The Rusagro Group of Companies announced the implementation of the domestic cloud service "Field History" on its fields, developed as a replacement for the foreign Cropwise. The service from GeomirAgro allows collecting, analyzing, and storing all information for each farm in a single system. It was created thanks to grant support from the Russian Fund for the Development of Information Technologies (part of the VEB Group) within the framework of the national project "Digital Economy". The grant amounted to 536 million rubles, while the total cost of the project is estimated at 670 million rubles.
In November 2024, the second phase of testing of "Field History" was completed: the service was integrated into production processes and then refined in accordance with the needs of farmers with the participation of Rusagro's IT "daughter" called Rusagro Tech.
The "Field History" project is strategically important for Rusagro's business and for the crop production industry as a whole. The technologically complex and most labor-intensive is the second stage. At this stage, we focused on developing new modules, integrating with weather stations and agricultural machinery sensors, as well as other important tasks. We strive to ensure high product quality in order to meet the needs of Rusagro's agricultural business line and achieve our goals.
At this stage, "Field History" improved parameters such as the database, field and cadastral map, GIS module, field inspections, crop monitoring, agronomic experiments, and precision farming.
GeomirAgro and Rusagro Tech also paid more attention to artificial intelligence models. AI was entrusted with more than five major parameters, in particular, the refinement of services for determining field and crop contours, the implementation of a system for determining the best varieties and hybrids using an ML model, the development of models for predicting diseases and pests, and the recognition of pests in a pheromone trap. At the same time, GeomirAgro was the first on the market to apply a system for determining the best varieties and hybrids using an ML model, and in this, they bypassed Cropwise.
In total, more than fifteen new functions appeared in "Field History" in the second stage. These include optimizing employee travel routes for each field and controlling crop movement, irrigation management, weather and crop forecasting, UAV surveying of piles, and calculating factors affecting yield for each field.
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