2022
DOI: 10.1145/3505264
|View full text |Cite
|
Sign up to set email alerts
|

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 fore… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2022
2022
2024
2024

Publication Types

Select...
3

Relationship

0
3

Authors

Journals

citations
Cited by 3 publications
(2 citation statements)
references
References 46 publications
0
2
0
Order By: Relevance
“…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).…”
Section: Literature Reviewmentioning
confidence: 99%
“…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).…”
Section: Literature Reviewmentioning
confidence: 99%
“…What are the potential challenges and ethical considerations that need to be addressed when implementing an IoT-based visualisation platform for tracking household CFs? How can the data collected through an IoT-based visualisation platform be used to promote sustainable behaviour and reduce household CFs [11]? What are some potential applications of an IoT-based visualisation platform for tracking household CFs beyond individual households, such as for community-wide carbon reduction initiatives?…”
Section: Introductionmentioning
confidence: 99%