Non-intrusive load monitoring for multi-objects in smart building

Li, Dandan and Li, Jiangfeng and Zeng, Xin and Stankovic, Vladimir and Stankovic, Lina and Shi, Qingjiang (2021) Non-intrusive load monitoring for multi-objects in smart building. In: Fourth International Balkan Conference on Communications and Networking, 2021-09-20 - 2021-09-22.

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    The rapidly expansion of Internet of Things (IoT) has ignited renewed interest in energy disaggregation via nonintrusive load monitoring (NILM). Compared to the more frequent NILM approach of training one model for each appliance, this paper proposes a multi-label learning approach based on the widely cited sequence2point convolutional neural network (CNN). Using the smart meter readings collected in an office building, we demonstrate the accuracy and practicality of the proposed network compared to start-of-the-art one-to-one NILM models.

    ORCID iDs

    Li, Dandan, Li, Jiangfeng, Zeng, Xin, Stankovic, Vladimir ORCID logoORCID:, Stankovic, Lina ORCID logoORCID: and Shi, Qingjiang;