◉Research
The Context Decoder is a research initiative aimed at analyzing complex urban fabrics and building morphologies to inform contemporary architectural practice using AI.
Team:
Keshava Narayan, Ashish Tiwari
Scope
Our scope involved developing an AI-driven framework to decode the underlying rules of successful urban spaces. We focused on mapping historical housing patterns and identifying how these can be re-interpreted for modern, high-density residential developments.
Challenges
The main challenge was the qualitative nature of urban “context.” We developed a methodology to quantify environmental, social, and aesthetic factors into a digital format that can be processed by neural networks for predictive design.
Innovation
We created a custom “Context Decoder” tool that allows architects to input topographical and cultural data to generate design guidelines. This ensures that new buildings are inherently compatible with their heritage while utilizing modern construction techniques.
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