How artificial intelligence is changing processes

Artificial Intelligence (AI) has the ability to extract knowledge and identify previously unknown behaviours by analysing large volumes of data. Companies in the agricultural and forestry sector have databases that accumulate a multitude of information collected in different processes: maps and aerial images, monitoring of machines, quality analysis of the raw material harvested, history of operations and products applied in each area of cultivation. The use of AI in these companies has helped them diagnose problems that require intervention for their solution.

One example is the detection of disease by means of images that make it possible to process huge areas remotely and indicate where corrective or other products need to be applied to restore productivity. Similarly, the analysis of machine behaviour allows the identification of more economical and efficient practices, supporting companies in the improvement of their activities and resource allocation. In state-of-the-art research, AI is also used to develop more productive plant varieties as well as to formulate more efficient and cost-effective inputs and pesticides.

At Hexagon, we apply AI to every field process - from planting planning to transportation to industry. Through technology, it is possible to test a gigantic number of alternatives until one reaches the most efficient and least costly for the agricultural enterprise. Thus, for example, it is possible to plan the harvest sequence of areas for the full time horizon of a crop or cycle. Or, make the machine as self-sufficient as possible, reducing the need for operator intervention, leading to reduced failures and overall performance gain.

Through AI, we are also able to remotely manage field activities, performed in control rooms that continuously receive data from field machines. In this environment, technology acts as an assistant to the company manager, treating all data received, projecting results and diagnosing situations that can cause business harm. When identifying a problem, AI-based forecasting models alert managers to make decisions and correct the problem as quickly as possible. The sooner one acts, the less one loses.

AI has been gaining ground day by day. We believe that in the near future, AI will conduct complete and autonomous driving of vehicles and machines in the field, performing harvesting and cultivation activities 24 hours a day and in a fully synchronised manner. We will do in the field what modern robotic factories already do in assembling and manufacturing finished products. By the time we reach that level, agriculture will have evolved to essentially perform research and management activities, leaving all the heavy lifting to automated mechanisation without human operators.