A Single Point Sensing Approach for Residential Power Monitoring with Appliance Recognition Using Random Forest

• Main Authors: Cabantac, Sheanne Eric P, Garcia, Felan Carlo, Macabebe, Erees Queen B
• Format: text
• Published: Archīum Ateneo 2019
• Subjects: refrigerators; light emitting diodes; aggregates; monitoring; energy management; machine learning algorithms; energy monitoring; machine learning; appliance recognition; Electrical and Computer Engineering; Power and Energy
• Online Access: https://archium.ateneo.edu/ecce-faculty-pubs/13; https://ieeexplore.ieee.org/abstract/document/8650282
• Institution: Ateneo De Manila University

This work utilized machine learning, specifically Random Forest, as a classifier to recognize appliance signal from an aggregate energy consumption signal obtained using a single point, nonintrusive load monitoring approach. Appliance level feedback allows energy consumers to make informed decisions...