Labeling spaces can be a tedious process, but Machine Learning tools have the potential to give designers reprieve from manually typing in each space name. Classifier algorithms are able to reference training data and group lists of new elements into classes based on their characteristics and similarities to the data on which it was trained.
Design processes tend to involve data. Whether a design exercise involves referencing a proforma table of areas into 3D conceptual layouts, adjusting geometries based on fabrication tolerances, or determining egress widths based on occupancy metrics - designers have the opportunity to leverage data to streamline their processes and meet targets. While there are a number of options available that can help designers adopt data-driven workflows, Rhino users have a free and open-source option with LunchBox.
