Automated Floor Generation and Thermal Comfort Optimization in Low-Income Housing

This project develops an automated floor generation system for low-income housing, integrating an indoor thermal comfort matrix and energy costs. The first phase involves creating a LIDAR-scanned BIM model of a typical low- and medium-income (LMI) house, enabling calculation of energy consumption rates per room by assessing external façade heat, daylight gains, and occupant thermal comfort. A central component is the use of generative design methods to predict energy-efficient layouts and support modular fabrication. The existing room matrix is translated into spatial areas and networks, with an algorithm optimizing room orientations based on energy use and external heat gain. This analysis helps identify how different configurations affect thermal performance, energy usage, and comfort levels, while intelligently positioning partition walls to improve energy efficiency, natural light access, and heat gain. To engage users, a web-based interface allows them to input preferences for room configurations, ensuring designs are both energy-efficient and tailored to occupants’ needs. BIM integration further streamlines modular part fabrication, enhancing design accuracy and construction efficiency. Comparing the thermal comfort of optimized designs with existing units, we offer insights into potential improvements for modular housing and demonstrate the advantages of this approach for affordable LMI housing. This interdisciplinary framework, drawing from architecture, engineering, and technology, aims to improve energy efficiency and thermal comfort, enhancing affordable housing. The project provides tools and insights for designers and architects, advancing adaptable, sustainable solutions for low-income families.