Title :
A Parallel Multi-appliance Recognition for Smart Meter
Author :
Lien-Chun Wang ; Wei-Ting Cho ; Yu-Sheng Chiu ; Chin-Feng Lai
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Chung Cheng Univ., Chiayi, Taiwan
Abstract :
This study proposes a non-invasive smart meter system that considers the power use habits of users unfamiliar with electric appliances, and can be used by inserting the smart meter into an electrical circuit. This study also creates a database mechanism, appliance recognition classification, and a waveform recognition method, in order to solve the large data volume problem in current appliance recognition systems. In comparison to other appliance recognition systems, the low-end embedded system chip used in this study has low power consumption, as well as high expandability and ease of use. This experiment is different from the research environments of other appliance recognition systems by considering parallel multi-appliance recognition and general users´ habit of using power. This study will not make any assumption of power utilization in the experiment. The total system recognition rate is 84.42%, and the total recognition rate of a single electric appliance is 93.82%, proving the high feasibility of this study.
Keywords :
domestic appliances; embedded systems; home automation; power consumption; power engineering computing; power utilisation; smart meters; appliance recognition classification; appliance recognition systems; database mechanism; electric appliances; electrical circuit; large data volume problem; low-end embedded system chip; noninvasive smart meter system; parallel multiappliance recognition; power consumption; power utilization; user power use habits; waveform recognition method; Databases; Decision trees; Feature extraction; Heuristic algorithms; Home appliances; Smart grids; Smart meters; Appliance Recognition; Parallel; Smart Meter;
Conference_Titel :
Dependable, Autonomic and Secure Computing (DASC), 2013 IEEE 11th International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4799-3380-8
DOI :
10.1109/DASC.2013.110