Fraunhofer Institute for Microelectronic Circuits and Systems
Fraunhofer Institute for Microelectronic Circuits and Systems
Engineer check and control welding robotics automatic arms machine in intelligent factory automotive industrial with monitoring system software. Digital manufacturing operation. Industry 4.0

Embedded AI for Smart Sensor and Machines

Efficiency directly in your processes and products: Energy-efficient AI, sensor fusion, and retrofittable solutions—for manufacturing, mechanical engineering, and intelligent sensor systems.

© Fraunhofer IMS

Embedded AI for Smart Sensor and Machines

Energy-efficient AI solutions at the edge increase the efficiency of production processes and enhance the value of machine and sensor products. Fraunhofer IMS develops customized concepts for smart sensor technology, anomaly detection, and remaining service life predictions – retrofittable, scalable, and future-proof.

Why embedded AI is crucial

Instead of transferring data to the cloud or maintaining machines at fixed intervals, embedded AI enables local, data-based condition monitoring directly at the sensor. This ensures:

  • Higher plant availability through precise predictions
  • Lower costs through optimized maintenance intervals
  • Greater safety through timely fault detection
  • Increased data security through edge computing without cloud dependency
  • Energy efficiency thanks to optimized AI models directly on the device

At a glance​

© Anna Lena Schall-Giesecke, Fraunhofer IMS

Costumer benefits

  • Energy- and cost-efficient
  • Real-time quality control
  • Cost reduction
  • Retrofit-ready
  • Increased data security

Technologies

  • Sensors & Hardware: FPGA/ASIC AI accelerators and sensor fusion
  • Embedded AI: On-device AI & federated learning
  • Modular AI: Sensor kits and model packages

Applications

  • Predictive maintenance in industry
  • Predicting the remaining service life of cutting tools
  • Predictive maintenance of conveyor belts to prevent breakdowns
  • Anomaly detection in complex manufacturing processes

Services

  • AI workshops & use case scouting
  • Smart sensor concepts & feasibility studies
  • ML for anomaly detection & classification
  • Data preprocessing & analysis
  • Edge AI integration & scaling

Our Expertise

We bring AI to where data is generated: at the sensor, on the edge, and within the edge-cloud continuum for secure, flexible integration and maximum scalability.

AI at the Edge

Our expertise lies in the execution of ML models on embedded systems. This means that machines can detect deviations in real time – quickly, securely, and reliably, without having to go through the cloud.

Tailored AI Solutions

We offer customized concepts for your production and your products: remaining life predictions, anomaly and pattern recognition, and prediction models for specific machines and processes.

Smart Sensor Concepts

We combine data collection and analysis with intelligent sensor solutions. Our smart sensors not only provide raw data, but also interpret it directly—the basis for efficient, retrofittable AI solutions.

Your Competitive Advantage

With our embedded AI solutions, you benefit from:

  • Maximum equipment availability
  • Reduced downtime and maintenance costs
  • Future-proof strategies with edge AI and smart sensor technology

Whether you optimize production processes or develop innovative machines and sensor systems – our solutions make your products and equipment more efficient, secure, and ready for the industry of tomorrow.

 

Reference projects

 

Wise-Cut: Wisdom in Machining

Real-life demonstration of a machining process with integrated vibration sensors and AI evaluation to predict tool life and workpiece quality

more info
 

PowerCare

PowerCare aims to make power modules in industry and mobility more efficient and sustainable through the use of intelligent power electronics with innovative gallium nitride (GaN) semiconductors and real-time failure models in motor controllers.

more info
 

GenSATIOn-Edge

The GenSATIOn-Edge project is developing self-learning AI models for condition diagnosis and prognosis based on vibration measurements.

more info
 

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