Projects & References

Cognitive Systems and Artificial Intelligence


Establishment Fraunhofer IKS

As part of a Bavaria-wide AI network, the Bavarian Ministry of Economic Affairs is supporting the establishment of the Fraunhofer Institute for Cognitive Systems IKS. 


ADA Lovelace Center for Analytics, Data and Applications

The Fraunhofer IKS participates in the ADA Lovelace Center for Analytics, Data and Applications. This is a cooperation platform on data analytics for science and industry in Bavaria. The aim is to develop new data analytics methods and algorithms in AI applications.


High Performance Center “Secure Intelligent Systems” (LZSiS)

The Fraunhofer Institute for Cognitive Systems IKS is part of the High Performance Center “Secure Intelligent Systems” (LZSiS). The LZSiS pools interdisciplinary expertise from university and extra-university research to make digitalization usable in Bavaria.


Trustworthy autonomous systems

Two Fraunhofer IKS researchers are participating in the »European Training Network for Safer Autonomous Systems« project, which is being funded within the framework of the EU »Horizon 2020« innovation initiative. The goal of the project is to come up with safety strategies for all stages of autonomous system development.



AutoDevSafeOps: Development and operation of safe automotive systems

The MANNHEIM project AutoDevSafeOps, is developing a holistic DevOps approach to meet the high demands of automated and networked vehicles on the already existing software architecture. This approach enables over-the-air updates for safety-critical (driving) functions.


safe.trAIn: Safe AI for driverless trains

In the safe.trAIn project, 17 partners are working to establish the groundwork for using AI safely in driverless rail vehicles to make regional rail transport more efficient and sustainable. Fraunhofer IKS is focusing in particular on the proof of safety for AI functions, the robustness of AI and the Operational design domain (ODD).


AI assurance: Safe artificial intelligence for autonomous driving

The “KI-Absicherung” project for AI assurance, an initiative by the German Association of the Automotive Industry (VDA), has defined its goal of making the safety of in-car AI systems verifiable. To this end, the project partners are developing a stringent, verifiable chain of arguments for the assurance of AI functions in highly automated vehicles.



Continental and Fraunhofer IKS make autonomous vehicles safer

Together with Continental, Fraunhofer IKS was able to create a concept for the dynamic distribution of vehicle functions and develop a technical safety concept that describes an implementation of the identified safety requirements.


System Health Monitoring for Autonomous Systems

As part of the collaboration with the worldwide development partnership   AUTomotive Open System ARchitecture (AUTOSAR) Fraunhofer IKS together with other members conducts research mainly in the practical application of System Health Management.  


Resilient Platforms for Autonomous Cyber-Physical Systems

In this project, Hitachi and Fraunhofer IKS developed a resilient architecture for cloud-based control systems based on the example of an automated valet parking service in a parking garage.


Future Vehicle Software Architectures

Because the number of ECUs for integrating new functions cannot be increased at will, new concepts are required that will allow more flexible mapping of functions to the ECUs. Therefore, Fraunhofer IKS researchers (former Fraunhofer ESK) are actively working on self-adaptive E/E system concepts.



Infrastructure sensors for safe, automated forklifts

Together with Hitachi, Fraunhofer IKS has investigated whether infrastructure sensors increase safety in a warehouse with automated forklifts. To do this, the researchers created a simulation framework for the movements of automated guided vehicles in warehouses based on Webots.


Safeguarding autonomous mobile robotic systems

Fraunhofer IKS and Magazino GmbH are conducting the research project “RoboDevOps – Continuous development and safeguarding of autonomous, mobile robotic systems” to research new DevOps concepts and evaluate them based on specific scenarios.


Simple AI integration for Industry 4.0

In the joint project REMORA, Fraunhofer IKS works on the simple integration of AI services in Industry 4.0. Its goal is to simplify the integration of AI for the real-time analysis of machine data and to develop tools for high-quality, dynamic machine data.


Cloud-Based Production Controls

In the Cloud-based Industrial Services (CICS) project the Fraunhofer IKS researchers shape the production steering to be interoperable and flexible, by transferring part of it into the cloud.

Medical Technology


AI-supported personnel planning in hospitals

AI can help make tedious routine tasks easier, such as forecasting staffing requirements in hospitals. Fraunhofer IKS is addressing this issue in a current project - the findings were presented at the Healthcare Hackathon 2023 in Mainz, Germany.


Promoting innovation in healthcare

Fraunhofer IKS organized the AI Innovation Days in Berlin to bring together experts from all areas of healthcare and to develop AI-based solutions for practical use cases that benefit the patient.


AI helps where humans get stuck

Artificial intelligence can help in the treatment of coronary artery disease using stents. It was possible to predict complications and reduce their occurrence.


AI assists in making treatment decisions

Clinicians, for the most part, suffer from enormous workloads. With the help of AI, a clinical multi-organ support system can be used even better for treatment.


Quantum computing and AI for reliable medical diagnoses

Together with the University Hospital at Munich’s Ludwig-Maximilians-Universität (LMU), Fraunhofer IKS has set itself the goal of improving medical diagnoses through hybrid quantum computing-based machine learning models in a project that is focusing on highly reliable QC-based artificial intelligence for medical diagnostic tasks.


Online tool checks reliability of AI models

In modern perception applications, such as in medical engineering, models based on artificial intelligence (AI) are increasingly being used due to their strong performance. However, this increasing performance often comes at the cost of the transparency of results. An online tool developed by the Fraunhofer Institute for Cognitive Systems IKS can help here.


Noncontact health monitoring of infectious patient groups

Sensors can be used to monitor health data of infectious patients without contact. This minimizes the risk of infection for the nursing staff. Together with Airbus, the Fraunhofer IKS is testing an ear sensor to ensure that it is safe enough for use in hospitals.

Artificial Intelligence in Medicine

Artificial intelligence (AI) is becoming increasingly important in medicine. At Fraunhofer IKS, we conduct research on the validation of digital applications in these safety-critical areas.

This allows artificial intelligence to also be used for medical applications such as:

  •  Clinical decision-making
  •  Robot-assisted surgery
  •  Medical imaging and diagnostics
  •  Chronic disease monitoring
  •  Hospital Data Management

You can find more information on this on our topic page:



Resource-Adaptive Mobile Assistance System for Complex Agriculture Machines

As part of the INVIA project, seven partners are working to design an innovative, cloud-based mobile assistance system for diagnosing and servicing complex agriculture machines and implement it in a prototype environment.


Harvesters Joining the Internet of Things

In a joint project, equipment manufacturer Holmer, telecommunications manufacturer Huawei and Fraunhofer IKS (former Fraunhofer ESK) succeeded in transferring the predictive maintenance method to a fleet of highlycomplex harvesting machines.

Smart Farming: Further projects

Much of our work in the areas of mobility and production can be transferred to smart farming and agricultural areas. Therefore, read on there as well:

Quantum Technology


Bench-QC – Application-driven benchmarking of quantum computers

The goal of the Bench-QC project is to investigate when quantum computers produce better results than classic high-performance computers. Only then will quantum computing become interesting for industrial use. For this purpose, the six project partners rely on systematic application-driven benchmarking of quantum computing.


QuaST — quantum-enabling services and tools for industrial applications

The aim of the QuaST project is to provide low-threshold access to quantum computers for companies of all sizes. Industrial end users will only need to have minimal knowledge of QC hardware and software to automatically receive easily accessible and reliable QC-supported solutions for their application problems.


Munich Quantum Valley

Munich Quantum Valley conducts research on the industrial use of quantum computers and quantum technologies. To ensure that quantum computing can be used safely, Fraunhofer IKS contributes its expertise on the reliable application of advanced technologies in safety-critical systems.


Bavarian Competence Center for Quantum Security and Data Science

The Bavarian Competence Center for Quantum Security and Data Science (BayQS) aims to address three important aspects of quantum computing: cybersecurity, reliability & robustness and optimization.


Quanten Computing

Quantum computing has the potential to bring about lasting change in many economic sectors. This is because the high computing capacity of quantum computers is tapping into new applications. Fraunhofer IKS is conducting research on safe software applications for quantum computers so that you can rely on the calculations.

You can find more information on quantum computing on our topic page: