New AI system predicts energy performance

The AI system can generate an almost instant prediction of building emissions rates (BER) for use in calculating the energy performance of non-domestic buildings. Current methods can take hours to days to produce BERs and are generated by manually inputting hundreds of variables. Dr Georgina Cosma and postgraduate student Kareem Ahmed, of the School of Science, have designed and trained an AI model to predict BER values with 27 inputs with little loss in accuracy. The model has been created with the support of Cundall's head of research and innovation, Edwin Wealend, and trained using data obtained from UK government energy performance assessments. Cosma said the research "is an important first step towards the use of machine learning tools for energy prediction in the UK" and it shows how data can "improve current processes in the construction industry".