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Core topic Embedded AI

AI algorithms and methods unsuitable for embedded systems

Usually, embedded systems are specifically adapted to their task such as data acquisition or control or signal processing in a device and optimised for minimal cost, space, energy and memory consumption. The numerous existing AI algorithms and methods, in contrast, usually operate on much more powerful, larger, more energy-intensive and more expensive computing technology and are unsuitable for embedded systems. In addition, there are often too few data sets available for applications to train an AI, such as from fault situations on a machine for which predictive maintenance is to be supported with AI.

We optimise AI algorithms and methods for embedded systems

We are researching to optimise AI algorithms and methods so that they can be used on embedded systems. For predictive maintenance applications, for example, we are working on generating artificial data, increasing robustness and transferring the solutions to similar problems.

Contact

Contact

Dr.-Ing. Tino Hutschenreuther

Head of System Design

tino.hutschenreuther(at)imms.de+49 (0) 3677 874 93 40

Dr. Tino Hutschenreuther will answer your questions on our research in Smart distributed measurement and test systems and the related core topics Analysis of distributed IoT systems, Embedded AI and Real-time data processing and communications, on the lead applications Adaptive edge AI systems for industrial application and IoT systems for cooperative environmental monitoring as well as on the range of services for the development of embedded systems.

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Project

thurAI

In thurAI, IMMS is working on sensor technology for SmartCity and methods to intelligently process data in the network for AI evaluations.

Project

KIQ

IMMS has developed an AI-based, retrofittable and cost-effective solution for quality assurance of machining tools.

Project

sUSe

To use compressed air for industrial processes in an energy-efficient way, IMMS has developed the electronics platform for an automatable sensor solution.

Project

AgAVE

Industry 4.0 communications for an assistance system, ML-based, that autonomously analyses connected production chains

Reference

Dr. Alexander Maier, Fraunhofer IOSB-INA

“We very much appreciate not only the sound, practical engineering knowledge of the IMMS staff concerning Industry 4.0-compatible protocols and systems but also the personal contact and the constructive manner of IMMS’ collaboration. And so we shall be delighted if we can tackle upcoming subjects together.”
All publications in the field of Embedded AI

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Lead application

Adaptive edge AI systems for industrial application

We are researching solutions for adaptive edge AI systems to make AI possible on low-consumption embedded systems in industry and to network them in real time.

Service for R&D

Development of embedded systems

We develop embedded systems for you as complete solutions consisting of sensors and actuators, signal processing and communications technology as well as open-loop and closed-loop controls.

Lead application

IoT systems for cooperative environmental monitoring

We are researching energy-efficient solutions for IoT systems to open up new applications for cooperative environmental monitoring, such as in agriculture.

Research field

Smart distributed measurement and test systems

Integrated sensor ICs are the heart of sensor and measurement systems like wireless sensors, stationary or handheld devices. We are researching solutions for ever more powerful sensors with more intrinsic intelligence and task allocation in the network.