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This Technical Note Thanks to the unstoppable technology progress, nowadays Artificial Intelligence (AI) and specifically Machine Learning (TN for shortML) is the first one of are spreading on low-power, resource constrained devices as well. In a series illustrating how machine learning-based inference applications are deployed and perform across different embedded platformstypical Industrial IoT scenario, which are eligible for building intelligent this means that [https://en.wikipedia.org/wiki/Edge_computing#Applications edge devicescan implement complex inference algorithms that were used to run on the cloud platforms only].

The idea This Technical Note (TN for short) is to develop the first one or more reference applications with the help of wella series illustrating how machine learning-known open-source frameworks/libraries based test applications are deployed and to test them on such perform across different embedded platforms , which are eligible for comparing performances, resource utilization, development flow, etcbuilding such intelligent edge devices.

The idea is to develop one or more reference applications with the help of well-known frameworks/libraries and to test them on these platforms for comparing performances, resource utilization, development flow, etc. In the following sections, these applications are described in more detail. Each article of this series explores in detail one specific platform or use case.