3D Reconstruction of BIM for Carbon Emission Monitoring #sciencefather
Description
This topic explores the integration of weakly-supervised learning techniques in the 3D reconstruction of Building Information Models (BIMs) to enhance carbon emission modelling in the built environment. By leveraging AI-driven approaches, the system can generate accurate reconstructions from incomplete or noisy data, optimizing carbon footprint estimations. The aim is to support sustainable urban planning and construction by reducing the environmental impact through advanced modelling techniques, enabling more precise emissions calculations and eco-friendly architectural designs.
Nomination Link: https://researchhypothesis.com/award-nomination/?
ecategory=Awards&rcategory=AwardeeContact us: contact@researchhypothesis.com
#bim
#ai
#3dreconstruction
#weaksupervision
#machinelearning
#ai
#3dreconstruction
#weaksupervision
#machinelearning
#sustainablearchitecture
#carbonemissions
#buildinginformationmodeling
#greencities
#carbonfootprint
#environmentalimpact
#smartconstruction
#sustainabledesign
#urbanplanning
#carbonreduction
#artificialintelligence
#aecindustry
#digitaltwins
#carbonemissions
#buildinginformationmodeling
#greencities
#carbonfootprint
#environmentalimpact
#smartconstruction
#sustainabledesign
#urbanplanning
#carbonreduction
#artificialintelligence
#aecindustry
#digitaltwins
#researchawards
#hypothesistesting
#scientificexcellence
#academicachievement
Comments
Post a Comment