TY - JOUR
T1 - Home energy management system for interconnecting and sensing of electric appliances
AU - Cho, Wei Ting
AU - Lai, Chin Feng
AU - Huang, Yueh Min
AU - Lee, Wei Tsong
AU - Huang, Sing Wei
PY - 2011/7/28
Y1 - 2011/7/28
N2 - Due to the variety of household electric devices and different power consumption habits of consumers at present, general home energy management (HEM) systems suffer from the lack of dynamic identification of various household appliances and a unidirectional information display. This study presented a set of intelligent interconnection network systems for electric appliances, which can measure the power consumption of household appliances through a current sensing device based on OSGi platform. The system establishes the characteristics and categories of related electric appliances, and searches the corresponding cluster data and eliminates noise for recognition functionality and error detection mechanism of electric appliances by applying the clustering algorithm. The system also integrates household appliance control network services so as to control them according to users' power consumption plans or through mobile devices, thus realizing a bidirectional monitoring service. When the system detects an abnormal operating state, it can automatically shut off electric appliances to avoid accidents. In practical tests, the system reached a recognition rate of 95%, and could successfully control general household appliances through the ZigBee network.
AB - Due to the variety of household electric devices and different power consumption habits of consumers at present, general home energy management (HEM) systems suffer from the lack of dynamic identification of various household appliances and a unidirectional information display. This study presented a set of intelligent interconnection network systems for electric appliances, which can measure the power consumption of household appliances through a current sensing device based on OSGi platform. The system establishes the characteristics and categories of related electric appliances, and searches the corresponding cluster data and eliminates noise for recognition functionality and error detection mechanism of electric appliances by applying the clustering algorithm. The system also integrates household appliance control network services so as to control them according to users' power consumption plans or through mobile devices, thus realizing a bidirectional monitoring service. When the system detects an abnormal operating state, it can automatically shut off electric appliances to avoid accidents. In practical tests, the system reached a recognition rate of 95%, and could successfully control general household appliances through the ZigBee network.
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U2 - 10.3837/tiis.2011.07.004
DO - 10.3837/tiis.2011.07.004
M3 - Article
AN - SCOPUS:79961087462
VL - 5
SP - 1274
EP - 1292
JO - KSII Transactions on Internet and Information Systems
JF - KSII Transactions on Internet and Information Systems
SN - 1976-7277
IS - 7
ER -