Digital Farming / Smart Farming

Sustainable, efficient, and smart – Fraunhofer IESE is shaping digital agriculture

The revolution leading to Agriculture 4.0

Agriculture faces many challenges that require optimization of the entire production system. In addition to climate change and the growing scarcity of natural resources, the decline in biodiversity is also forcing agriculture to change.

Fraunhofer IESE promotes digitalization of agriculture using software-based solutions. We support you in successfully integrating the concept of Agriculture 4.0 into agricultural practice.


What is Digital Farming or Smart Farming?

Digital Farming, or Agriculture 4.0, is characterized by the intensive use of software. Synonymously, digital technologies are also used in precision farming and smart farming.

Artificial Intelligence (AI) is a big part of digital agriculture. Data is collected, analyzed, and used more efficiently through automation. In addition to fully networked agricultural platforms and systems, autonomous agricultural robotics is being used to optimize processes along the entire value chain.

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The increased demands on productivity and sustainability are leading to new challenges in the agricultural industry.

With the help of digital solutions, agriculture is optimally equipped for the future.


We are the right partner at your side because we bring research into application!

How is data managed in digital agriculture?


Across system boundaries: Benefit from the successful establishment of your Digital Ecosystem in Digital Farming

Digitalization in agriculture offers many opportunities. Various processes and actors are interconnected along the entire value chain, meaning there is a continuous exchange of data. One characteristic of Agriculture 4.0 is the permanent collection of data. The collected data enables a higher knowledge yield if it is intelligently linked and evaluated. To do so, existing system boundaries between sensors, machines, and software must be overcome.

Data-driven services are already offered today via Farm Management Information Systems (FMIS) from various manufacturers. Future services will be based on Digital Ecosystems in which different players cooperate with each other. In this form, data, information, and services can be exchanged easily and without barriers. Within the Digital Ecosystem, diverse constellations arise between the participants. These relationships range from competitive to collaborative in order to jointly optimize applications for Digital Farming. For companies, this will result in a wide range of opportunities: the development of new business areas, the acquisition of new customers, and the initiation of innovative ideas in the area of Agriculture 4.0.


Security and data sovereignty: Get the decisive competitive edge

In addition to the system architecture, the trustworthiness, transparency, and data protection of the digital platform also play a key role in Digital Farming. For this reason, we focus on creating an infrastructure for efficient data exchange. Technical architectures are coordinated so that different agricultural platforms can be connected with each other.

With our solutions for data sovereignty, we ensure that you retain sovereignty and control over your data. We also ensure all aspects of data protection for the entire ecosystem and across system boundaries.

We fully support you in designing and implementing a Digital Ecosystem. In addition, we accompany you in the positioning and sustainable optimization of platforms in digital agriculture.


Read more about our solutions on Digital Ecosystems and data security

References: Agriculture 4.0 with Digital Ecosystem

Research project


Through knowledge transfer and
networking, the potential of digital
farming is increased.

Research project


The goal is to facilitate the exchange, processing, and analysis of data in a secure, trustworthy, and transparent manner.

Fraunhofer lighthouse project


The establishment of a data-based
ecosystem is set to become a milestone
in digital agriculture.

What are the key considerations when using data in Digital Farming?

landwirtschaft, digitalisierung, digitale landwirtschaft

“We are drowning in information, but starved for knowledge” – John Naisbitt

Whether in the field, in the stable, in the electronic arable land register, or in the Farm Management Information System: Digital data has become indispensable in Agriculture 4.0. Artificial Intelligence methods are used in a wide variety of ways. The areas of application range from the automated evaluation of large and complex data volumes to decision support and monitoring of the environment. It is also possible to assess the condition of plants and animals. AI also plays to its strengths in the use of autonomous agricultural robotics. However, quite often the full potential of the available information remains almost untapped.

We help you increase data quality in Digital Farming and create added value. Together, we will make the best of your data!


Entrust us with the reliable safety assurance of your AI applications

When using AI systems for information processing, it is not only data quality and data security that are important. The dependability and trustworthiness of the data also play a key role in Digital Farming. We provide safety arguments for AI systems and offer AI architectures that catch risks as early as possible. This way, the safety of safety-critical areas can be assured with a dependable AI system. Using Digital Dependability Identities (DDI), we integrate critical system parts from different vendors, which can then be combined dynamically at runtime. Applying Dynamic Risk Management (DRM), we enable efficient and effective interaction with the AI system. This form allows managing risk in self-learning AI systems. Furthermore, with the Uncertainty Wrapper we offer a holistic and model-agnostic approach to identify situationally reliable predictions of uncertainty in AI components.

We support you in identifying potentials and risks of your data and AI systems in various application scenarios. Using established templates and based on relevant norms, standards, and quality guidelines, we develop your individual AI system and thus create added value from your data.


Further information about our offerings on Dependable AI

References: Trustworthy AI use in Digital Farming

Industry project


Using automated analysis of data quality
to help farmers gain new knowledge
from their data in the long term.

Industry project


Development of systematic control of software diversity in agricultural engineering.

Industry project


A collaboration app for interdisciplinary
teams working together on data-driven
digital services.

How to assure the operational safety of autonomous agricultural vehicles?

Autonomer Traktor, Landwirtschaft 4.0, Smart Farming

We ensure functional safety between tractors and implements

When applying state-of-the-art safety engineering techniques, numerous safety-relevant aspects need to be considered. Systems are becoming increasingly complex due to the networking and automation of agricultural implements. This creates new risks and uncertainties.

Meet these challenges with our systematic and model-based safety engineering methods. In addition to consulting, support, and implementation of product development according to ISO 25119, we also offer relevant risk and safety analyses. Moreover, we develop comprehensive safety concepts specifically designed to meet given requirements. Using our own safety engineering tool “safeTbox”, we integrate all factors into a uniform and customized model of your system. Whether classic safety assurance methods such as FMEA (Failure Mode and Effects Analysis), FTA (Fault Tree Analysis), or CFTs (Component Fault Trees) – we help you manage the risks of your systems.


Further information about our Safety Engineering solutions

Referenzen: Digitale Landwirtschaft mit autonomen Nutzfahrzeugen

Industry project


The challenges in the development of highly automated and autonomous driving using the automotive industry as an example.

Research project


Development of new concepts for assuring and testing safety for highly automated and connected commercial vehicles.

Industry project


Assuring the functional safety of autonomous vehicles while complying with given safety standards using the automotive industry as an example.


Contact us!


We will be happy to discuss your individual challenges and design optimal solutions for you based on our competencies.