Water is the most important production factor in agriculture worldwide and therefore in the production of food. Additional irrigation is essential in unfavorable soil or climatic conditions, to safeguard and increase productivity in an environmentally friendly way or to grow higher-value products.
The district of Uelzen is one of the most irrigation-intensive districts in Germany, which is why the region is working intensively on sustainable additional field irrigation.
To carry out the project, a 5G campus network including a 25 to 30 meter high mobile phone mast was erected in Suderburg. The agricultural test area to be made accessible by radio technology was 1.4 km². A data center with several servers, the necessary system technology and an uninterruptible power supply was set up on the nearby test farm, the AGRAVIS Future Farm. The network components were connected to the district's own fiber optic network in order to be able to handle the resulting data traffic.
The central element was the design and development of a sensor network including airborne imaging sensors to gain an overview of the condition of the area using a large number of sensors and multispectral drones with cameras. At the start of the project, 5G-capable soil moisture sensors were not commercially available either in Germany or internationally. The project therefore aimed to further develop the hardware and software for the planned sensor mix.
The various field trials were carried out on the experimental cultivation area, the AGRAVIS Future Farm, using 5G technology and sensors under real conditions. The aim was to generate a detailed map of the soil and plant moisture of the agricultural trial area, which would form the basis for future site-specific irrigation. To this end, various soil sensors were placed in the area and drone overflights were carried out. The 5G-based real-time transmission of sensor data and images in the established 5G campus network was tested.
A core task of the project was to design, develop and test an open, AI-based data platform in which the data from the field trials could be recorded and processed. The software platform to be developed was to be used to process data of the sensors connected via 5G from the ground and air, combine it with other data sources (e.g. weather, harvest results, geodata, data on or from agricultural machinery, etc.) and derive an optimized irrigation recommendation. A first version of the platform is now available at the end of the project phase.
The aim of the projectwas to further develop the overall field irrigation system and to irrigate agricultural crops more efficiently and in a resource-saving manner in future. The sensor data and measurement results obtained during the trials were to be combined and processed using AI. In the future, 5G applications and software solutions should make it possible to make evidence-based decisions and achieve autonomous and effective irrigation that is accurate to the exact area and corresponds to the condition of the plants and soil.
