at the quickest rate, and 5G will play an important part in making this expansion possible.

• Smart agriculture and the iot: a 'ball' to keep grain fresh:

A smart sensor has the potential to be a game-changing piece of technology for an industry as scattered and out of the way as farming. It has the potential to significantly cut waste while simultaneously increasing production.

One such device is GrainSage, which is manufactured by Telesense as shown in Fig. (2).

It's a sensor that's been inserted in a ball, and the business says it looks like something a dog might use as a chew toy. The gadget is then tossed onto the existing heap of grain by the farmers. The ball is programmed to provide information numerous times each day on the temperature and humidity levels in the building.

Fig. (2))
GrainSage by Telesense to keep grain fresh (Courtesy: https://www.futurefarming.com/smart-farming).

The cloud receives this data wirelessly, and TeleSense's machine learning algorithms analyse it there to find significant patterns before transmitting it to the TeleSense app.

And how that LPWAN has been developed, there is an energy-saving, Internet of Things (IoT)-optimized connection that can link these sensors for up to ten years on a single battery charge.

• The robot that looks after chickens:

There's nobody else around here except us hens. not to mention a robot dubbed "The...