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NeuroCPS4 Maintenance – Neuromorphic Anomaly Detector

NeuroCPS4Maintenance is a project that aims to develop and demonstrate a neuromorphic edge anomaly detector that is robust against conceptual drift, alerts to faults early and provides fast, real-time response for predictive maintenance applications in high-demand industrial scenarios (industrial press). This anomaly detector will be based on deep learning algorithms (LSTM) and implemented on system on chips (SoC).

Duration: March 2021 - 2022

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