Buildings and Cities: Difference between revisions

 
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* '''Macro-scale [[Macro-scale energy demand assessment in cities|energy demand]] and [[Greenhouse Gas Emissions Detection|GHG emissions]] assessment in cities:''' While some electricity system operators release publicly-available data on energy use and the emissions associated with fossil fuel generators, this data is not available in many cases. ML can help map greenhouse gas emissions using remote sensing and/or on-the-ground data.
* '''[[Identifying building retrofit needs]]:''' For reducing energy use for thermal comfort in buildings, many buildings need to be retrofitted to increase their thermal performance. ML can help pinpoint which buildings and which specific parts of buildings would yield the best performance gains.
* '''[[Designing Low-carbonCarbon urbanUrban formForm|Designing from neighborhoods to large agglomerations|Low-carbon urban form, from neighborhoods toCarbon largeUrban agglomerationsForm]]:''' Urban form, the physical form of cities, has important implications of energy use and GHG emissions, for example sprawled cities can induce mobility demand. ML can help analyze energy use implications of different urban forms, simulate urban development pathways and (re-)designing neighborhoods by finding patterns in urban form data.
 
=== The future of cities ===