Using AI to improve building energy use and comfort

New study from Waterloo researchers creating climate change-proof buildings with deep learning-powered inspections

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Media Relations

University of Waterloo researchers have developed a new method that can lead to significant energy savings in buildings. The team identified 28 major heat loss regions in a multi-unit residential building with the most severe ones being at wall intersections and around windows. A potential energy savings of 25 per cent is expected if 70 per cent of the discovered regions are fixed.    

Building enclosures rely on heat and moisture control to avoid significant energy loss due to airflow leakage, which makes buildings less comfortable and more costly to maintain. This problem will likely be compounded by climate change due to volatile temperature fluctuations. Since manual inspection is time-consuming and infrequently done due to a lack of trained personnel, energy inefficiency becomes a widespread problem for buildings.   

Researchers at Waterloo, which is a leader in sustainability research and education and a catalyst for environmental innovation, solutions and talent, created an autonomous, real-time platform to make buildings more energy efficient. The platform combines artificial intelligence, infrared technology, and a mathematical model that quantifies heat flow to better identify areas of heat loss in buildings.

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