Summary of Ai4ef: Artificial Intelligence For Energy Efficiency in the Building Sector, by Alexandros Menelaos Tzortzis et al.
AI4EF: Artificial Intelligence for Energy Efficiency in the Building Sector
by Alexandros Menelaos Tzortzis, Georgios Kormpakis, Sotiris Pelekis, Ariadni Michalitsi-Psarrou, Evangelos Karakolis, Christos Ntanos, Dimitris Askounis
First submitted to arxiv on: 5 Dec 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: None
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The AI4EF tool utilizes machine learning to support decision-making in building energy retrofitting and efficiency optimization. It enables stakeholders to model, analyze, and predict energy consumption, costs, and environmental impacts of building upgrades. The modular framework includes customizable tools for retrofitting, photovoltaic installation assessment, and predictive modeling. Users can input building parameters to receive tailored recommendations for achieving energy savings and carbon reduction goals. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary AI4EF is a tool that helps people make good decisions about how to make buildings more energy-efficient. It uses special computer programs called machine learning models to look at data and make predictions about how different choices will affect energy use and the environment. The tool has different parts, each with its own set of tools for things like planning renovations or installing solar panels. Users can input information about their building and get personalized suggestions for improving energy efficiency and reducing carbon emissions. |
Keywords
* Artificial intelligence * Machine learning * Optimization
