Home appliances classification based on multi-feature using ELM Online publication date: Wed, 12-Sep-2018
by Qi Liu; Fangpeng Chen; Fenghua Chen; Zhengyang Wu; Xiaodong Liu; Nigel Linge
International Journal of Sensor Networks (IJSNET), Vol. 28, No. 1, 2018
Abstract: With the development of science and technology, smart home has become a hot topic. And pattern recognition adapting to smart home attracts more attention, while the improvement of the accuracy of recognition is an important and difficult issue of smart home. In this paper, the characteristics of electrical appliances are extracted from the load curve of household appliances, and a fast and efficient home appliance recognition algorithm is proposed based on the advantage of classification of extreme learning machine (ELM). At the same time, the sampling frequency with low rate is mentioned in this pa-per, which can obtain the required data through intelligent hardware directly, as well as reduce the cost of investment. Experiments in this paper show that the proposed method can accurately determine the using electrical appliances. And greatly improve the accuracy of identification, which can further improve the popularity of smart home.
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