Abstract
ABSTRACT Understanding indoor environmental quality (IEQ) and integrating indoor data into architectural design is a critical component of green building design for building occupants’ comfort and health. With a growing emphasis on creating healthy and comfortable indoor environments in green buildings, indoor data in architectural design has increasingly incorporated quantitative methods to analyze and optimize indoor environmental quality parameters. Data-driven design in architecture has been used as a decision-making approach to the green building design process; it has implications for the building occupants to voluntarily enhance their indoor environments and comfort. A higher degree of personal control for indoor environmental quality (IEQ) leads to higher satisfaction, energy savings, and productivity in work environments. IEQ data access related to thermal, visual, and acoustic comforts and indoor air enables occupants to acquire ownership of indoor controls, contributing to their comfort and task productivity. Undergraduate architecture students carried out a series of data-driven designs for IEQ monitoring and design integrations by conducting a field study, data collection, data analysis, and visualization, and linking findings to architectural proposals. Participating groups were requested to i) theoretically understand IEQ data parameters for four primary indoor environments, ii) experimentally conduct a field survey of target spaces, iii) numerically predict IEQ conditions by using diverse simulation tools and measurement devices, iv) graphically visualize IEQ findings, and v) finally integrate findings into the architectural design as a solutional proposal. The findings highlight that the potential of quantitative approaches in architectural design enhances students’ understanding of environmental contributors and design solutions for occupants’ comfort and health.
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