In the NaLamKI project, a cloud-based Software-as-a-Service-Platform will be created. It will offer open interfaces for partners from agriculture, industry, and service suppliers from crop production.
Therefore sensor- and machine data will be collected by satellites, drones, ground sensors, robots, and manually. This data will then be added to an International Data Space for Agriculture (IDSA) via GAIA-X conform services.
The ultimate goal is to make agricultural processes, such as irrigation, fertilization, and pest control more sustainable, efficient, and transparent.
The RRLab is in particular invested in collected sensor data by autonomous ground vehicles and the fusion of this data with other sources. The vehicles should drive autonomously on agricultural land, the sensor data should be collected by sensors that fulfill the specific agricultural requirements and be processed by modern AI-methods.
The goals of the project should be shown with the help of 8 demonstrators. The RRLab is mainly contributing to the following demonstrators:
- Quantity- and position precise fertilization and pest control, and area-specific validation of soil moisture levels with the help of AI in grassland and cultivated land
- Inspection of orchards
- Distributed inspection of potato- and salad fields
- Deutsches Forschungszentrum für Künstliche Intelligenz
- German Edge Cloud GmbH & Co. KG
- Fraunhofer‐Institut für Nachrichtentechnik Heinrich‐Hertz‐Institut
- John Deere GmbH & Co. KG
- Julius Kühn-Institut - Forschungszentrum für landwirtschaftliche Fernerkundung
- OptoPrecision GmbH
- Robot Makers GmbH
- Universität Hohenheim, Institut für Agrartechnik
- Deutsche Landwirtschaftsgesellschaft e.V.
- Förderverein Digital Farming
- Landwirtschaftliche Lehr- und Versuchsanstalt Hofgut Neumühle
Federal Ministry for Economic Affairs and Energy (BMWi)