Existing image data can help give a clearer picture of building energy efficiency

Dr Qunshan Zhao was interviewed for an article in the New Scientist, which explains how Artificial Intelligence (AI) can use existing Google Street View images and satellite imagery to estimate building energy efficiency in cities across the globe.

In the piece - AI can tell which buildings are energy efficient from the outside (subscription required) - Dr Zhao, UBDC's Lead on Urban Sensing & Analytics and Senior Lecturer in Urban Analytics at the University of Glasgow, comments:

"The benefit of using these images is you will be able to extend [the AI analysis] to a global level...You get Street View images in most countries".

He also notes that AI predictions could be improved with the use of higher-resolution thermal infrared imagery from new satellites and street scanning, which will be trialled this winter and next winter via a UBDC-funded scanning project.

Dr Zhao has co-authored a paper in Energy and Buildings journal on understanding building energy efficiency with administrative and emerging urban big data by deep learning in Glasgow, which is linked to in the article.

Files

No items found.

Latest news

IDEAMAPS network launches new platform

The IDEAMAPS Network launches its Data Ecosystem platform - a new digital mapping tool to support improvements in deprived areas in Low- and Middle-Income countries.

Learn More

UBDC team wins a top award at the ACM SIGSPATIAL conference

Researchers examined the 'Optimal Minimum Deployment of Electric Vehicle Charging Station Networks'.

Learn More

Indoor environment and energy use study

UBDC - in collaboration with Understanding Society, the UK Household Longitudinal Study - is launching a new study to provide linked-data on energy usage and indoor environment.

Learn More

Jointly funded by