Anomaly detection for predictive maintenance in the edge

Here you find the details for the internship named "Anomaly detection for predictive maintenance in the edge" in the company Verhaert Masters in Innovation.

Name: Anomaly detection for predictive maintenance in the edge
Company: Verhaert Masters in Innovation

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
• STM32’s Cube.AI and NanoEdgeAI Studio
• eIQ from NXP
• E-AI from Renesas
• Tensorflow lite
• Other

As internship outcome we expect the
• 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

Brochure: Download
Target profiles:
    In industries:
      Required special knowledge:

      You have a keen interest in AI and embedded
      • 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

      Duration: 2024 - 2025
      Paid: No
      Net wage: -
      Foreign: No