Artificial Intelligence Model for Accurate Prediction of Energy Consumption in Buildings at design stage (E-MAP)

Energy efficiency is crucial in helping to tackle the climate crisis - 26% of UK carbon dioxide emissions come from homes. The building environment is responsible for 40% of the UK's carbon footprint ([www.ukgbc.org/climate-change][0]) and the UK has one of the oldest and least efficient housing sectors in Europe (Green Finance Institute - Tooling up the Green Homes Industry).COP 26 in Glasgow in 2021 highlighted the increase in carbon dioxide emissions from human activity and the need to address this as a global priority.

This project(E-MAP) focuses on conducting a feasibility study for the development of an Artificial Intelligence (AI) model that can accurately and efficiently predict energy consumption at the design stage of buildings, without requiring extensive building feature details. E-MAP aims to assess the technical viability of implementing such a model by utilizing advanced machine-learning algorithms with its potential benefits for the construction industry and sustainable building practices.E-MAP will also support the government's challenge of substantially reducing the energy use of new buildings.

[0]: http://www.ukgbc.org/climate-change