Name
Abstract | ||
|---|---|---|
The concept of smart home has attracted considerable attention in recent years, and energy management is one of its key component. This attributes to the growing concern in environmental protection and energy conservation, as well as the demands for big data collection from utility companies and policy makers. Current solutions often approach this problem by either the centralized non-intrusive load monitoring (NILM) or the decentralized smart controls but seldom both, rendering them impractical to some extent. Therefore, in this paper, we propose a novel framework of smart home energy management systems incorporating both approaches, so that accurate power consumption monitoring and intuitive interaction with the home appliances are simultaneously achieved. The smart components directly control the appliances, while the central controller coordinates the data collection and communication. The key feature is the capability of automatically mapping the appliances to their corresponding sockets, reducing the necessity for manual initial setup. Numerical simulations prove the accuracy and efficiency of the framework. We believe that our systems, if widely deployed, can benefit not only individual households by saving energy bills and simplifying life but also society by the big data generated. |
Year | Venue | Field |
|---|---|---|
2015 | 2015 IEEE INTERNATIONAL CONFERENCE ON SMART GRID COMMUNICATIONS (SMARTGRIDCOMM) | Data collection,Energy management,Control theory,Energy conservation,Smart grid,Computer security,Real-time computing,Home automation,Engineering,Rendering (computer graphics),Big data,Distributed computing |
DocType | ISSN | Citations |
Conference | 2373-6836 | 1 |
PageRank | References | Authors |
0.35 | 7 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wenjin Jason Li | 1 | 1 | 0.35 |
| Xiaoqi Tan | 2 | 91 | 14.79 |
| Danny H. K. Tsang | 3 | 945 | 95.24 |