Agriculture is facing many challenges. Not only climate change, but also the scarcity of resources and the decline in biodiversity require adjustments in agriculture. This is where Fraunhofer IESE comes in and supports digitalization in agriculture with software-based solutions. Digital farming optimizes and automates agricultural work processes, both in the field and in the barn as well as in the office.
Die Digitalisierung erreicht auch den Agrarsektor.
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Digital Farming: Data Exchange, Artificial Intelligence and Sustainability
Software-based solutions for the digital transformation in agriculture
The aim is to provide comprehensive support to companies from the direct upstream and downstream agricultural business at all stages of their path to digitalization – be it through the provision of innovative technologies or the implementation of complex software systems or software-based systems that increase their efficiency. By organizing targeted events with agricultural companies, we also create a platform for the exchange of experiences and the formation of a joint network to learn from each other and promote synergies. Dialogue with farmers is also important to us in order to be as practical as possible. This commitment also extends to companies in the agricultural industry, particularly in the upstream and downstream sectors.
Research at the Kaiserslautern site is geared towards generating concrete added value. A particular focus here is on developing innovative solutions that not only increase efficiency, but also create the basis for the emergence of new and sustainable business models in this area. We are committed to establishing digitalization in agriculture as a pioneer for positive change and sustainable development.
Interoperability and Data Exchange
There are currently numerous different digital solutions in the agricultural sector, which often operate in isolation from one another. One of the primary objectives is to link these diverse solutions together and enable optimal networking. To this end, it is essential to ensure the efficient exchange of data [only available in German] between the systems. However, it is particularly important to ensure the sovereignty of data exchange. After all, only secure and barrier-free data transfer will enable the various agricultural technologies to be used optimally and profitably and enable precise planning of agricultural processes. In agriculture, this interoperability leads to well-founded decisions regarding cultivation planning, resource allocation and harvest times, saves time and achieves a better yield.
Artificial Intelligence and Data in Agriculture
Artificial intelligence offers a wide range of opportunities in agriculture to increase efficiency, optimize resource consumption or promote sustainable agricultural practices. Research at the Kaiserslautern site focuses on the following points:
- Autonomous agricultural robotics: We are researching technical developments such as sensor data to establish and design safe autonomous systems [only available in German] in agriculture. The focus is on the trustworthiness and safeguarding of AI models for autonomous driving functions as well as dynamic risk management during autonomous operation.
- Data management and data quality: Our core topics include the efficient handling of complex data volumes, including automated analysis in agriculture, also with regard to sensor data. We focus on decision support and environmental monitoring. Our aim is to support companies in the agricultural sector in evaluating the quality of their data, analyzing it in a meaningful way and generating added value from it. On the other hand, we are committed to developing customized, data-driven business models that help our customers to achieve their goals effectively and strengthen their competitiveness.
Digitalization as an Opportunity for More Sustainability in the Long-Term Economy
In order to take account of environmental protection in agriculture, a key focus is on resource conservation. Research concentrates on finding more efficient ways of using pesticides, fertilizers, irrigation and feed. The researchers at Fraunhofer IESE are focusing on three main areas: the digital mapping of nutrient cycles, the automation of documentation, i.e. the optimized process of data collection and reporting, and the development of approaches for identifying and evaluating data quality to ensure that only reliable data is used for automated documentation. The aim is to achieve a balance between productivity and environmental protection for greater sustainability [only available in German].