Smart and green buildings for sustainable cities

Source : Réseaux de centres d’excellence
Programme : Réseau IC-Impacts
Période : 2016-2018
Chercheur(s) du centre impliqué(s):

  • Mir Abolfazl Mostafavi

Résumé :
Research on sustainable building infrastructure has focused on energy use associated with
construction materials and methods, and during operations. The latter has received particular
attention in “smart building” research where a sensor network is used to provide continuous
feedback about indoor environmental conditions to HVAC and lighting systems to minimize
electrical demand. This approach is inadequate. Energy demand assessment in urban areas must
be done at the scale of urban districts and neighborhoods, not just individual buildings. This is
important because the Urban Heat Island (UHI) effect has a major impact on building energy
efficiency. With rapid urbanization, UHI intensity in urban and peri-urban areas will only
increase.
The proposed research aims to understand the relationship between UHI intensity and building
energy demands, two aspects which have not previously been studied together, using real world
quantitative data.
Using open source hardware-software platforms, we will build and deploy a low-cost sensor
network for UHI mapping and indoor temperature-humidity mapping. The network will provide
data about UHI variability within limited geographic areas. This data will be used together with
information on conditions external to the building – physical parameters such as built densities,
and volumetric and constructive characteristics of buildings, and functional characteristics such
as land use – to develop a model linking UHI intensity and urban morphology.
University campuses will serve as test beds representing urban areas. We propose to determine
the energy demand of individual buildings and study the UHI effect at three campuses in India
and two in Canada, each representing a different urban configuration.
Comparison with macro-scale data from satellite observations will allow expansion of the model
to urban areas beyond the study sites.