探勘使用者電器使用行為模式

最近幾年全球暖化的議題備受關注，而我們都知道說全球暖化是因為產生過量的CO2和溫室氣體所造成。根據研究，又以家中用電產生最多的溫室氣體，所以如果我們能節約家庭用電，不僅可以減少溫室氣體的產生，相對也可以減少家庭用電的支出。但是節約用電對居住者來說並不是一件簡單的任務，因為居住者無法獲得足夠的家庭用電資訊，居住者可以獲得用電資訊的來源主要來自每個月的帳單或是家中的電表，但是居住者只能從帳單中知道總電費或是從電表知道總耗電度數，即使看到帳單費用很貴，也無法做出有效且正確的決策在節約用電上，使電費下降。因此我們在智慧家庭的環境下開發了一個系統，去分析居住者使用電器的行為，這部份我們提出四種usage pattern去描述居住者使用電器的行為，所以當發現這個月帳單比上個月高時，可以透過我們的系統知道他的用電資訊，更進一步還可以知道是否有extraordinary的使用行為造成用電過高。所以居住者可以透過我們的系統知道更多的用電資訊，然後可以在節約用電的方面上做出有效率且正確的決策。此外我們利用真實智慧家庭收集的資料去呈現我們所提出的四種usage pattern。

關鍵字

使用行為特徵；智慧家庭；時間序列資料

並列摘要

In the last decade, considerable concern has arisen over the electricity saving due to the issue of reducing greenhouse gases. However, in daily lives, conserving electricity is not an easy task, since residents only can acquire the total electricity consumption from their bills or power meters. If more detailed behaviors of appliance usage are available, residents can make the correct policy to conserve the energy according to their frequent usage patterns. In this paper, based on four proposed usage patterns, we develop a system to analyze and aware users the detailed appliance usage information in a smart home environment. In advance, if the electricity cost is high, users can observe the extraordinary usage of appliances from the proposed system for energy saving easily. Furthermore, we also apply our system on real-world dataset to show the practicability of mining usage pattern in a smart home environment.

並列關鍵字

Usage patterns ； Smart environment ； time series data

參考文獻

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探勘使用者電器使用行為模式

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