Artificial Intelligence: How technology is transforming agribusiness

Present in sectors such as health, retail, education and finance, Artificial Intelligence (AI) occupies more and more spaces in our society, causing major changes in the markets wherever it goes. It is no surprise that today Brazil already has more than 700 startups with applications in this area, according to a study by the innovation platform Distrito. Now it's agribusiness's turn. Technology started to directly impact the field a few years ago, but it has already caused unimaginable advances in terms of efficiency. 

In short, we can say that AI is a field of computer science that seeks to create technological solutions with the capacity to carry out activities in an “intelligent” way. This means designing systems and machines that can assimilate to the human mind, reasoning, learning and making decisions.

Despite its recent prominence, the technology has been developing since 1955, when the concept of AI was first used by mathematics professor John McCarthy at a North American university. Over the last 65 years, the topic has been researched by thousands of people, finally reaching applications that impact our daily lives, such as e-commerce, internet searches and video streaming.

But how does this technology relate to agriculture? How has it been revolutionizing the field?

Diagnostics and predictability

One of the main applications of Artificial Intelligence in agribusiness occurs in the area of ​​diagnosis and predictability. 

With the advancement of mechanization, many plants and farms already have an advanced degree of automation of agricultural machinery. In this scenario, it was possible to install a series of sensors that began to record the activities of these equipment second by second, collecting hundreds of information about the operations carried out - from the simplest, such as machine speed and fuel level, to the most complex, such as hydraulic pressure and implement activation.

AI technology works by processing this data received in the cloud, designing scenarios, anticipating undesirable situations and making recommendations in real time. Some examples of common actions are warning of the ideal time to carry out maintenance on equipment and choosing the most efficient routes and movements to carry out operations. The objective is always to avoid waste, promote savings and optimize productivity.

Image analysis for problem detection

Identifying a disease or pest in a plant is relatively easy for an experienced agronomist. However, when dealing with very large areas, such as sugar cane plantations or forests, there are not enough specialists to manually identify these problems quickly. 

With the help of drones, Artificial Intelligence has been changing this scenario. The equipment, capable of capturing very high precision images, flies over large crops daily. AI technology, in turn, allows the collected images to be cross-referenced with images of healthy or sick plants, analyzing the conditions of each plant.

Thus, reports are issued that identify possible threats, weeds, fungal diseases and even nutritional deficiencies, showing exactly where the problems are on the plantation.

Assessment of climate phenomena

The traditional weather forecast that helps us plan our daily lives is insufficient for the reality of agriculture. For production to be successful, agricultural managers need to be aware of details related to temperature, solar incidence, rain, wind and other weather phenomena.

In recent years, the accuracy of these measurements has seen significant growth thanks to AI, which can analyze local property data in real time, producing safer and more reliable information.

This way, decision-making regarding the cultivation period, irrigation and the use of fertilizers and herbicides, for example, becomes much simpler and more accurate.

autonomous vehicles

Just as today we already have cars capable of driving without a driver, soon this reality will also reach the countryside. 

Currently, there are vehicles with autopilot and prototypes of “self-steering” machines that need AI to avoid making mistakes or causing accidents. However, with the advancement of technology, in addition to the popularization of this type of machine, we will soon have tractors and harvesters capable of operating with even more innovative features.

These machines will be able, for example, to dose the ideal amount of pesticide to be applied in an area, identify plants ready for harvest or that need to be discarded, and even change route when there is any external interference, such as an unmapped obstacle. All this on your own, without any human intervention.

The future of AI in agribusiness 

Without a doubt, the impact of Artificial Intelligence in the field is already great, but expectations are that the process will accelerate and bring more and more results, transforming all stages of agricultural operations with its innovations.

Of course, there are still challenges to be overcome. The main one is the connection in the field, which, in Brazil, still has a very low percentage when compared to the reality in the United States and Europe, for example. 

Furthermore, we cannot forget the amount of uncertainty that surrounds the rural environment, with unforeseen natural events that are still beyond our control. However, the more practical experience AI machines and systems obtain, the greater their database and learning capacity will be, which will allow a better understanding of the field and its needs.

National players who want to remain at the forefront of the agricultural and forestry market will need to be aware of these developments, investing in technology suppliers and training their teams. After all, the future will be marked by an increasingly digital field, with AI as one of the great protagonists of innovation.

Alexandre de Alencar, Director of Research and Development at Hexagon's Agriculture division