Franke, SvenSvenFrankeBommert, AndreaAndreaBommertBrandt, Marc JulianMarc JulianBrandtKuhlmann, Jean LenardJean LenardKuhlmannOlivier, Marie-ClaireMarie-ClaireOlivierSchorning, KirstenKirstenSchorningReining, ChristopherChristopherReiningKirchheim, AliceAliceKirchheim2025-02-172025-02-172024https://publica.fraunhofer.de/handle/publica/48400610.1109/ETFA61755.2024.10710674This article presents a toolchain for event detection of pallets using IMUs and a novel data set called SPARL. Basedon a logistical use case, two sensors are benchmarked in welldefined logistics scenarios. The data set contains the videos of two representative recordings from different perspectives andthe raw data of the three used sensors. A random forest time series classification model is deployed for activity recognition. The preliminary results indicate that it is possible to recognize logistical activities based on sensor data.enwarehousingevent detectionlogisticsactivity recognitionintertial measurementintelligent palletsinternet of thingsconference paper