Conditioned by the price of goods, the bioenergy market knows very well that costs, around 70% or more of a company's budget in the sector, are the main variable for managing and conducting its activities.

Optimizing costs without affecting the operational level is always a challenge for any entrepreneur. The search is incessant to reduce waste, be more precise, fast and efficient and operate in a synchronized and anticipated manner. Combining all of this is not easy and necessarily involves articulating the use of technologies, information and people. Technologies applied to control operations, highly dependent on reliable data, and which are the basis for exploring and obtaining gains in each possible opportunity.

In this article, I seek to explain a little about these innovations and how they have contributed to reducing agricultural costs. We start from the basics, which is the mechanization of field operations. Something that needs no details given the increasing performance and reliability of the machines and implements developed and launched with each new generation. However, it is vital that we understand that mechanization alone does not work miracles. It needs to be combined with the trinomial “technology, data and people” to generate the expected gain from its adoption.

Thus, the first essential technological lever for this mission is an infrastructure of control and planning systems for collecting and processing data relating to each stage of the production process. These systems need to be fully integrated and, ideally, with their data shared in the cloud to support the increasing volume of information and provide scalable processing capacity with high availability.

Report-based management is no longer able to meet the managers' growing need for mobile and real-time data that allows active action closer to the field. Simulation models, with analysis and data mining tools, are used to generate and optimize scenarios, calculating ideal routes and sequences for activities. This made them a central element in the conduct of harvest plans. In addition to being the main tool for reactivity to problems and minimizing risks, even in the planning phase.

After that, we move on to carrying out activities in the field, where the connection between planning and mechanization occurs with process automation. Here, machine control and precision agriculture are the main agents involved in making optimized and simulated gains in the office a reality. In other words, making machines and drones accurately execute the ideal plan of movements in planting, harvesting and processing operations, applying inputs and controlling implements while monitoring the operation to ensure the reduction in fuel consumption and the maximization of operating times.

The technology that enables this is on-board computers, installed to capture data from sensors and control the positioning of equipment through navigation systems that conduct operations with precision over the planting lines. A sometimes invisible actor, field infrastructure has also been evolving significantly in our country, finally bringing the reality of the digital world to the sector. At this point, the fundamental elements to ensure successful machine automation are positioning and communication.

The first, with the use of antennas based on global position and time determination system technology and supported by correction systems to ensure that machine positioning accuracy reaches mere centimeters of error. And the second being driven by the growing presence in the field of telephone companies, installing their transmission antennas and making 5G signal available for communicating gigantic volumes of data in broadband and at high speed.

Very soon, online video transmission and processing from the field will be decisive for automation, with virtualization and context awareness applications working integrated both locally on machines and remotely in control centers. These plants are another area of strong contribution of technology to bioenergy agriculture. The so-called Control Rooms operate entirely based on the processing of Internet of Things data, which are sent by equipment and machines, and enable operators to monitor remotely, 24/7, everything that occurs in the field, with particular concern for synchronizing operations.

In other words, for companies it is no longer enough to just have each machine perform its activities precisely and almost automatically. Field operations also need to be synchronized with each other, ensuring, for example, that tractors operate dynamically with the movements of harvesters and have the raw material transported by a flow of trucks that guarantees continuous supply to the industry. Stock on wheels, no queues, no waiting, no machines stopped. Reducing costs, increasing efficiency and ensuring a greater return on investment made with mechanization.

Control centers also work in incident management and operational security. Through monitoring systems, it is possible to configure alarms that detect and notify occurrences of activities outside an expected standard, as well as violating security standards. Everything is monitored on digital maps, with the location of each resource, and interpolated with climatological, statistical and designed data for each process. Furthermore, this entire infrastructure is now instantly integrated with the manager's cell phone, who can receive immediate notifications of critical events or events that require some type of intervention on their part. This ensures that stopped machines are put back into operation as quickly as possible and that problems are not postponed due to delays in their identification.

Once the processes are planned, automated and monitored, the technology then advances towards the massive processing of huge volumes of telemetry data and information collected from field operations. At this point, the research frontier occurs with the application of Artificial Intelligence and Machine Learning in the use of this data to generate knowledge and further contribute to efficiency gains in processes.

Applications of all kinds are emerging, among which we can mention image analysis to detect diseases and production failures, use of production forecasting and harvest estimation models and predictive analysis of equipment failures that allow preventive maintenance to be anticipated. Not to mention the use of this entire arsenal of intelligent tools in support of environmental, social and corporate governance actions, in recognition of the vanguard role of our sector in caring for nature, applying these technologies also in fighting fires, preserving areas and biodiversity and the constant reduction of environmental impacts of operations.

We see that Artificial Intelligence technology is also increasingly integrating directly with machine automation and control. We already have fatigue monitoring systems monitoring the activities and behavior of operators, valuing their health and safety in preventing accidents. The next step is coming with the implementation of perception systems in machines, with cameras and sensors feeding on-board computers with the identification of elements in the field.

The movement of equipment will be "monitored" by this on-board intelligence in order to avoid collisions and accidents, in addition to correcting positioning and routes based on real operational situations on the ground. Thus, the current navigation support automation will quickly move towards a new phase in which the control of machines will be assisted by these systems, possibly reaching, in the medium term, the expected full automation, with robotic machines being used, initially, in isolated processes. and controlled in which the risk to operators justifies their replacement.

From there, the more widespread use of autonomous vehicles will be a natural step resulting from the evolution of technology and its regulations. Even though it started a long time ago, this technological journey in the field seems to be far from over. We will increasingly see innovations being introduced in our sector, making it exciting and challenging to project and watch how we will operate in the not-so-distant future.