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Power Consuming Activity Recognition in Home Environment

机译：家庭环境中的功耗活动识别

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This work proposed an activity recognition model which focus on the power consuming activity in home environment, to help residents modify their behavior. We set the IoT system with lower number of sensors. The key data for identifying activity comes from widely used smart sockets. It first took residents' acceptability into consideration to set the IoT system, then used a seamless indoor position system to get residents' position to help recognize the undergoing activities. Based on ontology, it made use of domain knowledge in daily activity and built an activity ontology. The system took real home situation into consideration and make full use of both electric and electronic appliances' data into the context awareness. The knowledge helps improve the performance of the data-driven method. The experiment shows the system can recognize the common activities with a high accuracy and have a good applicability to real home scenario.
机译：这项工作提出了一个活动识别模型，该模型着重于家庭环境中的耗电活动，以帮助居民改变其行为。我们为IoT系统设置了较少的传感器。识别活动的关键数据来自广泛使用的智能插座。首先考虑居民的可接受性来设置物联网系统，然后使用无缝的室内位置系统获取居民的位置以帮助识别正在进行的活动。它基于本体，在日常活动中利用领域知识，建立了活动本体。该系统考虑了真实的家庭情况，并充分利用了电气和电子设备的数据来进行上下文感知。这些知识有助于提高数据驱动方法的性能。实验表明，该系统能够以较高的准确度识别常见的活动，并且对实际家庭场景具有良好的适用性。

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