Range of Application for AIfES

Fields of Application

  • Internet of Things / Intelligent Sensors
  • Medical Devices / Wearables
  • Smart Home / Smart City
  • Smart Factory / Condition Monitorig

Current research topics

Since AIfES is very versatile, we do not limit ourselves to special applications. We are currently working on the following research topics:

Human-Technology Interaction:

  • Further development of handwriting recognition on microcontrollers
  • Recognition of complex gestures on microcontrollers
  • New innovations of the interactive therapy ball "ichó" with ichó systems (a disruptive concept for people with dementia) by one partner of the Fraunhofer-inHaus-Center 

Industry 4.0:

  • Further development of the wireless current sensor
  • Predictive maintenance
  • Decentralized AI through distributed systems
  • Combination of AIfES and NILM (Nonintrusive Load Monitoring) 


  • Sensor near and real-time capability of AI for the Fraunhofer IMS LiDAR-Sensor Technology

Medical technology:

  • Development of an intelligent sensor for the detection of human stress in the Fraunhofer-inHaus-Zentrum
  • Extended evaluation of vital parameters (virtual sensors)

Machine learning algorithms and hardware accelerators:

  • Further development of learning methods and new network structures
  • Integration of the RISC-V neuroaccelerator into AIfES

What is planned for the near future?

RISC-V neuro accelerator AIfES
© Fraunhofer IMS
RISC-V neuro accelerator AIfES


RISC-V with neuroaccelerator

The Fraunhofer IMS is currently developing a RISC-V microprocessor, which will contain a hardware accelerator especially for neural networks. AIfES will be optimized in a special version for this hardware, to assure that the hardware resource can be used optimally.





AIfES especially suitable for sensors

In future, AIfES will contain functions for signal pre-processing in addition to the machine learning algorithms. These functions are particularly suitable for feature extraction.

Further network types

Since AIfES is constantly growing and new algorithms are being implemented, the next step is the integration of further neural network topologies. These include, for example, recurrent networks or a convolutional neural network (ConvNet).

Compatibility with other software applications

In the future, AIfES will also be able to import trained models from e.g. Tensorflow. Requirement for this is that the selected network structure is also available in AIfES.

Technical Details

Platform independency and special learning techniques distinguish AIfES.

Range of Application

Human-Technology Interaction, Industry 4.0, Metrology, Medical Technology, Machine Learning Algorithms and Hardware Accelerators.


How can I use AIfES and what does the Fraunhofer IMS offer besides AIfES? You can find out more about our services here.