Abstract

The Internet of Energy (IoE) paradigm is an advancing area of research in the field of energy efficiency encompassing data collection, processing, visualization, and decision making. Smart energy monitoring has witnessed technological advancements such as smart metering and IoE networking, allowing the expansion of smart energy networks in smart households. In this book chapter, we aim to understand energy behavior through big data collection and classification and improve energy efficiency using data 22lakes. A specialized case study is reported on the ODROID-XU4 multicore platform to realize a setup developed at De Montfort University (DMU), UK, at the Energy Lab and Artificial Intelligence (AI) Lab. It is aimed to build a novel appliance-level energy data lake with contextual ambient environmental data. Also, a novel labeling system is introduced for classifying domestic energy consumption coupled with data visualization examples. In conclusion, the proposed work aids in exploiting energy efficiency technologies for improving energy efficiency via an innovative, automated energy efficiency framework.

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