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.
Non-intrusive Load Monitoring on the Edge of the Network: A Smart Measurement Node / Wohrl, H.; Brunelli, D.. - ELETTRONICO. - 627:(2020), pp. 477-482. (Intervento presentato al convegno International Conference on Applications in Electronics Pervading Industry, Environment and Society, ApplePies 2019 tenutosi a Pisa nel 2019) [10.1007/978-3-030-37277-4_55].
Non-intrusive Load Monitoring on the Edge of the Network: A Smart Measurement Node
Brunelli D.
2020-01-01
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.File | Dimensione | Formato | |
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2019-Applepies-Hugo-NILM.pdf
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