GREENHOME: A Household Energy Consumption and CO ₂ Footprint Metering Environment

Abstract

This article presents the GREENHOME environment, a toolkit providing several data analytical tools for metering household energy consumption and CO 2 footprint under different perspectives. GREENHOME enables a multi-perspective analysis of household energy consumption and CO 2 footprint using and combining several variables through various statistics and data mining algorithms. To test GREENHOME, the article reports on experiments conducted for modelling and forecasting energy consumption and CO 2 footprint in the context of the Triple-A European project.

Model proposition for predicting sustainability classes using multicriteria decision support and artificial intelligence

“…There are studies with the application of several multicriteria decision support methods, in individual or hybrid form, as well as proposals for specific models aimed at solving electrical energy problems. This reveals trends to use models with Machine Learning and Neural Networks, for example, to infer results on production, efficiency and consumption of electricity (Ahmad et al, 2021;Ahmadi et al, 2022;Buțurache & Stancu, 2022;Kwakkel & Pruyt, 2013;Rolnick et al, 2022;Vargas-Solar et al, 2022). In addition, there are proposals for models for analyzing problems using Fuzzy logic, a theory for the mathematical treatment of data imprecision (Al-Barakati et al, 2022;Ervural et al, 2018a, b;Panchal et al, 2022;Qi et al, 2020;Zhou et al, 2019).…”