Author

Stefan Reitmann

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#machine learning Preprint Sep 2026

Edge AI on Constrained Devices for Binary Sleep-Wake Classification in Dynamic Environments

This paper presents an Edge AI-based system for detecting sleep and wake states in non-stationary mobile environments using resource-constrained embedded hardware. Conventional approaches relying on accelerometer-based activity metrics are highly susceptible to motion and vibration artifacts and are limited by strict c...

S. Reitmann, Lena Oden · 0 citations

Preprint Aug 2026

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge

Deploying three-dimensional deep learning frameworks to low-power embedded processors is bottlenecked by the unstructured nature of spatial data and the resource-intensive distance sorting algorithms often used before neural network inference. To address this gap, this paper presents a hardware-constrained workflow opt...

N. Meyer, Stefan Reitmann · 0 citations