Seemo: A new tool for early design window view satisfaction evaluation in residential buildings

People spend approximately 90% of their lives indoors, and thus arguably, the indoor space design can significantly influence occupant well-being. Adequate views to outside are one most cited qualities related However, due urbanization densification trends, designers may have difficulties in providing vistas with an assortment content, which support needs occupants. To better understand view satisfaction provide reliable feedback architects, existing data must be expanded capture a wider variety scenarios Most research remains challenging architectural practice lack easy-to-use early-design analysis tools. early assessment advantageous as decisions design, such building orientation, plan layout, facade improve quality. This paper, hence, presents results from 181 participant survey 590 window views. The is used train tree-regression model predict satisfaction. prediction performance was compared framework through case studies. result showed that new more accurate surveyed than framework. Further, generally high for responses, verifying reliability. facilitate this paper describes integrating ray-casting tool compute parameters CAD environment.