Digital Farming / Smart Farming

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?

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

• How to assure the operational safety of autonomous agricultural vehicles?

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

• Focus topic “Digital Ecosystems”
  Digital Ecosystems and platform economy in detail
   

• Competence “Security Engineering”
  Data sovereignty in Digital Ecosystems with “MY DATA Control Technologies”
   

• Study: Final report of Feasibility Study
  Feasibility study on government-run digital data platforms for agriculture [in German]
   

• Whitepaper: Agricultural Data Space (ADS)
  Added value of a data space and necessary prerequisites for digital farming

“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

• Focus topic “Dependable AI”
  Designing data-driven business models reliably with Artificial Intelligence
• Study: Operational Data Management and FMIS
  Feasibility study on “Operational Data Management and Farm Management Information System (FMIS)” in agricultural enterprises in the German state of Saxony [in German]

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

• Competence “Safety”
  Innovative safety concepts with special requirements
  
  
• Research program “Autonomous Systems”
  Concepts for the development of highly automated and autonomous systems
  
  
• Study: Autonomous Agriculture in 2045
  New study on the automatization of agricultural machinery
  
  
• Whitepaper: Making agriculture sustainable with AI and autonomous systems while keeping safety in mind!
  
  
• Pioneering Situation-aware Autonomy and Safety for Off-Highway Machinery in Unpredictable Terrain