Before the emergence of current technologies for monitoring and automating agricultural processes, the management of machines in the field was basically carried out via radio communication. The information that reached analysts and managers was delayed, and decision-making was relatively late in relation to the activities and facts that had occurred, not to mention that such information was often unreliable and filled in manually. As a result, problems were analyzed and treated late, with few positive effects in the short term of operations.

The installation of on-board computers in agricultural machines allowed the acquisition of data related to telemetry (records of vital signs of the equipment), mainly with data obtained through the reading of the CAN Network (Controller Area Network) and operator notes of operations, generating a large amount of data from agricultural operations in real time.

With on-board computers online, the analysis of monitoring data and notes for management and decision-making begins. Real-time communication is useless if there is no data analysis and decision-making in the search for continuous improvement of agricultural processes and operations.

Agricultural Operations Centers: To support analysis and decision-making, the operations centers gained prominence in the plants, receiving and analyzing data and transforming them into information, enabling a holistic view of each operation and communicating at all times with the managers, correcting operational deviations in real time, thus avoiding idleness in the field and improving the synchronism of operations.

With the mission of supporting and auditing operations, the Operations Center must always seek the standardization of operations, and this is only possible with operational discipline and alignment with the field. Communication from the Operations Center with the field teams is the main point. In addition to monitoring and passing on relevant information to field leaders and managers, the Operation Center must support them in drawing up action plans to correct the deviations identified in each part of the process.

Example of harvest management with artificial intelligence: One of the main reasons for sugarcane harvesters stoppages is the lack of transshipment. These stops do not necessarily indicate a bad dimensioning of the transshipment and harvester relationship, but the lack of synchronism of the operations involving these equipments. Just as a reference of values, approximately 14.2% of the 24 hours a day are lost due to lack of transshipment (average of data from 142 plants collected in July 2022), which represents 3.41 hours per day per harvester. A harvest front with 4 harvesters loses 13.64 hours per day, resulting in 200 effective days of harvest, the magnitude of 2,728 hours lost. There is no doubt that the automation of this process significantly reduces this lost time, making it productive and increasing the operational efficiency of the entire harvest front.

There are technological solutions with embedded artificial intelligence with autonomous and operator-independent decision-making, with the main objective of increasing the operational efficiency of sugarcane harvesters, through the automatic call of transshipments by the harvester, without any intervention by the operator. The logic of the automatic calls for transfers by the harvesters will be based on the times of each operation, these times being always updated by the last cycles.



Sugarcane traceability is another point that deserves full attention from the mills. Straw bills filled in manually are prone to errors and can generate complex problems, such as payment of sugarcane suppliers, service providers, agricultural partners, sugarcane productivity and machinery and equipment productivity. Some current technologies digitally track the entire CTT process, from the beginning of the harvest to the input scale, integrating all this data with the ERP (Enterprise Resource Planning) at the time of truck weighing. Data such as fields, zones, farms, harvesters, transhipments, trucks, trailers, operators and drivers are brought from the fields in a fully automatic way, guaranteeing the reliability of all of them.



Regarding the automation of logistics, it all starts with the online monitoring of all the equipment involved in CTT. This monitoring data feeds the logistics system in real time, activating or deactivating the equipment depending on its current operational state (working or stopped). In addition to monitoring data, data on transshipment cycles are essential for assertiveness in logistics, since, with the times of all cycles integrated to all harvesters and with the stop events updated online for all equipment, the calculation of the hourly production (tons per hour) of each front, considering the harvester and transshipment capacities, is updated minute by minute, enabling online integration with the logistics system, ensuring assertiveness in the dispatch of trucks to the harvest fronts and optimizing the sugarcane transport structure. The lack of a truck represents approximately 2 hours a day of transshipment notes (average of data from 142 plants collected in July 2022).



There are, currently, technologies embedded in harvesters that allow obtaining maps of sugarcane productivity automatically (without any manual intervention) and without the use of sensors external to the machine, showing points of higher and lower productivity in the fields. These maps can be used for the application of inputs and fertilizers at a variable rate, seeking to optimize these resources, applying them according to the export of nutrients from the sugarcane and the levels in the soil.



Management encompassing all mechanized operations: Operations involving the processes of soil preparation, planting and cultural treatments must also be monitored and analyzed in real time, always paying attention to the maximization of productive hours of the equipment, including the qualitative indicators of each operation, such as the speed and overlaps of operations and products, avoiding unnecessary rework and costs.

Regardless of the technologies to be adopted by the plants, it is always worth remembering that the managers' prior knowledge of each one is extremely important, especially with regard to the premises that must be met so that each solution delivers the maximum gain to the processes and agricultural operations. The lack of understanding of the functionalities of these technologies can impact their implementation, generating rework and extra costs, in addition to delaying the expected financial returns for each project.