A Supervised Learning Approach to Appliance Classification Based on Power Consumption Traces Analysis

[摘要] Electric appliances are everyday major power consumers. Management and control of these appliances can only be possible with appliance classification infrastructures. An appliance classification smart meter, with a provision for remote control, is developed based on time-dependent power features drawn by an appliance, from power-up to its steady state. The kNN classifier is highly accurate at 95.55% in classifying the appliance class.

[发布机构] Department of Engineering Education, University of Mindanao - Tagum, Visayan Village, Tagum City, Davao del Norte; 8100, Philippines^1;School of EECE, Mapua University, 658 Muralla St., Intramuros, Manila; 1002, Philippines^2

[效力级别] 无线电电子学 [学科分类] 计算机科学（综合）

[关键词] Highly accurate;K-NN classifier;Management and controls;Power consumers;Steady state;Supervised learning approaches;Time dependent