THE INTERSECTION OF TECHNOLOGY AND ARCHITECTURE: SMARTPHONE PHOTOGRAPHY IN CARBON ANALYSIS

Abstract

Our research introduces an innovative methodology that employs smartphone imaging for measuring dimensions and utilizes deep learning to estimate carbon emissions associated with facade materials. The dimensions of various components of building exteriors are obtained through smartphone imaging, and a network model on a cloud server automatically segments these components in the images, calculating their respective areas. By combining user-input material specifications such as thickness and density with standard values of material carbon coefficients, estimations for each component's material carbon footprint are derived. This approach offers the advantage of individual estimations for diverse materials, aiding in the design of low-carbon facades. Additionally, it features a user-friendly interface enabling swift carbon estimation through portable devices. The method provides a convenient and efficient means for assessing carbon emissions in building facades, contributing to sustainable efforts and informed material selections for a greener future.