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Since the power consumption of different electrical appliances in a household can be recorded by individual smart meters, it becomes possible to start considering in more detail the interactions of the residents with those devices throughout the day. Appliances' usages should not be considered as independent events, but rather as enablers for activities. Leveraging activity knowledge over time will...
While tasks such as segmenting images or determining the sentiment expressed in a sentence can be assigned to regular users, some others require background knowledge and thus, the selection of expert users. In the case of energy datasets, acquiring data represents an obstacle to develop data-driven methods, due to prohibitive monetary and time costs linked to the instrumentation of households in order...
Attaining energy efficiency requires understanding human behaviors triggering energy consumption within households. In conjunction to providing appliance-level feedback, targeting human activities that involve the usage of electrical appliances can provide a higher abstraction level to bring awareness to the electricity wastage. In this paper, we make use of a large dataset with appliance- and circuit-level...
Targeting human activities responsible for the energy consumption instead of focusing solely on single appliance feedback for achieving energy efficiency in residential homes would link human behaviors to the resulting energy consumption. To this end, learning when appliances are in an active or idle state and the related user activity is crucial. Until smart appliances become widespread and can communicate...
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