Abstract
In the last decade, considerable concern has arisen over the electricity saving due to the issue of reducing greenhouse gases. Previous studies on usage pattern utilization mainly are focused on power disaggregation and appliance recognition. Little attention has been paid to utilizing pattern mining for the target of energy saving. In this paper, we develop an intelligent system which analyzes appliance usage to extract users' behavior patterns in a smart home environment. With the proposed system, users can acquire the electricity consumption of each appliance for energy saving easily. In advance, if the electricity cost is high, users can observe the abnormal usage of appliances from the proposed system. Furthermore, we also apply our system on real-world dataset to show the practicability of mining usage pattern in smart home environment.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2012 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2012 |
| Pages | 319-322 |
| Number of pages | 4 |
| DOIs | |
| State | Published - 2012 |
| Event | 2012 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2012 - Tainan, Taiwan Duration: 16 Nov 2012 → 18 Nov 2012 |
Publication series
| Name | Proceedings - 2012 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2012 |
|---|
Conference
| Conference | 2012 Conference on Technologies and Applications of Artificial Intelligence, TAAI 2012 |
|---|---|
| Country/Territory | Taiwan |
| City | Tainan |
| Period | 16/11/12 → 18/11/12 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Abnormal detection
- Energy saving
- Smart home
- Usage pattern
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