Where do you come into play? During this hands-on internship,
you will work with different software solutions, development
boards and ecosystems designed for these ISPU and
embedded AI applications.
The use case around which this thesis is build is anomaly
detection of the motors of a motorized stairlift.
You will be able to work (but not limited to) the following
technologies:
• STM32’s Cube.AI and NanoEdgeAI Studio
• eIQ from NXP
• E-AI from Renesas
• Tensorflow lite
• Other

As internship outcome we expect the
following:
• State-of-the-art on embedded AI
technologies (hard- and software)
• A trade-off between available solutions
(hard- and software)
• Design guidelines and methodology for
embedded AI development and integration.
• Demonstration of anomaly detection on a
stairlift.

•
You have a keen interest in AI and embedded
applications.
• You are experienced in C or C++.
• You have experience in with microcontrollers and IMU sensors.
• You know the basics of AI development.
• Experience with any embedded AI solutions is