Fraunhofer Institute for Microelectronic Circuits and Systems

Embedded AI – sensor based and platform-independent

Fraunhofer IMS has developed AIfES – a continually growing machine learning library for sensors and embedded systems.

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LiDAR systems become increasingly important in advanced driver assistance systems and industrial robotics. For such applications Fraunhofer IMS develops highly sensitive CSPAD detectors and novel approaches for ambient light suppression on chip level. Together these guarantee best performance and reliable measurements.

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Fraunhofer IMS reinforces Biosensors

Prof. Dr. Karsten Seidl is the new head of the department micro- and nanosystems at Fraunhofer IMS in Duisburg. He also holds a chair for medical technology at the University of Duisburg-Essen. Karsten Seidl helps to strengthen the topic area of biosensors at the research institute in Duisburg.

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Sensor-readout at the highest level

Fraunhofer IMS developed highly-precise sensor-readout-ASICs for robust application. High-precision, robust and secure – regarding sensors, these characteristics seem to contradict. Fraunhofer Institute for Microelectronic Circuits and Systems IMS in Duisburg has again performed an important step for the secure implementing of industry 4.0 and developed two sensor-ASIC series for capacitive and inductive sensor readout that do combine these attributes.

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Microsystems Technology

New procedures of post-processing serve the integration of sensors with electronics onto a microchip. Deploying these high-end sensors in thermography and the health sector is part of the special know-how of the institute.

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Microsystems Technology

Microsystems technology and microelectronics merge closely to create compact “intelligent“ sensors and actors.


Profile of the institute

Fraunhofer IMS

For 30 years, scientists at the Fraunhofer IMS in Duisburg have been involved in the development of microelectronic circuits, electronic systems, microsystems and sensors.


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47057 Duisburg

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Latest News


Trustworthy embedded AI with RISC-V

The Fraunhofer Institute for Microelectronic Circuits and Systems IMS has developed a trustworthy embedded AI (Artificial Intelligence) on an RISC-V basis. With this development the research institute from Duisburg is expanding its offerings for Trusted Electronics.
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Condition Monitoring of Overhead Lines

In the context of climate protection, the importance of energy efficiency is increasing, as is the share of electricity from renewable energies. Thousands of wind farms, solar modules and biogas plants already generate large quantities of green electricity. The expansion of wind power plants in particular has led to leaps in performance in recent years. In addition to the optimal utilization of the high-voltage overhead lines, the rapid detection of hazardous situations is a central issue. Fraunhofer IMS has developed a sensor system with energy self-sufficient sensor modules for monitoring the operating parameters.
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Machine learning for sensors

Today microcontrollers can be found in almost any technical device, from washing machines to blood pressure meters and wearables. Researchers at the Fraunhofer Institute for Microelectronic Circuits and Systems IMS have develo-ped AIfES, an artificial intelligence (AI) concept for microcontrollers and sensors that contains a completely configurable artificial neural network. AIfES is a plat-form-independent machine learning library which can be used to realize self-learning microelectronics requiring no connection to a cloud or to high-perfor-mance computers. The sensor-related AI system recognizes handwriting and gestures, enabling for example gesture control of input when the library is running on a wearable.
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Fraunhofer IMS develops AI platform for health, care and social participation

An AI platform should build an ecosystem for health economy. The Fraunhofer-Gesellschaft is participating with the institutes IMS and IIS as consortium partners and wants to help SMEs with the integration of AI solutions. The VDE wins with the project “CareFul KI” in the AI innovation competition that was organized by the BMWi and thereby proving themselves against 130 other applicants.
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