Enerbox

Machine Learning, Monitoring/Analytics

A Machine Learning (ML) on-the-edge system, using online-, offline- and combined analysis of power quality events, variations and faults. The technology is based on novel ML and deep learning algorithms, e.g. root-cause-analysis, detection of anomalies and early faults, originating from years of power quality research. By moving calculations close to the sensor (utilizing parallel computations through GPU), the technology aims to show how new monitoring, analysis, warning and control tools can improve the management of power quality and fast distortions from power electronics. ML waveform analytics on-the-edge will enable scalability for larger datasets through selective data communication.

Software/App