Projects and products

ArGUS detects unmanned flight systems and generates deployment proposals for legally secured countermeasures.

Cyber resilience is seen as the next step in IT security and focuses primarily on incident response and restoring process capability. Appropriate monitoring of process-carrying automation systems and infrastructures is necessary to achieve cyber resilience.

Das Projekt CC-King hat sich zum Ziel gesetzt, KI-Spitzenforschung mit etablierten Ingenieurdisziplinen zu verbinden. Hierdurch sollen KI-Methoden und maschinelle Lernverfahren (ML) entsprechend den typischen Anforderungen und Vorgehensweisen von Ingenieuren nutzbar gemacht werden.

AKIT is researching a new type of recovery chain consisting of a highly automated recovery vehicle, support shuttle and communication components.

The topic of the "Wolverine" project is data integration and evaluation for medical applications.

Multisensory system for AI-based drone detection and classification with situation visualization.

RoboShield deals with automation technologies in human-robot collaboration. Artificial intelligence and machine learning are used to verify safety. New development processes for modules, systems and applications are being researched that ensure the safety of the resulting production facility ("Safety by Design"). A method kit with different verification techniques will enable the verification of third-party automation components.

The aim of the fully automated immun chip is to predict the immune response to a drug or chemical of up to 100 individuals at the same time.

The Karlsruher Forschungsfabrik for AI-integrated production offers the special opportunity to research and develop the topic of “Intelligent Production” in a practical way on real processes.

“AutoInspect” is a system for continuous object assessment (in real time) by multimodal inspection along the production cycle. Both a direct reaction to the results and their long-term observation are possible. The system is supported by a digital quality twin with open I4.0 standards.

Intelligent video surveillance systems increase patient safety in hospitals and care facilities.

"S²UCRE" is a project of the Federal Ministry of Education and Research (BMBF). The aim of this project is to improve security in urban environments through crowd monitoring, prediction and decision support.

Who even remembers all of their passwords?

The systems advise physicians like an expert for medical problem solving would.

Recycling is the largest source of raw materials in the world - at the Fraunhofer IOSB the necessary solutions for this have been researched and implemented for years in the department "Visual Inspection Systems".

The dynOpt energy manager is primarily intended for commercial properties such as apartment buildings and neighbourhoods where several components such as heat pumps, PV systems, solar heating systems, gas boilers or CHP units are operated in a coupled manner. Furthermore, dynOpt-En monitors energy consumption and costs and compares the real values with the expected values. In this way, malfunctions can be detected promptly and signalled via a clear visualisation or reported to the operator.

Breaking infection chains in the clinical environment is one of the biggest challenges in the healthcare system. At the same time, however, digitization is also being driven forward here and, for example, patient records are being maintained digitally. Increasingly, data entry and processing is done via smartphone or tablet. These devices often move from hand to hand, easily enabling pathogen transmission. Chemical disinfection of the sensitive devices is not possible due to the aggressiveness of the disinfectants.

By including a photodiode on the submount, accurate detection of the radiation intensity of each LED is possible. It uses the photodiode's characteristic curve to control the intensity of each LED via its current. Decreases in output due to aging can thus be detected and compensated for within certain limits. The aluminum reflector developed in the project, which was largely developed by project partner OSA OptoLight GmbH, collects and shapes the (UV) LED light. The downstream microlens array made of quartz glass mixes the different wavelengths with only a slight increase in divergence.

Respiratory masks are based almost exclusively on elimination of aerosols by filtering action of tissues. This is cost-effective, but also has the disadvantage that a reduction in the mesh width or pore size of the filter fabric is required to increase the filtering effect.

Common practice is currently wipe disinfection or disinfectant cleaning by cleaning professionals. However, the desirability of regular disinfection - ideally several times a day - is limited due to the large number of potentially contaminated surfaces. Moreover, cleaning agents or disinfectants are often applied in excess without concrete feedback on the associated disinfection performance.

The task of Fraunhofer IOSB-AST in this subproject is, on the one hand, the physical simulation of the radiation propagation as well as the air flow in the planned system and, on the other hand, a determination of the optimal LED arrangement and number and the simulative design of the necessary cooling system. Furthermore, an efficient control of the LEDs as well as their monitoring shall be realized.

This manual process is error-prone and tedious. In most cases, disinfection gels must be evenly distributed on the surface according to the manufacturer's instructions, allowed to act for a certain time, and then removed again in a further process step UV disinfection with high irradiation doses enables efficient, and rapid, inactivation of microorganisms adhering to the device, thus sterilizing it.

For the early detection of health-threatening contaminations in drinking water, therefore, an online-capable broadband test procedure for drinking water conformity is needed that reacts very quickly and reliably, is robust against false alarms, can be operated by persons without scientific qualifications and whose acquisition and maintenance costs are economically justifiable. Currently, such online-capable and broadband sensor systems are not commercially available.

Determining the degree of freshness and ripeness of fruits and vegetables with the help of various sensors and artificial intelligence opens up new possibilities for the anticipatory handling of food.

The production of bulk and fine chemicals on the basis of renewable raw materials has become increasingly important in recent years as "white biotechnology". Surfactants, which are currently produced industrially to a large extent from petrochemical starting materials, are a potential product for the use of biotechnological production processes.

In order to keep the total operating costs of wind turbines (WTGs) competitive, the risk of failure must be minimized, maintenance costs reduced, and system availability and energy efficiency increased. This goal is achieved by introducing the most efficient, automated multi-sensory online monitoring and diagnostic systems - so-called Condition Monitoring Systems (CMS) - whose economic importance is increasingly recognized by wind farm operators, manufacturers and insurers.

Process engineering processes usually have a large number of process variables which generate an alarm when a previously defined threshold value is exceeded in the event of abnormal process behavior. If a fault occurs in a central plant section, this leads to a flood of alarms, since the individual process variables are interdependent and the fault propagates through the plant.

By means of the developed and integrated data management and above all thanks to the advanced data evaluation, it is possible to carry out systematic data evaluation as well as plant monitoring, thus increasing the efficiency of the production process.

In the Fraunhofer ML4P lead project, several Fraunhofer Institutes are pooling their application experience and machine learning skills to develop solutions for industry. The aim is to develop a tool-supported process model that paves the way for flexible, fast-learning machines and systems.

The HeatSteel project is developing innovative and energy-efficient heat treatment lines for ultra-thin precision strip.