Energy-Efficient Deep Multi-Label ON/OFF Classification of Household Appliances from Low-Frequency Metered Data

The proposed Convolutional transpose Recurrent Neural Network (CtRNN) architecture achieves superior performance compared to state-of-the-art models while significantly reducing energy consumption, making it a more sustainable solution for NILM-based appliance activity monitoring.