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In this work, we pick up the ISE research on automation of intelligent integrated systems design and apply and adapt the concept, methodology, and tool implementation. In particular, a new platform, based on the proven machinelearning tool ORANGE will make the work multi-platform and open-access. We demonstrate the current status by the application to our Lab-on-Spoon (LoS) multi-sensory system and corresponding data. The creation of a an efficient Support-Vector-Machine (SVM)-based hierarchical classification architecture and options of automated feature selection (AFS) are investigated in the experiments. An improved in two cases to 100% classification accuracy with regard to the previous flat approach was achieved.

4.3 - Application-Specific Partially Automated Design of Multi-Sensor Intelligent Lab-on-Spoon System