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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Abstract
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: https://orcid.org/0000-0002-1075-2420, Stankovic, Lina ORCID: https://orcid.org/0000-0002-8112-1976 and Shi, Qingjiang;-
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Item type: Conference or Workshop Item(Paper) ID code: 77769 Dates: DateEvent22 September 2021Published30 August 2021AcceptedSubjects: Technology > Electrical engineering. Electronics Nuclear engineering Department: Faculty of Engineering > Electronic and Electrical Engineering Depositing user: Pure Administrator Date deposited: 10 Sep 2021 12:40 Last modified: 11 Nov 2024 17:04 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/77769