TY - GEN
T1 - Intelligent home-appliance recognition over IoT cloud network
AU - Chen, Shih Yeh
AU - Lai, Chin Feng
AU - Huang, Yueh Min
AU - Jeng, Yu Lin
PY - 2013/9/16
Y1 - 2013/9/16
N2 - In recent years, under the concern of energy crisis, the government has actively cooperated with research institutions in developing smart meters. As the Internet of Things (IoT) and home energy management system become popular topics, electronic appliance recognition technology can help users identifying the electronic appliances being used, and further improving power usage habits. However, according to the power usage habits of home users, it is possible to simultaneously switch on and off electronic appliances. Therefore, this study discusses electronic appliance recognition in a parallel state, i.e. recognition of electronic appliances switched on and off simultaneously. This study also proposes a non-invasive smart meter system that considers the power usage habits of users unfamiliar with electronic appliances, which only requires inserting a smart meter into the electronic loop. Meanwhile, this study solves the problem of large data volume of the current electronic appliance recognition system by building a database mechanism, electronic appliance recognition classification, and waveform recognition. In comparison to other electronic appliance recognition systems, this study uses a low order embedded system chip to provide low power consumption, which have high expandability and convenience. Differing from previous studies, the experiment of this study considers electronic appliance recognition and the power usage habits of general users. The experimental results showed that the total recognition rate of a single electronic appliance can reach 96.14%, thus proving the feasibility of the proposed system.
AB - In recent years, under the concern of energy crisis, the government has actively cooperated with research institutions in developing smart meters. As the Internet of Things (IoT) and home energy management system become popular topics, electronic appliance recognition technology can help users identifying the electronic appliances being used, and further improving power usage habits. However, according to the power usage habits of home users, it is possible to simultaneously switch on and off electronic appliances. Therefore, this study discusses electronic appliance recognition in a parallel state, i.e. recognition of electronic appliances switched on and off simultaneously. This study also proposes a non-invasive smart meter system that considers the power usage habits of users unfamiliar with electronic appliances, which only requires inserting a smart meter into the electronic loop. Meanwhile, this study solves the problem of large data volume of the current electronic appliance recognition system by building a database mechanism, electronic appliance recognition classification, and waveform recognition. In comparison to other electronic appliance recognition systems, this study uses a low order embedded system chip to provide low power consumption, which have high expandability and convenience. Differing from previous studies, the experiment of this study considers electronic appliance recognition and the power usage habits of general users. The experimental results showed that the total recognition rate of a single electronic appliance can reach 96.14%, thus proving the feasibility of the proposed system.
UR - http://www.scopus.com/inward/record.url?scp=84883668067&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84883668067&partnerID=8YFLogxK
U2 - 10.1109/IWCMC.2013.6583632
DO - 10.1109/IWCMC.2013.6583632
M3 - Conference contribution
AN - SCOPUS:84883668067
SN - 9781467324793
T3 - 2013 9th International Wireless Communications and Mobile Computing Conference, IWCMC 2013
SP - 639
EP - 643
BT - 2013 9th International Wireless Communications and Mobile Computing Conference, IWCMC 2013
T2 - 2013 9th International Wireless Communications and Mobile Computing Conference, IWCMC 2013
Y2 - 1 July 2013 through 5 July 2013
ER -