How artificial intelligence is changing processes in the field

A Intelligence Vision (IA) has a ability to extract knowledge and identify previously unknown behaviors through the analysis of 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 images aareas, monitoring of machines, quality analysis of the harvested raw material, history of operations and products applied in each cultivation area. The use of IA in these companies has helped them a diagnose problems that require intervention to resolve.

An example is a disease detection through images that make it possible to process immense areas remotely and indicate where it is necessary to apply correctives, or other products, to recover a productivity. Similarly, a Analysis of machine behavior allows the identification of more economical and efficient practices, supporting companies in improving their activities and resource allocation. In cutting-edge research, a IA It is also used in the development of more productive plant varieties, as well , the in the formulation of more efficient and lower-cost inputs and pesticides.

At Hexagon, we apply a IA in all field processes - from planting planning to transportation to a industry. Through technology, it is possible to test a huge number of alternatives until reaching the one with the greatest efficiency and lowest cost for a agricultural company. So, for example, it is possible to plan a harvest sequence of areas for the complete time horizon of a harvest or cycle. Or even, make a machine is as self-sufficient as possible, reducing a need for intervention by the operator, resulting in a reduction in failures and a general gain in performance.

Through IA, we were also able to do a remote management of field activities, carried out in control rooms that continuously receive data from machines in the field. In this environment,a technology acts , the an assistant to the company manager, processing all data received, projecting results and diagnosing situations that could generate losses for the business. When identifying a problem, forecasting models based on IA issue alerts for managers to make decisions and correct the problem as quickly as possible. The sooner you act, the less you lose.

A IA is gaining ground day after day. We believe that in the near future, a IA will make a complete and autonomous driving of vehicles and machines in the field, carrying out harvesting and cultivation activities 24 hours a day, and in a completely synchronized manner. We will do in the field what modern robotic factories already do in the assembly and manufacture of finished products. When we reach this level, a Agriculture will have evolved to act essentially with research and management activities, leaving all the heavy work to automated mechanization and without human operators.