Abstract
To efficiently reduce energy usage in buildings, it is necessary to understand how energy is consumed today. Non-intrusive load monitoring (NILM) is a promising approach where appliance level load profiles can be extracted from an agglomerated single-point measurement using statistical or machine-learning methodology. Moving NILM to the edge of the network holds many advantages like reduced operation cost and decreased power consumption while minimizing privacy concerns. In this paper, we present a NILM hardware that can apply real-time NILM on the edge of the network on an ultra-low power AI-optimized microcontroller.
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Wöhrl, H., Brunelli, D. (2020). Non-intrusive Load Monitoring on the Edge of the Network: A Smart Measurement Node. In: Saponara, S., De Gloria, A. (eds) Applications in Electronics Pervading Industry, Environment and Society. ApplePies 2019. Lecture Notes in Electrical Engineering, vol 627. Springer, Cham. https://doi.org/10.1007/978-3-030-37277-4_55
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DOI: https://doi.org/10.1007/978-3-030-37277-4_55
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