AUDIOSENSE: Leveraging Current to Acoustic Channel to Detect Appliances at Single-Point

Over the past years, smart ecology has attracted much attention, especially for smart home applications. As a key component, monitoring appliances performs significant impact. However, appliances under monitoring usually contain smart modules such as WiFi or Bluetooth, which are limited to traditional appliances. Existing approaches such as distributed sensing, energy disaggregation, and infrastructure-mediated sensing, require the installation of external hardware or have a limited sensing range. In this study, we developed AUDIOSENSE to leverage the acoustic signal generated by the power supply to monitor electrical appliances throughout the house remotely from a single point. In realizing AUDIOSENSE, we proposed an optimized Variation Mode Decomposition scheme to extract the frequency components, as well as a data augmentation scheme to improve generalizability and enable multi-label classification. In experiments, AUDIOSENSE achieved mAP values of 99.3% in multi-label classification.