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Lookup NU author(s): Weixian Li,
Dr Thillainathan Logenthiran,
Dr Van-Tung Phan,
Dr Wai Lok Woo
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IEEE Internet of things (IoT) makes deployment of smart home concept easy and real. Smart home concept ensures residents to control, monitor and manage their energy consumption without any wastage. This paper presents a self-learning Home Management System (SHMS). In the proposed system, a Home Energy Management System (HEMS), Demand Side Management (DSM) system, and Supply Side Management (SSM) system were developed and integrated for real time operation of a smart home. This integrated system has some capabilities such as Price Forecasting (PF), Price Clustering (PC) and Power Alert System (PAS) which to enhance its functions. These enhancing capabilities were developed and implemented using computational and machine learning technologies. In order to validate the proposed system, real-time power consumption data was collected from a Singapore smart home and a realistic experimental case study was carried out. The case study has shown that the developed system has performed well and created energy awareness to the residents. This proposed system also displays its ability to customize the model for different types of environments compared to traditional smart home models.
Author(s): Li W, Logenthiran T, Phan V, Woo WL
Publication type: Article
Publication status: Published
Journal: IEEE Internet of Things Journal
Print publication date: 01/06/2018
Online publication date: 18/04/2018
Acceptance date: 06/04/2018
ISSN (electronic): 2327-4662
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