Git for Sketches: An Intelligent Tracking System for Capturing Design Evolution
This addresses the need for better design evolution tracking in product conceptualization, offering a new paradigm for design education.
The paper tackled the problem of losing design context in traditional sketching tools by introducing DIMES with sGIT, a visual version control system using AI, resulting in a 160% increase in concept exploration breadth and improved replication fidelity (0.97 vs. 0.73) and user acceptance (4.2 vs. 3.1).
During product conceptualization, capturing the non-linear history and cognitive intent is crucial. Traditional sketching tools often lose this context. We introduce DIMES (Design Idea Management and Evolution capture System), a web-based environment featuring sGIT (SketchGit), a custom visual version control architecture, and Generative AI. sGIT includes AEGIS, a module using hybrid Deep Learning and Machine Learning models to classify six stroke types. The system maps Git primitives to design actions, enabling implicit branching and multi-modal commits (stroke data + voice intent). In a comparative study, experts using DIMES demonstrated a 160% increase in breadth of concept exploration. Generative AI modules generated narrative summaries that enhanced knowledge transfer; novices achieved higher replication fidelity (Neural Transparency-based Cosine Similarity: 0.97 vs. 0.73) compared to manual summaries. AI-generated renderings also received higher user acceptance (Purchase Likelihood: 4.2 vs 3.1). This work demonstrates that intelligent version control bridges creative action and cognitive documentation, offering a new paradigm for design education.