文章基本信息

标题：Reducing Energy Waste through Eco-Aware Everyday Things
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作者：Juan López-de-Armentia, Diego Casado-Mansilla, Sergio López-Pérez ; Diego López-de-Ipiña
期刊名称：Mobile Information Systems
印刷版ISSN：1574-017X
出版年度：2014
卷号：10
DOI：10.3233/MIS-130172
出版社：Hindawi Publishing Corporation
摘要：Society wastes much more energy than it should. This produces tons of unnecessary CO2 emissions. This is partly due to the inadequate use of electrical devices given the intangible and invisible nature of energy. This misuse of devices and energy unawareness is particularly relevant in public spaces (offices, schools, hospitals and so on), where people use electrical appliances, but they do not directly pay the invoice to energy providers. Embedding intelligence within public, shared appliances, transforming them into Eco-aware things, is valuable to reduce a proportion of the unnecessarily consumed energy. To this end, we present a twofold approach for better energy efficiency in public spaces: (1) informing persuasively to concerned users about the misuse of electronic appliances; (2) Customizing the operating mode of this everyday electrical appliances as a function of their real usage pattern. To back this approach, a capsule-based coffee machine placed in a research laboratory has been augmented. This device is able to continuously collect its usage pattern to offer feedback to coffee consumers about the energy wasting and also, to intelligently adapt its operation to reduce wasted energy. To this aim, several machine learning approaches are compared and evaluated to forecast the next-day device usage.