Work

A Unified Engineering–Semantic Framework for Transforming AI-Generated Residential Floor Plans into CAD Drawings and BIM Models

Year: 2026

Type: article

Abstract: Artificial intelligence has increasingly been applied to residential floor plan generation, producing outputs in diverse forms such as semantic raster images, graph-structured layouts, and vector polygons. However, these outputs still require substantial interpretation and reconstruction before they can enter conventional CAD and BIM workflows. This study develops a unified engineering–semantic framework for transforming heterogeneous AI-generated floor plans into editable CAD drawings and preliminary BIM information models. Three route-specific procedures—ColorPlan, TopoPlan, and PolyPlan—are established to parse and regularize the three representative input forms. The processed information is reorganized into a common engineering–semantic JSON core and subsequently mapped to native AutoCAD entities and Revit objects. The workflow was evaluated using 165 transformation-ready single-story residential samples. The effective CAD/BIM transformation rates reached 100.0%/97.7% for ColorPlan, 93.3%/85.3% for TopoPlan, and 100.0%/97.9% for PolyPlan. The results show that transformation stability is closely related to the completeness of semantic, geometric, topological, and opening information in the source representation. A controlled human–machine experiment further showed that the proposed workflow reduced CAD drafting time by approximately 85.2% and BIM modeling time by 90.0% compared with fully manual production. The study demonstrates a feasible approach for extending heterogeneous AI-generated layouts into editable and information-bearing engineering representations while substantially reducing repetitive drafting and preliminary modeling work.

Source: Buildings

DOI: 10.3390/buildings16173422

Authors: Yujia Xie, Ting Zhou

Institution: Tianjin University

Language: English

Topic: BIM and Construction Integration

Subfield: Building and Construction

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $3,137