An ensemble learning system based on convolutional neural network and long short memory recurrent neural network. With extracted features such as spectrogram and mel-frequency cepstrum coefficients from different channels, the proposed system can classify different domestic activities effectively. Our model achieved 92.19% F1-score performance, which is a 7.69% performance gain when compared with its baseline system.