Project Details
Description
Poor air quality is the largest-environmental-risk to public-health in UK, causing tens of thousands of early deaths and billions-of-pounds in health-impacts yearly (Parliament business,2018). Fact is air-pollution is a diffusion-system which, when there are no obstacles, diffuses into area of lower concentration, causing minimum impact.
Infrastructures such as bridges and buildings normally represent obstacles to air-pollution diffusing into lower-concentration-area, causing increased pollutant concentration with consequent impact on human health. However, research has shown that design parameters (e.g. structure-geometry, doors and windows positioning, materials used, roof-shape, etc.) can have great effect on how quickly air-pollution diffuses to an area of lower-concentration. Design can also reduce pollution flow into indoors thereby improving indoor air quality. A well-designed building can thus help quickly dissipate high-level concentrations of pollution in an environment thus reducing associated health-impact.
Lately, many local-authorities are requiring analysis of effect of the proposed building/infrastructure on air-pollution dispersion for permit applications. A recent example is the Bluecroft Property Development in Lewisham council in London which is causing outrage due to its proposed development’s potential effect on pollution. An air-pollution-analysis requires hiring a consultant, with average charge and analysis-duration of £3000 and 5-weeks (=50,400 minutes) respectively, thereby increasing cost and time of construction. Failure to engage the consultant can result in a building-permit reject costing 13 weeks of permit assessment period and money for redesign.
This project will develop a digital-tool, in form of a plugin in design software like Autodesk REVIT, that will automate the pollution-analysis-process by automatically assessing air-pollution impact of a building during design stage and make recommendations for improvements. it will carry out analysis of indoor air-quality including doors and recommend improvement thus potentially increasing quality and performance of buildings for users/occupants. This solution will be developed using geometry optimization algorithms (artificial intelligence), cloud computing, big-data-analytics and a recommender-system to carry out computations on building design parameters (e.g. geometry, doors and windows positioning, materials used, etc.) and data from air-pollution sensors.
Infrastructures such as bridges and buildings normally represent obstacles to air-pollution diffusing into lower-concentration-area, causing increased pollutant concentration with consequent impact on human health. However, research has shown that design parameters (e.g. structure-geometry, doors and windows positioning, materials used, roof-shape, etc.) can have great effect on how quickly air-pollution diffuses to an area of lower-concentration. Design can also reduce pollution flow into indoors thereby improving indoor air quality. A well-designed building can thus help quickly dissipate high-level concentrations of pollution in an environment thus reducing associated health-impact.
Lately, many local-authorities are requiring analysis of effect of the proposed building/infrastructure on air-pollution dispersion for permit applications. A recent example is the Bluecroft Property Development in Lewisham council in London which is causing outrage due to its proposed development’s potential effect on pollution. An air-pollution-analysis requires hiring a consultant, with average charge and analysis-duration of £3000 and 5-weeks (=50,400 minutes) respectively, thereby increasing cost and time of construction. Failure to engage the consultant can result in a building-permit reject costing 13 weeks of permit assessment period and money for redesign.
This project will develop a digital-tool, in form of a plugin in design software like Autodesk REVIT, that will automate the pollution-analysis-process by automatically assessing air-pollution impact of a building during design stage and make recommendations for improvements. it will carry out analysis of indoor air-quality including doors and recommend improvement thus potentially increasing quality and performance of buildings for users/occupants. This solution will be developed using geometry optimization algorithms (artificial intelligence), cloud computing, big-data-analytics and a recommender-system to carry out computations on building design parameters (e.g. geometry, doors and windows positioning, materials used, etc.) and data from air-pollution sensors.
Key findings
1. Outdoor air-pollution impact assessor (OPiA)
2. Indoor air-pollution quality assessor (IPqA)
3. A recommender system (ReS)
2. Indoor air-pollution quality assessor (IPqA)
3. A recommender system (ReS)
| Acronym | D-BuD |
|---|---|
| Status | Finished |
| Effective start/end date | 1/10/24 → 31/03/25 |
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