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.